Biology subjects

Edwards, A. G.

Publications and source records attributed to Edwards, A. G..

11 recordsLinked to original sources

bioRxiv2026

Computational modelling of natural cell-to-cell heterogeneity reveals key parameters that control the diversity of human pancreatic islet β-cell excitability in response to glucose

Insulin-producing {beta}-cells demonstrate remarkable heterogeneity in their individual responsiveness to glucose, and that cellular heterogeneity contributes to coordinating islet activity and glucose homeostasis. Our current understanding of how variation in cell-intrinsic factors control cellular excitability and insulin secretion is informed by foundational experiments conducted on dispersed single {beta}-cells. Such studies are limited in their ability to link multiple electrical or metabolic properties within a single cell and preclude the ability to relate, post hoc, each parameters contribution to glucose responsiveness. Computational modelling represents a unique and underutilized tool to integrate and investigate the role of natural {beta}-cell heterogeneity in physiologic glucose responses. Herein, we utilize a high-volume single-cell electrophysiology "patch-seq" dataset to define the physiologically relevant sources of variability in human {beta}-cell electrophysiology and model their influence on single-cell glucose responses. Three thousand in silico human {beta}-cells were fitted to physiologically relevant variations in glucokinase activity, K+ current, Na+ current, Ca2+ current, and exocytotic function. Four dominant electrical phenotypes arose at low (2 mM) and high (20 mM) glucose: silent, bursting, spiking, and depolarized. Approximately 50% of uncoupled {beta}-cells remained electrically silent at high glucose. Furthermore, Na+ channel half-inactivation voltage was a major predictor of the silent and spiking phenotypes at each glucose concentration, and of cells that transition from silent to spiking when glucose increased. Indeed, experimentally observed variation in Na+ channel voltage dependence was second only to variation in ATP-sensitive potassium channel conductance in determining {beta}-cell excitability. Our data-driven computational modelling highlights the functional importance of electrical heterogeneity in human {beta}-cell glucose responses, and provides a useful tool for generating testable hypotheses.

physiology↗

bioRxiv2025

Differentiating the Roles of Metabolic Similarity and Ionic Coupling in Determining the Beta Hub Cell Phenotype

Pancreatic beta cells regulate circulating glucose levels by releasing insulin. Beta cells transduce elevated blood glucose into electrical activity through an intrinsic cascade of metabolic and electrophysiologic responses. These responses are synchronized across the electrically connected network of beta cells, such that insulin release is also relatively synchronous. Despite their coordinated behavior, individual beta cells exhibit significant functional heterogeneity. This heterogeneity is thought to provide cells with specific functional phenotypes the ability to control the activity of the broader network. Hub cells, identified by their synchronized [Ca2+] activity, are one such functional subpopulation, and are believed to orchestrate the second, oscillatory phase of insulin release. However, it remains unclear whether the cell-autonomous characteristics of hub cells, such as their metabolic activity and electrophysiologic properties, are more important than their network characteristics (i.e. gap junctional coupling) for their ability to influence broader network activity. In this study, we investigate the roles of intrinsic metabolic and electrophysiologic properties and ionic coupling in determining the beta hub cell phenotype. Using a computational islet model of 1,000 beta cells, our analysis revealed that both intrinsic metabolic properties and structural coupling via gap junctions are crucial for determining the hub cell phenotype. After investigating the intrinsic coupling conductance of neighboring cells and the number of structural (direct electrical) links as independent contributors to the hub cells local electrical coupling, we find that the number of cells to which a beta cell is directly coupled may be a key determinant of its propensity to serve as a hub cell in the model. As predicted for this subpopulation, we also demonstrate that decoupling hub cells impairs the functional connectivity of the entire network. Our findings indicate the importance of both autonomous cellular dynamics and non-autonomous structural coupling for the hub cell phenotype. These insights help build a fundamental understanding of hub cells, which in turn may contribute to identifying potential approaches to preserve or improve beta cell function and thereby manage the progression of diabetes.

