Mapping and validating senescent cells in human muscle, ovary and breast

绘制并验证人体肌肉、卵巢和乳房中的衰老细胞

• 批准号: 10376499
• 负责人: Simon Melov
• 金额: $ 99.2万
• 依托单位: BUCK INSTITUTE FOR RESEARCH ON AGING
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10376499
• 关键词: Mapping; validating; senescent; cells; human

BIOLOGICAL ANALYSIS CORE - PROJECT SUMMARY This Buck Institute Tissue Mapping Center (TMC) proposes to map senescent cells in three human somatic and reproductive tissues; ovaries, breast tissue and skeletal muscle. A major gap in the field has been to define specific cellular senescence markers for distinct cells and tissue types. We propose to fill this gap by defining markers of cellular senescence in the context of aging in human tissues. The capabilities of this core include a deep knowledge of multiple aspects of senescence encompassing the SASP, novel senolytics, and preliminary data defining senescent cells in human muscle tissue. Tissues received in the Biospecimen Core will be conveyed to the Biological Analysis Core and subjected to multiple procedures designed to identify senescent cell signatures (either protein or mRNA) in nuclei or biofluids, and confirmed in tissue sections. The results from the Biological Analysis Core will be conveyed to the Data Analysis Core, and coordinated through the Administrative Core. The Biological Analysis Core will spatially map and determine the signatures of cellular senescence in healthy human ovaries, breast, and muscle in both sexes across an aging continuum through four specific aims. 1) Determine the unique transcriptional signature of large senescent cells. We will determine the transcriptional signatures of large senescent cells, which are lost during conventional single cell workflows and use this data to determine the prevalence of such signatures in the breast, ovary, and muscle. 2) Determine senescent protein signatures of the breast, ovary, and skeletal muscle. We will comprehensively analyze secreted senescence-associated secretory phenotype (SASP) proteins from bio fluids, and cell culture systems from muscle, breast, and ovaries using different senescence inducers and senolytics. 3) Determine senescent transcriptional signatures of the breast, ovary, and skeletal muscle. We will use a bootstrapping strategy on key cell types from the tissues in this aim, to determine unique single cell senescent signatures derived from a range of senescent inducers on prototypical cell cultures from each tissue. We will use these data to map similar signatures back to complex fully profiled data sets derived from intact tissues using snRNA‐seq, cell assignment, and expression analysis. 4) Determine spatial relationship and frequencies of senescent cells in tissue sections. We will take advantage of emerging technologies from Nanostring (Digital Spatial Profiling), and 10X technologies (Visium) to build on our knowledge discovered in the first three aims to better understand frequency and subtypes of senescent cells within tissue sections from tissue sections. In conjunction with other cores we expect to create a comprehensive spatial map and signatures of senescence in reproductive tissues (breast and ovary) and also the sex-specific and longitudinal differences in muscle, a somatic tissue, with age.

生物分析核心 - 项目摘要 这个Buck Institute组织映射中心（TMC）提案，以在三个人类体细胞和 生殖组织；卵巢，乳房组织和骨骼肌。该领域的主要差距是定义 不同细胞和组织类型的特定细胞感应标记。我们建议通过定义来填补这一空白 在人体组织衰老的背景下，细胞感应的标记。该核心的功能包括 深入了解涵盖SASP，新型鼻孔和初步的多个方面的知识 数据定义人类肌肉组织中的感觉细胞。在生物测量核心中收到的组织将是 传达给生物分析核心，并遵循多种旨在识别感觉的程序 细胞签名（蛋白质或mRNA）在核或生物流体中，并在组织切片中得到证实。结果 生物分析核心将被传达给数据分析核心，并通过 行政核心。生物分析核心将在空间上绘制并确定细胞的特征 健康的人类卵巢，乳房和肌肉的衰老，通过衰老连续性的男女 四个具体目标。 1）确定大型感觉细胞的独特转录特征。我们将确定 大型感觉细胞的转录特征，这些字符在常规的单细胞工作流程中丢失 并使用这些数据来确定乳房，卵巢和肌肉中这种特征的患病率。 2）确定 乳房，卵巢和骨骼肌的感觉蛋白质特征。我们将全面分析 来自生物流体和细胞培养的分泌感应相关的秘书表型（SASP）蛋白 肌肉，乳房和卵巢的系统使用不同的感应诱导剂和鼻孔剂。 3）确定 乳房，卵巢和骨骼肌的感觉转录特征。我们将使用自举 在此目的中，从组织中关键细胞类型的策略，以确定独特的单细胞感觉特征 来自每个组织的原型细胞培养物上的一系列感觉诱导剂。我们将使用这些数据 将相似的签名映射回使用SNRNA-SEQ的完整组织中的复杂完全剖析的数据集， 细胞分配和表达分析。 4）确定感觉细胞的空间关系和频率 在组织切片中。我们将利用纳米弦乐（数字空间分析）的新兴技术， 和10x技术（visium）以在前三个目标中发现的我们的知识来更好地理解我们的知识 组织切片组织切片中感觉细胞的频率和亚型。与其他 我们期望在生殖组织中创建全面的空间图和感应的签名 （乳房和卵巢）以及年龄的肌肉，体细胞组织的性别特异性和纵向差异。