Spatiotemporal skeletal muscle dynamics : experimental observations and numerical analyses

W. Groenendaal

Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

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Skeletal muscle microstructure is highly organized in space with respect to calcium handling, transcription processes, and ATP synthesis and hydrolysis [1-5]. Numerous spatial associations between cellular components have been revealed, e.g., lipid droplets are localized close to the mitochondria [6-8] and glycolysis is associated with the SR and the I-band region [9; 10]. Notably, in certain diseased and in certain knock out animals the microstructure is reorganized, e.g., in myopathic hearts the SR and T-tubuli systems are more abundant [11], while in muscles of diabetic subjects there are alterations in the distribution of the mitochondria [12]. Despite all these observations, it has remained unresolved how the functional properties of skeletal muscle are linked to the underlying structural foundation [13]. Structural properties are generally studied with imaging techniques that provide static information, while skeletal muscle physiology is mainly dependent on dynamic processes. Few studies have attempted to relate these two levels of information, i.e. to quantify the role of the microstructure on different aspects of muscle dynamics, e.g., Meyer et al. studied the phosphocreatine shuttle [14], Vendelin et al. studied ATP diffusion in the cardiac myocyte [15] and Baylor et al. studied local calcium dynamics at 16°C in fast-twitch muscle [16]. Even though quantification has often been lacking, several studies have hypothesized that the strategic location combined with temporal coding, i.e., different time frames of action, are related to specific physiological or pathological function. The current study aimed to develop and apply a framework that allows quantification of spatiotemporal regulation in skeletal muscle. Specifically, since calcium dynamics initiate many of the regulatory processes, we developed a computational model that calculates local calcium dynamics within the sarcomere. This model was successfully applied to quantify the role of local calcium dynamics in excitation-contraction and excitation-metabolism coupling. Skeletal muscle is a voluntary tissue: upon a neuronal stimulus, muscle is able to contract. The action potential induces release of calcium into the myoplasm, where local calcium dynamics control a large number of processes in the skeletal muscle cell, e.g., transcription and metabolism. Intriguingly, calcium is able to function as a signaling molecule for these processes on time scales of milliseconds to days [17]. It has been hypothesized that the strategic locations of different calcium handling processes might be essential in the versatility of calcium as a second messenger [18]. Unfortunately, spatiotemporal calcium dynamics cannot be obtained experimentally with the spatial and temporal resolution needed to understand these regulatory processes. Therefore, a computational model was developed that linked the level of the measurements to the local dynamics, thereby allowing comparison with biological data as well as investigation of local regulation (chapter 2 and 3). This model describes local calcium and calcium buffer dynamics in the skeletal muscle sarcomere at different workloads and temperatures in murine EDL muscles, thereby allowing integration of many independent data sets (chapter 4). Model simulations showed good agreement with several autonomous data sets which served as validation data. The model can be applied to analyze calcium dye measurements, re-analyze measurements at unphysiological temperature within a physiological framework and to predict the underlying local calcium and calcium-buffer dynamics. The model predicts higher than average calcium concentrations at the position of troponin C and close to sites of ATP synthesis, hence supporting the idea of calcium as signal to balance ATP synthesis and hydrolysis. The intracellular calcium dynamics are significantly different with respect to time constants and peak value in slow and fast twitch fibers [19-22]. This dissimilarity results in distinct levels of transcription, e.g. calcium-calmodulin induced signaling through calcineurin activates slow type specific gene transcription mediated by the NFAT and MEF2 transcription factors. Inhibition of calcineurin mediated signaling leads to a slow-to-fast fiber type transformation [23; 24]. Interestingly, the differences in calcium dynamics result from a basically identical calcium handling system, i.e. identical components with variations in isoforms and concentrations. This study investigated if the model originally developed for fast twitch skeletal muscle captured the physiological processes to describe calcium dynamics in slow twitch muscle (chapter 5). Hereto, calcium fluorescence indicator dynamics were obtained in EDL and Soleus muscles and these dynamics were compared with model simulations. Model analysis revealed that to describe the experimentally observed change in decay rate of the fluorescence signal during repetitive stimulation of Soleus