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-项目总结 该巴克研究所组织映射中心（TMC）提出在三个人体组织中映射衰老细胞， 生殖组织;卵巢、乳腺组织和骨骼肌。该领域的一个主要空白是界定 用于不同细胞和组织类型的特异性细胞衰老标记物。我们建议填补这一空白， 在人体组织衰老的背景下，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、新型衰老抑制剂和初步的 定义人类肌肉组织中衰老细胞的数据。生物样本核心中接收的组织将 传送到生物分析中心，并进行多个程序，旨在确定衰老的 细胞标记（蛋白质或mRNA）在细胞核或生物流体中，并在组织切片中确认。的结果 生物分析核心将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映射并确定细胞的特征， 健康人类卵巢、乳房和肌肉的衰老， 四个具体目标。1)确定大型衰老细胞的独特转录特征。我们将确定 大型衰老细胞的转录特征，其在常规单细胞工作流程中丢失 并使用这些数据来确定这些特征在乳房、卵巢和肌肉中的流行程度。2)确定 乳腺、卵巢和骨骼肌的衰老蛋白特征。我们将全面分析 来自生物流体和细胞培养物的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抑制剂从肌肉、乳房和卵巢中提取系统。3)确定 乳腺、卵巢和骨骼肌的衰老转录特征。我们将使用自举 从组织中的关键细胞类型的策略，以确定独特的单细胞衰老特征 来源于来自每个组织的原型细胞培养物上的一系列衰老诱导剂。我们将使用这些数据 为了使用snRNA-seq将类似的特征映射回来自完整组织的复杂的完全轮廓化的数据集， 细胞分配和表达分析。4)确定衰老细胞的空间关系和频率 在组织切片中。我们将利用Nanostring（数字空间轮廓）的新兴技术， 和10 X技术（Visium），以我们在前三个项目中发现的知识为基础， 来自组织切片的组织切片内衰老细胞的频率和亚型。结合其他 我们希望能够建立一个全面的空间地图和生殖组织衰老的标志， （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。