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

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）损伤主要由心脏骤停和中风引起， 神经损伤脑I/R损伤的一个关键组成部分是线粒体代谢功能障碍， 上维护线粒体网络由两种平衡力量维持：裂变和融合。在基础 这些动态过程的工作，以稳定线粒体网络和维持有效的能源 生产然而，线粒体动力学和质量控制的过程被严重破坏， 脑I/R损伤本研究建议的目的是确定中断的阶段， 严格时间限制性脑缺血再灌注损伤的线粒体动力学及相关分子机制 分辨率与传统的主观和定性方法不同， 将使用新的计算和定量工具进行探索。利用计算机科学的进步， 人工智能，一个半自动化的基于机器学习的分类管道将被构建为 分析线粒体形态学、线粒体动力学产物。分类模型将是 使用线粒体中已知分子参与者的条件性敲除模型开发和验证 动力学（例如Opa 1、Drp 1）。此外，基于代理的单细胞线粒体的计算模型， 动力学将使用来自原代神经元的活细胞成像和新的遗传学来构建和优化。 报告子（例如MitoTimer）。该计算模型将用于检验关于基础和 线粒体动力学和质量控制操作的病理率，以及为未来的实验提供信息。 作为减少所需实验组、时间点和动物数量的方法。利用 新开发和验证的计算工具，活细胞成像将在体外模型中进行， 脑I/R、氧葡萄糖剥夺和复氧（OGD/R）。追踪线粒体形态 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 损伤此外，将使用条件反射来探测与所识别的阶段相关的具体机制。 敲除关键动力学蛋白。上述程序将进一步扩展到3D分析， 局灶性缺血性中风的大脑中动脉闭塞（MCAO）模型中的线粒体形态。这 转移到体内实验将提供更大生物系统中的动力学知识， 未来关于脑I/R损伤的翻译工作。本研究沿着先进的学术研究， 强大科学指导，提供了大量的成长和专业机会 发展拟议的工作是独特的定位在计算机科学，数学， 和神经生物学，从而为年轻人的发展创造了一个显着的和独特的环境， 科学家