论文标题

两个混合隔室的扩散耦合阐明了基于蛋白质的模式形成的基本原理

Diffusive coupling of two well-mixed compartments elucidates elementary principles of protein-based pattern formation

论文作者

Brauns, Fridtjof, Halatek, Jacob, Frey, Erwin

论文摘要

细胞中蛋白质的空间组织对于许多生物学功能很重要。通常,仅在数值模拟中可以访问蛋白质形成的非线性,空间耦合模型,该模拟对一般潜在原理的见解有限。为了克服这一限制,我们采用了两个扩散耦合,混合良好的隔间的设置,该隔间代表了任何模式的基本特征 - 接口。对于细胞内系统,蛋白质的总数是在相关的图案形成时间尺度上保守的。因此,基本动力学是两个隔室之间全球保守的质量密度的重新分布。我们在重新分布质量的相位空间中介绍了相位板的分析,该质量提供了有关形成基本机制的见解。我们为多种范式模型系统演示了这种方法。特别是,我们表明大肠杆菌中的极极到极线振荡是思维极性取向的松弛振荡。这揭示了细胞极性振荡模式之间的密切关系。至关重要的是,我们的发现表明,细胞内模式形成的设计原理是在这些相肖像中的特征特征(无链接和固定点)中发现的。这些特征不是由蛋白质相互作用网络的拓扑唯一确定,而是取决于参数(动力学速率,扩散常数),而不同的网络可以产生同等的相位肖像特征。

Spatial organization of proteins in cells is important for many biological functions. In general, the nonlinear, spatially coupled models for protein-pattern formation are only accessible to numerical simulations, which has limited insight into the general underlying principles. To overcome this limitation, we adopt the setting of two diffusively coupled, well-mixed compartments that represents the elementary feature of any pattern -- an interface. For intracellular systems, the total numbers of proteins are conserved on the relevant timescale of pattern formation. Thus, the essential dynamics is the redistribution of the globally conserved mass densities between the two compartments. We present a phase-portrait analysis in the phase-space of the redistributed masses that provides insights on the physical mechanisms underlying pattern formation. We demonstrate this approach for several paradigmatic model systems. In particular, we show that the pole-to-pole Min oscillations in Escherichia coli are relaxation oscillations of the MinD polarity orientation. This reveals a close relation between cell polarity oscillatory patterns in cells. Critically, our findings suggest that the design principles of intracellular pattern formation are found in characteristic features in these phase portraits (nullclines and fixed points). These features are not uniquely determined by the topology of the protein-interaction network but depend on parameters (kinetic rates, diffusion constants) and distinct networks can give rise to equivalent phase portrait features.

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