Causes and consequences of lifespan biomarker variation in Caenorhabditis elegans

秀丽隐杆线虫寿命生物标志物变异的原因和后果

• 批准号: 9282763
• 负责人: Alexander Richard Mendenhall
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9282763
• 关键词: Address; Adult; Affect; Age; Aging; Animal Model; Animals; Biological Markers; Caenorhabditis elegans; Cell physiology; Cells; Chromatin; Colorado; Cultured Cells; Data; Development; Elderly; Environment; Etiology; Event; Free Radicals; Gene Expression; Genes; Heat-Shock Response; Heterogeneity; Human; Immobilization; Individual; Intestines; Laboratories; Life; Light; Literature; Longevity; Measurement; Measures; Methods; Monozygotic twins; Movement; Nematoda; Organism; Outcome; Output; Pathology; Physiological; Predictive Value; Process; Process Measure; Proteins; Reporter; Reporter Genes; Reporting; Research; Resistance; Scientist; Signal Pathway; Signal Transduction; System; Testing; Tissues; Transgenic Organisms; Twin Multiple Birth; Variant; Work; Yeasts; biological systems; embryo cell; epigenomics; experimental study; mature animal; neuronal cell body; non-genetic; novel; promoter; public health relevance; theories; transmission process; young adult

DESCRIPTION (provided by applicant): Specific Aims. In the past 30 years, scientists have learned a great deal from studying genes whose products contribute to differences in aging and lifespan (JOHNSON 2013; VIJG and SUH 2005). Yet, ample evidence shows that the rate of aging is also affected by non-genetic factors (KIRKWOOD and FINCH 2000; MARTIN 2009). For example, genetically identical C. elegans cultured in controlled homogeneous environments eventually reach a point in which some individuals are still capable of normal movement while others are not (HERNDON et al. 2002). There can be a tenfold difference in lifespan between the shortest and longest lived genetically identical C. elegans cultured on the same Petri dish (data from (JOHNSON 1990), analyzed by (KIRKWOOD and FINCH 2002)). The coefficient of variation for lifespan (CV; standard deviation /mean; an appropriate statistic to compare proportional variation) derived from 50 well controlled wild-type C. elegans experiments (homogeneous laboratory environment, Kaeberlein lab) and 1000 pairs of Danish monozygotic twins (heterogeneous environment, (HERSKIND et al. 1996)), gave values of 21% for worms and 23% for humans (Mendenhall et al. unpublished). These facts suggest that non-genetic, stochastic factors (likely including epigenomic changes to chromatin in the adult soma (FRAGA et al. 2005)) contribute significantly to differences in aging rate and lifespan (reviewed in(KIRKWOOD and FINCH 2000)). In 2005, Tom Johnson and coworkers identified a predictor of heterogeneity in lifespan, and I continued these studies in his lab. In genetically identical young adult animals in homogeneous environments, expression of GFP under control of the small heatshock protein promoter, hsp-16.2, defined a variable, whose value predicted subsequent lifespan (MENDENHALL et al. 2012; REA et al. 2005). High expression values thus defined a physiological state that persisted throughout the life of the animal, a state whose consequences included lengthened lifespan, increased resistance to subsequent heat shock, and a lower percentage of life spent immobilized (CYPSER et al. 2013; MENDENHALL et al. 2012; REA et al. 2005). Restated, this long-lived physiological state was defined, operationally, by high expression of a particular reporter gene. Similarly, in yeast, Dr. Brent's lab (COLMAN-LERNER et al. 2005) identified causes of differences in expression of particular combinations of reporters in genetically identical cells cultured in homogeneous environments. These experiments revealed persistent cell-to-cell differences in general ability to express genes into proteins, and in strength of signal transmission through a particular cell signaling pathway. Thus they also operationally defined hitherto unidentified physiological states. In preliminary work, I have extended my research from Colorado to develop rigorous quantitative methods to quantify, in single cells in tissues of C. elegans, previously identified physiological states, and cell- to-ell and animal-to-animal variation in these states. Over the next five years, I will develop numerous single- copy reporter genes to report on other variables, and make use of additional measurements to cast a wide net for additional physiological states. I will determine which physiological states and cellular processes contribute to differences in long term outcomes including rate of aging and lifespan. The central hypothesis of this proposal is that in biologica systems, variation in processes that are temporally upstream causes variation in downstream system outputs. Thus, these experiments will identify key processes (for examples, differences in the activity of particular signaling pathways during early development, or differences in young adult ability to express genes into proteins) for which variation in these measured processes contributes to distinct long term outcomes, and will shed light on the order in which these occur. They will generate data that will address current theories about aging (including, for example, the free radical theory and the disposable soma theory) and produce and test novel hypotheses about mechanisms that result in cell-to-cell and animal-to-animal differences in the rate of aging and lifespan. Finally, these experiments will identify additional reporter gene biomarkers in C. elegans that can be tested for predictive power in other organisms. During the five years of this project I will: Aim 1 (K99): Continue to develop single-copy reporters (>50) and rigorous reporter quantification methods to allow precise measurement of lifespan reporter biomarkers, in order to cast a wide net to quantify distinct physiological states and cellular processes. Aim 2 (K99): Evaluate preexisting and Aim 1-generated transgenic reporter animals to find which cellular reporter levels, signaling events, cellular processes, and organismic parameters are most variable at different points in the life of the animal, in order to decide on restricted subsets of variables to measure longitudinally in Aim 3. Aim 3 (K99/R00): Quantify the Aim 2 and literature-determined parameters longitudinally, from the E cell of the eight cell embryo all the way to the morbid intestine cells of the elderly hermaphrodite, to generate and test hypotheses on causality of inter-individual and inter-cellular variation in gene expression, lifespan and physiological state, to order reported aging pathologies, to establish which theories of aging are most supported by the new data, and to identify additional biomarkers of aging.