muscle, an additional calcium store, most likely the mitochondria, should be included in the model. This corresponds to experimental studies indicating that mitochondria shape the calcium transient in slow twitch but not in fast twitch muscles [25-27]. The resulting Soleus model is to our knowledge the first (spatiotemporal) model that describes the large range of calcium dynamics in slow-twitch muscles. Comparison of Soleus model with EDL model simulations demonstrated distinct levels in the predicted calcium-calmodulin dynamics. The peak of the transients is lower in Soleus than in EDL muscles, but the slower time course of the dynamics could induce a higher level of activation as reflected in the higher area under the calcium-calmodulin curve. Interestingly, it has been shown that to activate the calmodulin-calcineurin dependent signaling, calcium dynamics as in slow muscle are necessary and that the short transient calcium elevations observed in fast twitch muscle are not sufficient to activate the system [28; 29]. Further comparison between fiber types using the models combined with a model describing detailed gene transcription could provide additional understanding in the different levels in calcium mediated gene transcription between these fiber types. Intracellular calcium dynamics plays a key role in skeletal muscle contraction. Force generation might seem like a simple cascade of processes, i.e. dynamics of an isometric muscle twitch and tetanus appear to be straightforward, because force rises and then falls in an uncomplicated manner. However, the underlying kinetic processes are extremely complex and are complicated by interactions between the different processes. Experimental and modeling studies have proposed several kinetic mechanisms and interactions that regulate muscle contraction, for a review see Gordon et al. [30]. However, quantification of the contribution of these processes during isometric twitches and tetani in skeletal muscle has been lacking. In an attempt to quantify these contributions, again an integrated approach of experiments and computational modeling was used (chapter 6). Specifically, the roles of calcium-troponin C activation and cooperativity by strongly bound cross bridges were investigated. This approach identified that a model containing double activation by calcium-troponin C, a mechanism shown by McKillop and Geeves in purified myosin [31], could describe the biological data, while the other models could not. To our knowledge, this is the first computational model that successfully describes the entire dynamical range of skeletal muscle contraction from twitch to tetanus using a physiological spatially distinct calcium signal as an input. Remarkably, cooperativity by the cross bridges, shown to be important in the steady state calcium-force curve, was not necessary to reproduce the dynamic data. This can be explained that the steady state conditions used in constructing this curve are not achieved during the dynamic contractions [32]. Therefore, we propose that during short contraction dynamics activation by calcium-troponin C is the key regulatory process. The role of calcium in excitation-metabolism coupling was explored by investigation of the regulation of glycolysis (Chapter 7). Glycolytic enzyme kinetics have been extensively studied in in vitro environments. However, a computational model based on these kinetics did not match the in vivo data and required introduction of in vivo-like kinetics [33]. The current study tested the hypothesis that in vivo glycolytic flux is regulated by calcium-calmodulin activation of PFK. Hereto, in vivo glycolysis dynamics were obtained in an ischemic rat muscle at different workloads, thereby inducing different calcium levels inside the muscle cell. The calcium model was linked to a model describing glycolytic flux. Agreement between model simulations and experimental data significantly improved upon addition of calcium-calmodulin activation, thereby supporting the hypothesis. Notably, the activation curves of calcium-calmodulin binding to PFK showed qualitative similarity with skeletal muscle force dynamics. These results support the hypothesis of calcium as feed forward signal to balance ATP synthesis and hydrolysis. In general this study showed how computational models and measurements can be combined to further the understanding of skeletal muscle physiology and to link in vitro data to in vivo function. More specifically, the microstructure of skeletal muscle can significantly impact the physiology of the muscle by defining the shape of the calcium transient, thereby controlling muscle contraction and ATP metabolism. These results open the possibility to quantitatively study muscle diseases in which microstructure, metabolism or contractile performance are affected.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Department of Biomedical Engineering
  • Hilbers, Peter A.J. , Promotor
  • van Riel, Natal A.W., Copromotor
  • Jeneson, Jeroen, Copromotor
Award date6 Apr 2011
Place of PublicationEindhoven
Print ISBNs978-90-386-2445-7
Publication statusPublished - 2011

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