Biological Analysis Core

生物分析核心

基本信息

批准号：
10683324
负责人：
Hemali Phatnani
金额：
$ 102.17万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
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/10683324
关键词：
21 year old 3-Dimensional Address Adult Age Atlases Biological Biological Markers Biological Models Biology Blood Brain Cells Clinical assessments Computing Methodologies Data Data Analyses Elderly Exhibits Experimental Models Freezing Gene Expression Genetic Models Goals Image In Situ Indirect Immunofluorescence Individual Longevity Maps Modality Modeling Molecular Molecular Profiling Mus Organ Organoids Phenotype Physiological Population Prefrontal Cortex Proteome Proteomics Research Resolution Skin Spinal Cord Technology Testing Tissues Universities brain tissue cell type cohort computerized tools data integration design experience genome-wide human tissue in vitro Model in vivo induced pluripotent stem cell middle age mouse model multi-scale atlas multimodality novel pharmacologic senescence single nucleus RNA-sequencing spatial integration tissue mapping tissue preparation transcriptome transcriptomics validation studies young adult

项目摘要

BIOLOGICAL ANALYSIS CORE (BAC): PROJECT SUMMARY Thus far, our understanding of the cellular and molecular mechanisms underlying the heterogenous, cell type- specific phenotypes of senescence, including potentially convergent mechanisms, has been hindered by the inability to collect in situ ‘omics’ data across the range of scales required, from subcellular to whole organ, in multiple modalities, and with sufficient depth and throughput to locate the small percentage of cells that would exhibit a senescence phenotype. To address this unmet need, the Biological Analysis Core (BAC) will generate and analyze a single-cell level spatial atlas of cell type-specific transcriptome and proteome signatures at a depth sufficient to permit identification of the rare and heterogeneous senescent cell population. This will be achieved in intact tissues from healthy individuals ranging in age from 20 – 80 years, which represents a full spectrum of the human adult lifespan. The ultimate goals of the BAC are to identify and validate a panel of robust senescence biomarkers for each cell type in our target tissues, and their spatial context, at the single-cell level, and to assess the cell autonomous and cell non-autonomous effects of senescent cells on the cellular composition and molecular signatures of the tissue microenvironment. We will take advantage of the advanced technologies, workflows, and novel computational tools developed and established in the Columbia University Senescence Tissue Mapping (CUSTMAP) Center and our expertise/experience in generating multimodal omics data at the single-cell level in three target tissues – brain, spinal cord, and skin. We will achieve our research goals by employing: 1) the Spatial Transcriptomics (ST) approach pioneered by our team to generate an unbiased, transcriptome-wide, and cell type-specific map of senescence in the context of intact human tissues, in conjunction with single-nucleus RNA-seq (snRNA-seq) and novel computational methods developed by the Data Analysis Core (DAC) to uncover the signatures of heterogeneous senescent cells; and 2) Iterative Indirect Immunofluorescence Imaging (4i)-based proteomic profiling to enable the interpretation of spatially resolved gene expression data in the context of cell type-specific senescence-associated changes at the single-cell level. This combination, allowing for genome-wide molecular and cellular characterization of senescence at single-cell resolution in space, has not been attempted at this scale and is one of the primary strengths of the CUSTMAP Center approach. The BAC will achieve its goals in close coordination with the Biospecimen Core (BIO) and the DAC, using optimized tissue preparation and ST/snRNA-seq/4i parameters. In conjunction with the DAC, the BAC will integrate these data with analyses of CSF and blood (the biofluids associated with these tissues), to relate SASP factors with tissue-level signatures. The BAC will also carry out critical validation studies of the identified tissue- and cell type-specific senescence markers and senescence-associated molecular and cellular features, using both cutting-edge iPSC-based in vitro models and tissues from mouse models of genetic and pharmacological senolysis.

生物分析核心 (BAC)：项目摘要到目前为止，我们对异质细胞类型背后的细胞和分子机制的理解衰老的特定表型，包括潜在的收敛机制，已受到阻碍无法收集所需尺度范围（从亚细胞到整个器官）的原位“组学”数据多种模式，并具有足够的深度和吞吐量来定位一小部分细胞，为了解决这一未满足的需求，生物分析核心（BAC）将产生。并深度分析细胞类型特异性转录组和蛋白质组特征的单细胞水平空间图谱足以鉴定稀有且异质的衰老细胞群。这将得以实现。在年龄从 20 岁到 80 岁之间的健康个体的完整组织中，这代表了全方位的 BAC 的最终目标是识别和验证一组稳健的衰老现象。我们的目标组织中每种细胞类型的生物标志物及其空间背景，在单细胞水平上，并评估衰老细胞对细胞组成的细胞自主和细胞非自主影响我们将利用先进技术，哥伦比亚大学衰老研究所开发和建立的工作流程和新颖的计算工具组织图谱 (CUSTMAP) 中心以及我们在生成多模式组学数据方面的专业知识/经验我们将通过在三个目标组织（大脑、脊髓和皮肤）的单细胞水平来实现我们的研究目标。采用：1）我们团队首创的空间转录组学（ST）方法来生成公正的、在完整的人体组织中，转录组范围和细胞类型特异性的衰老图谱与单核 RNA-seq (snRNA-seq) 和 Data 开发的新颖计算方法相结合分析核心（DAC）揭示异质衰老细胞的特征；2）迭代间接；基于免疫荧光成像 (4i) 的蛋白质组分析能够解释空间分辨单细胞水平上细胞类型特异性衰老相关变化背景下的基因表达数据。这种组合允许对单细胞衰老进行全基因组分子和细胞表征空间分辨率，尚未在这种规模上进行过尝试，这是 CUSTMAP 的主要优势之一 BAC 将与生物样本核心 (BIO) 和生物样本中心密切协调来实现其目标。 DAC，使用优化的组织制备和 ST/snRNA-seq/4i 参数与 DAC 结合使用。 BAC 将把这些数据与脑脊液和血液（与这些组织相关的生物体液）的分析相结合，以 BAC 还将对具有组织水平相关特征的 SASP 因子进行关键验证研究。确定了组织和细胞类型特异性衰老标记以及衰老相关分子和细胞特征，使用基于 iPSC 的尖端体外模型和来自遗传和遗传的小鼠模型的组织药理衰老作用。