Self-organized Patterning by Diffusible Factors: Roles of a Community Effect

Batmanov, Kirill; Kuttler, Celine; Lhoussaine, Cédric; Saka, Yasushi

doi:10.3233/fi-2012-723

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…by Ref. [ 77 , 78 ]. If mechanochemical coupling is chosen as less intense (such as for a weaker coupling of stretch to the morphogen production), these transient patterns stabilise after t ≈ 4 days without gastrulation and are strongly related to the patterns of basal constriction: in this case, deformations are essentially the same but the morphogen is no longer co-located with the inwards-directed deformation but co-located with the now active outward-directed deformation around these invaginations (see Fig.…”

Section: Resultsmentioning

confidence: 99%

Post-Turing tissue pattern formation: Advent of mechanochemistry

et al. 2018

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Chemical and mechanical pattern formation is fundamental during embryogenesis and tissue development. Yet, the underlying molecular and cellular mechanisms are still elusive in many cases. Most current theories assume that tissue development is driven by chemical processes: either as a sequence of chemical patterns each depending on the previous one, or by patterns spontaneously arising from specific chemical interactions (such as “Turing-patterns”). Within both theories, mechanical patterns are usually regarded as passive by-products of chemical pre-patters. However, several experiments question these theories, and an increasing number of studies shows that tissue mechanics can actively influence chemical patterns during development. In this study, we thus focus on the interplay between chemical and mechanical processes during tissue development. On one hand, based on recent experimental data, we develop new mechanochemical simulation models of evolving tissues, in which the full 3D representation of the tissue appears to be critical for obtaining a realistic mechanochemical behaviour. The presented modelling approach is flexible and numerically studied using state of the art finite element methods. Thus, it may serve as a basis to combine simulations with new experimental methods in tissue development. On the other hand, we apply the developed approach and demonstrate that even simple interactions between tissue mechanics and chemistry spontaneously lead to robust and complex mechanochemical patterns. Especially, we demonstrate that the main contradictions arising in the framework of purely chemical theories are naturally and automatically resolved using the mechanochemical patterning theory.

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Section: Resultsmentioning

confidence: 99%

Post-Turing tissue pattern formation: Advent of mechanochemistry

et al. 2018

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“…2,4 Dynamics of morphogen gradients are therefore crucial for tissue patterning, as corroborated by our theoretical study. 5 As biochemical gradients in vivo may never be static, investigations of cellular response to gradients require experimental means to control gradients in a dynamic manner to reproduce a natural cellular environment.…”

Section: Introductionmentioning

confidence: 99%

Generation and precise control of dynamic biochemical gradients for cellular assays

Saka

MacPherson

Giuraniuc

2017

Physica A: Statistical Mechanics and its Applications

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Spatial gradients of diffusible signalling molecules play crucial roles in controlling diverse cellular behaviour such as cell differentiation, tissue patterning and chemotaxis.In this paper, we report the design and testing of a microfluidic device for diffusionbased gradient generation for cellular assays. A unique channel design of the device eliminates cross-flow between the source and sink channels, thereby stabilising gradients by passive diffusion. The platform also enables quick and flexible control of chemical concentration that makes highly dynamic gradients in diffusion chambers. A model with the first approximation of diffusion and surface adsorption of molecules recapitulates the experimentally observed gradients. Budding yeast cells cultured in a gradient of a chemical inducer expressed a reporter fluorescence protein in a concentrationdependent manner. This microfluidic platform serves as a versatile prototype applicable to a broad range of biomedical investigations.

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Symmetry-Based Model Reduction for Approximate Stochastic Analysis

Batmanov

Kuttler

Lemaire

et al. 2012

Computational Methods in Systems Biology

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Abstract. For models of cell-to-cell communication, with many reactions and species per cell, the computational cost of stochastic simulation soon becomes intractable. Deterministic methods, while computationally more efficient, may fail to contribute reliable approximations for those models. In this paper, we suggest a reduction for models of cell-to-cell communication, based on symmetries of the underlying reaction network.To carry out a stochastic analysis that otherwise comes at an excessive computational cost, we apply a moment closure (MC) approach. We illustrate with a community effect, that allows synchronization of a group of cells in animal development. Comparing the results of stochastic simulation with deterministic and MC approximation, we show the benefits of our approach. The reduction presented here is potentially applicable to a broad range of highly regular systems.

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Self-organized Patterning by Diffusible Factors: Roles of a Community Effect

Cited by 3 publications

References 49 publications

Post-Turing tissue pattern formation: Advent of mechanochemistry

Post-Turing tissue pattern formation: Advent of mechanochemistry

Generation and precise control of dynamic biochemical gradients for cellular assays

Symmetry-Based Model Reduction for Approximate Stochastic Analysis

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