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动态稀释对齐模型揭示了细胞更新对组织极性模式可塑性的影响。

A dynamically diluted alignment model reveals the impact of cell turnover on the plasticity of tissue polarity patterns.

机构信息

Centre for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

出版信息

J R Soc Interface. 2017 Oct;14(135). doi: 10.1098/rsif.2017.0466.

Abstract

The polarization of cells and tissues is fundamental for tissue morphogenesis during biological development and regeneration. A deeper understanding of biological polarity pattern formation can be gained from the consideration of pattern reorganization in response to an opposing instructive cue, which we here consider using the example of experimentally inducible body axis inversions in planarian flatworms. We define a dynamically diluted alignment model linking three processes: entrainment of cell polarity by a global signal, local cell-cell coupling aligning polarity among neighbours, and cell turnover replacing polarized cells by initially unpolarized cells. We show that a persistent global orienting signal determines the final mean polarity orientation in this stochastic model. Combining numerical and analytical approaches, we find that neighbour coupling retards polarity pattern reorganization, whereas cell turnover accelerates it. We derive a formula for an effective neighbour coupling strength integrating both effects and find that the time of polarity reorganization depends linearly on this effective parameter and no abrupt transitions are observed. This allows us to determine neighbour coupling strengths from experimental observations. Our model is related to a dynamic 8-Potts model with annealed site-dilution and makes testable predictions regarding the polarization of dynamic systems, such as the planarian epithelium.

摘要

细胞和组织的极化是生物发育和再生过程中组织形态发生的基础。通过考虑对相反的指导线索的模式重组,可以更深入地了解生物极性模式形成,我们在这里以扁形虫实验诱导的身体轴反转为例进行考虑。我们定义了一个动态稀释对齐模型,将三个过程联系起来:全局信号对细胞极性的诱导、局部细胞-细胞耦合在相邻细胞之间对齐极性,以及通过最初无极性的细胞替代极化细胞的细胞更新。我们表明,在这个随机模型中,持续的全局定向信号决定了最终的平均极性方向。通过数值和分析方法相结合,我们发现邻居耦合会延迟极性模式的重组,而细胞更新则会加速其重组。我们推导出了一个用于有效邻居耦合强度的公式,该公式综合了这两个效应,并发现极性重组的时间线性依赖于这个有效参数,不会观察到突然的转变。这使得我们能够从实验观察中确定邻居耦合强度。我们的模型与具有退火位稀释的动态 8-Potts 模型相关,并对动态系统(如扁形虫上皮)的极化做出了可测试的预测。

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