Srinivasan Parthasarathy, Zervantonakis Ioannis K, Kothapalli Chandrasekhar R
Department of Mathematics, Cleveland State University, Cleveland, Ohio, United States of America.
Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS One. 2014 Jun 10;9(6):e99640. doi: 10.1371/journal.pone.0099640. eCollection 2014.
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（ECM）中的众多信号引导生长中的神经突沿着特定路径到达其预定目标。神经突的运动由通过神经突尖端的生长锥进行的细胞外信号感知控制，包括化学吸引和排斥信号。然而，在成体中枢神经系统中，因损伤或疾病而丢失或退化的神经突束很难再生和恢复。因此，评估ECM与这些信号的浓度梯度之间的动态相互作用非常重要，这将引发强大的神经突生成。此类信息对于理解发育生物学所涉及的过程、制定损伤后高保真神经突再生策略以及神经退行性疾病的药物发现和靶向治疗至关重要。在此，我们结合数学建模和体外实验对这种关系进行了定量研究，并确定了引导信号和ECM对神经突生长和转向的协同作用。使用仿生微流控系统，我们已经表明，在三维支架内的化学梯度（IGF - 1或BDNF）下，皮质神经突的生长和转向受到引导信号的源浓度和支架物理特性的高度调节。我们提出了一个神经突生长的机制驱动的偏微分方程模型，该模型也可前瞻性地用作预测工具。模型中趋化项的参数通过我们的微流控测定从实验数据中确定。由此产生的模型模拟展示了神经突生长如何受到实验变量的关键影响，这得到了细胞表面受体表达实验数据的进一步支持。模型结果与实验结果非常吻合。这种综合方法代表了一个框架，用于进一步阐明在发育的各个阶段以及健康或患病条件下，特殊细胞类型神经元反应背后的生物学机制。
