Abstract
Substantial variation in relaxation rate exists among cardiomyocytes within small volumes of myocardium; however, it is unknown how this variability affects the overall relaxation mechanics of heart muscle. In this study, we sought to modulate levels of cellular heterogeneity in a computational model, then validate those predictions using an engineered heart tissue platform. We formulated an in silico tissue model composed of half-sarcomeres with varied relaxation rates, incorporating single-cell cardiomyocyte experimental data. These model tissues randomly sampled relaxation parameters from two offset distributions of fast- and slow-relaxing populations of half-sarcomeres. Isometric muscle twitch simulations predicted a complex relationship between relaxation time and the proportion of fast-versus slow-relaxing cells in heterogeneous tissues. Specifically, a 50/50 mixture of fast and slow cells did not lead to relaxation time that was the mean of the relaxation times associated with the two pure cases. Rather, the mean relaxation time was achieved at a ratio of 70:30 slow:fast relaxing cells, suggesting a disproportionate impact of fast-relaxing cells on overall tissue relaxation. To examine whether this behavior persists in vitro, we constructed engineered heart tissues from two lines of fast- and slow-relaxing human iPSC-derived cardiomyocytes. Cell tracking via fluorescent nanocrystals confirmed the presence of both cell populations in the 50/50 mixed tissues at the time of mechanical characterization. Isometric muscle twitch relaxation times of these mixed-population engineered heart tissues showed agreement with the predictions from the model, namely that the measured relaxation rate of 50/50 mixed tissues more closely resembled that of tissues made with 100% fast-relaxing cells. Our observations suggest that cardiomyocyte diversity can play an important role in determining tissue-level relaxation.