Projects:

Multiscale Simulation of Avian Limb Development

Coordinators:

M.S. Alber (Dept. of Applied and Computational Mathematics and Statistics, University of Notre Dame), J. Izaguirre (Dept. of Computer Science and Engineering, University of Notre Dame), and S. A. Newman (Dept. of Cell Biology, New York Medical College)

Participants:

J. A. Glazier (Dept. of Physics, University of Notre Dame), J. Jones (Dept. of Physics, University of Notre Dame), M. S. Alber (Dept. of Applied and Computational Mathematics and Statistics, University of Notre Dame), F. Castellino (Dept. of Chemistry and Biochemistry, University of Notre Dame), J. Izaguirre (Dept. of Computer Science and Engineering, University of Notre Dame), G. Hentschel (Dept. of Physics, Emory University), Y. Jiang (Los Alamos National Laboratory), P. Kulesa (Beckman Institute, California Institute of Technology), R. Lansford (Beckman Institute, California Institute of Technology), G. Niebur (Dept. of Aerospace and Mechanical Engineering, University of Notre Dame), Elliot Rosen (Keck Transgene Center, University of Notre Dame), C. Weijer (Wellcome Institute Biocenter, University of Dundee)

Summary:

Developing multicellular organisms exhibit dramatic changes in shape and form and successive changes in spatial organization of specialized (differentiated) cell types, e.g. neurons and muscle fibers. How functional and spatiotemporal specialization takes place is an outstanding open question in cell and developmental biology. These events, which generate the body plan and the various organs, depend on regulated gene expression, elaborate interactions among cells, and coordinated cell movement. Differentiation and cell migration may occur simultaneously or sequentially. During development, genetics and biochemistry interact with the physical properties of individual cells creating a multiscale process of enormous complexity. However, we can discover dynamic and organizational rules at various levels. Every cell of a multicellular organism carries the same genetic information. Nevertheless, through cell-cell, cell-matrix, and cell-growth factor interactions cells differentiate in a spatiotemporal fashion. Through differentiation, cells express different subsets of genes and acquire distinct physico-chemical properties. How do these pattern-forming, morphogenetic and mechanical properties affect the shape and function of the tissues these cells build? Computer simulations which allow the separate study of individual mechanisms and their reintegration in controlled conditions are essential to disentangle the complex interacting phenomena of both embryonic pattern formation and tissue mechanics. Computer simulation allows integration of these data with experimental results. Ultimately the simulations should quantitatively predict phenomenology.