描述（由申请人提供）：具体目标。在过去的 30 年中，科学家们通过研究导致衰老和寿命差异的基因，学到了很多东西（JOHNSON 2013；VIJG 和 SUH 2005）。然而，大量证据表明衰老速度也受到非遗传因素的影响（KIRKWOOD 和 FINCH 2000；Martin 2009）。例如，在受控同质环境中培养的基因相同的秀丽隐杆线虫最终会达到一些个体仍然能够正常运动而另一些则不能的程度（HERNDON 等人，2002）。在同一培养皿中培养的基因相同的最短和最长寿命线虫之间的寿命可能存在十倍差异（数据来自（JOHNSON 1990），由（KIRKWOOD 和 FINCH 2002）分析）。寿命变异系数（CV；标准差/平均值；比较比例变异的适当统计量）源自 50 个控制良好的野生型线虫实验（同质实验室环境，Kaeberlein 实验室）和 1000 对丹麦同卵双胞胎（异质环境，（HERSKIND 等人，1996 年）），得出的蠕虫值为 21%，人类为 23% （Mendenhall 等人未发表）。这些事实表明，非遗传、随机因素（可能包括成人体中染色质的表观基因组变化（FRAGA et al. 2005））对衰老率和寿命的差异有显着影响（综述于（KIRKWOOD 和 FINCH 2000））。 2005 年，汤姆·约翰逊 (Tom Johnson) 和同事发现了寿命异质性的预测因素，我在他的实验室继续进行这些研究。在同质环境中基因相同的年轻成年动物中，在小热休克蛋白启动子 hsp-16.2 控制下的 GFP 表达定义了一个变量，其值可预测随后的寿命（MENDENHALL 等人，2012 年；REA 等人，2005 年）。因此，高表达值定义了动物一生中持续存在的生理状态，这种状态的后果包括寿命延长、对随后的热休克的抵抗力增强以及固定不动的生命百分比较低（CYPSER等人，2013年；MENDENHALL等人，2012年；REA等人，2005年）。重申一下，这种长寿的生理状态在操作上是由特定报告基因的高表达来定义的。同样，在酵母中，Brent 博士的实验室（COLMAN-LERNER 等人，2005）确定了在同质环境中培养的基因相同的细胞中特定报告基因组合表达差异的原因。这些实验揭示了细胞与细胞之间在将基因表达为蛋白质的一般能力以及通过特定细胞信号传导途径的信号传输强度方面存在持续差异。因此，他们也在操作上定义了迄今为止尚未确定的生理状态。 在前期工作中，我 扩展了我在科罗拉多州的研究，开发了严格的定量方法来量化秀丽隐杆线虫组织中的单细胞、先前确定的生理状态以及这些状态中细胞与细胞和动物与动物之间的变异。在接下来的五年中，我将开发大量单拷贝报告基因来报告其他变量，并利用额外的测量来广泛撒网以获得更多的生理状态。我将确定哪些生理状态和细胞过程会导致长期结果的差异，包括衰老速度和寿命。 该提案的中心假设是，在生物系统中，暂时上游过程的变化会导致下游系统输出的变化。因此，这些实验将确定关键过程（例如，早期发育过程中特定信号通路活性的差异，或年轻人将基因表达为蛋白质的能力的差异），这些测量过程的变化有助于不同的长期结果，并将揭示这些过程发生的顺序。他们将产生的数据将解决当前有关衰老的理论（包括自由基理论和一次性体体理论），并产生和测试有关导致细胞与细胞和动物与动物之间衰老速度和寿命差异的机制的新假设。最后，这些实验将确定秀丽隐杆线虫中额外的报告基因生物标志物，这些生物标志物可以在其他生物体中测试其预测能力。在这个项目的五年内，我将： 目标1（K99）：继续开发单拷贝报告基因（> 50）和严格的报告基因定量方法，以精确测量寿命报告生物标志物，从而广泛撒网来量化不同的生理状态和细胞过程。目标 2 (K99)：评估预先存在的和目标 1 生成的转基因报告动物，以找出哪些细胞报告水平、信号事件、细胞过程和有机参数在动物生命的不同阶段变化最大，以便决定限制子集 目标 3 中纵向测量的变量。目标 3 (K99/R00)：纵向量化目标 2 和文献确定的参数，从八细胞胚胎的 E 细胞一直到老年雌雄同体的病态肠细胞，以生成和检验关于基因表达、寿命和生理方面的个体间和细胞间变异的因果关系的假设 国家，命令报告的衰老病理学，确定哪些衰老理论最受新数据支持，并确定其他衰老生物标志物。