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Mirams, G. R.

Publications and source records attributed to Mirams, G. R..

At least 19 recordsLinked to original sources
bioRxiv2026

Lysosomal abundance in young and aged mouse hearts assessed by In Vivo Imaging Systems (IVIS) Lysotracker imaging and autophagy-related gene expression

Lysosomal function is essential for cardiac proteostasis and cellular health, yet its regulation during ageing remains poorly defined. We hypothesised that ageing alters both the abundance of acidic organelles and the machinery supporting their acidification. Using fluorescence-based In Vivo Imaging Systems (IVIS) with Lysotracker Red in young (2-4 months) and aged (18 months) mouse hearts, we quantified whole-heart acidic-vesicle signals and assessed expression of lysosomal and autophagy-related genes (Lamp2, Atp6v1a, Sqstm1, Cd63, Atg12, Nfe2l2, M6pr) by RT-qPCR. Whole-heart labelled Lysotracker fluorescence did not differ significantly between age groups, indicating preservation of the total acidic-vesicle pool. No changes in Atp6v1a and Lamp2 expression suggest acidification capacity and structural stability are maintained, whereas the minor, upregulation of Sqstm1 might indicate increased autophagic demand and altered vesicle trafficking, which warrants further investigation. No statistical significant changes in M6pr, Atg12, or Nfe2l2 were detected, suggesting transcriptional stability in enzyme trafficking, core autophagy, and oxidative stress pathways. Regionally, atria showed higher Lysotracker signal than ventricles, consistent with known enrichment of acidic vesicular stores in atrial physiology. These findings highlight the utility of IVIS imaging of Lysotracker-labelled hearts, providing rapid whole-organ assessment of acidic vesicle distribution, albeit with limited depth resolution. Complementary techniques such as RT-qPCR analysis is essential to interpret IVIS findings, enabling insight into underlying molecular changes in lysosomal and autophagy pathways during cardiac ageing.

physiology↗
bioRxiv2025

Comparison of in silico predictions of action potential duration in response to inhibition of IKr and ICaL with new human ex vivo recordings

During drug development, candidate compounds are extensively tested for proar-rhythmic risk and in particular risk of Torsade de Pointes (TdP), as indicated by prolongation of the QT interval. Drugs that inhibit the rapid delayed rectifier K+ current (IKr) can prolong the action potential duration (APD) and thereby the QT interval, and so are routinely rejected. However, simultaneous inhibition of the L-type Ca2+ current (ICaL) can mitigate the effect of IKrinhibition, so that including both effects can improve test specificity. Mathematical models of the action potential (AP) can be used to predict the APD prolongation resulting from a given level of IKr and ICaL inhibition, but for use in safety-testing their predictive capabilities should first be carefully verified. We present the first systematic comparison between experimental drug-induced APD and predictions by AP models. New experimental data were obtained ex vivo for APD response to IKr and/or ICaL inhibition by applying 9 compounds at different concentrations to adult human ventricular trabeculae at physiological temperature. Compounds with similar effects on IKr and ICaL exhibited less APD prolongation compared to selective IKr inhibitors. We then integrated in vitro IC50 patch-clamp data for IKr and ICaL inhibition by the tested compounds into simulations with AP models. Models were assessed against the ex vivo data on their ability to recapitulate drug-induced APD changes observed experimentally. None of the tested AP models reproduced the APD changes observed experimentally across all combinations and degrees of IKr and/or ICaL inhibition: they matched the data either for selective IKr inhibitors or for compounds with comparable effects on IKr and ICaL. This work introduces a new benchmarking framework to assess the predictivity of current and future AP models for APD response to IKr and/or ICaL inhibition. This is an essential primary step towards an in silico framework that integrates in vitro data for translational clinical cardiac safety. Author summaryBefore an investigational drug reaches patients, it is tested in vitro to ensure it does not disrupt the hearts electric activity. This testing often focuses on the drugs ability to block a specific current called IKr, which, if inhibited, can prolong the heart cells action potential duration (APD), which is associated with an increased risk of irregular heartbeats (proarrhythmia). Our study examines how blocking another current, ICaL, along with IKr, affects APD. We found that adding ICaL inhibition may mitigate the proarrhythmic effects caused by IKr inhibition alone. Understanding this balance can improve how we assess the cardiac safety of new drugs, potentially saving promising compounds from being incorrectly discarded. Currently, mathematical models help predict such cardiac responses, but no existing model accurately predicted our findings. Our new data could aid in developing more predictive models in the future. This will contribute to safer drug development and more effective treatments.

