Biology subjects

Clark, A. P.

Publications and source records attributed to Clark, A. P..

10 recordsLinked to original sources

bioRxiv2026

SP1 tethers NR2F2 to drive atrial cardiomyocyte identity

Human heart development is guided by complex gene regulatory networks (GRNs), which are difficult to unravel and differ from that in animal models. In this study, we use a systematic approach to identify gene interactions driving human fetal atrial cardiomyocyte identity. We inferred GRNs for atrial and ventricular cardiomyocytes from human fetal single-cell RNA-seq and ATAC-seq data, predicting transcription factors that differentially regulate atrial vs. ventricular cardiomyocyte identity. Comparison of GRNs constrained by ATAC-seq vs. promoter annotations revealed that during human heart development, the canonical transcription factor for atrial specification, NR2F2, drives atrial genes not directly but by interacting with SP1. The predicted NR2F2-SP1 relationship at atrial gene promoters was supported with AlphaFold predictions of biophysical tethering and comparison with previous ChIP-seq data. These predictions were experimentally validated in human iPSC-derived atrial cardiomyocyte differentiation, which was suppressed by SP1 knockdown. Further, proximity ligation experiments validated the physical interaction of NR2F2 and SP1 in the nucleus, coincident with atrial identity. This study reveals SP1 as a transcription factor necessary for atrial cardiomyocyte identity in human development, helping to coordinate the effects of NR2F2. Furthermore, comparing GRNs based on current and potential epigenetic state offers a novel systematic approach to study interactions between transcription factors, which is key to understanding complex GRNs.

developmental biology↗

bioRxiv2026

Paired single-cell imaging of calcium and expres-sion to map niches of identity and function

Cellular identity is often inferred from molecular markers, while function is measured independently, obscuring how these dimensions align at single-cell resolution. In cardiomyocytes, this disconnect is especially limiting, as calcium dynamics and subtype markers are typically assessed in bulk or separate cells then averaged across populations. In human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), this gap has limited our ability to determine whether heterogeneity in electrophysiology and calcium handling reflects noise, maturation, or structured biological states. This lack of clarity is due in part to the lack of methods that directly link live functional measurements with molecular identity at single-cell resolution. Here, we introduce CARBONITE (Calcium Recordings Before Identification by Expression), a scalable single-cell imaging framework that pairs live calcium dynamics with protein expression and spatial phenotyping. Using high-content imaging in 96-well plates, CARBONITE integrates per-cell calcium transient features with immunofluorescent identification applied to cardiomyocyte subtype markers, enabling quantitative functional-molecular mapping within the same cells. Applying CARBONITE to mixed human induced pluripotent stem cell derived cardiomyocyte (iPSC-CM) populations reveals heterogeneity in calcium transient dynamics and marker expression within individual wells. Canonical atrial and ventricular markers capture only a subset of functional variability. Notably, calcium transient shape segregates cells into two discrete functional states that exhibit perinuclear ANP (atrial marker) enrichment and nucleation state (i.e., mono- vs. binucleation). Notably, these groups show know relationship to MYL2 (ventricular marker) expression. Binucleated cells are more likely to exhibit a spike-like calcium transient, identifying nucleation as a dominant and previously underappreciated axis of cardiomyocyte identity influencing calcium function. Together, these results establish CARBONITE as a functional multimodal single-cell platform that reveals organizational principles of cell identity, providing a foundation for dissecting functional niches in development and disease.

bioengineering↗

bioRxiv2025

Reduced TBX5 dosage undermines developmental control of atrial cardiomyocyte identity in a model of human atrial disease

While atrial septal defects (ASDs) and atrial fibrillation (AF) present differently, there is evidence that they share some genetic basis. Here, we used directed differentiation of human induced pluripotent stem cells into atrial or ventricular cardiomyocytes (CMs) to delineate gene regulatory networks (GRNs) that define each identity. We uncovered accessible chromatin regions, transcription factor motifs and key regulatory nodes specific to, or shared by, both CM types, including the transcription factor TBX5, which is linked to genetic susceptibility of ASDs and AF in humans. Complete TBX5 loss resulted in a near absence of atrial CMs with a concomitant increase in the abundance of other cell types. Reduced dosage of TBX5 in human atrial CMs caused cellular, electrophysiologic and molecular phenotypes consistent with features of atrial CM dysfunction. This included dose-dependent aberrant accessibility of many chromatin regions and perturbation of gene regulatory networks of atrial CM identity. These results suggest that, in addition to stemming from ion channel or extracellular matrix dysfunction, atrial diseases such as ASDs or AF may result from disruptions of atrial CM identity.

developmental biology↗

bioRxiv2024

Heart tube morphogenesis is regulated by segment-specific gene regulatory networks controlled by MEF2C

