MOLECULAR MECHANISMS OF NATURAL LIFESPAN VARIATION

自然寿命变化的分子机制

• 批准号: 10418827
• 负责人: Alaattin Kaya
• 金额: $ 12.87万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10418827
• 关键词: Age of Onset; Aging; Animals; Bayesian Modeling; Biological; Biological Process; Biology of Aging; Biometry; Collaborations; Complex; Computational Biology; Data; Data Aggregation; Data Analyses; Data Set; Development; Dietary Intervention; Disease; Environment; Environmental Risk Factor; Gene Expression; Gene Proteins; Genes; Genetic; Genetic Transcription; Genetic Variation; Genetic study; Genome; Genomics; Genotype; Goals; Individual; Internet; Knowledge; Laboratories; Laboratory Animals; Lead; Link; Longevity; Maps; Mentors; Metabolic; Methods; Mitochondria; Molecular; Multiomic Data; Natural Selections; Nature; Network-based; Organism; Pathway interactions; Pattern; Pharmacology; Phenotype; Phylogenetic Analysis; Population; Process; Protein Biosynthesis; Proteins; Proteome; Regulation; Research; Research Personnel; Resources; Respiration; Saccharomycetales; Shapes; System; Systems Biology; Testing; Training; Transcript; Variant; Yeasts; age related; base; career; career development; comparative genomics; computerized data processing; data integration; dietary; dietary restriction; experience; experimental study; fitness; gene discovery; gene network; gene product; gene therapy; genetic architecture; genetic variant; innovation; learning strategy; life history; macromolecule; metabolome; multidimensional data; multiple omics; mutant; network models; next generation; predictive marker; programs; protein metabolite; response; skills; tool; trait; transcriptome; translatome; trend

MOLECULAR MECHANISMS OF NATURAL LIFESPAN VARIATION Which genes and gene networks are responsible of causing (or retarding) the aging process? Which of these components can be manipulated to maximize lifespan? Despite the fundamental nature of these questions, we have very limited understanding of the cellular mechanisms governing aging. From this perspective, our overarching goal is to apply systems biology approaches to construct a molecular network of longevity, based on multi-omics datasets from 87 natural yeast isolates. Yeast offers a rich resource of available genetic and molecular tools as well as established experimental paradigms for characterizing mechanisms of aging and longevity, and its interaction networks have been previously constructed. Towards this goal, we have generated three important sets of preliminary data. First, we evaluated replicative lifespan (RLS) of 87 natural isolates under three metabolic conditions and uncovered a wide diversity of natural variation in aging. Second, we sequenced the genomes of these strains to characterize their genetic diversity. Third, we found that dietary restriction and activation of mitochondrial respiration extend lifespan in some genotypes, while in others there is no response at all. Based on this data we will test the hypothesis that genetic variation and environmental factors coordinately regulate components of the transcriptional, translational and metabolic machinery, generating variation in dietary response and aging. Application of data integration methods to multiple omics resources will facilitate the discovery of underlying biological processes associated with longevity. We will test this hypothesis in the following Specific Aims: 1) Analyze transcriptomes, translatomes and metabolomes to link variation in these ‘endo-phenotypes’ to external ‘aging phenotypes’ under different metabolic conditions known to modulate lifespan. 2) Integrate the findings of -omics data and identify regulatory networks of lifespan control. This innovative approach of data aggregation and processing, multidimensional data analysis and network-based methods will aid in conceptualizing the molecular mechanisms that underlie natural variation of aging and aging-related perturbations at an unprecedented scale and level of detail. Finally, these studies will identify general trends in lifespan control by leveraging our extensive experience in systems approaches of life history of traits of more complex organisms. The application proposes a program for expanded training with established mentor and two co-mentors in network, systems, and computational biology to facilitate the PI's development into an independent investigator focusing on basic biology of aging. The experience, knowledge, and skills gained through the research plan and career development activities will carry the candidate forward towards a career as an independent investigator.

自然寿命变异的分子机制 哪些基因和基因网络负责引起（或延迟）衰老过程？其中哪一个 可以操纵组件以最大化寿命？尽管这些问题的基本本质，我们 对管理衰老的细胞机制的了解非常有限。从这个角度来看，我们的 总体目标是应用系统生物学方法来构建基于寿命的分子网络 在来自87种天然酵母菌株的多媒体数据集上。酵母提供可用遗传和的丰富资源 分子工具以及已建立的实验范式，以表征衰老机制和 寿命及其交互网络先前已经构建。达到这个目标，我们有 生成了三组重要的初步数据集。首先，我们评估了87天然的复制寿命（RLS） 在三种代谢条件下的分离株，并发现了衰老的自然变异的广泛多样性。第二， 我们对这些菌株的基因组进行了测序，以表征它们的遗传多样性。第三，我们发现饮食 线粒体呼吸的限制和激活在某些基因型中延长了寿命，而在其他基因型中则延长了寿命 根本没有反应。基于这些数据，我们将测试遗传变异和 环境因素协同调节转录，翻译和 代谢机制，产生饮食反应和衰老的变化。数据集成的应用 多种OMICS资源的方法将有助于发现相关的基本生物过程 长寿。我们将在以下特定目的中检验该假设：1）分析转录组， 翻译和代谢组将这些“内部表型”中的变异与外部“衰老表型”联系起来 在不同的代谢条件下，已知可以调节寿命。 2）整合 - 组数据的发现和 确定寿命控制的监管网络。这种数据聚合和处理的创新方法， 多维数据分析和基于网络的方法将有助于概念化分子 衰老和与衰老相关的扰动的自然变化的机制是前所未有的 和细节水平。最后，这些研究将通过利用我们的 在系统的生命历史上，广泛的经验更复杂的生物特征。这 申请建议是一项计划，用于扩展培训的计划，并在网络中既定的心理和两个联合会员， 系统和计算生物学，以促进PI的开发成为独立研究者的关注 关于衰老的基本生物学。通过研究计划和职业获得的经验，知识和技能 开发活动将使候选人朝着独立调查员的职业发展。

项目成果

Genetic perturbation of mitochondrial function reveals functional role for specific mitonuclear genes, metabolites, and pathways that regulate lifespan.

• DOI: 10.1007/s11357-023-00796-4
• 发表时间: 2023-08
• 期刊: GEROSCIENCE
• 影响因子: 5.6
• 作者: Phua, Cheryl Zi Jin;Zhao, Xiaqing;Turcios-Hernandez, Lesly;McKernan, Morrigan;Abyadeh, Morteza;Ma, Siming;Promislow, Daniel;Kaeberlein, Matt;Kaya, Alaattin
• 通讯作者: Kaya, Alaattin