pharmacology and toxicology↗
bioRxiv2025

IonBench: a benchmark of optimisation strategies for mathematical models of ion channel currents

Ion channel models present many challenging optimisation problems. These include unidentifiable parame- ters, noisy data, unobserved states, and a combination of both fast and slow timescales. This can make it difficult to choose a suitable optimisation routine a priori. Nevertheless, many attempts have been made to design optimisation routines specifically for ion channel models, however, little work has been done to compare these optimisation approaches. We have developed ionBench, an open-source optimisation bench- marking framework, to evaluate and compare these approaches against a standard set of ion channel optimisation problems. We included implementations of thirty-four unique optimisation approaches that have been previously applied to ion channel models and evaluated them against the ionBench test suite, consisting of five parameter optimisation problems derived from the cardiac ion channel literature. Each optimisation approach was initiated from multiple starting parameters and tasked with reproducing a problem-specific simulated dataset. Through ionBench, we tracked and evaluated the performance of these optimisations, identifying the expected run time until a successful optimisation for each approach, which was used for comparisons. Finally, we used these results, in addition to other literature results, to identify a new efficient approach. Its use could reduce computation time by multiple orders of magnitude, while also improving the reliability of ion channel parameter optimisation.

biophysics↗
bioRxiv2024

Optimising experimental designs for model selection of ion channel drug binding mechanisms

The rapid delayed rectifier current carried by the human Ether-a-go-go-Related Gene (hERG) channel is susceptible to drug-induced reduction which can lead to an increased risk of cardiac arrhythmia. Establishing the mechanism by which a specific drug compound binds to hERG can help to reduce uncertainty when quantifying pro-arrhythmic risk. In this study, we introduce a methodology for optimising experimental voltage protocols to produce data that enable different proposed models for the drug-binding mechanism to be distinguished. We demonstrate the performance of this methodology via a synthetic data study. If the underlying model of hERG current is known exactly, then the optimised protocols generated show noticeable improvements in our ability to select the true model when compared to a simple protocol used in previous studies. However, if the model is not known exactly, and we assume a discrepancy between the data-generating hERG model and the hERG model used in fitting the models, then the optimised protocols become less effective in determining the true binding dynamics. While the introduced methodology shows promise, we must be careful to ensure that, if applied in a real data study, we have a well-calibrated model of hERG current gating.

pharmacology and toxicology↗
bioRxiv2024

Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs

Mathematical models are increasingly being relied upon to provide quantitatively accurate predictions of cardiac electrophysiology. Many such models concern the behaviour of particular subcellular components (namely, ion channels) which, together, allow the propagation of electrical signals through heart-muscle tissue--namely, the firing of action potentials. In particular, IKr, a voltage-sensitive potassium ion-channel current, is of interest owing to its central pores propensity for blockage by various small molecules. We use newly collected data obtained from an ensemble of voltage-clamp experiments to validate the predictive accuracy of various dynamical models of IKr. To do this, we fit models to each protocol individually, and quantify the error in the resultant model predictions. This allows the comparison of predictive accuracy for IKr models under a diverse collection of previously unexplored dynamics. Our results highlight heterogeneity between parameter estimates obtained from different cells, suggesting the presence of latent effects not yet accounted for in our models. This heterogeneity has a significant impact on our parameter estimates and suggests routes for model improvement.

biophysics↗
bioRxiv2024

A range of voltage-clamp protocol designs for rapid capture of hERG kinetics

We provide details of a series of short voltage-clamp protocols designed for gathering a large amount of information on hERG (Kv11.1) ion channel gating. The protocols have a limited number of steps and consist only of steps and ramps, making them easy to implement on any patch clamp setup, including automated platforms. The primary objective is to assist with parameterisation, selection and refinement of mathematical models of hERG gating. We detail a series of manual and automated model-driven designs, together with an explanation of their rationale and design criteria. Although the protocols are intended to study hERG1a currents, the approaches could be easily extended and generalised to other ion channel currents.

