Abstract

Sarcomeres are the basic contractile units of cardiac muscles. We cultured individual hiPSC-derived cardiomyocytes on biomimetic patterned substrate. We automatically tracked single sarcomere dynamics from high-speed confocal recordings with a custom machine-learning tool. While the emergent cell-level motion is very smooth, we revealed highly stochastic and heterogeneous motion of single sarcomeres. Rigid mechanical constraints force sarcomeres into a tug-of-war like competition driving dynamic heterogeneity. Analysis of a large data set (>1200 cells) indicates that sarcomere heterogeneity is not caused by static non-uniformity among sarcomeres (e.g., strong/weak units), but can be primarily attributed to the stochastic and non-linear nature of sarcomere dynamics and thus occurs intrinsically during cardiomyocyte beating. We show that a simple dynamic model reproduces crucial experimental findings by assuming non-monotonic force-velocity relations for single sarcomeres, as previously predicted for ensembles of motor proteins. This led us to a novel, active matter perspective on sarcomere motion, with sarcomeres as interacting non-linear and stochastic agents.