The design principles of the eukaryotic cell: uncovering the coordination of systems-level organelle dynamics, metabolism and growth

真核细胞的设计原理：揭示系统级细胞器动力学、代谢和生长的协调

• 批准号: 10274898
• 负责人: Arindam Shankar Mukherji
• 金额: $ 39.38万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10274898
• 关键词: Aging; Biochemical; Biogenesis; Biological; Cell Proliferation; Cells; Cellular biology; Chemicals; Complex; Data; Diabetes Mellitus; Disease; Eukaryota; Eukaryotic Cell; Foundations; Future; Gene Expression; Gene Expression Regulation; Goals; Growth; Growth and Development function; Health; Individual; Investigation; Knowledge; Machine Learning; Malignant Neoplasms; Mammals; Measurement; Measures; Mediating; Metabolic; Metabolism; Modeling; Organelles; Organism; Output; Pathology; Physiological; Play; Positioning Attribute; Property; Research; Role; Route; Shapes; Site; System; Testing; base; cell growth; cell type; design; flexibility; fungus; genetic manipulation; imaging platform; insight; mathematical model; metabolic profile; metabolomics; new therapeutic target; predictive modeling; programs; public health relevance

Project Summary Perhaps the defining feature of the eukaryotic cell is its organization into biochemically distinct compartments known as organelles. While the biochemical functions of individual organelles are often well known, how cells regulate the copy numbers, sizes, and subcellular positions of its diverse organelles in a coordinated fashion and how organelles interact to produce integrated physiological outputs remain one of the grand challenges in cell biology. The goal of my research program is to discover the quantitative principles governing how cells regulate systems-level organelle dynamics to coordinate metabolism, growth, and proliferation. To achieve this goal, my research strategy will proceed along two directions. In the first direction, I will quantitatively determine how cells coordinate systems-level organelle dynamics with cellular growth demands. Specifically, I will quantify and build a mathematical model of the relationship between cellular organelle composition and cell growth. The model will be calibrated from data obtained by simultaneously visualizing all major metabolic organelles using our machine learning-based hyperspectral imaging platform, exerting chemical biological control over cell growth and proliferation rates, and genetically perturbing key organelle biogenesis, organization, and interaction factors. In the second direction, I will determine how cells coordinate systems-level organelle dynamics and gene expression to control metabolism during growth and proliferation. I will categorize single cells according to their organelle content and systematically measure the temporal correlations in their expression of genes whose products execute organelle-specific functions. I will concomitantly measure the metabolomic profile of these cells sorted by organelle content. I will then combine these measurements to develop a mathematical model that quantitatively captures the connection between gene expression and metabolism as mediated by the cell's organelle makeup. I will subsequently test predictions of this model by systematically tuning organelle interaction strengths by modulating the expression of organelle biogenesis factors and organelle contact sites. Successful investigations along these two directions will yield mechanistic insight into how to untangle the complex interdependencies between organelle dynamics, metabolism, and cell growth and proliferation. A systems- level understanding of how organelle composition and interactions coordinate metabolism to control cellular growth and development will lay a rigorous foundation into future investigations into how the cell actively shapes its organelle composition to match biochemical supply with physiological demand through, how this plasticity is leveraged in health by multicellular organisms to provide the metabolic flexibility needed to develop its myriad cell types, but also in disease by allowing for multiple routes to metabolic pathologies in cancer, diabetes, and aging.

项目摘要 也许真核细胞的决定性特征是它组织成生物化学上不同的隔间。 被称为细胞器。虽然单个细胞器的生化功能通常是众所周知的， 细胞如何协调地调节不同细胞器的拷贝数、大小和亚细胞位置 细胞器如何相互作用以产生综合的生理输出仍然是最重要的问题之一 细胞生物学方面的挑战。我的研究计划的目标是发现量化原理 控制细胞如何调节系统水平的细胞器动力学，以协调新陈代谢、生长和 扩散。为了实现这一目标，我的研究策略将沿着两个方向进行。在第一个 方向，我将定量地确定细胞如何协调系统水平的细胞器动力学与细胞 增长需求。具体地说，我将量化并建立一个数学模型来描述 细胞器组成和细胞生长。该模型将根据以下项目获得的数据进行校准 使用我们基于机器学习的高光谱同时可视化所有主要代谢细胞器 成像平台，对细胞生长和增殖率施加化学生物控制，并从基因上 扰乱关键细胞器的生物发生、组织和相互作用因素。在第二个方向，我会 确定细胞如何协调系统水平的细胞器动力学和基因表达来控制新陈代谢 在生长和繁殖过程中。我将根据细胞器内容物对单个细胞进行分类 系统地测量其产品执行的基因表达中的时间相关性 细胞器特有的功能。我将同时测量这些细胞的代谢谱，按 细胞器内容物。然后，我将把这些测量结果结合起来，建立一个数学模型，定量地 捕捉由细胞细胞器介导的基因表达和新陈代谢之间的联系 化妆。我随后将通过系统地调整细胞器相互作用来测试这个模型的预测。 通过调节细胞器生物发生因子和细胞器接触部位的表达来增强优势。成功 沿着这两个方向进行的调查将产生对如何理清复杂情况的机械性见解 细胞器动力学、新陈代谢和细胞生长与增殖之间的相互依存关系。A系统- 对细胞器组成和相互作用如何协调新陈代谢以控制细胞有深入的了解 生长和发育将为未来研究细胞如何活跃奠定坚实的基础 通过塑造它的细胞器组成来匹配生化供应和生理需求，这是如何 在健康中，多细胞生物体利用可塑性来提供发育所需的代谢灵活性。 它的无数种细胞类型，但也在疾病中，允许多种途径进入癌症的代谢病理， 糖尿病和衰老。