System approaches to determine mechanisms underlying yeast replicative aging

确定酵母复制老化机制的系统方法

基本信息

  • 批准号:
    8372233
  • 负责人:
  • 金额:
    $ 63.68万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-09-01 至 2017-06-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The use of invertebrate organisms has become a mainstay of aging research, leading to the identification of hundreds of aging genes. Emphasizing the utility of these studies, at least some of these genes and pathways have conserved effects on longevity in mammals. In taking stock of the progress, it is clear that a new, more system wide approach is required to effective move forward. As we see it, there are two main questions that need to be answered: (1) Given that there are hundreds of aging genes, in which altered expression is associated with lifespan extension, in an organism, how many pathways do they represent and how can they be delineated?; (2) what are the mechanisms that drive aging in invertebrate aging models and are they conserved? This latter question has remained stubbornly refractory to a variety of approaches in the aging research field. With an eye toward answering these two questions, in this proposal three research groups with complementary expertise have joined forces to develop a comprehensive understanding of replicative aging in Saccharomyces cerevisiae using a combination of high throughput and state-of-the-art approaches. Dr. Kennedy (in collaboration with Dr. Matt Kaeberlein at the University of Washington) has just completed a genome-wide screen of yeast ORF knockouts for enhanced replicative lifespan. In Aim 1, we will develop the largest epistasis network of aging using the high-throughput capacity of the Kennedy lab to functionally assess which downstream pathways are required for lifespan extension in a set of representative yeast aging genes. In Aim 2, Dr. Li's research group will use a newly developed microfluidic system to determine the state of pathways purported to be involved in aging in the context of long-lived yeast mutants and in Aim 3, Dr. Brem's group will use RNA sequencing to develop a comprehensive gene expression analysis dataset in a range of long-lived mutants. These latter two approaches will help determine the cellular consequences of longevity mutants and by combing those with the epistasis studies in Aim 1, we will generate a comprehensive understanding of replicative aging, identifying the pathways involved and moving toward a mechanistic understanding of longevity. PUBLIC HEALTH RELEVANCE: Understanding the pathways that regulate aging is of critical importance to medical research. The field has come to understand that aging is the biggest risk factor in a range of chronic diseases that are principle causes of morbidity and mortality in the United States. Moreover, slowing aging in model organisms does not just extend lifespan but, more importantly, delays the onset and progression of these diseases. In this proposal, a key step forward, we take a comprehensive system-wide approach to understand aging in a commonly studied model organism: yeast. To date, studies in yeast have led in large part to the identification of two pathways (TOR and Sirtuins) that are among the most studied in mammals, lending strength to the hypothesis that the knowledge we gain from studies in yeast will be applicable to human aging.
描述(申请人提供):使用无脊椎动物生物体已成为衰老研究的支柱,导致识别出数百个衰老基因。强调这些研究的效用的是,至少其中一些基因和途径对哺乳动物的寿命有保守的影响。在评估进展情况时,显然需要一种新的、更全系统的办法才能有效地向前推进。正如我们所看到的,有两个主要的问题需要回答:(1)鉴于生物体中有数百个衰老基因,其中表达变化与寿命延长有关,它们代表了多少条途径,如何描述它们?(2)在无脊椎动物衰老模型中,驱动衰老的机制是什么,它们是保守的吗?后一个问题对于衰老研究领域中的各种方法来说仍然是顽固的难题。着眼于回答这两个问题,在这项提案中,三个具有互补专业知识的研究小组联合起来,使用高通量和最先进的方法相结合,对酿酒酵母的复制衰老进行了全面的了解。肯尼迪博士(与华盛顿大学的马特·凯伯莱因博士合作)刚刚完成了对酵母ORF基因敲除的全基因组筛选,以延长复制寿命。在目标1中,我们将利用肯尼迪实验室的高通量能力来开发最大的上位性衰老网络,以从功能上评估一组典型的酵母衰老基因中延长寿命所需的下游途径。在目标2中,李博士的研究小组将使用新开发的微流控系统,在长寿命酵母突变的背景下确定据称与衰老有关的途径的状态;在目标3中,Brem博士的团队将使用RNA测序来开发一系列长寿命突变的全面基因表达分析数据集。后两种方法将有助于确定长寿突变体的细胞后果,通过将这些方法与目标1中的上位性研究相结合,我们将对复制衰老有一个全面的理解,确定涉及的途径,并走向对长寿的机械论理解。 公共卫生相关性:了解调节衰老的途径对医学研究至关重要。这一领域已经认识到,老龄化是一系列慢性病中最大的风险因素,这些慢性病是美国发病率和死亡率的主要原因。此外,延缓模式生物的衰老不仅延长了寿命,更重要的是,延缓了这些疾病的发生和发展。在这项提案中,我们向前迈出了关键的一步,我们采取了全面的系统范围的方法来理解一种普遍研究的模式生物:酵母的衰老。到目前为止,对酵母的研究在很大程度上导致了两条在哺乳动物中研究最多的途径(TOR和sirtuins)的确定,这为我们从酵母研究中获得的知识将适用于人类衰老的假设提供了支持。

