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

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已发表的数据集进行无偏分析， 在衰老和肺部感染甲型流感的过程中， 相对于长基因编码的水平，短基因编码的水平。基因表达稳态的失败 影响几乎所有涉及衰老损害器官功能的细胞过程的变阻能力， 特别是在应对系统性压力时。转录组不平衡可以解释衰老的表现 通过几种潜在的机制，包括：1）个别基因的失调，2） 大分子复合物的化学计量学，3）短早期反应炎症反应的相对上调， 基因，4）分子途径和基因编码的过程之间协调的破坏， 不同长度和5）蛋白质稳态和细胞应激反应响应的能力降低 通过将其活性隔离以缓冲转录组不平衡来对抗外部刺激。的 研究者将检验衰老过程中转录组失衡全面干扰 基因组编码的功能，并导致老年人丧失弹性。到 为了解决这个基本问题，他将专注于创新的哺乳动物离体，体外和体内模型 与年龄相关的转录组不平衡，以及机器学习方法。反映了跨学科 他将在他的主要导师Amaral博士的监督下工作，Amaral博士是一位网络科学家和数据科学家， 科学家，和他的共同导师森本博士，研究蛋白质稳态和衰老的分子生物学家。进一步 这标志着他向独立的过渡，他将接受研究变化的免疫学家布丁格博士的指导。 McNally博士是一位遗传学家和生物信息学家，这不是他的项目资助的一部分。 导师目的1（K99）：确定SFPQ是否调节衰老中的转录组失衡。目标2（K99）： 为了确定在衰老过程中蛋白质稳定的适应性变化是否缓冲了转录组的不平衡， 甲型流感肺炎。目的3（R00）：将转录组失衡与年龄相关易感性联系起来 甲型流感肺炎重要的是，调查员的指导委员会有一个非常强大的跟踪记录， 培训博士后研究员转变为独立调查员。他将参加研讨会， 最近的实验技术，赠款写作，生物伦理学培训，以及实验室管理培训，并获得 关于小鼠衰老生物学的额外非现场培训，旨在促进合作。结合 他在K99指导阶段学到的新技能，以及他之前在数据科学和转录组学方面的专业知识 将确保建立一个独立的基因表达稳态实验室的强大技术基础 以及多系统功能障碍的潜在机制。

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.