CAREER: A Systems Approach to Discovering Mechanical Sensors in Heart Muscle Cells

点击翻译按钮获取中文摘要

Like every tissue in the body, heart muscle adapts to mechanical loading. One example is the effect of endurance running, which tends to enlarge the volume of the heart's main pumping chamber. Weight lifters experience a thickening of the heart walls instead of increased volume. Little is known about how heart cells translate different types of exercise or mechanical loads into patterns of self-remodeling. In order to understand why different exercises cause different heart muscle changes, a computer model of heart tissue will be created. The virtual tissue will be stretched in different ways to produce dozens of cell response predictions that will be compared to identical experimental results. By comparing the model predictions to experimental data an explanation of how the muscle cells detect different types of mechanical load will emerge. This Faculty Early Career Development (CAREER) Program research project has two educational objectives, one focused on post-graduate trainees and the other towards undergraduate students. Undergraduate research positions on the project will be created and the PI will continue ongoing mentoring of 20 undergraduate students through programs based at Yale University.Cardiac cells can distinguish between different types of mechanical loads, as evidenced by diverse types of cardiac remodeling observed in athletes. When this mechanosensory process is disrupted, it results in disease. While many mechanosensory components have been identified in cardiomyocytes so far, building an integrated understanding this system, its sensors, and their effectors, remains challenging. The purpose of this proposal is to map the relationships between many candidate mechanosensitive proteins in cardiac cells and the cellular processes they affect. This involves first creating a new theoretical framework capable of using macroscopic tissue deformation to predict the microscopic distortion of specific cellular proteins. Once complete, the model will be used to plan multiple macroscopic loading schemes for engineered heart tissue that will distort subcellular structures in diverse ways. The designed loads will then be administered to real engineered tissues, and their effect on cellular growth responses will be measured. A systems biology approach known as 'cue-signal-response analysis' will be used to correlate growth responses with patterns of subcellular protein distortion predicted by the model. In so doing, new mechanosensors and their specific functions will be exposed.