A multi-scale model of human skeletal muscle: extracting metabolite dynamics at cellular scale from measurements at whole organ

Objective: Insight in the intracellular metabolic network underlying ATP synthesis and hydrolysis is essential to understand skeletal muscle physiology and pathophysiology, such as insulin resistance. However, skeletal muscle tissue is highly heterogeneous anddynamic. It contains three distinct muscle fiber types with different metabolic characteristics. An additional level of organization is the grouping of fibers of the same type in motor units, enervated by the same motor neuron. Motor unit recruitment is a sophisticated,dynamic process. We developed a multi-scale model of human skeletal muscle. Model simulations were validated with in vivo 31P NMR measurements.Results: At the fiber level the model is composed of detailed models of mitochondria, glycolysis, ATP buffering and ATP consumption. A set of fiber type specific parameters was identified and parameterized for the three different types of muscle fibers.The whole muscle scale was modeled as the average behavior of a representative pool of motor units of different types. Dynamic data of [PCr], [Pi] and [ATP] were obtained from 31P NMR spectra measured during in magnet bicycle exercise. The mitochondrial enzyme content in each of the three types of muscle fiber was estimated based upon the 31P NMR data. The predicted rate of postexercise [PCr] recovery was the highest in oxidative slow twitch fibers, intermediate in oxidative fast twitch fibers and the lowest in glycolytic fast twitch fibers. These [PCr] recovery rates agreed well with values available in literature.Conclusion: The computational model is able to reproduce human skeletal muscle dynamics as obtained with 31P NMR spectroscopy and predicts the behavior of different types of skeletal muscle fibers. 31P NMR spectroscopy is a powerful research and clinical tool to study in vivo dynamics of skeletal muscle metabolism. However, the 31P NMR data represents the behavior of the whole muscle and, thus, the mean behavior of all motor units / muscle fibers, hampering any straightforward interpretation of the data. The developed multi-scale model can be applied to extract the dynamic behavior of different types of myocytes from 31PNMR measurements.