A Stochastic Simulation of Skeletal Muscle Calcium Transients in a Structurally Realistic Sarcomere Model using MCell
Supplemental Information high quality video Animation of half sarcomere model highlighting Ca2+ release, and diffusion (88.91Mb)
Supplemental Information high quality video animation of half sarcomere model highlighting the binding of Ca2+ to Tn-c locations (46.54Mb)
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AbstractSkeletal muscle contraction is initiated when an action potential triggers the release of Ca2+ into the sarcomere in a process referred to as excitation-contraction coupling. The speed and scale of this process makes direct observation very challenging and invasive. To determine how the concentration of Ca2+changes within the myofibril during a single activation, several simulation models have been developed. These models follow a common pattern; divide the half sarcomere into a series of compartments, then use ordinary differential equations to solve reactions occurring within and between the compartments. To further develop this type of simulation, we have created a realistic structural model of a skeletal muscle myofibrillar half-sarcomere using MCell software that incorporates the myofilament lattice structure. Using this simulation model, we were successful in reproducing the averaged calcium transient during a single activation consistent with both the experimental and previous simulation results. In addition, our simulation demonstrated that the inclusion of the myofilament lattice within our model produced an asymmetric distribution of Ca2+, with more Ca2+ accumulating near the Z-disk and less Ca2+ reaching the m-line. This asymmetric distribution of Ca2+ is apparent when we examine how the Ca2+are bound to the troponin-c proteins along the actin filaments. Our simulation model also allowed us to produce advanced visualizations of this process, including two simulation animations, allowing us to view Ca2+ release, diffusion, binding and uptake within the myofibrillar half-sarcomere.
GrantingagencyNatural Sciences and Engineering Research Council - Discovery Grant
Data repository for a PLOS computational biology submission