CAREER:Systems analysis of the cardiac hypertrophy signaling network

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

1252854 Saucerman A python's heart grows by a remarkable 40% a mere 48 hours after feeding, returning to normal size on a similar timescale. But in humans and other mammals, exposure to pathological stress such as myocardial infarction (heart attack) leads to a detrimental and irreversible form of heart growth that ultimately leads to heart failure. Because postnatal cardiac myocytes generally do not proliferate, heart growth is due to an enlargement of existing cells, termed hypertrophy. The myocyte hypertrophy response is controlled by a complex web of biochemical signaling pathways, triggered by a range of neurotransmitters, hormones, cytokines and mechanical stimuli. While many individual pieces of this network have been discovered, major advances are required to achieve a quantitative understanding of how these molecular circuits work and how they may be controlled therapeutically. Thus there is an urgent need for new approaches, both theoretical and experimental, that allow such integrative understanding. Yet systems biology approaches to date have been most focused on more tractable model organisms and cell lines, with much less work done on biochemical networks regulating the heart. Here, new computational and experimental systems approaches will be developed to understand how extracellular signals drive physiological and pathological myocyte remodeling. Dr. Saucerman's lab has adapted techniques from image processing to perform the first highthroughput microscopy of cardiac myocyte morphology, identifying distinct forms of hypertrophy depending on the stimulated receptor. In parallel, they have developed the first largescale computational model of the hypertrophy signaling network, predicting that PI3K and Ras are key network decision points. The research objective of this proposal is to test the overall hypothesis that the balance of PI3K and Ras signaling determines how diverse receptors induce distinct forms of cardiac myocyte hypertrophy. This hypothesis will be tested by 1) experimentally measuring and perturbing PI3K and Ras signaling to determine their distinct regulation of myocyte size, shape and sarcomeric organization; 2) training a computational model of hypertrophy signaling based on biochemical and morphological data; and 3) applying the model to predict and then experimentally validate signaling mechanisms that mediate the distinct roles for PI3K and Ras in hypertrophy signaling. The training of individuals ranging from high school students through postdoctoral researchers is highly integrated into this program. Specific educational aims include: 1) mentoring of undergraduate students in graduate-level research; and 2) outreach to high school students from underrepresented populations, particularly in developing original computational models of cardiac signaling networks. This training is aided by user-friendly network modeling software and accompanying problem-based learning curricular materials. Intellectual Merit: This research will integrate new computational and experimental approaches to identify PI3K and Ras as network decision points for myocyte size, shape, and sarcomeric organization. The educational program is innovative in graduate-level research by undergraduates and in problem-based learning of systems biology with high school students. Broader Impact: This research is expected to identify new potential therapeutic targets for cardiac hypertrophy. The educational program will provide mentoring for underrepresented high school students and undergraduates, enhancing their career development. Modeling software and curricular materials will make these approaches accessible to a much larger community. Further impact will ultimately be achieved by the scientific achievements and career successes of diverse trainees.