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线虫生长过程中突触密度的内稳态控制的图灵机制。

Turing mechanism for homeostatic control of synaptic density during C. elegans growth.

机构信息

Department of Mathematics, University of Utah 155 South 1400 East, Salt Lake City, Utah 84112, USA.

出版信息

Phys Rev E. 2017 Jul;96(1-1):012413. doi: 10.1103/PhysRevE.96.012413. Epub 2017 Jul 21.

Abstract

We propose a mechanism for the homeostatic control of synapses along the ventral cord of Caenorhabditis elegans during development, based on a form of Turing pattern formation on a growing domain. C. elegans is an important animal model for understanding cellular mechanisms underlying learning and memory. Our mathematical model consists of two interacting chemical species, where one is passively diffusing and the other is actively trafficked by molecular motors, which switch between forward and backward moving states (bidirectional transport). This differs significantly from the standard mechanism for Turing pattern formation based on the interaction between fast and slow diffusing species. We derive evolution equations for the chemical concentrations on a slowly growing one-dimensional domain, and use numerical simulations to demonstrate the insertion of new concentration peaks as the length increases. Taking the passive component to be the protein kinase CaMKII and the active component to be the glutamate receptor GLR-1, we interpret the concentration peaks as sites of new synapses along the length of C. elegans, and thus show how the density of synaptic sites can be maintained.

摘要

我们提出了一种在秀丽隐杆线虫腹索发育过程中进行突触稳态控制的机制,该机制基于生长域上的图灵模式形成形式。秀丽隐杆线虫是理解学习和记忆背后的细胞机制的重要动物模型。我们的数学模型由两种相互作用的化学物质组成,其中一种是被动扩散的,另一种是由分子马达主动运输的,分子马达在前进和后退运动状态(双向运输)之间切换。这与基于快速和慢速扩散物质相互作用的标准图灵模式形成机制有很大的不同。我们在缓慢增长的一维域上推导出化学浓度的演化方程,并使用数值模拟来演示随着长度的增加如何插入新的浓度峰值。将被动成分视为蛋白激酶 CaMKII,将主动成分视为谷氨酸受体 GLR-1,我们将浓度峰值解释为线虫长度上新突触的位置,从而展示了如何维持突触位置的密度。

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