Multiscale modeling of mitochondria

Doctoral thesis (2019)

Life is based on energy conversion by which cells and organisms can adapt to the environment. The involved biological processes are intrinsically multiscale phenomena since they are based on molecular ... [more ▼]

Life is based on energy conversion by which cells and organisms can adapt to the environment. The involved biological processes are intrinsically multiscale phenomena since they are based on molecular interactions on a small scale leading to the emerging behavior of cells, organs and organisms. To understand the underlying regulation and to dissect the mechanisms that control system behavior, appropriate mathematical multiscale models are needed. Such models do not only offer the opportunity to test different hypothesized mechanisms but can also address current experimental technology gaps by zooming in and out of the dynamics, changing scales, coarse-graining the dynamics and giving us distinct views of the phenomena. In this dissertation substantial efforts were done to combine different computational modeling strategies based on different assumptions and implications to model an essential system of eukaryotic life -- the energy providing mitochondria -- where the spatiotemporal domain is suspected to have a substantial influence on its function. Mitochondria are highly dynamic organelles that fuse, divide, and are transported along the cytoskeleton to ensure cellular energy homeostasis. These processes cover different scales, in space and time, where on the more global scale mitochondria exhibit changes in their molecular content in response to their physiological context including circadian modulation. On the smaller scales, mitochondria show also faster adaptation by changing their morphology within minutes. For both processes, the relation between the underlying structure of either their regulating network or the spatial morphology and the functional consequences are essential to understand principles of energy homeostasis and their link to health and disease conditions. This thesis focuses on different scales of mitochondrial adaptation. On the small scales, fission and fusion of mitochondria are rather well established but substantial evidence indicates that the internal structure is also highly variable in dependence on metabolic condition. However, a quantitative mechanistic understanding how mitochondrial morphology affects energetic states is still elusive. In the first part of this dissertation I address this question by developing an agent-based dynamic model based on three-dimensional morphologies from electron microscopy tomography, which considers the molecular dynamics of the main ATP production components. This multiscale approach allows for investigating the emergent behavior of the energy generating mechanism in dependence on spatial properties and molecular orchestration. Interestingly, comparing spatiotemporal simulations with a corresponding space-independent approach, I found only minor space dependence in equilibrium conditions but qualitative difference in fluctuating environments and in particular indicate that the morphology provides a mechanism to buffer energy at synapses. On the more global scale of the regulation of mitochondrial protein composition, I applied a data driven approach to explore how mitochondrial activity is changing during the day and how food intake restrictions can effect the structure of the underlying adaptation process. To address the question if at different times of the day, the mitochondrial composition might adapt and have potential implications for function, I analyzed temporal patterns of hepatic transcripts of mice that had either unlimited access to food or were hold under temporal food restrictions. My analysis showed that mitochondrial activity exhibits a temporal activity modulation where different subgroups of elements are active at different time points and that food restriction increases temporal regulation. Overall, this thesis provides new insights into mitochondrial biology at different scales by providing an innovative computational modeling framework to investigate the relation between morphology and energy production as well as by characterizing temporal modulation of the regulatory network structure under different conditions. [less ▲]

Mitochondrial morphology provides a mechanism for energy buffering at synapses.

in Scientific reports (2019), 9

Mitochondria as the main energy suppliers of eukaryotic cells are highly dynamic organelles that fuse, divide and are transported along the cytoskeleton to ensure cellular energy homeostasis. While these ... [more ▼]

Mitochondria as the main energy suppliers of eukaryotic cells are highly dynamic organelles that fuse, divide and are transported along the cytoskeleton to ensure cellular energy homeostasis. While these processes are well established, substantial evidence indicates that the internal structure is also highly variable in dependence on metabolic conditions. However, a quantitative mechanistic understanding of how mitochondrial morphology affects energetic states is still elusive. To address this question, we here present an agent-based multiscale model that integrates three-dimensional morphologies from electron microscopy tomography with the molecular dynamics of the main ATP producing components. We apply our modeling approach to mitochondria at the synapse which is the largest energy consumer within the brain. Interestingly, comparing the spatiotemporal simulations with a corresponding space-independent approach, we find minor spatial effects when the system relaxes toward equilibrium but a qualitative difference in fluctuating environments. These results suggest that internal mitochondrial morphology is not only optimized for ATP production but also provides a mechanism for energy buffering and may represent a mechanism for cellular robustness. IM [less ▲]

Building blocks of self-sustained activity in a simple deterministic model of excitable neural networks.

in Frontiers in computational neuroscience (2012), 6

Understanding the interplay of topology and dynamics of excitable neural networks is one of the major challenges in computational neuroscience. Here we employ a simple deterministic excitable model to ... [more ▼]

Understanding the interplay of topology and dynamics of excitable neural networks is one of the major challenges in computational neuroscience. Here we employ a simple deterministic excitable model to explore how network-wide activation patterns are shaped by network architecture. Our observables are co-activation patterns, together with the average activity of the network and the periodicities in the excitation density. Our main results are: (1) the dependence of the correlation between the adjacency matrix and the instantaneous (zero time delay) co-activation matrix on global network features (clustering, modularity, scale-free degree distribution), (2) a correlation between the average activity and the amount of small cycles in the graph, and (3) a microscopic understanding of the contributions by 3-node and 4-node cycles to sustained activity. [less ▲]

Effect of the topology and delayed interactions in neuronal networks synchronization.

in PloS one (2011), 6(5), 19900

As important as the intrinsic properties of an individual nervous cell stands the network of neurons in which it is embedded and by virtue of which it acquires great part of its responsiveness and ... [more ▼]

As important as the intrinsic properties of an individual nervous cell stands the network of neurons in which it is embedded and by virtue of which it acquires great part of its responsiveness and functionality. In this study we have explored how the topological properties and conduction delays of several classes of neural networks affect the capacity of their constituent cells to establish well-defined temporal relations among firing of their action potentials. This ability of a population of neurons to produce and maintain a millisecond-precise coordinated firing (either evoked by external stimuli or internally generated) is central to neural codes exploiting precise spike timing for the representation and communication of information. Our results, based on extensive simulations of conductance-based type of neurons in an oscillatory regime, indicate that only certain topologies of networks allow for a coordinated firing at a local and long-range scale simultaneously. Besides network architecture, axonal conduction delays are also observed to be another important factor in the generation of coherent spiking. We report that such communication latencies not only set the phase difference between the oscillatory activity of remote neural populations but determine whether the interconnected cells can set in any coherent firing at all. In this context, we have also investigated how the balance between the network synchronizing effects and the dispersive drift caused by inhomogeneities in natural firing frequencies across neurons is resolved. Finally, we show that the observed roles of conduction delays and frequency dispersion are not particular to canonical networks but experimentally measured anatomical networks such as the macaque cortical network can display the same type of behavior. [less ▲]

The generation of respiratory rhythms in birds

in Physica A. Statistical Mechanics and its Applications (2006), 371(1), 84-87

The generation of precise respiratory rhythms is vital for birds, which must generate specific pressure patterns to perform several activities, song being one of the most demanding ones. These rhythms ... [more ▼]

The generation of precise respiratory rhythms is vital for birds, which must generate specific pressure patterns to perform several activities, song being one of the most demanding ones. These rhythms emerge as the interaction between a peripheral system and a set of neural nuclei which control the action of expiratory and inspiratory muscles. A computational model was proposed recently to account for this interaction. In this work, we describe the set of solutions that this model can display as its parameters are varied, and compare experimental records of air sac pressure patterns with the predictions of the model. © 2006 Elsevier B.V. All rights reserved. [less ▲]