Frontiers in immunology · 2026
Combination of single-cell and bulk RNA-seq reveals changes in the immune landscape in osteomyelitis.
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Zhu Zhenhua, Jing Xiaopeng, Chen Jun, Li Siteng, Tan Jie, Zeng Ji, Jin Zheng
Аннотация
OBJECTIVE: This study presented a comprehensive characterization of the osteomyelitis immune microenvironment, identified driver genes and pathogenic cell populations underlying disease progression, and uncovered potential therapeutic targets through single-cell and bulk transcriptomic analysis.
METHODS: We analyzed time-series transcriptomic sequencing data from mouse osteomyelitis samples in the dataset GSE168896. Fuzzy c-means clustering was applied to reveal gene sets linked to disease progression. Immune cell infiltration analysis was conducted through the online tool ImmuCellAI-mouse. Furthermore, by leveraging single-cell sequencing data, we characterized immune cell subpopulations and pinpointed the key cell subtypes that were present in the osteomyelitis mice.
RESULTS: We identified six gene clusters exhibiting distinct temporal expression patterns and functional roles in osteomyelitis, such as leukocyte and lymphocyte activation and ossification. Single-cell sequencing analysis further showed seven distinct cellular subpopulations. Among these, macrophages demonstrated a significant increase following osteomyelitis, and the infiltration of Mif+Cd63+, Arg1+Sdc4+, and Cxcl1+Ccl4+ macrophages significantly increased. Moreover, Ccl3-Ccr1 and Cxcl2-Cxcr2 ligand-receptors contributed mostly in immune cells.
CONCLUSION: Our findings tracked the transcriptional dynamics and evolving immune landscape of osteomyelitis, highlighting macrophages as central regulators of disease progression. We identified that significant infiltration of Arg1+Sdc4+, Cxcl1+Ccl4+, and Mif+Cd63+ macrophages may affect osteomyelitis through the Ccl3-Ccr1 and Cxcl2-Cxcr2 signaling pathways. These findings offer a new perspective on immune regulation in osteomyelitis.
METHODS: We analyzed time-series transcriptomic sequencing data from mouse osteomyelitis samples in the dataset GSE168896. Fuzzy c-means clustering was applied to reveal gene sets linked to disease progression. Immune cell infiltration analysis was conducted through the online tool ImmuCellAI-mouse. Furthermore, by leveraging single-cell sequencing data, we characterized immune cell subpopulations and pinpointed the key cell subtypes that were present in the osteomyelitis mice.
RESULTS: We identified six gene clusters exhibiting distinct temporal expression patterns and functional roles in osteomyelitis, such as leukocyte and lymphocyte activation and ossification. Single-cell sequencing analysis further showed seven distinct cellular subpopulations. Among these, macrophages demonstrated a significant increase following osteomyelitis, and the infiltration of Mif+Cd63+, Arg1+Sdc4+, and Cxcl1+Ccl4+ macrophages significantly increased. Moreover, Ccl3-Ccr1 and Cxcl2-Cxcr2 ligand-receptors contributed mostly in immune cells.
CONCLUSION: Our findings tracked the transcriptional dynamics and evolving immune landscape of osteomyelitis, highlighting macrophages as central regulators of disease progression. We identified that significant infiltration of Arg1+Sdc4+, Cxcl1+Ccl4+, and Mif+Cd63+ macrophages may affect osteomyelitis through the Ccl3-Ccr1 and Cxcl2-Cxcr2 signaling pathways. These findings offer a new perspective on immune regulation in osteomyelitis.