CRCNS: Activity-dependent growth cone guidance

描述（由申请人提供）：生长锥导航至其目标对于神经系统发育期间神经回路的建立至关重要。生长锥位于生长神经突的顶端，在各种细胞外环境中导航，它们必须感知，整合和响应无数信号。本项目旨在研究正常神经系统发育过程中生长锥引导所需的多信号通路整合的分子机制。这些多信号通路的相互作用的复杂性，在生长锥的指导，如重合检测和串扰信号，以及他们的时空变化在发展过程中，防止他们的阐明单独的生物学方法。该项目的目标是将生物学家和计算科学家聚集在一起，使用完善的实验方法和先进的计算分析，确定在建立突触接触之前由多种神经递质引导信号引起的神经元活动的转导机制。我们的目标是通过实验研究内在生长锥特性的发育变化，这些特性决定了生长锥对外部信号的反应，即，离子通道和神经递质信号，并将它们编码在计算模型中，该计算模型可以模拟在体内神经系统发育期间响应外部引导信号而发生的正常生长锥行为。我们将在体外确定神经递质和指导信号的发育阶段依赖性变化对生长锥转向的影响，随后在体外和体内测试它们的依赖性，并开发计算，多信号整合和化学传感生长锥模型。多信号整合模型将用于模拟生长锥的生物反应，预测生物学上最有效的双向引导信号机制，并预测是否有足够的数据来忠实地表示生长锥多信号整合，以充分描述体内发生的正常生长锥迁移。化学传感模型将用于解码生长锥在体内引导期间遇到的外部环境化学梯度，并预测生长锥行为所需的基本环境参数，以通过直接实验进行确认。

DESCRIPTION (provided by applicant): Navigation of growth cones to their targets is essential for the establishment of neural circuits during nervous system development. Growth cones, at the tips of growing neurites, navigate through a variety of extracellular environments in which they must sense, integrate and respond to a myriad of signals. This project seeks to investigate the molecular mechanisms of integration of the multi-signaling pathways required for growth cone guidance during normal nervous system development. The complexity of the interactions of these multi-signaling pathways during growth cone guidance, such as coincident detection and cross-talk signaling, as well as their spatiotemporal changes during development, prevents their elucidation by biological methods alone. The goal of this project is to bring together biologists and computational scientists to determine the mechanisms by which neuronal activities evoked by multiple neurotransmitter-guidance signals are transduced before synaptic contacts are established, using well established experimental methods and advanced computational analyses. We aim to experimentally investigate the developmental changes in intrinsic growth cone properties that determine growth cone responses to external signals, i.e., ion channels and neurotransmitter signals, and to encode them in a computational model that can simulate the normal growth cone behavior that occurs in response to external guidance signals during nervous system development in vivo. We will determine the effects of developmental stage-dependent changes in neurotransmitter and guidance signals on growth cone turning in vitro, and subsequently test their dependencies both in vitro and in vivo, and develop computational, multi-signal integration and chemo-sensing growth cone models. Multi-signal integration models will be used to simulate biological responses of growth cones, to predict the most biologically efficient bi-directional guidance signaling mechanisms and to predict whether there is sufficient data to allow a faithful representation of growth cone multi-signal integration to fully describe normal growth cone migration as it occurs in vivo. Chemo-sensing models will be used to decode the external environmental chemical gradients that growth cones encounter during their guidance in vivo, and predict the essential environmental parameters required for growth cone behavior to allow their confirmation by direct experimentation.