Abstract: Diabetes increases the risk and frequency of bacterial infection and alters the adaptive immune response. Surprisingly little is known about the impact of diabetes on dendritic cells and how it may increase susceptibility to periodontitis. The lack of understanding until recently has been hampered by limited technical ability to define the specific behavior of dendritic cells and interactions with other cell types during active periodontal disease. New advances in single cell transcriptomics such as single cell RNA-seq (scRNA-seq) have provided an exponential increase in our ability to dissect the behavior of specific cell types under various disease conditions. The studies proposed will elucidate how diabetes alters dendritic cell function in a way that contributes to periodontitis. New Prel Data has been added resulting a completely revised proposal demonstrating that diabetes alters dendritic cell gene expression in vivo as assessed by scRNA-seq. The studies proposed involve sophisticated bioinformatic analysis of scRNA-seq data very recently obtained and a new experimental approach, spatially resolved transcriptomics, to provide new insight on how diabetes may affect dendritic cell activity. The risk in this approach in Aim 1 is mitigated by Prel Data that have identified potential key genes that are up- or down-regulated in the periodontium in dendritic cells during active periodontal disease progression, which will be further investigated by bioinformatic analysis of scRNA-seq results. In addition, translational studies are proposed in Aim 1 as a preclinical step for therapeutic intervention. Functional studies are proposed in Aim 2 to examine gene candidates in vitro to establish cause and effect relationships between candidate genes and functional outcomes. Experiments in Aim 3 will use spatial transcriptomics to define how diabetes may alter the spatial compartments in which DC and other leukocytes are found during the initiation of periodontitis and investigate co-localization of cells and pattern of inflammatory gene expression to better understand their interaction. Taken together this proposal combines an unbiased approach for hypothesis discovery with functional in vitro and in vivo methods for hypothesis testing and establishing mechanisms.