467092 Predictive Multi-Scale Computational Modeling Environment for Simulating Multicellular Dynamics

Wednesday, November 16, 2016: 3:15 PM
Continental 8 (Hilton San Francisco Union Square)
Ali Nematbakhsh1, Pavel Brodskiy2, Wenzhao Sun1, Cody Narciso2, Zhiliang Xu1, Jeremiah J. Zartman2 and Mark Alber1,3, (1)Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, (2)Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, (3)Department of Medicine, Indiana University School of Medicine, Indianapolis, IN

Multicellular development depends in large part on the growth, patterning and morphogenesis of epithelial sheets. How individual epithelial cells coordinate multicellular processes is still poorly understood due to the inherent complexity of emergent systems-level behavior. Generating and testing hypothetical novel biophysical mechanisms combining multiple spatial and time scales requires the creation of multi-scale computational models that can span subcellular to tissue levels. However, the task of including detailed descriptions of interactions between the cytoplasm, cortically enriched cytoskeleton and intercellular adhesion has been challenging due to the prohibitively high computational costs. Here, we introduce a multi-scale modeling environment called Epi-Scale for simulating epithelial tissue dynamics using a modified subcellular element method. Epi-Scale explicitly and in detail simulates the separate mechanical interactions between multiple subcellular components. Computational implementation of the model is based on an efficient parallelization algorithm that utilizes clusters of Graphical Processing Units (GPUs) for simulating large numbers of cells within a reasonable computational time. Epi-Scale naturally recapitulates cellular and tissue-scale properties observed in epithelial systems such as cell neighbor relationships and cell geometries. As a demonstration of the predictive power of the model, detailed simulations cell-cell rearrangement outcomes as a result of changes in tissue growth rates and dynamic mitotic rounding are described. A particular advantage for the Epi-Scale environment is its extensibility toward investigating complex biological processes of multiple cell types and interactions between cells and extracellular matrix, including morphogenesis, wound healing and metastasis. Identifying the control systems for tissue homeostasis is important for understanding the underlying causes of birth defects as well as diseases that occur due to misregulated growth such as cancer.

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See more of this Session: Multiscale Systems Biology
See more of this Group/Topical: Food, Pharmaceutical & Bioengineering Division