biophysics↗
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

Variability in reported midpoints of (in)activationof cardiac INa

Electrically active cells like cardiomyocytes show variability in their size, shape, and electrical activity. But should we expect variability in the properties of their ionic currents? In this brief review we gather and visualise measurements of two important electrophysiological parameters: the midpoints of activation and inactivation of the cardiac fast sodium current, INa. We find a considerable variation in reported mean values between experiments, with a smaller cell-to-cell variation within experiments. We show how the between-experiment variability can be decomposed into a correlated and an uncorrelated component, and that the correlated component is much larger and affects both midpoints almost equally. We then review biological and methodological issues that might explain the observed variability, and attempt to classify each as within-experiment or correlated and uncorrelated between-experiment factors. Although the existence of some variability in measurements of ionic currents is well-known, we believe that this is the first work to systematically review it and that the scale of the observed variability is much larger than commonly appreciated, which has implications for modelling and experimental design.

cell biology↗
bioRxiv2024

Optimal experimental designs for characterising ion channel gating by filling the phase-voltage space of model dynamics

Voltage-clamp waveforms are imposed in the patch-clamp electrophysiology technique to provoke ion currents, the particular waveform that is used is known as the voltage-clamp protocol. Designing protocols to probe and quantify how gating for a particular ion channel occurs has typically been done manually and results in a suite of long protocols. It is desirable to gain the same, or even more, information in a shorter time, and also to automate the process of designing these protocols. In this paper we introduce a new optimal experimental design objective for ion channel characterisation, which involves considering a 3-dimensional phase space for the channel states combined with the voltage, using room-temperature hERG/Kv11.1 currents as an example. A range of designs are proposed, the best of which visits 82% of the discretised phase-voltage space in a 9 second protocol. This new protocol design strategy results in a simulated current visiting a wide range of channel gating states, at a wide variety of voltages, and we therefore expect these designs to be very useful in characterising ion currents, parameterising models, as well as being a challenging test of assumptions made about ion channel gating.

biophysics↗
bioRxiv2023

Neural network emulation of the human ventricular cardiomyocyte action potential: a tool for more efficient computation in pharmacological studies

AbstractComputer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.21 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

cell biology↗
bioRxiv2023

The impact of uncertainty in hERG binding mechanism on in silico predictions of drug-induced proarrhythmic risk

Background and PurposeDrug-induced reduction of the rapid delayed rectifier potassium current carried by the human Ether-a-go-go-Related Gene (hERG) channel is associated with increased risk of arrhythmias. Recent updates to drug safety regulatory guidelines attempt to capture each drugs hERG binding mechanism by combining in vitro assays with in silico simulations. In this study, we investigate the impact on in silico proarrhythmic risk predictions due to uncertainty in the hERG binding mechanism and physiological hERG current model. Experimental ApproachPossible pharmacological binding models were designed for the hERG channel to account for known and postulated small molecule binding mechanisms. After selecting a subset of plausible binding models for each compound through calibration to available voltage-clamp electrophysiology data, we assessed their effects, and the effects of different physiological models, on proarrhythmic risk predictions. Key ResultsFor some compounds, multiple binding mechanisms can explain the same data produced under the safety testing guidelines, which results in different inferred binding rates. This can result in substantial uncertainty in the predicted torsade risk, which often spans more than one risk category. By comparison, we found that the effect of a different hERG physiological current model on risk classification was subtle. Conclusion and ImplicationsThe approach developed in this study assesses the impact of uncertainty in hERG binding mechanisms on predictions of drug-induced proarrhythmic risk. For some compounds, these results imply the need for additional binding data to decrease uncertainty in safety-critical applications.

biophysics↗
bioRxiv2023

Compartmentalisation proteomics revealed endolysosomal protein network changes in a goat model of atrial fibrillation

Endolysosomes (EL) are known for their role in regulating both intracellular trafficking and proteostasis. EL help facilitate elimination of damaged membrane and cytosolic proteins, protein aggregates, membranous organelles and also play an important role in calcium signalling. Despite the importance of EL, their specific role in cardiovascular disease is not well understood. In particular, its unclear how EL contribute to atrial pathology over longer time frames. To shed light on this question, we conducted a comprehensive analysis that involved proteomics, transcriptomics, integrated analysis, electron tomography, western blotting, and enzyme assays. To identify the role of EL in atrial fibrillation (AF), we applied a recently published organelle protein isolation method. We used this method to study biopsies from AF goat model and analyse the EL-specific proteins and pathways involved in this condition. Our results revealed the upregulation of the AMPK pathway and the expression of EL-specific proteins that were not found in whole tissue lysates (TL), including GAA, DYNLRB1, CLTB, SIRT3, CCT2, and muscle-specific HSPB2. We also observed structural anomalies, such as autophago-vacuole formation, irregularly shaped mitochondria, and glycogen deposition, which provide insights into the ELs contribution to AF and related pathways and molecular mechanisms. Overall, our findings suggest that EL play an important role in the development of AF over longer time frames, and provide a more detailed understanding of the underlying molecular processes involved.

