Abstract
Cardiovascular diseases constitute a significant global health burden and are the leading cause of death in the United States. By 2020, it is estimated that cardiovascular disease will be the leading cause of death worldwide, accounting for an estimated 25 million deaths annually. The contemporary view of heart failure states the development of the failing heart is driven in large part by circulating neurohormones and catecholamines which can stimulate pathologic remodeling events such as cardiac hypertrophy and fibrosis. However, these circulating factors also act on signaling pathways important for regulating normal cardiac function, such as the β-adrenergic signaling pathway, which regulates contractility in the fight-or-flight response. The overall goal of this dissertation is to investigate mechanisms which differentially regulate β-adrenergic signaling-stimulated contractility and β-adrenergic signaling-stimulated hypertrophy.
Like most signaling pathways, the β-adrenergic signaling pathway is a complex network of signaling species that interact to elicit diverse cellular functions in response to receptor stimulation. An open challenge therefore remains in understanding how certain cardiac functions are selectively activated or silenced in the presence of a common biochemical stress. Traditional reductionist approaches have proven very successful for identifying components of the β-adrenergic signaling pathway, but the complexity of this network renders intuitive understanding of signaling responses difficult. These challenges provide opportunities for quantitative engineering methods, such as computational modeling, to provide insight into cardiac biology and potential therapies. In this dissertation, we take a multidisciplinary approach, integrating computational modeling with analysis of published experimental data and novel live-cell imaging strategies to interrogate the mechanisms regulating β-adrenergic signaling dynamics.
Complex signaling networks contain many topological network motifs that may be important for regulating signaling flow through the network. In the present work, we develop highly mechanistic and carefully constrained models of cardiac β-adrenergic signaling to test the hypothesis that topological features in this network may be important for regulating contractile responses. By this approach, we show an incoherent feed-forward loop formed by two protein kinase A substrates accelerates and induces adaptation in cardiac contractility responses. Moreover, extending these methods to Angiotensin II signaling, we show this network motif is also an important regulator of cardiac fibrosis. Together, these results implicate an important role of network topology in regulating β-adrenergic signaling.
Recent studies from our lab and by others indicate β-adrenergic signaling is spatially and temporally heterogeneous in the cardiac myocyte. Because the protein kinase A substrates regulating cardiac contractility and hypertrophy reside in different subcellular compartments of the cardiac myocyte, we have hypothesized that such compartmentation may be important for regulating stimulated hypertrophic responses. In the present work, we have used computational models as a hypothesis-generating inference tool to inspire experiments investigating the regulation of nuclear protein kinase A activity its downstream effects on cardiac myocytes. With this approach, we show that in contrast to HEK 293 cells, where nuclear protein kinase A activity is regulated by a subnuclear A-kinase anchoring protein signaling complex, nuclear protein kinase A activity in cardiac myocytes is directly regulated by catalytic subunit compartmentation.
Together, this body of work provides insight into how β-adrenergic signaling responses are selectively manipulated. These findings are important as the current therapeutic strategy for treating heart disease is antagonism of the entire β-adrenergic signaling pathway, which leaves patients vulnerable to electrophysiological and mechanical deficiencies. The present work provides evidence suggesting these therapies may be improved with a therapeutic strategy which more directly inhibits nuclear protein kinase A activity, while preserving or enhancing cytosolic protein kinase A activity.
