Regulation of excitation-contraction coupling in cardiac myocytes : insights from mathematical modelling

Abstract

Background – The heart cell is a prime example of a system, in which numerous interconnected regulatory mechanisms affect the dynamic balance of cellular function. The function of the system emerges from the interactions of its components rather than from their individual properties. Thus, it is a challenging task to understand the causal relations within such a system, based on the analysis of experimental results. Facing this complexity, the systems biological approach has gained interest during recent years, since with using it we can make an effort to observe, quantitatively and simultaneously, multiple components and their interdependencies in biological networks.

Methods and aims – One of the most important tools in systems biology is mathematical modelling. In this thesis, novel model components have been developed and existing components integrated to describe mathematically the calcium dynamics in cardiac myocytes with improved physiological accuracy. Special attention was paid to both the activity-dependent and automatic regulation of the dynamics. This enabled the quantitative analysis of the regulation’s role in both physiological and pathophysiological conditions.

Results – Validation of the novel model components that describe the calcium transport mechanisms indicates that the developed schemes are accurate and applicable also beyond the normal physiological state of the cardiac myocyte. Results also highlight the importance of autoregulation of calcium dynamics in the excitation-contraction coupling. Furthermore, the analysis indicates that the CaMK-dependent regulation of the calcium uptake to and release from the sarcoplasmic reticulum calcium stores could have substantial roles as downstream effectors in beta-adrenergic stimulation.

Conclusions – Results emphasize mathematical modelling as a valuable complement to experiments in understanding causal relations within complex biological systems such as the cardiac myocytes. That is, rigorous data integration with mathematical models can provide significant insight to the quantitative role of both the individual model components and the interconnected regulatory loops. This is especially true for the analysis of genetically engineered animal models, in which the intended modification is always accompanied by compensatory changes that can mask to a varying degree the actual phenomenon of interest.