Modeling the dynamics of genes and excitable membranes

模拟基因和可兴奋膜的动力学

• 批准号: 6233340
• 负责人: John H Byrne
• 金额: $ 19.39万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-25 至 2004-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6233340
• 关键词: Aplysia; alternatives to animals in research; cAMP response element binding protein; calcium flux; computational neuroscience; electrostimulus; genetic models; long term memory; membrane model; model design /development; neural plasticity; single cell analysis

The main function of the nervous system is to process information in ways that lead to adaptive behavior, and to accomplish this, the excitability of neurons and the strength of their synaptic connections need to be modulated continual. After a neuron of neural system has been analyzed for years, it becomes possible to ask what information it carries and how it contributes to this plasticity. At this point, computational approaches can greatly assist integrating accumulated data to explain how different components of a system interact. This proposal will, via computation supplemented with experiments, improve the understanding of the dynamics of a key genetic regulatory system necessary for neuronal plasticity, and of the reciprocal interactions that could be expected between such genetic systems and membrane currents. Two distinct levels of organization will be modeled. At the molecular level, a detailed model will be developed for the genetic regulatory system that utilizes CREB and related transcription factors. This system is known from experiments with mammals and invertebrates to be important for synaptic plasticity and long-term memory formation. At the level of the bioelectrical properties of a single neuron, there is abundant experimental evidence for regulation of ion channel densities by electrical activity. The extensively characterized neuron R15 of Aplysia will serve as a model with which to computationally investigate the consequences of this feedback. A conductance-based model of R15 will be improved by adding coupling terms to the CREB genetic model to provide a plausible description of the effects of gene expression on electrical behavior and to describe feedback from electrical activity, via calcium influx, to gene expression. With this combined model, and parameter values derived from experiment or from the literature, we will also investigate whether known kinetic properties of CREB regulation could provide a mechanism for optimal transcription at specific stimulus frequencies-such a mechanism Could help explain experiments that have demonstrated optimal stimulus frequencies for long-term memory formation in invertebrates. Finally, focusing on these systems is expected to further the aim of our Preliminary Studies-to determine how specific observed behaviors of genes arise from general organizational principles of genetic regulatory systems.

神经系统的主要功能是以产生适应性行为的方式处理信息，为了实现这一目标，需要不断调节神经元的兴奋性及其突触连接的强度。分析了神经系统的神经元后 多年来，我们可以询问它携带哪些信息以及它如何促进这种可塑性。在这一点上，计算方法可以极大地帮助整合积累的数据来解释系统的不同组件如何相互作用。该提案将通过计算 辅以实验，提高对神经元可塑性所必需的关键遗传调控系统动力学的理解，以及对此类遗传系统和膜电流之间可能预期的相互作用的理解。 将模拟两个不同层次的组织。在分子水平上，将开发利用CREB和相关转录因子的遗传调控系统的详细模型。从哺乳动物和无脊椎动物的实验中得知，该系统对于突触可塑性和长期记忆的形成非常重要。在单个神经元的生物电特性水平上，有大量的实验证据表明电活动调节离子通道密度。海兔的广泛表征的神经元 R15 将作为 用于通过计算研究这种反馈的后果的模型。基于电导的 R15 模型将通过在 CREB ​​遗传模型中添加耦合项来改进，以提供基因表达对电行为影响的合理描述，并描述从电活动通过钙流入到基因表达的反馈。有了这个组合模型，以及从实验或文献中得出的参数值，我们还将研究 CREB ​​调节的已知动力学特性是否可以提供一种在特定刺激频率下实现最佳转录的机制——这种机制可以帮助解释已经证明最佳转录的实验无脊椎动物长期记忆形成的刺激频率。最后，关注这些系统预计将进一步实现我们初步研究的目标——确定基因的特定观察行为是如何产生的 遗传调控系统的一般组织原则。