Cyclic AMP is a highly versatile second messenger in the heart, transducing an array of different receptor stimuli into coordinated regulation of cardiac functions including excitation-contraction (EC) coupling and gene transcription. But how cAMP can selectively regulate diverse cardiac functions is an important unanswered question in cardiac biology. This lack of basic understanding limits therapeutic strategies for heart disease aimed at suppressing certain cAMP-responsive phenotypes (e.g. structural remodeling, arrhythmia) while preserving other cAMP-responsive phenotypes (e.g. contractility, heart rate). Compartmentation of cAMP and protein kinase A (PKA) has now been directly visualized in cardiac myocytes, and compartmentation is widely hypothesized to be a fundamental mechanism providing cAMP/PKA specificity. The long term objective of this proposal is to develop a systems level understanding of how molecular mechanisms interact to determine cAMP/PKA compartmentation and selective cAMP/PKA signaling. To address this central question, we will use a unique and innovative combination of systems biology approaches: spatiotemporal systems modeling and real-time imaging of cAMP/PKA biosensors in cultured ventricular myocytes. By developing the first molecularly-detailed model of 2-adrenergic signaling (mediated by cAMP and PKA), and the first combination of mechanistic signaling models with FRET biosensors, we pioneered new integrative approaches for understanding cardiac signaling networks from a systems perspective. By iterating between these mechanistic systems models and newly possible experiments in cultured ventricular myocytes, we will test the overall hypothesis that local cAMP/PKA signals are restricted by cAMP degradation, physical barriers, and buffering, which together help mediate selective PKA activity in cytosol, sarcolemma, caveolae, and nucleus. We will test this hypothesis through 3 Specific Aims.
Specific Aim 1 characterizes mechanisms restricting local cAMP signals by imaging waves of cAMP diffusion at high spatial and temporal resolution with FRET biosensors and spatially explicit modeling.
Specific Aim 2 targets cAMP and PKA FRET biosensors specifically to caveolae, to provide the first direct measurements of local cAMP/PKA signals in this compartment. Finally, Specific Aim 3 examines mechanisms determining how nuclear PKA pathways regulate gene transcription independently of contractile function. Together, these aims will unify our understanding of how cAMP/PKA compartmentation mechanisms selectively coordinate contractility and transcription in response to diverse receptor stimuli. This work reflects a necessary first step towards quantitatively understanding selective regulation of cAMP signaling pathways in the heart. Heart disease is the leading cause of death in the U.S. and many other developed countries. Indeed, the insights provided by this work will aid future efforts towards selectively targeting therapeutics to cardiac disease mechanisms, ultimately improving public health in the U.S. and abroad.

Public Health Relevance

We propose to combine computer modeling and heart cell imaging to identify how cyclic AMP selectively regulates heart contraction vs. heart growth. We expect that this work will aid future efforts towards selectively targeting therapeutic agents towards cardiac disease mechanisms.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL094476-04
Application #
8305508
Study Section
Electrical Signaling, Ion Transport, and Arrhythmias Study Section (ESTA)
Program Officer
Adhikari, Bishow B
Project Start
2009-07-01
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
4
Fiscal Year
2012
Total Cost
$329,505
Indirect Cost
$106,755
Name
University of Virginia
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Zeigler, A C; Richardson, W J; Holmes, J W et al. (2016) A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation. J Mol Cell Cardiol 94:72-81
Lindsey, Merry L; Saucerman, Jeffrey J; DeLeon-Pennell, Kristine Y (2016) Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction. Biochim Biophys Acta 1862:2288-2292
Ryall, Karen A; Saucerman, Jeffrey J (2015) Automated microscopy of cardiac myocyte hypertrophy: a case study on the role of intracellular ?-adrenergic receptors. Methods Mol Biol 1234:123-34
Amanfu, Robert K; Saucerman, Jeffrey J (2014) Modeling the effects of ?1-adrenergic receptor blockers and polymorphisms on cardiac myocyte Ca2+ handling. Mol Pharmacol 86:222-30
Greenwald, Eric C; Polanowska-Grabowska, Renata K; Saucerman, Jeffrey J (2014) Integrating fluorescent biosensor data using computational models. Methods Mol Biol 1071:227-48
Greenwald, Eric C; Redden, John M; Dodge-Kafka, Kimberly L et al. (2014) Scaffold state switching amplifies, accelerates, and insulates protein kinase C signaling. J Biol Chem 289:2353-60
Yang, Jason H; Polanowska-Grabowska, Renata K; Smith, Jeffrey S et al. (2014) PKA catalytic subunit compartmentation regulates contractile and hypertrophic responses to ?-adrenergic signaling. J Mol Cell Cardiol 66:83-93
Ryall, Karen A; Bezzerides, Vassilios J; Rosenzweig, Anthony et al. (2014) Phenotypic screen quantifying differential regulation of cardiac myocyte hypertrophy identifies CITED4 regulation of myocyte elongation. J Mol Cell Cardiol 72:74-84
Saucerman, Jeffrey J; Greenwald, Eric C; Polanowska-Grabowska, Renata (2014) Mechanisms of cyclic AMP compartmentation revealed by computational models. J Gen Physiol 143:39-48
Saucerman, Jeffrey J (2013) Modeling mitochondrial ROS: a great balancing act. Biophys J 105:1287-8

Showing the most recent 10 out of 27 publications