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Biology subjects

Clippinger, S. R.

Publications and source records attributed to Clippinger, S. R..

2 recordsLinked to original sources

Disrupted mechanobiology links the molecular and cellular phenotypes in familial dilated cardiomyopathy

Familial dilated cardiomyopathy (DCM) is a leading cause of sudden cardiac death and a major indicator for heart transplant. The disease is frequently caused by mutations of sarcomeric proteins; however, it is not well understood how these molecular mutations lead to alterations in cellular organization and contractility. To address this critical gap in our knowledge, we studied the molecular and cellular consequences of a DCM mutation in troponin-T, {Delta}K210. We determined the molecular mechanism of {Delta}K210 and used computational modeling to predict that the mutation should reduce the force per sarcomere. In mutant cardiomyocytes, we found that {Delta}K210 not only reduces contractility, but also causes cellular hypertrophy and impairs cardiomyocytes ability to adapt to changes in substrate stiffness (e.g., heart tissue fibrosis that occurs with aging and disease). These results link the molecular and cellular phenotypes and implicate alterations in mechanosensing as an important factor in the development of DCM.

biophysics

Computational tool to study perturbations in muscle regulation and its application to heart disease

Striated muscle contraction occurs when myosin thick filaments bind to thin filaments in the sarcomere and generate pulling forces. This process is regulated by calcium, and it can be perturbed by pathological conditions (e.g., myopathies), physiological adaptations (e.g., {beta}-adrenergic stimulation), and pharmacological interventions. Therefore, it is important to have a methodology to robustly determine the mechanism of these perturbations and statistically evaluate their effects. Here, we present an approach to measure the equilibrium constants that govern muscle activation, estimate uncertainty in these parameters, and statistically test the effects of perturbations. We provide a MATLAB-based computational tool for these analyses, along with easy-to-follow tutorials that make this approach accessible. The hypothesis testing and error estimation approaches described here are broadly applicable, and the provided tools work with other types of data, including cellular measurements. To demonstrate the utility of the approach, we apply it to determine the biophysical mechanism of a mutation that causes familial hypertrophic cardiomyopathy. This approach is generally useful for studying the mechanisms of muscle diseases and therapeutic interventions that target muscle contraction.

biophysics