Synergistic Effects of 3D ECM and Chemogradients on Neurite Outgrowth and Guidance: A Simple Modeling and Microfluidic Framework

During nervous system development, numerous cues within the extracellular matrix microenvironment (ECM) guide the growing neurites along specific pathways to reach their intended targets. Neurite motility is controlled by extracellular signal sensing through the growth cone at the neurite tip, including chemoattractive and repulsive cues. However, it is difficult to regenerate and restore neurite tracts, lost or degraded due to an injury or disease, in the adult central nervous system. Thus, it is important to evaluate the dynamic interplay between ECM and the concentration gradients of these cues, which would elicit robust neuritogenesis. Such information is critical in understanding the processes involved in developmental biology, and in developing high-fidelity neurite regenerative strategies post-injury, and in drug discovery and targeted therapeutics for neurodegenerative conditions. Here, we quantitatively investigated this relationship using a combination of mathematical modeling and in vitro experiments, and determined the synergistic role of guidance cues and ECM on neurite outgrowth and turning. Using a biomimetic microfluidic system, we have shown that cortical neurite outgrowth and turning under chemogradients (IGF-1 or BDNF) within 3D scaffolds is highly regulated by the source concentration of the guidance cue and the physical characteristics of the scaffold. A mechanistic-driven partial differential equation model of neurite outgrowth has been proposed, which could also be used prospectively as a predictive tool. The parameters for the chemotaxis term in the model are determined from the experimental data using our microfluidic assay. Resulting model simulations demonstrate how neurite outgrowth was critically influenced by the experimental variables, which was further supported by experimental data on cell-surface-receptor expressions. The model results are in excellent agreement with the experimental findings. This integrated approach represents a framework for further elucidation of biological mechanisms underlying neuronal responses of specialized cell types, during various stages of development, and under healthy or diseased conditions.

在神经系统发育过程中，细胞外基质微环境（extracellular matrix microenvironment, ECM）内存在众多导向信号，可引导正在生长的神经突起沿特定路径抵达其靶标位点。神经突起的运动由神经突起顶端的生长锥感知的细胞外信号调控，这类信号包括趋化吸引性与趋化排斥性导向信号。然而，成年中枢神经系统中因损伤或疾病丢失或退化的神经突起束难以实现再生与修复。因此，探究细胞外基质微环境与这类导向信号浓度梯度之间的动态相互作用，对于诱导高效的神经突起发生至关重要。此类信息对于理解发育生物学中的相关过程、开发损伤后高保真的神经突起再生策略，以及针对神经退行性疾病的药物研发与靶向治疗均具有重要意义。
本研究结合数学建模与体外实验对该关系进行了定量探究，明确了导向信号与细胞外基质微环境对神经突起生长与转向的协同调控作用。借助仿生微流控系统，本研究证实：三维支架内基于胰岛素样生长因子1（insulin-like growth factor 1, IGF-1）或脑源性神经营养因子（brain-derived neurotrophic factor, BDNF）的趋化梯度环境下，皮层神经突起的生长与转向受到导向信号源浓度与支架物理特性的严格调控。本研究提出了一种机制驱动的神经突起生长偏微分方程模型，该模型可作为前瞻性预测工具加以应用。模型中趋化项的参数可通过本研究的微流控检测实验从实验数据中拟合得到。模型仿真结果揭示了实验变量对神经突起生长的关键影响，这一结论得到了细胞表面受体表达相关实验数据的进一步验证。模型结果与实验观测结果高度吻合。该整合研究框架可为进一步阐明特定细胞类型神经元在发育不同阶段、健康或疾病状态下的应答相关生物学机制提供研究范式。