Frontiers in Molecular Biosciences (Feb 2022)
Bioinformatics-Guided Analysis Uncovers AOX1 as an Osteogenic Differentiation-Relevant Gene of Human Mesenchymal Stem Cells
Abstract
Background: The available therapeutic options of bone defects, fracture nonunion, and osteoporosis remain limited, which are closely related to the osteogenic differentiation of bone marrow–derived mesenchymal stem cells (BMSCs). Thus, there remains an urgent demand to develop a prediction method to infer osteogenic differentiation–related genes in BMSCs.Method: We performed differential expression analysis between hBMSCs and osteogenically induced samples. Association analysis, co-expression analysis, and PPI analysis are then carried out to identify potential osteogenesis-related regulators. GO enrichment analysis and GSEA are performed to identify significantly enriched pathways associated with AOX1. qRT-PCR and Western blotting were employed to investigate the expression of genes on osteogenic differentiation, and plasmid transfection was used to overexpress the gene AOX1 in hBMSCs.Result: We identified 25 upregulated genes and 17 downregulated genes. Association analysis and PPI network analysis among these differentially expressed genes show that AOX1 is a potential regulator of osteogenic differentiation. GO enrichment analysis and GSEA show that AOX1 is significantly associated with osteoblast-related pathways. The experiments revealed that AOX1 level was higher and increased gradually in differentiated BMSCs compared with undifferentiated BMSCs, and AOX1 overexpression significantly increased the expression of osteo-specific genes, thereby clearly indicating that AOX1 plays an important role in osteogenic differentiation. Moreover, our method has ability in discriminating genes with osteogenic differentiation properties and can facilitate the process of discovery of new osteogenic differentiation–related genes.Conclusion: These findings collectively demonstrate that AOX1 is an osteogenic differentiation-relevant gene and provide a novel method established with a good performance for osteogenic differentiation-relevant genes prediction.
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