Abstract 14927: Real-Time Super-Resolution Analysis of Sarcomere Motion Reveals Context-Dependent Stochastic Heterogeneity in Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Abstract

Studies of sarcomere dynamics in cardiac myofibrils are key to understand how myosin-actin contractility translates to whole heart contractions. Such analyses require high spatial (nm) and temporal (ms) resolution of multiple sarcomeres in parallel. Here, we present a new imaging and computational method to analyze sarcomere structure and function in human induced pluripotent stem cell (iPSC)-derived cardiomyocytes. For this we (1) engineered a fluorescent z-band tag (ACTN2-Citrine) by CRISPR-editing, (2) developed micropatterned soft (7:1, 10 kPa) substrate cultures to mimic in vivo conditions, (3) made use of high-speed microscopy (66 fps), and (4) designed an automated AI-based sarcomere detection and analysis tool (SarcAsM - Sarcomere Analysis Multitool). Cardiomyocytes were differentiated from the ACTN2-Citrine iPSC-line and purified using a staged growth factor and metabolic selection protocol (>95% purity with a ventricular myocyte phenotype). Our analysis revealed highly heterogeneous single sarcomere motion, i.e., shortening and lengthening patterns during the same time of the contraction cycle. Notably, the observed rich dynamics on single sarcomere-level are not apparent from whole cell analyses. Interestingly, culture on stiffer substrates (>20 kPa; mimicking cardiac fibrosis) resulted in reduced cell-level contraction, but constant sarcomere level contractility with however enhanced heterogeneity. Analysis of a large data set (>1,200 cells) in conjunction with a biophysical model showed that heterogeneous sarcomere motion is not caused by static non-uniformity (e.g., strong/weak sarcomeres), but can be primarily attributed to the stochastic and non-linear nature of sarcomere dynamics and thus occurs intrinsically during cardiomyocyte beating. Our findings show that that sarcomere heterogeneity is an important feature of cardiomyocyte contractility. The introduced tools for unbiased high-throughput analysis of sarcomere-level dynamics can be exploited to gain a better understanding on how sarcomere level contractility translates to whole cardiomyocyte contractions under simulated physiological and pathological conditions.