Investigating mitochondrial dynamics in cerebral ischemia/reperfusion injury using novel morphological analyses and computational modeling

使用新型形态分析和计算模型研究脑缺血/再灌注损伤中的线粒体动力学

• 批准号: 10314377
• 负责人: Garrett McGuire Fogo
• 金额: $ 3.84万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2022-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10314377
• 关键词: Investigating; mitochondrial; dynamics; cerebral; ischemia; Investigating; mitochondrial; dynamics; cerebral; ischemia

PROJECT SUMMARY Cerebral ischemia/reperfusion (I/R) injury, mainly caused by cardiac arrest and stroke, induces debilitative neurological damage. A key component of cerebral I/R injury is dysfunction in mitochondrial metabolism and maintenance. The mitochondrial network is maintained by two balancing forces: fission and fusion. Under basal conditions, these dynamic processes work to stabilize the mitochondrial network and maintain efficient energy production. However, the processes of mitochondrial dynamics and quality control are severely disrupted by cerebral I/R injury. The objective of the present research proposal is to identify the phases of disrupted mitochondrial dynamics and the related molecular mechanisms in cerebral I/R injury with strict temporal resolution. Rather than using the traditional subjective and qualitative methodologies, mitochondrial dynamics will be probed using novel computational and quantitative tools. Utilizing advances in computational science and artificial intelligence, a semi-automated machine learning-based classification pipeline will be constructed for the analysis of mitochondrial morphology, the product of mitochondrial dynamics. The classification model will be developed and validated using conditional knockout models of known molecular players in mitochondrial dynamics (e.g. Opa1, Drp1). Additionally, an agent-based computational model of single cell mitochondrial dynamics will be constructed and optimized using live cell imaging from primary neurons and novel genetic reporters (e.g. MitoTimer). This computational model will be used to test hypotheses regarding the basal and pathological rates of mitochondrial dynamics and quality control operations, as well as, inform future experiments as a method of reducing the required number of experimental groups, timepoints, and animals. Utilizing the newly developed and validated computational tools, live cell imaging will be performed in an in vitro model of cerebral I/R, oxygen glucose deprivation and reoxygenation (OGD/R). Tracking mitochondrial morphology over time during OGD/R will allow for the identification of distinct phases of mitochondrial dynamics in cerebral I/R injury. Additionally, the specific mechanisms involved with the identified phases will be probed using conditional knockout of key dynamics proteins. The above-mentioned procedures will further be scaled to 3D analysis of mitochondrial morphology in the middle cerebral artery occlusion (MCAO) model of focal ischemic stroke. This move to in vivo experimentation will provide knowledge of dynamics in a larger biological system and allow for future translational work regarding cerebral I/R injury. This research, along with advanced academic study and strong scientific mentorship, provide a tremendous amount of opportunities for growth and professional development. The proposed work is uniquely positioned at the intersection of computer science, mathematics, and neurobiology, and thus creates a remarkable and distinctive environment for the development of young scientist.

项目摘要 脑缺血/再灌注（I/R）损伤，主要是由心脏骤停和中风引起的 神经损害。大脑I/R损伤的关键组成部分是线粒体代谢和 维护。线粒体网络由两个平衡力维持：裂变和融合。在基础下 条件，这些动态过程可以稳定线粒体网络并保持有效的能量 生产。但是，线粒体动力和质量控制的过程严重破坏了 大脑I/R损伤。本研究建议的目的是确定破坏的阶段 严格的时间损伤中的线粒体动力学和相关的分子机制 解决。线粒体动力学不使用传统的主观和定性方法 将使用新颖的计算和定量工具进行探测。利用计算科学的进步和 人工智能，将为基于机器学习的半自动化的分类管道构建 线粒体形态的分析，线粒体动力学的产物。分类模型将是 使用线粒体中已知分子玩家的有条件基因敲除模型开发和验证 动力学（例如OPA1，DRP1）。此外，单细胞线粒体的基于代理的计算模型 动力学将使用原代神经元和新遗传的活细胞成像构建和优化 记者（例如mitotimer）。该计算模型将用于测试有关基础和基础的假设 线粒体动力学和质量控制操作的病理速率，并为未来的实验提供信息 作为减少所需数量的实验组，时间点和动物的方法。利用 新开发和经过验证的计算工具，将在体外模型中执行实时单元成像 大脑I/R，氧葡萄糖剥夺和氧合（OGD/R）。跟踪线粒体形态 OGD/R期间的时间将允许识别脑I/R中线粒体动力学的不同阶段 受伤。此外，将使用条件探测所识别阶段所涉及的特定机制 关键动力学蛋白的敲除。上述程序将进一步缩放到3D分析 局灶性缺血性中风中脑动脉闭塞（MCAO）模型中的线粒体形态。这 转到体内实验将提供更大的生物系统中动态的知识，并允许 关于脑I/R损伤的未来翻译工作。这项研究以及高级学术研究以及 强大的科学指导，为成长和专业提供了巨大的机会 发展。拟议的工作是在计算机科学，数学的交集中唯一位置的 和神经生物学，因此为年轻人的发展创造了一个非凡而独特的环境 科学家。