molecular biology↗
bioRxiv2022

Model-driven optimal experimental design for calibrating cardiac electrophysiology models

Models of the cardiomyocyte action potential (AP) have contributed immensely to the understanding of heart function, pathophysiology, and the origin of heart rhythm disturbances. However, AP models are nonlinear, complex, and can contain more than a hundred differential equations, making them difficult to parameterise. Therefore, cellular cardiac models have been limited to describing average cell dynamics, when cell-specific models would be ideal to uncover inter-cell variability but are too experimentally challenging to be achieved. Here, we focus on automatically designing experimental protocols that allow us to better identify cell-specific maximum conductance values for each major current type--optimal experimental designs--for both voltage-clamp and current-clamp experiments. We show that optimal designs are able to perform better than many of the existing experiment designs in the literature in terms of identifying model parameters and hence model predictive power. For cardiac cellular electrophysiology, this approach will allow researchers to define their hypothesis of the dynamics of the system and automatically design experimental protocols that will result in theoretically optimal designs.

systems biology↗
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↗
bioRxiv2022

Ion channel model reduction using manifold boundaries

Mathematical models of voltage-gated ion channels are used in basic research, industrial and clinical settings. These models range in complexity, but typically contain numerous variables representing the proportion of channels in a given state, and parameters describing the voltage-dependent rates of transition between states. An open problem is selecting the appropriate degree of complexity and structure for an ion channel model given data availability. Here, we simplify a model of the cardiac human Ether-a-go-go Related Gene (hERG) potassium ion channel, which carries cardiac IKr, using the manifold boundary approximation method (MBAM). The MBAM approximates high-dimensional model-output manifolds by reduced models describing their boundaries, resulting in models with fewer parameters (and often variables). We produced a series of models of reducing complexity starting from an established 5-state hERG model with 15 parameters. Models with up to 3 fewer states and 8 fewer parameters were shown to retain much of the predictive capability of the full model and were validated using experimental hERG1a data collected in HEK293 cells at 37{degrees}C. The method provides a way to simplify complex models of ion channels that improves parameter identifiability and will aid in future model development.

biophysics↗
bioRxiv2021

Models of the cardiac L-type calcium current: a quantitative comparison

The L-type calcium current (ICaL) plays a critical role in cardiac electrophysiology, and models of ICaL are vital tools to predict arrhythmogenicity of drugs and mutations. Five decades of measuring and modelling ICaL have resulted in several competing theories (encoded in mathematical equations). However, the introduction of new models has not typically been accompanied by a data-driven critical comparison with previous work, so that it is unclear which model is best suited for any particular application. In this review, we describe and compare 73 published mammalian ICaL models, and use simulated experiments to show that there is a large variability in their predictions, which is not substantially diminished when grouping by species or other categories. We provide model code for 60 models, list major data sources, and discuss experimental and modelling work that will be required to reduce this huge list of competing theories and ultimately develop a community consensus model of ICaL.

cell biology↗
bioRxiv2019

Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments

Mathematical models of ion channels, which constitute indispensable components of action potential models, are commonly constructed by fitting to whole-cell patch-clamp data. In a previous study we fitted cell-specific models to hERG1a (Kv11.1) recordings simultaneously measured using an automated high-throughput system, and studied cell-cell variability by inspecting the resulting model parameters. However, the origin of the observed variability was not identified. Here we study the source of variability by constructing a model that describes not just ion current dynamics, but the entire voltage-clamp experiment. The experimental artefact components of the model include: series resistance, membrane and pipette capacitance, voltage offsets, imperfect compensations made by the amplifier for these phenomena, and leak current. In this model, variability in the observations can be explained by either cell properties, measurement artefacts, or both. Remarkably, by assuming that variability arises exclusively from measurement artefacts, it is possible to explain a larger amount of the observed variability than when assuming cell-specific ion current kinetics. This assumption also leads to a smaller number of model parameters. This result suggests that most of the observed variability in patch-clamp data measured under the same conditions is caused by experimental artefacts, and hence can be compensated for in post-processing by using our model for the patch-clamp experiment. This study has implications for the question of the extent to which cell-cell variability in ion channel kinetics exists, and opens up routes for better correction of artefacts in patch-clamp data.

biophysics↗