Core D - Senescence Molecular Phenotyping Core (SMPC)

Core D: PROJECT SUMMARY Cellular senescence is a key driver of aging and age-related diseases. There are however many challenges to identifying and characterizing senescent cells in tissues such as the absence of specific markers, their relative low abundance and vast heterogeneity. Studies conducted during the first cycle of the PPG revealed the presence of sub-populations of senescent cells in aged tissues, which can be p21Cip1- and/or p16Ink4a-dependent and exhibit a heterogeneous SASP profile. In the new cycle of the PPG, our team collectively aims to investigate the impact of targeting these specific sub-populations of senescent cells using unique animal models we have developed. The overall goal of the Senescence Molecular Phenotyping Core (SMPC) (Core D) is to collaborate closely with the various projects and Cores and apply emerging single-cell technologies to provide high-resolution molecular, cellular, and spatial characterization of cellular senescence in different tissues during aging and how it is modified by interventions targeting sub- populations of senescent cells in situ or systemically. Our research strategy builds on recent advances in single-cell transcriptomics and proteomics and the recognition of the significant complexity and heterogeneity in senescent cell phenotypes in different cell-types during aging. We will apply dissociative methods such as single-cell (Sc) and single-nuclei (Sn) RNA- sequencing but also spatially resolved multi-plex imaging methods such as CosMx, Imaging Mass cytometry and CODEX. We will complement these analyses with a variety of established assays to evaluate senescence-associated markers using RNA-scope, Immuno-FISH, FISH, and immunofluorescence. Finally, we will work closely together with Core A and utilize cutting-edge computational tools we developed, to define and analyze the transcriptome and proteome of senescent cells in diverse tissues, considering their spatial distribution, microenvironment, and integrating data from various sources.