Forciniti Leandro, Schmidt Christine E, Zaman Muhammad H
Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Ann Biomed Eng. 2009 Feb;37(2):363-74. doi: 10.1007/s10439-008-9613-x. Epub 2008 Dec 9.
Neuronal cell polarization (i.e., establishment of an axon) and axon guidance are mediated and controlled by mechanical and chemical signals from the environment. Unfortunately, an integrated approach to study cell-substrate interactions in a unified framework incorporating structural and chemical effects of the substrate has been lacking. In this paper, we present a new model combining experimental and computational methods to better understand the distinct behavior of E18 hippocampal neurons in response to topographical vs. immobilized chemical cues. We present results from our coarse-grain physiological computational model that correctly describes previously observed phenomena and predicts behavior that was subsequently tested through new experiments. The model differentiates topographical from chemical cues via a difference in cue spacing in these two substrates. Using the feature size spacing for topographical cues and a minimum step size, governed by the physics of filopodia protrusion, for chemical cues, the model successfully mimics the trend observed in experimental polarization probability for four different topographical feature sizes and constant chemical cue spacing. Our results not only show good agreement with experiments, but also provide novel suggestions for development of substrates for finer control of neuronal cell polarization.
神经元细胞极化（即轴突的形成）和轴突导向由来自环境的机械和化学信号介导并控制。遗憾的是，一直缺乏一种在统一框架内研究细胞与底物相互作用的综合方法，该框架需纳入底物的结构和化学效应。在本文中，我们提出一种结合实验和计算方法的新模型，以更好地理解E18海马神经元在响应地形与固定化学线索时的不同行为。我们展示了粗粒度生理计算模型的结果，该模型正确描述了先前观察到的现象，并预测了随后通过新实验测试的行为。该模型通过这两种底物中线索间距的差异来区分地形线索和化学线索。利用地形线索的特征尺寸间距以及由丝状伪足伸出的物理原理控制的化学线索的最小步长，该模型成功模拟了在四种不同地形特征尺寸和恒定化学线索间距下实验极化概率中观察到的趋势。我们的结果不仅与实验结果吻合良好，还为开发用于更精细控制神经元细胞极化的底物提供了新的建议。
