Abstract
Inter-cellular heterogeneity is central to the dynamic range and robustness of function in many tissues, particularly electrically excitable tissues. In pancreatic islet 𝛽-cells, inter-cellular heterogeneity underlies the range of insulin response to glucose. In human-induced-pluripotent stem cell-derived cardiomyocytes (hiPSCCMs), inter-cellular heterogeneity presents a key challenge for drug screening applications. In this study, we assess the ability to reconstruct inter-cellular heterogeneity in silico by applying a “population of models” (PoMs) framework, i.e. collections of computational cells created via Monte Carlo variation of model parameters. We define parameter variation based on experimentally observed heterogeneity in properties such as ion current conductances and enzymatic affinities. We then assess the accuracy of those reconstructions, based on the degree to which variation in PoM outputs (e.g. action potential duration) matches experimentally observed variation. We report that this “ground-up” approach underestimates functional heterogeneity in the hiPSC-CM population, but overestimates it in adult human cardiomyocytes. In contrast, the 𝛽-cell PoM captures three distinct and physiologically relevant subclasses of 𝛽-cell function. In the future, we expect PoM approaches like these willpermit incorporation of realistic cellular heterogeneity in detailed models of intact tissues, and thereby aid development of sophisticated tissue-engineered platforms for therapeutics.
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Bloothooft, M., Shuttleworth, J.G., Neiman, G., Goswami, I., Edwards, A.G. (2023). Recapitulating Functional Heterogeneity in Electrophysiologically Active Tissues. In: McCabe, K.J. (eds) Computational Physiology. Simula SpringerBriefs on Computing(), vol 13. Springer, Cham. https://doi.org/10.1007/978-3-031-25374-4_4
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DOI: https://doi.org/10.1007/978-3-031-25374-4_4
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