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

Investigation of the Effects of the Short QT Syndrome D172N Kir2.1 Mutation on Ventricular Action Potential Profile Using Dynamic Clamp

The congenital short QT syndrome (SQTS) is a cardiac condition that leads to abbreviated ventricular repolarization and an increased susceptibility to arrhythmia and sudden death. The SQT3 form of the syndrome is due to mutations to the KCNJ2 gene that encodes Kir2.1, a critical component of channels underlying cardiac inwardly rectifying K(+) current, I(K1). The first reported SQT3 KCNJ2 mutation gives rise to the D172N Kir2.1 mutation, the consequences of which have been studied on recombinant channels in vitro and in ventricular cell and tissue simulations. The aim of this study was to establish the effects of the D172N mutation on ventricular repolarization through real-time replacement of I(K1) using the dynamic clamp technique. Whole-cell patch-clamp recordings were made from adult guinea-pig left ventricular myocytes at physiological temperature. Action potentials (APs) were elicited at 1 Hz. Intrinsic I(K1) was inhibited with a low concentration (50 µM) of Ba(2+) ions, which led to AP prolongation and triangulation, accompanied by a ∼6 mV depolarization of resting membrane potential. Application of synthetic I(K1) through dynamic clamp restored AP duration, shape and resting potential. Replacement of wild-type (WT) I(K1) with heterozygotic (WT-D172N) or homozygotic (D172N) mutant formulations under dynamic clamp significantly abbreviated AP duration (APD(90)) and accelerated maximal AP repolarization velocity, with no significant hyperpolarization of resting potential. Across stimulation frequencies from 0.5 to 3 Hz, the relationship between APD(90) and cycle length was downward shifted, reflecting AP abbreviation at all stimulation frequencies tested. In further AP measurements at 1 Hz from hiPSC cardiomyocytes, the D172N mutation produced similar effects on APD and repolarization velocity; however, resting potential was moderately hyperpolarized by application of mutant I(K1) to these cells. Overall, the results of this study support the major changes in ventricular cell AP repolarization with the D172N predicted from prior AP modelling and highlight the potential utility of using adult ventricular cardiomyocytes for dynamic clamp exploration of functional consequences of Kir2.1 mutations

Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology

Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications in disease modeling, cell therapy, drug screening and personalized medicine. Computational models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different cell lines display different expression of ion channels, pumps and receptors, and show differences in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC-CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this model to the specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs. This demonstrates the need and the feasibility to tailor models to individual cell lines, although a more refined approach will be needed to characterize individual currents, address differences in ion current kinetics, and further improve these results

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop.

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings

Background and AimsHuman induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have become an essential tool to study arrhythmia mechanisms. Much of the foundational work on these cells, and the computational models built from the resultant data, has overlooked the contribution of seal-leak current on the immature and heterogeneous phenotype that has come to define these cells. The aim of this study is to understand the effect of seal-leak current on recordings of action potential (AP) morphology.MethodsAPs were recorded in human iPSC-CMs using patch clamp and simulated using previously published mathematical models.ResultsOur in silico and in vitro studies demonstrate how seal-leak current depolarises APs, substantially affecting their morphology, even with seal resistances (Rseal) above 1 GΩ. We show that compensation of this leak current is difficult due to challenges with obtaining accurate measures of Rseal during an experiment. Using simulation, we show that Rseal measures: 1) change during an experiment, invalidating the use of pre-rupture values, and 2) are polluted by the presence of transmembrane currents at every voltage. Finally, we posit that the background sodium current in baseline iPSC-CM models imitates the effects of seal-leak current and is increased to a level that masks the effects of seal-leak current on iPSC-CMs.ConclusionBased on these findings, we make recommendations to improve iPSC-CM AP data acquisition, interpretation, and model-building. Taking these recommendations into account will improve our understanding of iPSC-CM physiology and the descriptive ability of models built from such data

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

A deep learning algorithm to translate and classify cardiac electrophysiology

The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network approach intended to address the low throughput, high variability, and immature phenotype of the iPSC-CM platform. The rationale for combining translation and classification tasks is because the most likely application of the deep learning technology we describe here is to translate iPSC-CMs following application of a perturbation. The deep learning network was trained using simulated action potential (AP) data and applied to classify cells into the drug-free and drugged categories and to predict the impact of electrophysiological perturbation across the continuum of aging from the immature iPSC-CMs to the adult ventricular myocytes. The phase of the AP extremely sensitive to perturbation due to a steep rise of the membrane resistance was found to contain the key information required for successful network multitasking. We also demonstrated successful translation of both experimental and simulated iPSC-CM AP data validating our network by prediction of experimental drug-induced effects on adult cardiomyocyte APs by the latter

Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings

Aims: Human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have become an essential tool to study arrhythmia mechanisms. Much of the foundational work on these cells, as well as the computational models built from the resultant data, has overlooked the contribution of seal-leak current on the immature and heterogeneous phenotype that has come to define these cells. The aim of this study is to understand the effect of seal-leak current on recordings of action potential (AP) morphology. Methods and results: Action potentials were recorded in human iPSC-CMs using patch clamp and simulated using previously published mathematical models

Modellistica computazionale di cardiomiociti derivati da cellule staminali umane - Texture descriptor per l'elaborazione di immagini biologiche

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.Questa tesi indaga due distinti temi di ricerca. Il tema principale (Parte I) è la modellistica computazionale di cardiomiociti derivati da cellule staminali umane, sia embrionali (hESC-CM) che pluripotenti-indotte (hiPSC-CM). Lo scopo di questa parte consiste nello sviluppare modelli elettrofisiologici di hESC-CM e hiPSC-CM al fine di integrare i dati sperimentali disponibili ed ottenere modelli in-silico utilizzabili per studiare/produrre ipotesi/pianificare esperimenti su aspetti ancora poco chiari come il processo di maturazione, la funzionalità del Ca2+ handling e le cause per cui i potenziali d'azione(PA)di hESC-CM/hiPSC-CM mostrino alcune differenze rispetto ai PA di cardiomiociti adulti. Il capitolo I.1 introduce i concetti base su hESC-CM/hiPSC-CM, PA cardiaco e modellistica computazionale. Il capitolo I.2 presenta il modello di PA di hESC-CM in grado di riprodurre il processo di maturazione attraverso due stadi di sviluppo, Early e Late, basato su esperimenti e dati di letteratura. Il capitolo I.3 descrive il modello di PA di hiPSC-CM, in grado di riprodurre i fenotipi ventricular-like ed atrial-like. Questo modello è stato utilizzato per valutare quali correnti siano le principali responsabili delle differenze tra il PA ventricular-like e quello di cardiomiociti ventricolari adulti. Il tema secondario (Parte II) consiste nello studio di texture descriptor per la classificazione di immagini biologiche. Nel capitolo II.1 viene fornita una panoramica dei principali texture descriptor come Local Binary Pattern e Local Phase Quantization. Inoltre viene presentato il concetto di codifica non-binaria e approccio multi-threshold. Il Capitolo II.2 mostra che l'utilizzo della codifica non-binaria e dell'approccio multi-threshold portano ad un incremento delle performance di classificazione su sei dataset di immagini cellulari o di parti subcellulari. Il capitolo II.3 presenta un caso di studio di classificazione di immagini di immunofluorescenza indiretta su cellule HEp2, utilizzate in clinica per il test degli anticorpi antinucleo. Infine vengono riportate le conclusioni generali