Bio-Analysis-Core

摘要 生物分析核心。心肺系统是人体重要的相互依赖的器官系统 身体，这对整体寿命和衰老有重大影响。了解区分 有益于有害的衰老和该器官中衰老细胞状态的异质性 系统至关重要。生物分析核心（BAC）的总体目标是生成高分辨率地图 使用最先进的技术，在整个生命周期中，肺和心脏组织的细胞衰老， 鉴定细胞衰老的稳健生物标志物，其将预测对衰老清除剂的治疗反应。我们将 在健康肺中以单细胞分辨率生成和细化细胞衰老的内源性特征， 使用无偏高含量的当前衰老标记物的综合分析的心脏组织 筛选我们将应用一系列最先进的、高分辨率和高通量的方法来校准， 验证，并产生精确的衰老映射数据。这些将包括多色流式细胞术，高 清除以及天然组织的分辨率成像，scRNASeq/snATAC/PIC-seq多组学，蛋白质组学， 空间转录组学我们将询问3D离体人类肺和心脏组织受到特定的驱动程序 衰老（例如，DNA损伤，端粒磨损）来定义衰老异质性和细化电流 衰老信号肺和心脏PCTS将接受定义的衰老诱导扰动 使用组学分析和3D高分辨率技术， 共聚焦延时成像，用于自然衰老细胞的可视化，跟踪和追踪 体外环境。最后，我们将定义原代衰老细胞的衰老表型和功能 从人肺和心脏组织中分选出来，并将通过以下方法确定细胞和器官对senolytics的特异性反应： 评估他们衰老特征和SASP生物标志物的变化。这些新的签名和 BAC中产生的衰老生物标志物将持续地输入组织绘图分析， 从而通过分层聚类和去卷积来细化细胞衰老的时空映射 使用计算分析和人工智能方法。这将使我们能够绘制衰老细胞， 前所未有的空间分辨率和3D重建，并在整个生命周期内生成全面的， 深入的肺和心脏衰老地图。

ABSTRACT Biological Analysis Core. The cardiopulmonary system is a major inter-dependent organ system in the human body, which has a major impact on overall life span and aging. Understanding the mechanisms that distinguish beneficial from deleterious senescence and the heterogeneity underlying senescent cell states in this organ system is critical. The overall aim of the Biological Analysis Core (BAC) is to generate a high-resolution map of cellular senescence in lung and heart tissue across the lifespan, using state-of-the-art technologies, and identify robust biomarkers of cellular senescence that will predict therapeutic responses to senolytics. We will generate and refine endogenous signatures of cellular senescence at single cell resolution in healthy lung and heart tissue employing comprehensive profiling of current markers of senescence using unbiased high-content screening. We will apply a range of state-of-the-art, high-resolution, and high-throughput methods to calibrate, validate, and produce precise mapping data of senescence. These will include multi-color flow cytometry, high resolution imaging of cleared as well as native tissue, scRNASeq/snATAC/PIC-seq multi-omics, proteomics, and spatial transcriptomics. We will interrogate 3D ex vivo human lung and heart tissue subjected to specific drivers of senescence (e.g., DNA damage, telomere attrition) to define senescence heterogeneity and refine current senescence signatures. Lung and heart PCTS will be subjected to defined senescence-inducing perturbations to map the response of single cells in their natural 3D environment using omics analysis and 3D high-resolution confocal time-lapse imaging for visualization, tracking, and tracing of senescence cells in their natural environment ex vivo. Finally, we will define the senescence phenotype and function of primary senescent cells sorted from human lung and heart tissue and will determine cell- and organ-specific responses to senolytics by assessing their changes in senescence signatures and SASP biomarkers. These novel signatures and biomarkers of senescence generated in the BAC will continuously feed into tissue mapping analysis and will thereby refine the spatiotemporal mapping of cellular senescence by hierarchical clustering and deconvolution using computational analysis and artificial intelligence approaches. This will allow us to map senescent cells at unprecedent spatial resolution and 3D reconstruction across the lifespan and to generate a comprehensive and in-depth Lung and Heart Senescence Map.