Combination of single-cell and bulk RNA-seq reveals changes in immune landscape in osteomyelitis
Objective: This study profiled the osteomyelitis immune micro-environment in depth, pinpointed driver genes and cell populations that fuel disease progression, and mined the data for actionable drug targets. Methods: We analyzed time-series transcriptomic sequencing data from mouse tibial osteomyelitis samples in dataset GSE168896. Fuzzy c-means clustering was applied to reveal gene sets linked to disease progression. Immune cell infiltration analysis was conducted through online tool ImmuCellAI-mouse. Furthermore, by leveraging single-cell sequencing data, we characterized immune cell subpopulations and pinpointed the key cell subtypes that exhibited in osteomyelitis mouse. Results: We identified six gene clusters exhibiting distinct temporal expression patterns and functional roles in osteomyelitis processes, such as leukocyte and lymphocyte activation, ossification. Single-cell sequencing analysis further revealed 7 distinct cellular subpopulations. Among these, M2-like macrophages demonstrated a significant increase following osteomyelitis. Arg+Sdc4+ Mac and Cxcl1+Ccl4+ Mac were new subpopulations of macrophages that emerged after osteomyelitis, the infiltration of Mif+Cd63+ Mac significantly increased. Besides, Cxcl2-Cxcr2 ligand-receptors contributed mostly in immune cells. Overall design: Single cell RNA-seq profilling of bone marrow flox mouse, osteomylities flox mouse and Trim59-cKO mouse (flox_ctrl,flox_om,cko_om) two weeks after modeling.