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，以 了解单细胞老化的复杂性和潜在的调控动态 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变。 疾病。了解衰老的基本生物学的进展将促进新的 旨在减轻年龄相关疾病和延长人类健康寿命的干预策略。虽然在中国的研究 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，出现了 挑战是要了解这些基因和因素是如何相互作用和动态地驱动衰老的 过程，并确定寿命。在之前的资助期间，我们的多学科团队使用 微流控和成像技术结合计算模型，发现了同基因酵母 细胞衰老有两种不同的形式：一种是核糖体DNA(RDNA)沉默减少和核仁下降 (模式1)，而另一例伴有血红素耗竭和线粒体下降(模式2)。我们进一步确定了一种 核心分子回路，由赖氨酸脱乙酰酶Sir2和血红素活化蛋白(HAP)组成 转录复合体，它控制着单细胞衰老途径之一的命运决定。建房 在这些结果的基础上，在下一个资金阶段，我们将研究能量随年龄变化的动态 真核生物中两条保守的衰老标志通路--动态平衡和蛋白质动态平衡系统 与Sir2-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 在衰老和能量平衡系统之间的关系，并开发一个模型来模拟老年人的衰老动力学 这个系统。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，并在收集的数据基础上建立衰老过程中蛋白质平衡的动态模型。在AIM 3，我们将实验和建模相结合来描述、模拟和预测单细胞老化轨迹 以及在复杂环境条件下的寿命，以及不同营养物质和压力的组合。这个 拟议的研究将促进对潜在监管网络的定量和预测性理解 在复杂环境条件下的单细胞老化，为干预策略奠定了基础 改善年龄相关疾病，延年益寿。

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.