Contributions of Ca^(2+)-Independent Thin Filament Activation to Cardiac Muscle Function
Although Ca^(2+) is the principal regulator of contraction in striated muscle, in vitro evidence suggests that some actin-myosin interaction is still possible even in its absence. Whether this Ca^(2+)-independent activation (CIA) occurs under physiological conditions remains unclear, as does its potential impact on the function of intact cardiac muscle. The purpose of this study was to investigate CIA using computational analysis. We added a structurally motivated representation of this phenomenon to an existing myofilament model, which allowed predictions of CIA-dependent muscle behavior. We found that a certain amount of CIA was essential for the model to reproduce reported effects of nonfunctional troponin C on myofilament force generation. Consequently, those data enabled estimation of ΔG_(CIA), the energy barrier for activating a thin filament regulatory unit in the absence of Ca^(2+). Using this estimate of ΔG_(CIA) as a point of reference (∼7 kJ mol^(−1)), we examined its impact on various aspects of muscle function through additional simulations. CIA decreased the Hill coefficient of steady-state force while increasing myofilament Ca^(2+) sensitivity. At the same time, CIA had minimal effect on the rate of force redevelopment after slack/restretch. Simulations of twitch tension show that the presence of CIA increases peak tension while profoundly delaying relaxation. We tested the model's ability to represent perturbations to the Ca^(2+) regulatory mechanism by analyzing twitch records measured in transgenic mice expressing a cardiac troponin I mutation (R145G). The effects of the mutation on twitch dynamics were fully reproduced by a single parameter change, namely lowering ΔG_(CIA) by 2.3 kJ mol^(−1) relative to its wild-type value. Our analyses suggest that CIA is present in cardiac muscle under normal conditions and that its modulation by gene mutations or other factors can alter both systolic and diastolic function.
© 2015 by the Biophysical Society. Submitted May 1, 2015, and accepted for publication September 11, 2015. The authors acknowledge Sander Land for helpful discussions and comments on an early draft of the article. This work was supported in part by the facilities and staff of the Yale University Faculty of Arts and Sciences High Performance Computing Center. It was also supported in part by National Institutes of Health award No. 1R21HL126025 to S.G.C. and Clinical and Translational Science Award No. UL1 TR000142 from the National Center for Advancing Translational Science, a component of the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the National Institutes of Health. Author Contributions: Y.A., J.A.B., K.J.M., and S.G.C. designed and implemented the computational model; Y.A., J.A.B., and K.J.M. performed simulations; and Y.A., J.A.B., and S.G.C. wrote the article.
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