项目成果

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BRIAN K KENNEDY其他文献

BRIAN K KENNEDY的其他文献

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{{ truncateString('BRIAN K KENNEDY', 18)}}的其他基金

Cellular Aging and Rejuvenation: A Comprehensive Picture from a Dynamic and Network Perspective - Administrative Supplement
细胞衰老与复兴:动态和网络视角的综合图景 - 行政补充
  • 批准号:
    10405350
  • 财政年份:
    2021
  • 资助金额:
    $ 63.68万
  • 项目类别:
Cellular Aging and Rejuvenation: A Comprehensive Picture from a Dynamic and Network Perspective
细胞衰老与复兴:动态和网络视角的综合图景
  • 批准号:
    10171745
  • 财政年份:
    2018
  • 资助金额:
    $ 63.68万
  • 项目类别:
Cellular Aging and Rejuvenation: A Comprehensive Picture from a Dynamic and Network Perspective
细胞衰老与复兴:动态和网络视角的综合图景
  • 批准号:
    9767638
  • 财政年份:
    2018
  • 资助金额:
    $ 63.68万
  • 项目类别:
Cellular Aging and Rejuvenation: A Comprehensive Picture from a Dynamic and Network Perspective
细胞衰老与复兴:动态和网络视角的综合图景
  • 批准号:
    10406920
  • 财政年份:
    2018
  • 资助金额:
    $ 63.68万
  • 项目类别:
Cellular Aging and Rejuvenation: A Comprehensive Picture from a Dynamic and Network Perspective
细胞衰老与复兴:动态和网络视角的综合图景
  • 批准号:
    10667875
  • 财政年份:
    2018
  • 资助金额:
    $ 63.68万
  • 项目类别:
mTORC1 signaling in aging and metabolism
衰老和代谢中的 mTORC1 信号传导
  • 批准号:
    9357510
  • 财政年份:
    2016
  • 资助金额:
    $ 63.68万
  • 项目类别:
System approaches to determine mechanisms underlying yeast replicative aging
确定酵母复制老化机制的系统方法
  • 批准号:
    8536202
  • 财政年份:
    2012
  • 资助金额:
    $ 63.68万
  • 项目类别:
System approaches to determine mechanisms underlying yeast replicative aging
确定酵母复制老化机制的系统方法
  • 批准号:
    8891342
  • 财政年份:
    2012
  • 资助金额:
    $ 63.68万
  • 项目类别:
System approaches to determine mechanisms underlying yeast replicative aging
确定酵母复制老化机制的系统方法
  • 批准号:
    8724849
  • 财政年份:
    2012
  • 资助金额:
    $ 63.68万
  • 项目类别:
TOR, Translation and Aging
TOR、翻译和时效
  • 批准号:
    8214175
  • 财政年份:
    2009
  • 资助金额:
    $ 63.68万
  • 项目类别:

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