Network-Driven Dynamics of Replicative Aging

网络驱动的复制老化动态

• 批准号: 10659600
• 负责人: JEFF M HASTY
• 金额: $ 57.66万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10659600
• 关键词: 5' -AMP-activated protein kinase; Affect; Age; Aging; Automobile Driving; Autophagocytosis; Biology of Aging; Cell Aging; Cells; Complex; Computer Models; Consumption; Data; Deacetylase; Development; Diabetes Mellitus; Disease; Environment; Environmental Risk Factor; Equilibrium; Eukaryota; Foundations; Funding; Genes; Genetic Engineering; Genetic Transcription; Heat-Shock Response; Heme; Homeostasis; Human; Imaging technology; Incidence; Individual; Intervention; Longevity; Lysine; Malignant Neoplasms; Measurement; Mediating; Metabolic; Metabolism; Microfluidics; Mitochondria; Modeling; Molecular; Molecular Chaperones; Neurodegenerative Disorders; Nutrient; Pathway interactions; Phenotype; Process; Production; Property; Proteins; Regulation; Research; Ribosomal DNA; Role; Saccharomyces cerevisiae; Stochastic Processes; Stress; System; Systems Biology; Technology; Testing; Therapeutic Intervention; Yeasts; age related; cell age; dynamic system; environmental change; experimental study; functional decline; gene interaction; gene network; healthspan; innovation; model organism; multicatalytic endopeptidase complex; multidisciplinary; population based; protein aggregation; protein folding; proteostasis; proteotoxicity; sensor; success

Project Summary This project aims at integrating computational modeling and innovative measurement technologies to understand the complexity of single-cell aging and the emergent dynamics from the underlying regulatory networks. Aging is closely associated with many diseases, such cancer, diabetes, and neurodegenerative diseases. Advances in understanding the basic biology of aging will facilitate the development of new interventional strategies to mitigate age-related diseases and prolong human healthspan. Although studies in model organisms have identified many genes and factors that influence lifespan in eukaryotes, emerging challenges are to understand how these genes and factors interact and operate dynamically to drive the aging process and to determine the lifespan. During the previous funding period, our multidisciplinary team, using microfluidic and imaging technologies combined with computational modeling, discovered that isogenic yeast cells age with two distinct forms: one with decreased ribosomal DNA (rDNA) silencing and nucleolar decline (Mode 1) whereas the other with heme depletion and mitochondrial decline (Mode 2). We further identified a core molecular circuit, consisting of the lysine deacetylase Sir2 and the heme-activated protein (HAP) transcriptional complex, that governs the fate decision toward one of the aging paths in single cells. Building upon these results, for the next funding period, we will investigate the age-dependent dynamics of the energy homeostasis and protein homeostasis systems, two conserved aging hallmark pathways in eukaryotes, and their interactions with the Sir2-HAP fate-decision circuit. In Aim 1, we will quantitatively characterize the interactions between aging and the energy homeostasis system and develop a model that simulates the aging dynamics of the system. In Aim 2, we will quantitatively characterize the interactions between aging and the protein homeostasis system and develop a dynamic model of proteostasis in aging based on the data collected. In Aim 3, we will combine experiments with modeling to characterize, simulate, and predict single-cell aging trajectories and lifespan under complex environmental conditions, with a combination of different nutrients and stresses. The proposed research will advance a quantitative and predictive understanding of regulatory networks underlying single-cell aging under complex environmental conditions, laying the foundation for interventional strategies for ameliorating age-related diseases and promoting longevity.

项目摘要 该项目旨在将计算建模和创新测量技术整合到 了解单细胞衰老的复杂性和来自基础调节的新兴动态 网络。衰老与许多疾病，例如癌症，糖尿病和神经退行性密切相关 疾病。了解衰老的基本生物学的进步将有助于发展新的 减轻与年龄有关的疾病并延长人类健康状况的介入策略。虽然研究 模型生物已经确定了许多影响真核生物中寿命的基因和因素 挑战是了解这些基因和因素如何相互作用和动态操作以推动衰老 过程并确定寿命。在上一个资金期间，我们的多学科团队使用 微流体和成像技术与计算建模相结合，发现了等基因酵母 具有两种不同形式的细胞：一种核糖体DNA（rDNA）沉默和核仁下降的细胞 （模式1）另一个有血红素耗竭和线粒体下降（模式2）。我们进一步确定了 核心分子电路，由赖氨酸脱乙酰基酶SIR2和血红素激活蛋白（HAP）组成 转录复合物，该复合物控制了单个细胞中衰老路径之一的命运决定。建筑 根据这些结果，在下一个资金期间，我们将研究能量的年龄依赖性动力学 体内平衡和蛋白质体内平衡系统，两个保守的衰老标志性途径及其 与SIR2-HAP命运决策电路的相互作用。在AIM 1中，我们将定量地表征相互作用 在衰老和能量体内平衡系统之间，并开发了模拟模拟衰老动力学的模型 系统。在AIM 2中，我们将定量地表征衰老与蛋白质之间的相互作用 稳态系统并根据收集的数据在衰老中开发蛋白抑制的动态模型。目标 3，我们将实验与建模相结合以表征，模拟和预测单细胞衰老轨迹 在复杂的环境条件下的寿命以及不同的营养和应力的组合。这 拟议的研究将进一步对基础监管网络的定量和预测性理解 在复杂的环境条件下的单细胞衰老，为介入策略奠定了基础 改善与年龄有关的疾病并促进寿命。