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.

在小体积心肌内的心肌细胞之间存在显着的舒张率变化；然而，尚不清楚这种可变性如何影响心肌的整体松弛机制。在这项研究中，我们试图在计算模型中调节细胞异质性水平，然后使用工程心脏组织平台验证这些预测。我们制定了一个in silico由具有不同松弛率的半肌节组成的组织模型，结合了单细胞心肌细胞实验数据。这些模型组织从半肌节的快速和缓慢松弛群体的两个偏移分布中随机采样松弛参数。等长肌肉抽搐模拟预测了松弛时间与异质组织中快松弛细胞与慢松弛细胞的比例之间的复杂关系。具体来说，快细胞和慢细胞的 50/50 混合物不会导致弛豫时间，这是与两个纯病例相关的弛豫时间的平均值。相反，平均松弛时间以 70:30 的慢速：快速松弛细胞的比例实现，这表明快速松弛细胞对整体组织松弛的影响不成比例。检查此行为是否持续存在在体外，我们从快速和缓慢松弛的人类 iPSC 衍生心肌细胞的两条线构建了工程心脏组织。通过荧光纳米晶体进行的细胞追踪证实了在机械表征时 50/50 混合组织中两种细胞群的存在。这些混合群体工程心脏组织的等长肌肉抽搐松弛时间与模型的预测一致，即测量的 50/50 混合组织的松弛率更接近于 100% 快速松弛细胞制成的组织。我们的观察结果表明，心肌细胞多样性可以在确定组织水平的松弛中发挥重要作用。