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

点击翻译按钮获取中文摘要

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.