bioengineering↗

bioRxiv2025

Exploring the intrinsic and extrinsic determinants of heterogeneity in a β-cell network

Pancreatic islets are micro-organs composed of multiple endocrine cell types. {beta}-cells are the most common of these and are highly heterogeneous in both their intrinsic properties, such as ion channel conductances and metabolic activity, and extrinsic properties, including gap junction coupling and paracrine signaling. Capturing these diverse sources of heterogeneity is essential for computational models that aim to reproduce islet function. We evaluate two established multicellular models, the coupled Cha-Noma model of the mouse {beta}-cell network, and the Riz human model. Prior work with these two models suggest that the Cha-Noma model involves minimal intrinsic heterogeneity and therefore bursts with highly synchronized activity, whereas heterogeneity in the Riz model prescribed from in vitro patch-clamp results in highly unsynchronized behavior of the coupled network. We hypothesize that adjusting the number of bursting cells in both model formulations may invoke more physiologically realistic network coordination. We applied a categorical sensitivity analysis to establish which parameters are most important for determining bursting in single cells of the Riz model. We also introduced new heterogeneity (based on single-cell gene expression) in parameters that had previously been treated as invariant among {beta}-cells. We hypothesized that introducing heterogeneity in the small conductance Ca2+ K+ channel in particular could promote a higher proportion of bursting cells. Lastly, both models fail to incorporate the influences of non-{beta}-cells. We introduced paracrine signaling between and {beta}-cells into the coupled Cha-Noma model and showed it plays a role in accelerating the response time of {beta}-cells to acute glucose stimulation (i.e. promotes a 1st responder phenotype).

bioengineering↗

bioRxiv2024

The Sodium/Glucose Cotransporter 2 Inhibitor Empagliflozin Inhibits Long QT 3 Late Sodium Currents in a Mutation Specific Manner

BackgroundSodium/glucose cotransporter 2 inhibitors (SGLT2is) such as empagliflozin have demonstrated substantial cardioprotective effects in patients with or without diabetes. The SGLT2is have been shown to selectively inhibit the late component of cardiac sodium current (late INa). Induction of late INa is also the primary mechanism involved in the pathophysiology of congenital long QT syndrome type 3 (LQT3) gain-of-function mutations in the SCN5A gene that encodes the major cardiac sodium channel isoform Nav1.5. Therefore, we investigated the effect of empagliflozin on late INa in thirteen known LQT3 mutations located in distinct regions of the channel structure. MethodsThe whole-cell patch-clamp technique was used to investigate the effect of empagliflozin (10 {micro}M) on late INa in recombinantly expressed Nav1.5 channels containing different LQT3 mutations. Molecular modeling of human Nav1.5 and simulations in a mathematical model of human ventricular myocytes were used to extrapolate our experimental results to excitation contraction coupling. ResultsEmpagliflozin selectively inhibited late INa in LQT3 mutations residing in the inactivation gate region of Nav1.5, with no effect on either peak current or channel kinetics. In contrast, empagliflozin caused inhibition of both peak and late INa in mutations in the S4 voltage-sensing regions as well as changes in activation and inactivation kinetics and a slowing of recovery from inactivation. Empagliflozin had no effect on late/peak INa or channel kinetics in channels containing LQT3 mutations located in the putative empagliflozin binding region. Simulation of our experimental findings in a mathematical model of human ventricular myocytes predicts that empagliflozin may have a desirable therapeutic effect in LQT3 mutations located in the inactivation gate region. ConclusionsOur results show that empagliflozin selectively inhibits late INa, without affecting gating kinetics, in LQT3 mutations residing in the inactivation gate region. Patients with mutations in voltage-sensing regions are less suitable candidates as empagliflozin may prevent action potential firing. The SGLT2is may therefore be a promising novel precision medicine approach for patients with certain LQT3 mutations.

pharmacology and toxicology↗

bioRxiv2022

Mechanisms of spontaneous Ca2+ release-mediated arrhythmia in a novel 3D human atrial myocyte model: I. Transverse-axial tubule variation