The gene regulatory networks (GRNs) that control early heart formation are beginning to be understood, but lineage-specific GRNs remain largely undefined. We investigated networks controlled by the vital transcription factor MEF2C, with a time course of single-nucleus RNA- and ATAC-sequencing in wild-type and Mef2c-null embryos. We identified a "posteriorized" cardiac gene signature and chromatin landscape in the absence of MEF2C. Integrating our multiomics data in a deep learning-based model, we constructed developmental trajectories for each of the outflow tract, ventricular, and inflow tract segments, and alterations of these in Mef2c-null embryos. We computationally identified segment-specific MEF2C-dependent enhancers, with activity in the developing zebrafish heart. Finally, using inferred GRNs we discovered that the Mef2c-null heart malformations are partly driven by increased activity of the nuclear hormone receptor NR2F2. Our results delineate lineage-specific GRNs in the early heart tube and provide a generalizable framework for dissecting transcriptional networks governing developmental processes.

developmental biology↗

bioRxiv2024

Resolving artefacts in voltage-clamp experiments with computational modelling: an application to fast sodium current recordings

Cellular electrophysiology is the foundation of many fields, from basic science in neurology, cardiology, oncology to safety critical applications for drug safety testing, clinical phenotyping, etc. Patch-clamp voltage clamp is the gold standard technique for studying cellular electrophysiology. Yet, the quality of these experiments is not always transparent, which may lead to erroneous conclusions for studies and applications. Here, we have developed a new computational approach that allows us to explain and predict the experimental artefacts in voltage-clamp experiments. The computational model captures the experimental procedure and its inadequacies, including: voltage offset, series resistance, membrane capacitance and (imperfect) amplifier compensations, such as series resistance compensation and supercharging. The computational model was validated through a series of electrical model cell experiments. Using this computational approach, the artefacts in voltage-clamp experiments of cardiac fast sodium current, one of the most challenging currents to voltage clamp, were able to be resolved and explained through coupling the observed current and the simulated membrane voltage, including some typically observed shifts and delays in the recorded currents. We further demonstrated that the typical way of averaging data for current-voltage relationships would lead to biases in the peak current and shifts in the peak voltage, and such biases can be in the same order of magnitude as those differences reported for disease-causing mutations. Therefore, the presented new computational pipeline will provide a new standard of assessing the voltage-clamp experiments and interpreting the experimental data, which may be able to rectify and provide a better understanding of ion channel mutations and other related applications.

systems biology↗

bioRxiv2024

Logic-based modeling of biological networks with Netflux

Molecular signaling networks drive a diverse range of cellular decisions, including whether to proliferate, how and when to die, and many processes in between. Such networks often connect hundreds of proteins, genes, and processes. Understanding these complex networks is aided by computational modeling, but these tools require extensive programming knowledge. In this article, we describe a user-friendly, programming-free network simulation tool called Netflux (https://github.com/saucermanlab/Netflux). Over the last decade, Netflux has been used to construct numerous predictive network models that have deepened our understanding of how complex biological networks make cell decisions. Here, we provide a Netflux tutorial that covers how to construct a network model and then simulate network responses to perturbations. Upon completion of this tutorial, you will be able to construct your own model in Netflux and simulate how perturbations to proteins and genes propagate through signaling and gene-regulatory networks.

bioengineering↗

bioRxiv2023

Optimization of a Cardiomyocyte Model Illuminates Role of Increased INaL in Repolarization Reserve

Cardiac ion currents may compensate for each other when one is compromised by a congenital or drug-induced defect. Such redundancy contributes to a robust repolarization reserve that can prevent the development of lethal arrhythmias. Most efforts made to describe this phenomenon have quantified contributions by individual ion currents. However, it is important to understand the interplay between all major ion channel conductances, as repolarization reserve is dependent on the balance between all ion currents in a cardiomyocyte. Here, a genetic algorithm was designed to derive a profile of nine ion-channel conductances that optimizes repolarization reserve in a mathematical cardiomyocyte model. Repolarization reserve was quantified using a previously defined metric, repolarization reserve current, i.e., the minimum constant current to prevent normal action potential repolarization in a cell. The optimization improved repolarization reserve current by 77 % compared to baseline in a human adult ventricular myocyte model and increased resistance to arrhythmogenic insult. The optimized conductance profile was characterized by increased repolarizing current conductances, but also uncovered a previously un-reported behavior by the late sodium current. Simulations demonstrated that upregulated late sodium increased action potential duration, without compromising repolarization reserve current. The finding was generalized to multiple models. Ultimately, this computational approach in which multiple currents were studied simultaneously illuminated mechanistic insights into how the metrics magnitude could be increased, and allowed for the unexpected role of late sodium to be elucidated. NEW & NOTEWORTHYGenetic algorithms are typically used to fit models or extract desired parameters from data. Here, we utilize the tool to produce a ventricular cardiomyocyte model with increased repolarization reserve. Since arrhythmia mitigation is dependent on multiple cardiac ion-channel conductances, study using a comprehensive, unbiased, and systems-level approach is important. This use of this optimization strategy allowed us to find a robust profile that illuminated unexpected mechanistic determinants of key ion-channel conductances in repolarization reserve.

