Systems analysis of beta-adrenergic signaling in cardiac myocytes.

摘要

beta-adrenergic signaling mediates the cellular response to sympathetic stimulation of the heart, and targeting this signaling network with beta-AR blockers is currently the most effective therapy for heart failure. However, the spatial, temporal, and combinatorial complexities of this signaling network obscure understanding of both basic and therapeutic mechanisms. The recent emergence of systems biology brings hope that large biological networks can be understood using tools from systems analysis. While such approaches have most often been applied to model organisms such as yeast and bacteria, systems analysis of mammalian biochemical networks may provide enhanced understanding of biomedical problems relevant to human disease.; In this work, we developed mechanistic computational models to explore how the components and topology of the cardiac beta-adrenergic signaling network contribute to systems level behavior. In-silico molecular perturbations revealed key signaling interactions involved in enhanced cardiac contractility. Multi-scale computational models allowed characterization of the physiologic consequences of a gene mutation from subcellular to tissue levels, providing a mechanistic explanation for the development of a long QT syndrome. Integrative use of live-cell fluorescence imaging and computational models enabled quantitative characterization of protein kinase A dynamics and compartmentation, leading to improved understanding of underlying mechanisms. These studies provide a starting point for a more comprehensive and quantitative understanding of cardiac beta-adrenergic signaling. The approaches developed in this work will also be valuable for attaining similar systems level understanding of other signaling networks, both in the heart and other mammalian systems.