Department of Physics and Astronomy, Tufts University, Medford, Massachusetts.
Department of Physics and Astronomy, Tufts University, Medford, Massachusetts.
Biophys J. 2022 Mar 1;121(5):769-781. doi: 10.1016/j.bpj.2022.01.020. Epub 2022 Jan 31.
The formation of neuronal networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body and axonal navigation toward target neurons. Axonal growth is guided by the interactions between the tip of the axon (growth cone) and its extracellular environmental cues, which include intercellular interactions, the biochemical landscape around the neuron, and the mechanical and geometrical features of the growth substrate. Here, we present a comprehensive experimental and theoretical analysis of axonal growth for neurons cultured on micropatterned polydimethylsiloxane (PDMS) surfaces. We demonstrate that closed-loop feedback is an essential component of axonal dynamics on these surfaces: the growth cone continuously measures environmental cues and adjusts its motion in response to external geometrical features. We show that this model captures all the characteristics of axonal dynamics on PDMS surfaces for both untreated and chemically modified neurons. We combine experimental data with theoretical analysis to measure key parameters that describe axonal dynamics: diffusion (cell motility) coefficients, speed and angular distributions, and cell-substrate interactions. The experiments performed on neurons treated with Taxol (inhibitor of microtubule dynamics) and Y-27632 (disruptor of actin filaments) indicate that the internal dynamics of microtubules and actin filaments plays a critical role for the proper function of the feedback mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which high-curvature geometrical features impart high traction forces to the growth cone. These results have important implications for our fundamental understanding of axonal growth as well as for bioengineering novel substrate to guide neuronal growth and promote nerve repair.
神经元网络的形成是理解神经系统发育的一个非常重要的基本现象。网络形成的基本过程是轴突生长,这是一个涉及轴突从细胞体延伸和轴突向靶神经元导航的过程。轴突生长受轴突尖端(生长锥)与其细胞外环境线索之间相互作用的指导,这些线索包括细胞间相互作用、神经元周围的生化环境以及生长基质的机械和几何特征。在这里,我们对培养在微图案化聚二甲基硅氧烷(PDMS)表面上的神经元的轴突生长进行了全面的实验和理论分析。我们证明,闭环反馈是这些表面上轴突动力学的一个重要组成部分:生长锥不断测量环境线索,并根据外部几何特征调整其运动。我们表明,该模型捕获了未经处理和化学修饰神经元在 PDMS 表面上的所有轴突动力学特征。我们将实验数据与理论分析相结合,以测量描述轴突动力学的关键参数:扩散(细胞迁移)系数、速度和角度分布以及细胞-基底相互作用。用紫杉醇(微管动力学抑制剂)和 Y-27632(肌动蛋白丝破坏剂)处理神经元的实验表明,微管和肌动蛋白丝的内部动力学对于反馈机制的正常功能起着关键作用。我们的结果表明,轴突通过接触引导机制遵循几何图案,其中高曲率几何特征向生长锥施加高牵引力。这些结果对于我们深入了解轴突生长以及为引导神经元生长和促进神经修复而设计新型基底具有重要意义。