Biological Analysis Core

生物分析核心（bac）：项目总结

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.