Intracellular calcium (Ca2+) cycling is tightly regulated in the healthy heart ensuring effective contraction. This is achieved by transverse (t)-tubule membrane invaginations that facilitate close coupling of key Ca2+-handling proteins such as the L-type Ca2+ channel (LCC) and Na+-Ca2+ exchanger (NCX) on the cell surface with ryanodine receptors (RyRs) on the intracellular Ca2+ store. Though less abundant and regular than in the ventricle, t-tubules also exist in atrial myocytes as a network of transverse invaginations with axial extensions known as the transverse-axial tubule system (TATS). In heart failure and atrial fibrillation there is TATS remodeling that is associated with aberrant Ca2+-handling and Ca2+-induced arrhythmic activity, however the mechanism underlying this is not fully understood. To address this, we developed a novel 3D human atrial myocyte model that couples electrophysiology and Ca2+-handling with variable TATS organization and density. We extensively parameterized and validated our model against experimental data to build a robust tool examining TATS regulation of subcellular Ca2+ release. We found that varying TATS density and thus the localization of key Ca2+-handling proteins has profound effects on Ca2+ handling. Following TATS loss there is reduced NCX that results in increased cleft Ca2+ concentration through decreased Ca2+ extrusion. This elevated Ca2+ increases RyR open probability causing spontaneous Ca2+ releases and promotion of arrhythmogenic waves (especially in the cell interior) that leads to voltage instabilities through delayed afterdepolarizations. In summary, this study demonstrates a mechanistic link between TATS remodeling and Ca2+-driven proarrhythmic behavior that likely reflects the arrhythmogenic state observed in disease. Key PointsO_LITransverse-axial tubule systems (TATS) modulate Ca2+ handling and excitation-contraction coupling in atrial myocytes, with TATS remodeling in heart failure and atrial fibrillation associated with altered Ca2+ cycling and subsequent arrhythmogenesis. C_LIO_LITo investigate the poorly understood mechanisms linking TATS variation and spontaneous Ca2+ release, we built, parameterized and validated a 3D human atrial myocyte model coupling electrophysiology and spatially-detailed subcellular Ca2+ handling governed by the TATS. C_LIO_LISimulated TATS loss causes diastolic Ca2+ and voltage instabilities through reduced NCX-mediated Ca2+ removal, cleft Ca2+ accumulation and increased RyR open probability, resulting in spontaneous Ca2+ release and promotion of arrhythmogenic waves and delayed afterdepolarizations. C_LIO_LIAt fast electrical rates typical of atrial tachycardia/fibrillation, spontaneous Ca2+ releases are larger and more frequent in the cell interior than at the periphery. C_LIO_LIOur work provides mechanistic insight into how atrial TATS remodeling can lead to Ca2+- driven instabilities that may ultimately contribute to the arrhythmogenic state in disease. C_LI

physiology↗

bioRxiv2022

Mechanisms of spontaneous Ca2+ release-mediated arrhythmia in a novel 3D human atrial myocyte model: II. Ca2+-handling protein variation

