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Pattern Formation Mechanisms of Self-organizing Reaction-diffusion Systems

Overview
Journal Dev Biol
Publisher Elsevier
Date 2020 Feb 4
PMID 32008805
Citations 41
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Abstract

Embryonic development is a largely self-organizing process, in which the adult body plan arises from a ball of cells with initially nearly equal potency. The reaction-diffusion theory first proposed by Alan Turing states that the initial symmetry in embryos can be broken by the interplay between two diffusible molecules, whose interactions lead to the formation of patterns. The reaction-diffusion theory provides a valuable framework for self-organized pattern formation, but it has been difficult to relate simple two-component models to real biological systems with multiple interacting molecular species. Recent studies have addressed this shortcoming and extended the reaction-diffusion theory to realistic multi-component networks. These efforts have challenged the generality of previous central tenets derived from the analysis of simplified systems and guide the way to a new understanding of self-organizing processes. Here, we discuss the challenges in modeling multi-component reaction-diffusion systems and how these have recently been addressed. We present a synthesis of new pattern formation mechanisms derived from these analyses, and we highlight the significance of reaction-diffusion principles for developmental and synthetic pattern formation.

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References
1.
capek D, Muller P . Positional information and tissue scaling during development and regeneration. Development. 2019; 146(24). DOI: 10.1242/dev.177709. View

2.
Gierer A, Meinhardt H . A theory of biological pattern formation. Kybernetik. 1972; 12(1):30-9. DOI: 10.1007/BF00289234. View

3.
Luo N, Wang S, You L . Synthetic Pattern Formation. Biochemistry. 2019; 58(11):1478-1483. DOI: 10.1021/acs.biochem.8b01242. View

4.
Rogers K, Muller P . Nodal and BMP dispersal during early zebrafish development. Dev Biol. 2018; 447(1):14-23. DOI: 10.1016/j.ydbio.2018.04.002. View

5.
Scholes N, Schnoerr D, Isalan M, Stumpf M . A Comprehensive Network Atlas Reveals That Turing Patterns Are Common but Not Robust. Cell Syst. 2019; 9(3):243-257.e4. DOI: 10.1016/j.cels.2019.07.007. View