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The emergence of tissue in evolution: Lessons from Trichoplax adhaerensAxel Krinner, Dirk Drasdo Interdisciplinary Centre for Bioinformatics University of Leipzig Peter F. Stadler Bioinformatics Group Institute for Computer Science University of Leipzig Cooperation: Wolfgang Grill Dept. of Physics and Geosciences University of Leipzig Bernd Schierwater Institute of Animal Ecology and Cell Biology Ecology and Evolution Univ. of Veterinary Medicine Hannover The understanding of the emergence of tissue requires to unveil the link between molecular organization processes and the multi-cellular phenotype and hence requires to understand the interplay of many times and lengths scales. While e.g. in cell populations of de-differentiated cells and many observations can be largely explained by physical mechanisms the organization processes in higher animals is believed to involve a well orchestrated strict genetic program which controls the bio-physical properties of the cell. An ideal model organism to understand the interplay of the different regulatory processes on many time and lengths scales is Trichoplax adhaerens, which may be considered as the simplest organism that shows a tissue-like multi-cellularity. It consists of a layer of five cell types 
Figure 1: The three layered morphological structure of Trichoplax adhaerens: The transparent and less ciliated upper epithelium consists of
extensive cover cells and shiny spheres. The lower, nutritive epithelium is denser packed with gland cells and ciliated cylinder cells.
The intermediate, connective layer is formed by a syncytial network of contractile fiber cells embedded in seawater like environment
In this project different biological observations on the multi-cellular level on the developmental time scale of Trichoplax, namely growth, reproduction, movement, sorting and regeneration, should be explained within the same mathematical model. The same model type should then be used to test different hypotheses of the evolution of lower metazoan animals. One hypothesis is depicted in Fig.2. It will be explored by systematic computer simulations which of the observations may be explained by physical mechanisms and in which cases a control of the parameters on the cellular scale by differentiation, gene expression and molecular interactions inside the cells has to be assumed. 
Figure 2: Gallertoid Hypothesis: Hypothetical pelagic precursor of Trichoplax adhaerens. b) & c) Infolding of canals.
d) Formation of inner canal system leading e.g. to Porifera.
Models: Single-cell-based models in which the model parameters are controlled by the state of intracellular regulatory networks and the cells’ environment will be used as the most promising approach to multi-cellular organization processes. A cell is modelled as a sphere with radius R, the shape it adopts when it is isolated. Cell-cell interaction, which occur only between nearest neighbours is split into two components: the repulsive force is modelled by a Hertz model and the adhesive force is derived from a contact area dependent potential. The dynamics of the cell motion is described by a “Langevin equation”, an equation of motion for a cell in which the inertia term is neglected. The movement of a cell then results from active and passive force components. The size of the parameters in the equation of motion are controlled by the regulation and differentiation states of the cell and modelled by a cell-internal network. As in (DD & Kruspe, Attolini et al.) the state of the networks determines the action and parameters of the cell. Results: Aiming at modelling cell sorting a first simulation tool has been coded on the basis of individual cells and force based equations. The advantage of an extended model which includes intra-cellular regulation in contrast to the differential adhesion hypothesis of Steinberg will ne inverstigated. Outlook: The project should give answers on the question of how multicellularity has emerged in the history of evolution as well as yield the first in-silico “whole metazoan” experiment. This will clarify many questions on metazoan organization principles.
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