Understanding Metabolism in Space and Time – Mechanistic Analysis of the Dynamic Spatial Organization of Metabolism

了解时空代谢 — 代谢动态空间组织的机制分析

• 批准号: 10473024
• 负责人: Chi-Lun Chang
• 金额: $ 163.8万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-08
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10473024
• 关键词: 3-Dimensional; Address; Algorithms; Architecture; Area; Behavior; Biochemistry; Cell Differentiation process; Cells; Cellular biology; Complement; Complex; Data; Dimensions; Dimerization; Disease; Engineering; Equilibrium; Genetic; Imaging technology; Individual; Ions; Knock-out; Life; Light; Logistics; Maps; Mathematics; Metabolic; Metabolic Pathway; Metabolism; Monitor; Organelles; Organism; Outcome; Physical activity; Proteins; Research; Resolution; Scanning Electron Microscopy; Site; Technology; Time; Work; automated segmentation; base; deep learning; disease diagnosis; disease prognosis; interdisciplinary approach; nanoarchitecture; nanoscale; screening; synthetic protein; temporal measurement; tool; trafficking; tumorigenesis; two-dimensional

All living organisms are dynamic metabolic entities that balance between synthesis and breakdown of complex biomolecules to support activities of life. While work from genetics, biochemistry, and recent omics analyses allow us to build comprehensive 2-dimensional (2D) metabolic maps associated with normal and diseased conditions, the results are limited due to insufficient information from the dimensions of subcellular organization and dynamics where metabolic activities physically occur. Thus, we are still largely in dark about bridging scales from 2D maps to 3D subcellular terrain over time, hindering a holistic understanding of metabolism. One major issue is that much about this subcellular terrain throughout an entire cell at meaningful resolution remain elusive. To overcome this barrier, I will apply newly developed whole-cell focus ion beam-scanning electron microscopy (FIB-SEM) and deep learning-based automatic segmentation pipeline to systematically examine and reconstruct subcellular organization at isotropic resolution during metabolic reprogramming, such as cell differentiation and tumorigenesis. This approach will allow us to further develop algorithm to mathematically define architectural features associated with specific metabolic conditions and diseases, which will generate new hypotheses of how changes in subcellular organization can impact metabolic outcomes and provide conceptual advances in disease diagnosis or prognosis. I will further bridge scales of liner metabolic pathways to 3D terrain to dissect the structural-functional crosstalk by correlative super-resolution microcopy. An evolutionarily conserved structural platform connecting metabolic pathways is contact sites, where organelles are tethered to form nanoscale adjoining architecture within ~20 nm to direct trafficking for biomolecules. Regulating these organelle interfaces can accelerate or limit inter-organelle material flow and thus, directly impact metabolic outcomes. To quantitatively interrogate these dynamic nano-architecture, I will engineer a generalizable tool platform based on reversible split fluorescent protein (FP) complementation for visualizing contact sites using imaging technologies with a wide range of spatial and temporal resolutions. Using orthogonal reversible split FPs, this platform will be readily applied to monitor multiple contact sites simultaneously in different metabolic conditions. In conjunction with light-inducible protein dimerization motifs, this platform will be modified to quantitatively manipulate the size and duration of contact sites, allowing us to address how changes in inter-organelle logistics impact metabolic outcome. I will further combine these tools with CRIPSR knockout screening to identify functional and structural components of organelle interfaces, which will be mechanistically defined via an interdisciplinary approach. Build on a wealth of prior data and newly developed technologies, I expect this proposal to significantly transform our understanding in the dynamic spatial organization accommodating metabolism as well as generate new research directions in advancing architecture-to-function crosstalk in various areas of cell biology.

所有的生物体都是动态的代谢实体，它们在复合物的合成和分解之间保持平衡。 支持生命活动的生物分子。虽然遗传学、生物化学和最近的组学分析 允许我们建立与正常和患病相关的全面的二维（2D）代谢图 条件下，由于亚细胞组织维度的信息不足，结果受到限制 以及新陈代谢活动发生的动力学。因此，我们仍然在很大程度上是在黑暗中的桥梁 随着时间的推移，从2D地图扩展到3D亚细胞地形，阻碍了对新陈代谢的整体理解。一 主要问题是，在有意义的分辨率下，贯穿整个细胞的亚细胞地形的大部分仍然存在 难以捉摸。为了克服这一障碍，我将应用新开发的全细胞聚焦离子束扫描电子显微镜， 显微镜（FIB-SEM）和基于深度学习的自动分割流水线， 并在代谢重编程期间以各向同性分辨率重建亚细胞组织，例如细胞 分化和肿瘤发生。这种方法将使我们能够进一步开发算法， 定义与特定代谢状况和疾病相关的结构特征， 关于亚细胞组织变化如何影响代谢结果的新假设， 疾病诊断或预后的概念进展。我将进一步桥接线性代谢途径的尺度， 应用相关超分辨率显微技术对三维地形进行结构-功能串扰的解剖。一个 连接代谢途径的进化上保守的结构平台是接触位点， 在~20 nm范围内形成纳米级邻接结构，以引导生物分子的运输。 调节这些细胞器界面可以加速或限制细胞器间的物质流动，因此，直接 影响代谢结果。为了定量地询问这些动态纳米结构，我将设计一个 用于可视化的基于可逆分裂荧光蛋白（FP）互补的可推广工具平台 使用具有宽范围的空间和时间分辨率的成像技术来检测接触部位。使用 正交可逆分裂FP，该平台将很容易应用于监测多个接触部位 同时在不同的代谢条件下。结合光诱导蛋白二聚化基序， 这个平台将被修改，以定量地操纵接触点的大小和持续时间，使我们能够 解决细胞器间物流的变化如何影响代谢结果。我将进一步联合收割机这些工具 通过CRIPSR敲除筛选来鉴定细胞器界面的功能和结构组分， 这将通过跨学科的方法来机械地定义。基于丰富的先前数据， 新开发的技术，我希望这项建议能大大改变我们对 适应新陈代谢的动态空间组织，并产生新的研究方向 在细胞生物学的各个领域推进结构与功能的串扰。