Disruption of the transverse-axial tubule system (TATS) in diseases such as heart failure and atrial fibrillation occurs in combination with changes in the expression and distribution of key Ca2+- handling proteins. Together this ultrastructural and ionic remodeling is associated with aberrant Ca2+ cycling and electrophysiological instabilities that underly arrhythmic activity. However, due to the concurrent changes in TATs and Ca2+-handling protein expression and localization that occur in disease it is difficult to distinguish their individual contributions to the arrhythmogenic state. To investigate this, we applied our novel 3D human atrial myocyte model with spatially detailed Ca2+ diffusion and TATS to investigate the isolated and interactive effects of changes in expression and localization of key Ca2+-handling proteins and variable TATS density on Ca2+- handling abnormality driven membrane instabilities. We show that modulating the expression and distribution of the sodium-calcium exchanger, ryanodine receptors, and the sarcoplasmic reticulum (SR) Ca2+ buffer calsequestrin have varying pro and anti-arrhythmic effects depending on the balance of opposing influences on SR Ca2+ leak-load and Ca2+-voltage relationships. Interestingly, the impact of protein remodeling on Ca2+-driven proarrhythmic behavior varied dramatically depending on TATS density, with intermediately tubulated cells being more severely affected compared to detubulated and densely tubulated myocytes. This work provides novel mechanistic insight into the distinct and interactive consequences of TATS and Ca2+-handling protein remodeling that underlies dysfunctional Ca2+ cycling and electrophysiological instability in disease. Key PointsO_LIIn our companion paper we developed a 3D human atrial myocyte model, coupling electrophysiology and Ca2+ handling with subcellular spatial details governed by the transverse-axial tubule system (TATS). C_LIO_LIHere we utilize this model to mechanistically examine the impact of TATS loss and changes in the expression and distribution of key Ca2+-handling proteins known to be remodeled in disease on Ca2+ homeostasis and electrophysiological stability. C_LIO_LIWe demonstrate that varying the expression and localization of these proteins has variable pro- and anti-arrhythmic effects with outcomes displaying dependence on TATS density. C_LIO_LIWhereas detubulated myocytes typically appear unaffected and densely tubulated cells seem protected, the arrhythmogenic effects of Ca2+ handling protein remodeling are profound in intermediately tubulated cells. C_LIO_LIOur work shows the interaction between TATS and Ca2+-handling protein remodeling that underlies the Ca2+-driven proarrhythmic behavior observed in AF and may help to predict the effects of antiarrhythmic strategies at varying stages of ultrastructural remodeling. C_LI

physiology↗

bioRxiv2021

Mutations change excitability and the probability of re-entry in a computational model of cardiac myocytes in the sleeve of the pulmonary vein

Atrial fibrillation (AF) is a common health problem with substantial individual and societal costs. The origin of AF has been debated for more than a century, and the precise, biophysical mechanisms that are responsible for the initiation and maintenance of the chaotic electrochemical waves that define AF, remains unclear. It is well accepted that the outlet of the pulmonary veins is the primary anatomical site of AF initiation, and that electrical isolation of these regions remains the most effective treatment for AF. Furthermore, it is well known that certain ion channel or transporter mutations can significantly increase the likelihood of AF. Here, we present a computational model capable of characterizing functionally important features of the microanatomical and electrophysiological substrate that represents the transition from the pulmonary veins (PV) to the left atrium (LA) of the human heart. This model is based on a finite element representation of every myocyte in a segment of this (PV/LA) region. Thus, it allows for investigation a mix of typical PV and LA myocytes. We use the model to investigate the likelihood of ectopic beats and re-entrant waves in a cylindrical geometry representing the transition from PV to LA. In particular, we investigate and illustrate how six different AF- associated mutations can alter the probability of ectopic beats and re-entry in this region.

biophysics↗

bioRxiv2020

Quantitative cross-species translators of cardiac myocyte electrophysiology: model training, experimental validation, and applications

Animal experimentation is key in the evaluation of cardiac efficacy and safety of novel therapeutic compounds. However, inter-species differences in the mechanisms regulating excitation-contraction coupling can limit the translation of experimental findings from animal models to human physiology, and undermine the assessment of drugs efficacy and safety. Here, we built a suite of translators for quantitatively mapping electrophysiological responses in ventricular myocytes across species. We trained these statistical operators using a broad dataset obtained by simulating populations of our biophysically detailed computational models of action potential and Ca2+ transient in mouse, rabbit, and human. We then tested our translators against experimental data describing the response to stimuli, such as ion channel block, change in beating rate, and {beta}-adrenergic challenge. We demonstrate that this approach is well suited to predicting the effects of perturbations across different species or experimental conditions, and suggest its integration into mechanistic studies and drug development pipelines.

systems biology↗

bioRxiv2020

Sex-specific classification of drug-induced Torsade de Pointes susceptibility using cardiac simulations and machine learning

Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for all new therapeutic compounds. Unfortunately, these have proven to be poor predictors of torsadogenic risk, and are likely to have prevented safe compounds from reaching clinical phases. While this has stimulated numerous efforts to define new paradigms for cardiac safety, none of the recently developed strategies accounts for patient conditions. In particular, despite being a well-established independent risk factor for TdP, female sex is vastly underrepresented in both basic research and clinical studies, and thus current TdP metrics are likely biased toward the male sex. Here, we apply statistical learning to synthetic data, generated by simulating drug effects on cardiac myocyte models capturing male and female electrophysiology, to develop new sex-specific classification frameworks for TdP risk. We show that (1) TdP classifiers require different features in females vs. males; (2) malebased classifiers perform more poorly when applied to female data; (3) female-based classifier performance is largely unaffected by acute effects of hormones (i.e., during various phases of the menstrual cycle). Notably, when predicting TdP risk of intermediate drugs on female simulated data, male-biased predictive models consistently underestimate TdP risk in women. Therefore, we conclude that pipelines for preclinical cardiotoxicity risk assessment should consider sex as a key variable to avoid potentially lifethreatening consequences for the female population.

pharmacology and toxicology↗

bioRxiv2020

A unified computational model for cortical post-synaptic plasticity

Cortical synapses possess a machinery of signalling pathways that leads to various modes of post-synaptic plasticity. Such pathways have been examined to a great detail separately in many types of experimental studies. However, a unified picture on how multiple biochemical pathways collectively shape the observed synaptic plasticity in the neocortex is missing. Here, we built a biochemically detailed model of post-synaptic plasticity that includes the major signalling cascades, namely, CaMKII, PKA, and PKC pathways which, upon activation by Ca2+, lead to synaptic potentiation or depression. We adjusted model components from existing models of intracellular signalling into a single-compartment simulation framework. Furthermore, we propose a statistical model for the prevalence of different types of membrane-bound AMPA-receptor tetramers consisting of GluR1 and GluR2 subunits in proportions suggested by the biochemical signalling model, which permits the estimation of the AMPA-receptor-mediated maximal synaptic conductance. We show that our model can reproduce neuromodulator-gated spike-timing-dependent plasticity as observed in the visual cortex. Moreover, we demonstrate that our model can be fit to data from many cortical areas and that the resulting model parameters reflect the involvement of the pathways pinpointed by the underlying experimental studies. Our model explains the dependence of different forms of plasticity on the availability of different proteins and can be used for the study of mental disorder-associated impairments of cortical plasticity. Significance statementNeocortical synaptic plasticity has been studied experimentally in a number of cortical areas, showing how interactions between neuromodulators and post-synaptic proteins shape the outcome of the plasticity. On the other hand, non-detailed computational models of long-term plasticity, such as Hebbian rules of synaptic potentiation and depression, have been widely used in modelling of neocortical circuits. In this work, we bridge the gap between these two branches of neuroscience by building a detailed model of post-synaptic plasticity that can reproduce observations on cortical plasticity and provide biochemical meaning to the simple rules of plasticity. Our model can be used for predicting the effects of chemical or genetic manipulations of various intracellular signalling proteins on induction of plasticity in health and disease.

neuroscience↗

bioRxiv2018

Inversion and computational maturation of drug response using human stem cell derived cardiomyocytes in microphysiological systems

While cardiomyocytes differentiated from human induced pluripotent stems cells (hiPSCs) hold great promise for drug screening, the electrophys-iological properties of these cells can be variable and immature, producing results that are significantly different from their human adult counterparts. Here, we describe a computational framework to address this limitation, and show how in silico methods, applied to measurements on immature cardiomyocytes, can be used to both identify drug action and to predict its effect in mature cells. Our synthetic and experimental results indicate that optically obtained waveforms of voltage and calcium from microphysiological systems can be inverted into information on drug ion channel blockage, and then, through assuming functional invariance of proteins during maturation, this data can be used to predict drug induced changes in mature ventricular cells. Together, this pipeline of measurements and computational analysis could significantly improve the ability of hiPSC derived cardiomycocytes to predict dangerous drug side effects.

biophysics↗