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反馈、受体聚类以及受体对单细胞的限制为基于配体-受体的图灵模型产生了大的图灵空间。

Feedback, receptor clustering, and receptor restriction to single cells yield large Turing spaces for ligand-receptor-based Turing models.

作者信息

Kurics Tamás, Menshykau Denis, Iber Dagmar

机构信息

Department for Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.

Department for Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland and Swiss Institute of Bioinformatics (SIB), Switzerland.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Aug;90(2):022716. doi: 10.1103/PhysRevE.90.022716. Epub 2014 Aug 22.

DOI:10.1103/PhysRevE.90.022716
PMID:25215767
Abstract

Turing mechanisms can yield a large variety of patterns from noisy, homogenous initial conditions and have been proposed as patterning mechanism for many developmental processes. However, the molecular components that give rise to Turing patterns have remained elusive, and the small size of the parameter space that permits Turing patterns to emerge makes it difficult to explain how Turing patterns could evolve. We have recently shown that Turing patterns can be obtained with a single ligand if the ligand-receptor interaction is taken into account. Here we show that the general properties of ligand-receptor systems result in very large Turing spaces. Thus, the restriction of receptors to single cells, negative feedbacks, regulatory interactions among different ligand-receptor systems, and the clustering of receptors on the cell surface all greatly enlarge the Turing space. We further show that the feedbacks that occur in the FGF10-SHH network that controls lung branching morphogenesis are sufficient to result in large Turing spaces. We conclude that the cellular restriction of receptors provides a mechanism to sufficiently increase the size of the Turing space to make the evolution of Turing patterns likely. Additional feedbacks may then have further enlarged the Turing space. Given their robustness and flexibility, we propose that receptor-ligand-based Turing mechanisms present a general mechanism for patterning in biology.

摘要

图灵机制能够从嘈杂、均匀的初始条件中产生多种多样的模式,并且已被提出作为许多发育过程中的模式形成机制。然而,产生图灵模式的分子成分仍然难以捉摸,而且允许图灵模式出现的参数空间规模较小,这使得解释图灵模式如何进化变得困难。我们最近表明,如果考虑配体-受体相互作用,单个配体就能产生图灵模式。在此我们表明,配体-受体系统的一般特性会导致非常大的图灵空间。因此,受体局限于单个细胞、负反馈、不同配体-受体系统之间的调节相互作用以及受体在细胞表面的聚集,所有这些都极大地扩大了图灵空间。我们进一步表明,在控制肺分支形态发生的FGF10-SHH网络中发生的反馈足以导致大的图灵空间。我们得出结论,受体的细胞局限性提供了一种机制,足以增加图灵空间的规模,从而使图灵模式的进化成为可能。额外的反馈可能随后进一步扩大了图灵空间。鉴于其稳健性和灵活性,我们提出基于受体-配体的图灵机制是生物学中一种普遍的模式形成机制。

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