Pairing Modeling and Experiment to Understand Microtubule Behavior in Healthy and Injured Neurons

项目摘要 神经元依赖于微管细胞骨架的极性和稳定性来支持远距离定向 运输和长期生存。然而，极性和稳定性都可以快速改变，以响应 损伤和这些重排对神经元的弹性至关重要。越来越明显的是，与其说是 通过时间和空间控制神经元微管组织的单一主机制，多个 各机构并行运行。这种复杂性使人们很难理解每种机制如何 有助于细丝组织和系统作为一个整体的工作方式。为了克服这一挑战，一个 将建立包含已知机制的数学框架。这一框架将是无价的。 以了解树突微管系统，以及它如何对损伤引起的扰动做出反应。 目的1.神经元中微管的极化组织对于正确地将货物运送到轴突和 树枝状结构。树枝状微管极化阵列的空间随机模型将使用 果蝇树突中已知的极性控制机制。该型号还将包含已知的 微管生长动力学参数。将使用实验数据进行模型验证 对极性控制机制的扰动以及对微管动力学的测量。这 模型将提供一个框架，用于理解单个微管动力学和局部极性 机制影响微管的空间组织和极性。 目的2.神经元通常在一生中保持相同的微管极化排列。但是，如果 轴突被移除后，树突可以反转极性，成为再生的轴突。极性如何反转 发生的情况还不清楚。增加微管从细胞体进入的假设驱动 逆转将在体内和硅胶中进行测试。其他控制机制在极性反转中的作用也将是 通过测试数学模型和告知新的实验方向，系统地解决了问题。 目的3.大多数神经元都有几个树突从细胞体中冒出。轴突损伤后，只有一个 树枝晶改变了极性，而其他枝晶则恢复到损伤前的取向。这种选择偏向是 假设依赖于树突的分枝模式。轴突摘除实验的结合 在具有明显分支特征和微管行为的简化数学描述的神经元中， 提供有关枝晶几何形状如何影响极性控制、稳定性和再生的见解。 复杂的活体神经元微管活体成像与新数学的结合 对微管行为的建模将推动对神经元如何维持极化的、但动态的和 灵活的微管细胞骨架终生存在。轴突损伤带来的挑战需要根治 细胞骨架重组。通过健康神经元的测量开发和验证的模型将是 用于深入了解对轴突再生至关重要的微管控制机制。

Project Summary Neurons rely on polarity and stability of the microtubule cytoskeleton to support long-range directed transport and long-term survival. However, both polarity and stability can be rapidly altered in response to injury and these rearrangements are critical for neuronal resilience. It is becoming clear that rather than a single master mechanism controlling neuronal microtubule organization through time and space, multiple mechanisms operate in parallel. This complexity makes it challenging to understand how each mechanism contributes to filament organization and how the system works as a whole. To overcome this challenge, a mathematical framework that incorporates known mechanisms will be built. This framework will be invaluable for understanding the dendrite microtubule system, and how it responds to perturbations induced by injury. Aim 1. Polarized organization of microtubules in neurons is critical for correct cargo delivery to axons and dendrites. A spatial stochastic model of the polarized array of dendritic microtubules will be constructed using known mechanisms of polarity control in Drosophila dendrites. This model will also incorporate known parameters for microtubule growth dynamics. Model validation will be carried out using experimental perturbations of polarity control mechanisms as well as using measurements of microtubule dynamics. This model will provide a framework for understanding how individual microtubule dynamics and local polarity mechanisms influence microtubule spatial organization and polarity. Aim 2. Neurons normally maintain the same polarized arrangement of microtubules for a lifetime. However, if the axon is removed, a dendrite can reverse polarity and become a regenerating axon. How polarity reversal occurs is not understood. The hypothesis that increased entry of microtubules from the cell body drives reversal will be tested in vivo and in silico. The role of other control mechanisms in polarity reversal will also be systematically addressed by testing the mathematical model and informing new experimental directions. Aim 3. Most neurons have several dendrites emerging from the cell body. After axon damage, only one dendrite switches polarity whereas the others revert to their pre-injury orientation. This selection bias is hypothesized to depend on branching patterns of the dendrites. The combination of axon removal experiments in neurons with distinct branching features and a reduced mathematical description of microtubule behavior will provide insights on how dendrite geometry influences polarity control, robustness, and regeneration. The combination of sophisticated live imaging of microtubules in neurons in vivo with new mathematical modeling of microtubule behavior will drive new insights on how neurons maintain a polarized, yet dynamic and flexible microtubule cytoskeleton for a lifetime. The challenges posed by axonal injury require radical cytoskeletal reorganization. Models developed and validated with measurements from healthy neurons will be used to gain deep understanding of microtubule control mechanisms that are critical for axonal regeneration.