physiology↗

bioRxiv2023

Rapid ionic current phenotyping (RICP) identifies mechanistic underpinnings of iPSC-CM AP heterogeneity

As a renewable, easily accessible, human-derived in vitro model, human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) are a promising tool for studying arrhythmia-related factors, including cardiotoxicity and congenital proarrhythmia risks. An oft-mentioned limitation of iPSC-CMs is the abundant cell-to-cell variability in recordings of their electrical activity. Here, we develop a new method, rapid ionic current phenotyping (RICP), that utilizes a short (10 s) voltage clamp protocol to quantify cell-to-cell heterogeneity in key ionic currents. We correlate these ionic current dynamics to action potential recordings from the same cells and produce mechanistic insights into cellular heterogeneity. We present evidence that the L-type calcium current is the main determinant of upstroke velocity, rapid delayed rectifier K+ current is the main determinant of the maximal diastolic potential, and an outward current in the excitable range of slow delayed rectifier K+ is the main determinant of action potential duration. We measure an unidentified outward current in several cells at 6 mV that is not recapitulated by iPSC-CM mathematical models but contributes to determining action potential duration. In this way, our study both quantifies cell-to-cell variability in membrane potential and ionic currents, and demonstrates how the ionic current variability gives rise to action potential heterogeneity. Based on these results, we argue that iPSC-CM heterogeneity should not be viewed simply as a problem to be solved but as a model system to understand the mechanistic underpinnings of cellular variability. New & NoteworthyWe present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage clamp protocol. The method captures a rich snapshot of ionic currents that provides quantitative information about multiple currents (e.g., ICaL, IKr) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of IKr in establishing the maximum diastolic potential.

bioengineering↗

bioRxiv2022

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

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, 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. Here, we use in silico and in vitro studies to demonstrate how seal-leak current depolarises action potentials (APs), substantially affecting their morphology, even with seal resistances (Rseal) above 1 G{Omega}. We show that compensation of this leak current is difficult due to challenges with recording 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 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. Based on these findings, we make three 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. Key pointsO_LIHuman induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are an essential tool in the study of cardiac arrhythmia mechanisms. C_LIO_LITheir immature and heterogeneous action potential phenotype complicates the interpretation of experimental data, and has slowed their acceptance in industry and academia. C_LIO_LIWe suggest that a leak current caused by an imperfect pipette-membrane seal during single-cell patch-clamp experiments is partly responsible for inducing this phenotype. C_LIO_LIUsing in vitro experiments and computational modelling, we show that this seal-leak current affects iPSC-CM AP morphology, even under ideal experimental conditions. C_LIO_LIBased on these findings, we make recommendations that should be considered when interpreting, analysing and fitting iPSC-CM data. C_LI

physiology↗

bioRxiv2021

A model-guided pipeline for drug cardiotoxicity screening with human stem-cell derived cardiomyocytes

New therapeutic compounds go through a preclinical drug cardiotoxicity screening process that is overly conservative and provides limited mechanistic insight, leading to the misclassification of potentially beneficial drugs as proarrhythmic. There is a need to develop a screening paradigm that maintains this high sensitivity, while ensuring non-cardiotoxic compounds pass this phase of the drug approval process. In this study, we develop an in vitro-in silico pipeline using human induced stem-cell derived cardiomyocytes (iPSC-CMs) to address this problem. The pipeline includes a model-guided optimization that produces a voltage-clamp (VC) protocol to determine drug block of seven cardiac ion channels. Such VC data, along with action potential (AP) recordings, were acquired from iPSC-CMs before and after treatment with a control solution or a low-, intermediate-, or high-risk drug. We identified significant AP prolongation (a proarrhythmia indicator) in two high-risk drugs and, from the VC data, determined strong ion channel blocks that led to the AP changes. The VC data also uncovered an undocumented funny current (If) block by quinine, which we confirmed with experiments using a HEK-293 expression line. We present a new approach to cardiotoxicity screening that simultaneously evaluates proarrhythmia risk (e.g. AP prolongation) and mechanism (e.g. channel block) from iPSC-CMs.

bioengineering↗