Integrative Multi-Scale Systems Analysis of Gene-Expression-Driven Aging Morbidity

基因表达驱动的衰老发病率的综合多尺度系统分析

• 批准号: 10260623
• 负责人: Thomas Stoeger
• 金额: $ 12.29万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10260623
• 关键词: Address; Adult; Age; Aging; Animals; Area; Biochemical; Bioethics; Biology of Aging; Brain; Buffers; Cause of Death; Cell Line; Cell physiology; Cellular Stress; Cellular biology; Collaborations; Communicable Diseases; Complement; Complex; Data; Data Science; Data Scientist; Data Set; Disease; Drug Screening; Economic Burden; Elderly; Elements; Embryo; Ensure; Epithelial; Failure; Foundations; Functional disorder; Funding; Gene Expression; Gene Expression Profiling; Genes; Genetic Transcription; Genome; Genotype-Tissue Expression Project; Geroscience; Global Change; Glutamine; Grant; Health; Heat-Shock Response; Homeostasis; Human; Human Cell Line; Immune; Immunologist; Impairment; In Vitro; Individual; Infection; Inflammatory Response; Influenza A virus; Intervention; Laboratories; Lead; Learning; Length; Life; Link; Lung; Lung diseases; Lung infections; Machine Learning; Macromolecular Complexes; Mentors; Mentorship; Modeling; Molecular; Morbidity - disease rate; Mus; Organ; Pathway interactions; Phase; Pneumonia; Polymerase; Postdoctoral Fellow; Predisposition; Process; Proline; Proteome; Publishing; RNA; RNA Splicing; RNA metabolism; Recovery; Regulation; Reporting; Research; Research Personnel; Running; Scientist; Site; Stimulus; Stress; Supervision; System; Systems Analysis; Techniques; Testing; Tissues; Training; Training Programs; Transcript; United States; Up-Regulation; Virus Diseases; Work; Writing; age related; aged; biological adaptation to stress; cell age; genome-wide; healthspan; immune function; improved; in vivo; in vivo Model; influenza A pneumonia; influenza infection; innovation; interest; loss of function; mortality; mouse model; multiple chronic conditions; normal aging; novel; novel strategies; overexpression; pneumonia model; post-doctoral training; programs; proteostasis; resilience; response; skills; social; stoichiometry; transcriptome; transcriptome sequencing; transcriptomics

Project Summary In a well-received preprint, the investigator identified through unbiased analysis of own and published datasets that during aging, and infection of the lung with influenza A, there is a progressive imbalance in the transcript levels encoded by short genes relative to those encoded by long genes. Failure of gene expression homeostasis impacts the rheostatic ability of almost all cellular processes implicated in aging impairing organ function, particularly in response to systemic stress. Transcriptome imbalance could account for manifestations of aging through several potential mechanisms, including: 1) The dysregulation of individual genes, 2) A dysregulation of the stoichiometry of macromolecular complexes, 3) A relative upregulation of short early-response inflammatory genes, 4) A breakdown of the coordination between molecular pathways and processes encoded by genes of different lengths and 5) A reduction in the capacity of protein homeostasis and cell stress responses to respond towards external stimuli by sequestering its activity toward a buffering of transcriptome imbalance. The investigator will test the hypothesis that during aging transcriptome imbalance globally interferes with the functions encoded by the genome and contributes to the loss of resilience in older individuals. To address this fundamental question, he will focus on innovative mammalian ex vivo, in vitro, and in vivo models of age-dependent transcriptome imbalance, and machine-learning approaches. Reflecting the interdisciplinary character, he will work under the supervision of his main mentor Dr. Amaral, a network scientist and data- scientist, and his co-mentor Dr. Morimoto, a molecular biologist studying protein homeostasis and aging. Further marking his transition to independence, he will be mentored by Dr. Budinger, an immunologist studying changes in immune aging, and Dr. McNally, a geneticist and bioinformatician, which is not part of a project grant of his mentors. Aim 1 (K99): To determine whether SFPQ regulates transcriptome imbalance in aging. Aim 2 (K99): To determine whether adaptive changes in proteostasis buffer transcriptome imbalance during aging after influenza A pneumonia. Aim 3 (R00): To causally link transcriptome imbalance to the age-related susceptibility to influenza A pneumonia. Importantly, the investigator’s mentoring committee has a very strong track record of training postdoctoral fellows in transitioning into independent investigators. He will engage in seminars and learn recent experimental techniques, grant writing, bioethics training, and training on running a laboratory, and obtain additional off-site training on the biology of aging in mice with the purpose to facilitate collaborations. Combining the new skills learned during his K99 mentored phase with his prior expertise in data science and transcriptomics will ensure a strong technical foundation to launch an independent laboratory on gene expression homeostasis in aging and the mechanisms underlying multi-system dysfunction.

项目摘要 在一份广受欢迎的预印本中，研究人员通过对自己和发布的数据集进行公正的分析确定了 在衰老和肺部感染甲型流感期间，转录本存在逐渐的不平衡 短基因编码的水平相对于长基因编码的水平。基因表达动态平衡失灵 影响几乎所有与衰老有关的细胞过程的流变能力，损害器官功能， 尤其是在应对系统性压力的情况下。转录组失衡可以解释衰老的表现 通过几种可能的机制，包括：1)个别基因的失调，2) 大分子络合物的化学计量学，3)短早期反应性炎症的相对上调 基因，4)基因编码的分子途径和过程之间的协调崩溃 不同的长度和5)蛋白质稳态和细胞应激反应能力的降低 通过隔离其活性以缓冲转录组的不平衡来应对外部刺激。这个 研究人员将检验这一假设，即在衰老过程中，全球转录组不平衡会干扰 由基因组编码的功能，并导致老年人丧失韧性。至 为了解决这个根本问题，他将专注于创新的哺乳动物体外、体外和体内模型 与年龄相关的转录组失衡，以及机器学习方法。反映出跨学科 角色，他将在他的主要导师阿马拉尔博士的监督下工作，阿马拉尔博士是一名网络科学家和数据- 科学家和他的共同导师森本博士，一位研究蛋白质动态平衡和衰老的分子生物学家。进一步 标志着他向独立的过渡，他将得到研究变化的免疫学家布丁格博士的指导 以及遗传学家和生物信息学家麦克纳利博士，这不是他的项目拨款的一部分 导师。目的1(K99)：确定SFPQ是否调节衰老过程中的转录组失衡。目标2(K99)： 为了确定蛋白质平衡缓冲区转录组失衡在衰老过程中是否发生适应性变化 甲型流感肺炎。目标3(R00)：转录组失衡与年龄相关性易感性的因果联系 到甲型流感肺炎。重要的是，调查员的指导委员会有非常好的记录 培训博士后研究员过渡为独立调查人员。他将参加研讨会并学习 最新的实验技术，资助撰写，生物伦理学培训，以及实验室运营培训，并获得 关于小鼠衰老生物学的额外场外培训，目的是促进合作。组合 在他的K99指导阶段学到的新技能，以及他以前在数据科学和转录学方面的专业知识 将确保建立基因表达动态平衡的独立实验室的强大技术基础 在衰老和多系统功能障碍的机制方面。