Monitoring the aging lung using genomics, proteomics and informatics

摘要_核心B 肺和其他组织的长期健康与蛋白质折叠的可持续性密不可分 及其功能。折叠和功能与细胞的能量健康密切相关。这是通过 细胞功能（DNA、RNA和蛋白质）与蛋白质稳态协调的新范式， 蛋白质稳态，是产生、维持和修复蛋白质组的整合生物学途径的集合。 上一个资助期的工作揭示了蛋白质稳定敏感途径和蛋白质合成的重要性。 线粒体在老化肺的管理，对延长寿命的药物有反应的途径 二甲双胍被认为影响线粒体复合物I的功能，ISRIB，我们的初步研究表明， 数据表明在多种损伤模型中加速肺修复。 在核心B中，我们将定量跟踪甲型流感诱导组织恢复期间蛋白质稳态的变化 使用集成的批量和单细胞RNA-Seq、空间转录组学和严格质谱分析的损伤 (MS)接近。我们将这些方法应用于高质量的流式细胞术分选的肺，骨骼， 由Core C提供的来自老年小鼠的肌肉和脑组织。我们在西北大学的计算小组， Scripps Research通过共享的电子平台自由互动。他们将使用这些数据来创建一个多- 对老年动物感染甲型流感后恢复受损的维度理解。核心B将 将这些强大的技术与遗传和药理学研究相结合，研究人员建议， 操纵线粒体复合物I功能，整合的应激反应和ATF 4。我们将 通过关注三个具体目标来支持这些重要的衰老生物学研究： 目的1：使用流式分选技术提供批量和单细胞RNA-Seq和空间转录组学数据 细胞群和均质化组织由核心C提供。 目的2：提供从流式分选的细胞群获得的质谱分析， 老年动物的肺、脑和骨骼肌。 目标3：使用先进的机器学习和系统科学工具将遗传和 衰老期间的药理学干预与来自衰老动物的多组学实验数据。 虽然本核心采用的方法本质上是无偏见的，但我们利用了 在该核心和PPG中，重点关注蛋白质稳态、巨噬细胞生物学和整个生命周期的代谢。 通过提供肺泡II型细胞，肺泡巨噬细胞， 核心B，我们将创建衰老过程中损伤后组织恢复的多组基因型-表型图谱， 将广泛适用于其他限制健康寿命的环境挑战。

ABSTRACT_CORE B The long-term health of the lung and other tissues is inextricably linked to the sustainability of the protein fold and its function. Fold and function are tightly coupled to the energetic health of the cell. This is achieved by the emerging paradigm of harmonization of cell function (DNA, RNA and protein) with protein homeostasis or proteostasis, a collection of integrated biological pathways that generate, maintain and repair the proteome. Efforts in the previous funding period revealed the importance of both proteostasis sensitive pathways and the mitochondria in management of the aging lung, pathways that are responsive to the life-span extending drug metformin that is thought to impact the function of mitochondrial complex I, and ISRIB, which our preliminary data suggests accelerates lung repair in a variety of injury models. In Core B, we will quantitatively track changes in proteostasis during recovery from influenza A-induced tissue injury using integrated bulk and single cell RNA-Seq, spatial transcriptomics and rigorous mass spectrometry (MS) approaches. We will apply these approaches to high quality flow cytometry sorted samples of lung, skeletal muscle and brain tissue from aged mice provided by Core C. Our computational groups at Northwestern and Scripps Research interact freely via shared electronic platforms. They will use these data to create a multi- dimensional understanding of the impaired recovery from influenza A infection in older animals. Core B will couple these powerful technologies with the genetic and pharmacologic studies the investigators propose to manipulate mitochondrial complex I function, the integrated stress response and ATF4 over the lifespan. We will support these important studies in aging biology by focusing on three Specific Aims: Aim 1: To provide bulk and single cell RNA-Seq and spatial transcriptomic data using flow-sorted cell populations and homogenized tissues provided by Core C. Aim 2: To provide mass spectroscopy analyses from flow-sorted cell populations obtained from the lung, brain and skeletal muscle of aged animals. Aim 3. To use advanced machine learning and system science tools to couple genetic and pharmacologic interventions during aging with multi-omic experimental data from aging animals. While the methods employed in this Core are inherently unbiased, we take advantage of the special expertise within this Core and the PPG to focus on proteostasis, macrophage biology and metabolism over the lifespan. By providing simultaneous RNA-Seq and proteomic analysis of alveolar type II cells, alveolar macrophages, Core B we will create a multi-omic genotype to phenotype map of tissue recovery after injury during aging that will be broadly applicable to other environmental challenges that limit healthspan.