Network-Driven Dynamics of Replicative Aging

项目摘要 该项目旨在整合计算建模和创新的测量技术， 了解单细胞衰老的复杂性和潜在的调控机制的紧急动态 网络.衰老与许多疾病密切相关，如癌症、糖尿病和神经退行性疾病。 疾病对衰老基本生物学的理解的进步将促进新的 采取干预性战略，减轻与年龄有关的疾病，延长人类健康寿命。虽然研究在 模式生物已经确定了许多影响真核生物寿命的基因和因素， 挑战是要了解这些基因和因素如何相互作用，并动态运作，以推动老化 过程和确定寿命。在上一个资助期间，我们的多学科团队，使用 微流控和成像技术结合计算建模，发现同基因酵母， 细胞衰老有两种不同的形式：一种是核糖体DNA（rDNA）沉默减少和核仁衰退 (Mode 1）而另一个具有血红素耗竭和线粒体下降（模式2）。我们进一步确定了一个 核心分子回路，由赖氨酸脱乙酰酶Sir 2和血红素活化蛋白（HAP）组成 转录复合物，它控制着单细胞中衰老路径之一的命运决定。建筑 根据这些结果，在下一个资助期，我们将研究能量的年龄依赖性动态 内稳态和蛋白质内稳态系统，真核生物中两个保守的衰老标志途径，及其 与Sir 2-HAP命运决定电路的相互作用。在目标1中，我们将定量描述相互作用 之间的老化和能量稳态系统，并开发一个模型，模拟老化的动态， the system.在目标2中，我们将定量描述衰老和蛋白质之间的相互作用， 动态平衡系统，并根据收集到的数据建立衰老过程中蛋白质平衡的动态模型。在Aim中 3、我们将联合收割机实验与建模相结合，对单细胞老化轨迹进行表征、模拟和预测 在复杂的环境条件下，不同的营养和压力的组合。的 拟议的研究将促进对监管网络的定量和预测性理解， 复杂环境条件下的单细胞衰老，为干预策略奠定基础， 改善与年龄有关的疾病和促进长寿。

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.