Turing patterns in a morphogenetic model with single regulatory function

IF 1.8 4区 数学 Q2 BIOLOGY
Mohamed Amine Ouchdiri , Saad Benjelloun , Adnane Saoud , Irene Otero-Muras
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引用次数: 0

Abstract

Confirming Turing’s theory of morphogens in developmental processes is challenging, and synthetic biology has opened new avenues for testing Turing’s predictions. Synthetic mammalian pattern formation has been recently achieved through a reaction–diffusion system based on the short-range activator (Nodal) and the long-range inhibitor (Lefty) topology, where a single function regulates both morphogens. In this paper, we investigate the emergence of Turing patterns in the synthetic Nodal-Lefty system. First, we prove the existence of a global solution and derive conditions for Turing instability through linear stability analysis. Subsequently, we examine the behavior of the system near the bifurcation threshold, employing weakly nonlinear analysis, and using multiple time scales, we derive the amplitude equations for supercritical and subcritical cases. The results demonstrate the ability of the system to support various patterns, with the subcritical Turing instability playing a crucial role in the formation of dissipative structures observed experimentally.
具有单一调控功能的形态发生模型中的图灵模式。
证实图灵关于发育过程中形态因子的理论是具有挑战性的,而合成生物学为测试图灵的预测开辟了新的途径。最近,通过一种基于短程激活剂(Nodal)和远程抑制剂(Lefty)拓扑结构的反应扩散系统,合成哺乳动物的模式形成已经实现,其中一个功能调节两个形态因子。在本文中,我们研究了图灵模式在合成左节点系统中的出现。首先,通过线性稳定性分析,证明了全局解的存在性,并导出了图灵不稳定性的条件。随后,我们研究了系统在分岔阈值附近的行为,采用弱非线性分析,并使用多时间尺度,我们推导了超临界和亚临界情况下的振幅方程。结果表明,该系统具有支持多种模式的能力,亚临界图灵不稳定性在实验观察到的耗散结构的形成中起着至关重要的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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