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The self-organization of plant microtubules inside the cell volume yields their cortical localization stable alignment and sensitivity to external cues

机译:细胞体积内植物微管的自组织产生其皮层定位稳定的排列和对外​​部线索的敏感性

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摘要

Many cell functions rely on the ability of microtubules to self-organize as complex networks. In plants, cortical microtubules are essential to determine cell shape as they guide the deposition of cellulose microfibrils, and thus control mechanical anisotropy of the cell wall. Here we analyze how, in turn, cell shape may influence microtubule behavior. Building upon previous models that confined microtubules to the cell surface, we introduce an agent model of microtubules enclosed in a three-dimensional volume. We show that the microtubule network has spontaneous aligned configurations that could explain many experimental observations without resorting to specific regulation. In particular, we find that the preferred cortical localization of microtubules emerges from directional persistence of the microtubules, and their interactions with each other and with the stiff wall. We also identify microtubule parameters that seem relatively insensitive to cell shape, such as length or number. In contrast, microtubule array anisotropy depends on local curvature of the cell surface and global orientation follows robustly the longest axis of the cell. Lastly, we find that geometric cues may be overcome, as the network is capable of reorienting toward weak external directional cues. Altogether our simulations show that the microtubule network is a good transducer of weak external polarity, while at the same time, easily reaching stable global configurations.
机译:许多细胞功能依赖于微管自组织为复杂网络的能力。在植物中,皮质微管对决定细胞形状至关重要,因为它们可引导纤维素微纤维的沉积,从而控制细胞壁的机械各向异性。在这里,我们分析了细胞形状又如何影响微管行为。在以前将微管限制在细胞表面的模型的基础上,我们介绍了封闭在三维空间中的微管的代理模型。我们表明,微管网络具有自发对齐的配置,可以解释许多实验观察而无需诉诸特定法规。尤其是,我们发现微管的首选皮质定位来自于微管的方向性持久性以及它们彼此之间以及与硬质壁的相互作用。我们还确定了似乎对细胞形状相对不敏感的微管参数,例如长度或数量。相比之下,微管阵列各向异性取决于细胞表面的局部曲率,并且总体取向牢固地遵循细胞的最长轴。最后,我们发现可以克服几何线索,因为网络能够重新定向到较弱的外部定向线索。总的来说,我们的仿真表明,微管网络是弱极性的良好换能器,同时,很容易达到稳定的全局配置。

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