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: 10684955
• 负责人: Simon Melov
• 金额: $ 89.08万
• 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/10684955
• 关键词: Age; Aging; Atlases; Automobile Driving; Back; Biological; Breast; Cell Aging; Cell Culture System; Cell Culture Techniques; Cell Nucleus; Cells; Characteristics; Collaborations; Complex; Custom; Data; Data Analyses; Data Set; Emerging Technologies; Encapsulated; Ensure; Epigenetic Process; Experimental Models; Female breast; Follicular Fluid; Freezing; Frequencies; Gene Expression Profile; Gene Expression Profiling; Goals; Health; Histologic; Human; Knowledge; Liquid substance; Mammary Gland Parenchyma; Maps; Mass Spectrum Analysis; Messenger RNA; Monitor; Muscle; Muscle satellite cell; Organ; Outcome; Outcome Study; Ovary; Phenotype; Plasma; Prevalence; Procedures; Process; Proteins; Role; Sex Differences; Skeletal Muscle; Techniques; Technology; Tissues; Urine; Validation; Work; age related; cell preparation; cell type; design; digital; experimental study; female reproductive system; human female; human tissue; muscular system; nano-string; novel; protein profiling; reproductive; reproductive senescence; sarcopenia; senescence; sex; single nucleus RNA-sequencing; skeletal muscle wasting; spatial relationship; therapeutic development; therapeutic target; tissue biomarkers; tissue culture; tissue mapping; transcriptomic profiling; whole genome

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 巴克研究所组织图谱中心 (TMC) 提议绘制三种人类体细胞和衰老细胞的图谱。 生殖组织；卵巢、乳腺组织和骨骼肌是该领域的一个主要空白。 我们建议通过定义不同细胞和组织类型的特定细胞衰老标记来填补这一空白。 人体组织衰老过程中细胞衰老的标志物该核心的功能包括： 对衰老的多个方面有深入的了解，包括 SASP、新型衰老药物和初步研究 生物样本核心中接收到的定义人体肌肉组织中衰老细胞的数据。 传送到生物分析核心并接受旨在识别衰老的多种程序 细胞核或生物液中的细胞特征（蛋白质或 mRNA），并在组织切片中得到证实。 生物分析核心将传送到数据分析核心，并通过 管理核心。生物分析核心将在空间上绘制并确定细胞的特征。 健康人类卵巢、乳房和肌肉在衰老过程中的衰老过程 四个具体目标 1) 确定大衰老细胞的独特转录特征。 大衰老细胞的转录特征，这些特征在传统的单细胞工作流程中丢失 并使用该数据来确定此类特征在乳房、卵巢和肌肉中的患病率 2) 确定。 我们将全面分析乳房、卵巢和骨骼肌的衰老蛋白特征。 从生物体液和细胞培养物中分泌衰老相关分泌表型 (SASP) 蛋白 使用不同的衰老诱导剂和衰老剂的肌肉、乳房和卵巢系统 3) 确定。 乳房、卵巢和骨骼肌的衰老转录特征我们将使用引导法。 为此目的，针对组织中的关键细胞类型制定策略，以确定独特的单细胞衰老特征 来自每个组织的原型细胞培养物的一系列衰老诱导剂我们将使用这些数据。 使用 snRNA-seq 将类似的特征映射回源自完整组织的复杂的完整分析数据集， 4) 确定衰老细胞的空间关系和频率。 我们将利用 Nanostring（数字空间分析）的新兴技术， 和 10X 技术 (Visium)，以我们在前三项中发现的知识为基础，旨在更好地理解 组织切片中衰老细胞的频率和亚型与其他组织切片相结合。 我们希望创建一个全面的空间图和生殖组织衰老的特征 （乳房和卵巢）以及肌肉（一种体细胞组织）随年龄的性别特异性和纵向差异。