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Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929774/ https://www.ncbi.nlm.nih.gov/pubmed/36819522 http://dx.doi.org/10.21037/atm-22-6437 |
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author | Miao, Fang Li, Xixi Wang, Chenglin Yuan, Heju Wu, Zhongming |
author_facet | Miao, Fang Li, Xixi Wang, Chenglin Yuan, Heju Wu, Zhongming |
author_sort | Miao, Fang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9929774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-99297742023-02-16 Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification Miao, Fang Li, Xixi Wang, Chenglin Yuan, Heju Wu, Zhongming Ann Transl Med Original Article 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. AME Publishing Company 2023-01-31 2023-01-31 /pmc/articles/PMC9929774/ /pubmed/36819522 http://dx.doi.org/10.21037/atm-22-6437 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Miao, Fang Li, Xixi Wang, Chenglin Yuan, Heju Wu, Zhongming Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title | Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title_full | Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title_fullStr | Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title_full_unstemmed | Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title_short | Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
title_sort | bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929774/ https://www.ncbi.nlm.nih.gov/pubmed/36819522 http://dx.doi.org/10.21037/atm-22-6437 |
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