How do neurons maintain mitochondrial homeostasis in vivo?

神经元如何维持体内线粒体稳态？

• 批准号: 10586450
• 负责人: Erin L Barnhart
• 金额: $ 41.13万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586450
• 关键词: Active Biological Transport; Affect; Alzheimer' s Disease; Architecture; Axon; Binding; Biological Models; Cell Culture System; Cell Culture Techniques; Cells; Complement; Complex; Data Set; Defect; Dendrites; Diffusion; Distal; Drosophila genus; Ensure; Genetic; Goals; Health; Homeostasis; Individual; Label; Link; Maintenance; Measurement; Measures; Mitochondria; Mitochondrial Proteins; Modeling; Molecular; Morphology; Motion; Movement; Neurodegenerative Disorders; Neurons; Organism; Outcome; PINK1 gene; Parkin; Parkinson Disease; Pattern; Physiological; Play; Population; Role; Spatial Distribution; Stress; System; Testing; Time; Vision; Visual system structure; base; cell motility; cell type; experimental study; fly; imaging approach; in vivo; in vivo imaging; in vivo imaging system; innovation; insight; mathematical model; meter; millisecond; mitochondrial autophagy; nanometer; neuronal cell body; oxidative damage; predictive modeling; prevent; self organization; spatiotemporal; tool; visual stimulus

Project Summary Mitochondria are critical for neuronal function and must be reliably distributed throughout the entire neuron. To maintain healthy, properly distributed mitochondria, neurons must coordinate mitochondrial dynamics, including motility, fission and fusion, and degradation, over space and time. The broad goal of this proposal is to define mechanisms for spatiotemporal control of mitochondrial dynamics in neurons in vivo. To that end, we will employ an innovative in vivo imaging approach to measure mitochondrial dynamics in well-defined motion vision neurons in Drosophila. By combining our in vivo measurements with mathematical modeling, we will gain mechanistic insight into how neurons maintain mitochondrial homeostasis at the systems level. We propose three specific aims. In Aim 1 we will determine how neurons maintain steady-state mitochondrial distribution patterns despite high levels of mitochondrial motility within complex neuronal morphologies. Specifically, we will test the hypothesis that neuronal architectures are optimized for the robust self- organization of specific mitochondrial localization patterns. We will use experimental measurements of in vivo mitochondrial motility and neuronal branching patterns to develop a quantitative model linking large-scale mitochondrial distributions to branch scaling rules. We will test this model by predicting mitochondrial localization patterns from experimental measurements of neuronal architecture across morphologically and functionally diverse Drosophila visual system neurons. We will then test our model predictions by comparing to ground truth measurements of mitochondrial distributions in EM datasets. In Aim 2 we will investigate how proper spatiotemporal control of mitochondrial fission and fusion contributes to the maintenance of healthy mitochondria in distal axons and dendrites. We will test the hypothesis that neurons optimize fission and fusion rates to both maximize complementation across mitochondria and ensure efficient delivery of newly- synthesized mitochondrial proteins to distal axons and dendrites. Finally, in Aim 3 we will probe the relationship between neuronal activity and mitophagy rates in neurons in vivo. Altogether, this proposal promises to provide a critical mechanistic framework for understanding how neurons regulate mitochondrial movement, fission and fusion, and degradation to maintain healthy, properly distributed mitochondrial populations in vivo, providing new insight into the molecular and cellular basis for neurodegenerative diseases.

项目摘要 线粒体对于神经元功能至关重要，并且必须可靠地分布在整个神经元中。到 维持健康，适当分布的线粒体，神经元必须协调线粒体动力学， 包括空间和时间上的运动性、裂变和融合以及降解。该提案的总体目标是 以确定在体内神经元中线粒体动力学的时空控制机制。为此我们 将采用一种创新的体内成像方法来测量线粒体在明确运动中的动力学 果蝇的视觉神经元。通过结合我们的体内测量与数学建模，我们将 获得神经元如何在系统水平上维持线粒体稳态的机械见解。我们 提出三个具体目标。在目标1中，我们将确定神经元如何维持线粒体的稳态 分布模式，尽管复杂的神经元形态内的线粒体运动水平高。 具体来说，我们将测试的假设，神经元结构优化的强大的自我， 组织特定的线粒体定位模式。我们将使用实验测量体内 线粒体运动和神经元分支模式，以建立一个定量模型， 线粒体分布符合分支标度规则。我们将通过预测线粒体来测试这个模型， 来自神经元结构的实验测量的定位模式， 功能多样的果蝇视觉系统神经元。然后，我们将通过比较来测试我们的模型预测， EM数据集中线粒体分布的地面实况测量。在目标2中，我们将研究如何 适当的时空控制线粒体的分裂和融合有助于维持健康的 线粒体在远端轴突和树突。我们将测试神经元优化裂变和融合的假设 速率，以最大限度地提高线粒体之间的互补作用，并确保新的 合成线粒体蛋白到远端轴突和树突。最后，在目标3中，我们将探讨 神经元活性和线粒体自噬率之间的关系。总的来说，这项提案承诺提供 理解神经元如何调节线粒体运动，分裂和 融合和降解，以维持体内健康的、适当分布的线粒体群体， 对神经退行性疾病的分子和细胞基础有了新的认识。