Biological Analysis Core

生物分析核心(BAC)的目标是应用多模式单细胞和成像技术 建立小鼠全寿命组织衰老图谱的研究 多个菌株。我们的老龄化和生物信息学专家团队拥有广泛的基础设施和独特的专业知识 这非常适合于建立一个全面的小鼠细胞衰老图谱，包括它的调节因子，细胞 表现，以及对组织环境内细胞通讯的影响。为了实现这一目标，我们将发展 使用基因组、成像和计算方法进行组织分析的集成流水线 衰老与单细胞和/或空间背景有关。我们将利用NIA对小鼠纵向衰老的研究 (SLAM)多品系小鼠衰老项目，转基因报告和衰老耗竭小鼠，并广泛 单细胞数据集与新的转移学习相结合产生SNCs的跨组织识别 血浆/血清和多个选定组织(由于SNCs的流行及其与衰老的关系而选择) 小鼠的相关病理，以及它们被纳入人类Sennet计划)。我们提出以下建议 特定的目标，包括一种多层次的方法来筛选和深入描述小鼠的SNCs 纸巾的整个生命周期： 目的1：建立衰老小鼠的多模式图谱和转基因模型以鉴定细胞衰老 在小鼠组织中的寿命及其对组织生理学的影响。 目的2：建立小鼠衰老的单细胞转录和表观基因组测序图谱 揭示特定于组织的SNC身份。 目标3：利用成像技术确定组织中SNCs对其邻近细胞生态系统的影响 基于表型和空间衰老图谱。

The goal of the Biological Analysis Core (BAC) is to apply multi-modal single-cell and imaging technologies toward developing an Atlas of Senescence in Murine Tissues in male and female mice across the lifespan in multiple strains. Our team of aging and bioinformatics experts have extensive infrastructure and unique expertise that is ideally suited to build a comprehensive map of murine cellular senescence, including its regulators, cellular manifestations, and impact on cell communication within the tissue environment. To achieve this, we will develop an integrated pipeline for tissue analysis using genomic, imaging, and computational methods to characterize senescence with single-cell and/or spatial context. We will leverage the NIA Study of Longitudinal Aging in Mice (SLAM) multi-strain mouse aging project, transgenic reporter and senescence-depleted mice, and extensive single-cell datasets combined with novel transfer learning to yield cross-tissue identification of SnCs in plasma/serum and multiple select tissues (chosen due to the prevalence of SnCs, their association with aging- related pathologies in mice, and their inclusion in the Human SenNet Program). We propose the following Specific Aims, which encompass a multi-tiered approach to screen and deeply characterize SnCs in murine tissues across their lifespan: Aim 1: Establish multi-modal profiling of aging mice and transgenic models to identify cell senescence in murine tissues across lifespan and their impact on tissue physiology. Aim 2: Generate single-cell transcriptomic and epigenomic sequencing atlases of mouse aging to reveal tissue-specific SnC identities. Aim 3: Determine the impact of SnCs in tissues on their neighboring cell ecosystems using imaging- based phenotypic and spatial senescent mapping.