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Spatial modelling of community effects

Kirill Batmanov 1 
1 BioComputing - Programming Languages for Biological Modeling and Simulation
LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : A developing embryo, consisting initially of identical cells, transforms itself into a spatially organized structure made of distinct tissues with clear boundaries. This process, known as pattern formation, is studied in the eld of developmental biology. Cell interaction plays a key role in pattern formation, and the community e ect is an example of such an interaction. A population of cells in an embryo is said to exhibit a community e ect when they form a cell community with a common identity by virtue of exchanging di usible signalling molecules (morphogens). This e ect helps the cell community to maintain a common gene expression pro le over an extended period of time, and to eventually di erentiate co-ordinately into a functional tissue, such as muscle. Self-organizing processes like community e ects are di cult to understand intuitively. Instead, a satisfactory description can be given in the form of a formal model. Several computational models of community e ects were given in the literature. However, the concept of space was not explicitly included in these models, making it di cult to understand how community e ects participate in pattern formation. In this work, we study the behaviour of a community e ect in space and investigate its roles in other pattern formation processes, using computational modelling. Main contributions of this thesis are the following: * A model reduction method is developed for stochastic analysis, and using it we have shown how the model of the community e ect in Xenopus is in uenced by stochastic noise. * Using the simplest possible spatial community e ect model, we show that the community e ect must eventually spread across the entire population of cells which respond to the morphogen. This is con rmed in a more detailed model. ˆ* Two models demonstrating how this expansion can be controlled are presented. First, if the community e ect is augmented with a negative feedback mechanism, it forms a reaction-di usion system which self-organizes and forms a stable, localized area of activation. Second, when a simple cross-repression gene circuitry is combined with a community e ect loop, a gene expression pattern with a well-demarcated boundary appears in response to a transient morphogen gradient. The pattern remains stable even after the gradient disappears, which shows that the gene network has the memory of morphogen dynamics.
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Submitted on : Thursday, April 10, 2014 - 5:03:46 PM
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Kirill Batmanov. Spatial modelling of community effects. Bioinformatics [q-bio.QM]. Université des Sciences et Technologie de Lille - Lille I, 2014. English. ⟨NNT : ⟩. ⟨tel-00977082⟩

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