The Effects of Load on Transmural Differences in Contraction of Isolated Mouse Ventricular Cardiomyocytes

Abstract

Mechanical properties of cardiomyocytes from different transmural regions are heterogeneous in the left ventricular wall. The cardiomyocyte mechanical environment affects this heterogeneity because of mechano-electric feedback mechanisms. In the present study, we investigated the effects of load upon transmural differences in contraction of subendocardial (ENDO) and subepicardial (EPI) single cells isolated from the murine left ventricle. Various loads were applied to the cells using carbon fiber techniques for single myocytes. To simulate experimentally obtained results and to predict mechanisms underlying the cellular response to change in load, our mathematical models of the ENDO and EPI cells were used. Extent of the transmural gradient in the time course of contractions was independent of the loading conditions where unloaded and heavy loaded (isometric) contractions were examined, but the regional gradient of the relaxation time characteristics tended to decrease when the load decreased. Under auxotonic contractions, time to peak contraction (Tmax) was significantly longer in ENDO cells than in EPI cells at low preload. An increase in preload (axial stretch) prolonged Tmax in both cell types; however, the prolongation was greater in EPI cells, resulting in a decrease in transmural gradient in Tmax at high preload. The [Ca 2+ ]i transient decay time constant was consistent with the greater preload dependency in Tmax of EPI cells. Our modified mathematical models reproduced experimental results, suggesting that differences in cooperativity of cross bridges and calcium troponin C complex interactions between the ENDO and EPI cardiomyocytes may contribute to Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: Highlights •Mechanical behavior of ENDO and EPI cells was examined at different loads • ENDO and EPI cells were different in their mechanical response to changes in preload • Underlying subcellular mechanisms are predicted via mathematical cellular models