Related Experiment Video
Updated: Aug 9, 2025
Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice
Published on: May 2, 2025
Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental
Fang Miao1,2, Xixi Li3, Chenglin Wang2
1NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Background:
Molecular changes are closely related to the pathogenesis and healing process of diabetic foot ulcers (DFUs), and are crucial for the early prediction and intervention of DFU.
Methods:
Bioinformatics analysis was performed in this study to identify the key differentially expressed genes (DEGs) in DFU, analyze their functions and function modes, and conduct preliminary experimental verification to determine the potential pivotal genes in the pathogenesis of DFU. Two datasets, GSE68183 and GSE80178, were obtained from the Gene Expression Omnibus (GEO). DEGs were obtained using GEO2R. Six co-expressed DEGs (co-DEGs) were obtained by R language analysis. The co-DEGs were constructed by using STRING and Cytoscape 3.7.2 to construct a protein-protein interaction (PPI) network, and two hub genes, NHLRC3 and BNIP3, were identified. The BNIP3 gene was selected for further analysis. Co-DEGs were used for Gene Ontology (GO) function analysis using the WebGestalt database, and BNIP3-related biological processes focused on mitochondrial protein decomposition. GO function analysis of the BNIP3 gene and its interacting genes was carried out using the cluster profile package and org.hs.eg. db package of the R language and its biological process was enriched in the cell response to external stimuli and autophagy.
Results:
BNIP3 and its interacting genes were retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and KEGG pathway enrichment analysis was performed using the WebGestalt database. The results showed that BNIP3 was significantly correlated with mitochondrial autophagy and the FoxO signaling pathway. The miRDB and TargetScan databases were used to identify the relevant microRNAs (miRNAs) regulating the BNIP3 gene, and it was found that miRNA-182 may be involved in the targeted regulation of BNIP3. Western blot analysis was performed to determine the abnormal expression of BNIP3.
Conclusions:
Our study found that the BNIP3 gene may be a new biomarker and intervention target for DFU.
