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Flow Cytometry Analysis of Immune Cell Subsets within the Murine Spleen, Bone Marrow, Lymph Nodes and Synovial Tissue in an Osteoarthritis Model
Published on: April 24, 2020
SEMA4A signaling in macrophage subpopulations and its implication in osteoarthritis
Yue Qiu1, Shuzhong Huang1, Bo Yu1
1Sports Medicine Department, Liuzhou People's Hospital, Liuzhou, China.
Background:
Osteoarthritis (OA) is a common degenerative disease characterized by the deterioration of articular cartilage, affecting approximately 240 million people worldwide. Low-grade inflammation-particularly the imbalance in macrophage polarization-is a critical factor in osteoarthritis progression. M1-type macrophages exacerbate cartilage destruction by secreting pro-inflammatory factors and matrix-degrading enzymes, while M2-type macrophages promote repair through anti-inflammatory factors. While macrophage polarization changes in OA have been reported, the macrophage subpopulation communication architecture and dominant ligand-receptor axes across dynamic state transitions remain unclear-and that this is what our integrated framework aims to address.
Materials And Methods:
This study leverages single-cell transcriptomic data, including 6 normal samples and 12 OA samples, to systematically analyze the interaction patterns and key ligand-receptor pairs of M1/M2 macrophages during OA progression. Methods include cell subset annotation, GSVA functional enrichment, pseudotemporal trajectory analysis, and hdWGCNA network construction. This study provides single-cell-level evidence for the inflammatory mechanisms of OA.
Results:
Cell-cell communication analysis revealed strong bidirectional interactions between M1 and M2 macrophages. Integrative analysis of macrophage subpopulations, pseudotime, hdWGCNA, and cell-cell communication analysis identified SEMA4A as the only overlapping key gene. The SEMA4 signaling pathway exhibited active communication among macrophage subpopulations, with M1 macrophages acting as dominant signal senders. Ligand-receptor analysis showed that SEMA4A-PLXNB2 was the predominant interaction pair with the highest communication probability.
Discussion:
This study identified a dynamic "increase-then-decrease" expression pattern of SEMA4A along the macrophage pseudotime trajectory, suggesting its involvement in macrophage differentiation and state transitions. Ligand-receptor analysis revealed SEMA4A-PLXNB2 as the dominant interaction signaling pathway among macrophage subpopulations, with M1 macrophages acting as central hubs in sending and receiving signals. Together with previous evidence that SEMA4A forms a positive feedback loop with NF-κB and amplifies IL-6/TNF-α production, thereby promoting cartilage catabolism and tissue remodeling, these findings indicate that, in osteoarthritic joints, SEMA4A-PLXNB2 signaling pathway sustains and amplifies the inflammatory microenvironment through macrophage-stromal crosstalk and represents a potential therapeutic candidate that warrants further validation.
Conclusion:
The SEMA4A-PLXNB2 signaling pathway plays an important role in the macrophage-associated inflammatory network and may contribute to the progression of OA, representing a potential therapeutic candidate warranting further validation.