Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis
Objective: Sepsis is a common disease in internal medicine, with a high incidence and dangerous condition. Due to the limited understanding of its pathogenesis, the prognosis is poor. The goal of this project is to screen potential biomarkers for the diagnosis of sepsis and to identify competitive e...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1031589/full |
| _version_ | 1811180074394714112 |
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| author | Li-ming Zheng Jun-qiu Ye Jun-qiu Ye Heng-fei Li Heng-fei Li Quan Liu Quan Liu |
| author_facet | Li-ming Zheng Jun-qiu Ye Jun-qiu Ye Heng-fei Li Heng-fei Li Quan Liu Quan Liu |
| author_sort | Li-ming Zheng |
| collection | DOAJ |
| description | Objective: Sepsis is a common disease in internal medicine, with a high incidence and dangerous condition. Due to the limited understanding of its pathogenesis, the prognosis is poor. The goal of this project is to screen potential biomarkers for the diagnosis of sepsis and to identify competitive endogenous RNA (ceRNA) networks associated with sepsis.Methods: The expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) were derived from the Gene Expression Omnibus (GEO) dataset. The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were screened by bioinformatics analysis. DEmRNAs were analyzed by protein-protein interaction (PPI) network analysis, transcription factor enrichment analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Set Enrichment Analysis (GSEA). After the prediction of the relevant database, the competitive ceRNA network is built in Cytoscape. The gene-drug interaction was predicted by DGIgb. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm five lncRNAs from the ceRNA network.Results: Through Venn diagram analysis, we found that 57 DElncRNAs, 6 DEmiRNAs and 317 DEmRNAs expressed abnormally in patients with sepsis. GO analysis and KEGG pathway analysis showed that 789 GO terms and 36 KEGG pathways were enriched. Through intersection analysis and data mining, 5 key KEGG pathways and related core genes were revealed by GSEA. The PPI network consists of 247 nodes and 1,163 edges, and 50 hub genes are screened by the MCODE plug-in. In addition, there are 5 DElncRNAs, 6 DEmiRNAs and 28 DEmRNAs in the ceRNA network. Drug action analysis showed that 7 genes were predicted to be molecular targets of drugs. Five lncRNAs in ceRNA network are verified by qRT-PCR, and the results showed that the relative expression of five lncRNAs was significantly different between sepsis patients and healthy control subjects.Conclusion: A sepsis-specific ceRNA network has been effectively created, which is helpful to understand the interaction between lncRNAs, miRNAs and mRNAs. We discovered prospective sepsis peripheral blood indicators and proposed potential treatment medicines, providing new insights into the progression and development of sepsis. |
| first_indexed | 2024-04-11T06:45:28Z |
| format | Article |
| id | doaj.art-15c025d8278147208fe9b34135b5db99 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T06:45:28Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-15c025d8278147208fe9b34135b5db992022-12-22T04:39:22ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-11-011310.3389/fgene.2022.10315891031589Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysisLi-ming Zheng0Jun-qiu Ye1Jun-qiu Ye2Heng-fei Li3Heng-fei Li4Quan Liu5Quan Liu6College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, ChinaDepartment of Infection, Hubei Provincial Hospital of Traditional Chinese Medicine, Affiliated to Hubei University of Chinese Medicine, Wuhan, ChinaHubei Provincial Academy of Traditional Chinese Medicine, Wuhan, ChinaDepartment of Infection, Hubei Provincial Hospital of Traditional Chinese Medicine, Affiliated to Hubei University of Chinese Medicine, Wuhan, ChinaHubei Provincial Academy of Traditional Chinese Medicine, Wuhan, ChinaHubei Provincial Academy of Traditional Chinese Medicine, Wuhan, ChinaDepartment of Pulmonary Disease, Hubei Provincial Hospital of Traditional Chinese Medicine, Affiliated to Hubei University of Chinese Medicine, Wuhan, ChinaObjective: Sepsis is a common disease in internal medicine, with a high incidence and dangerous condition. Due to the limited understanding of its pathogenesis, the prognosis is poor. The goal of this project is to screen potential biomarkers for the diagnosis of sepsis and to identify competitive endogenous RNA (ceRNA) networks associated with sepsis.Methods: The expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) were derived from the Gene Expression Omnibus (GEO) dataset. The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were screened by bioinformatics analysis. DEmRNAs were analyzed by protein-protein interaction (PPI) network analysis, transcription factor enrichment analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Set Enrichment Analysis (GSEA). After the prediction of the relevant database, the competitive ceRNA network is built in Cytoscape. The gene-drug interaction was predicted by DGIgb. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm five lncRNAs from the ceRNA network.Results: Through Venn diagram analysis, we found that 57 DElncRNAs, 6 DEmiRNAs and 317 DEmRNAs expressed abnormally in patients with sepsis. GO analysis and KEGG pathway analysis showed that 789 GO terms and 36 KEGG pathways were enriched. Through intersection analysis and data mining, 5 key KEGG pathways and related core genes were revealed by GSEA. The PPI network consists of 247 nodes and 1,163 edges, and 50 hub genes are screened by the MCODE plug-in. In addition, there are 5 DElncRNAs, 6 DEmiRNAs and 28 DEmRNAs in the ceRNA network. Drug action analysis showed that 7 genes were predicted to be molecular targets of drugs. Five lncRNAs in ceRNA network are verified by qRT-PCR, and the results showed that the relative expression of five lncRNAs was significantly different between sepsis patients and healthy control subjects.Conclusion: A sepsis-specific ceRNA network has been effectively created, which is helpful to understand the interaction between lncRNAs, miRNAs and mRNAs. We discovered prospective sepsis peripheral blood indicators and proposed potential treatment medicines, providing new insights into the progression and development of sepsis.https://www.frontiersin.org/articles/10.3389/fgene.2022.1031589/fullbioinformatics analysiscompeting endogenous RNA network (ceRNA network)mRNA-miRNA-lncRNAsepsistherapeutic targets |
| spellingShingle | Li-ming Zheng Jun-qiu Ye Jun-qiu Ye Heng-fei Li Heng-fei Li Quan Liu Quan Liu Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis Frontiers in Genetics bioinformatics analysis competing endogenous RNA network (ceRNA network) mRNA-miRNA-lncRNA sepsis therapeutic targets |
| title | Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis |
| title_full | Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis |
| title_fullStr | Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis |
| title_full_unstemmed | Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis |
| title_short | Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis |
| title_sort | construction of a potentially functional lncrna mirna mrna network in sepsis by bioinformatics analysis |
| topic | bioinformatics analysis competing endogenous RNA network (ceRNA network) mRNA-miRNA-lncRNA sepsis therapeutic targets |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1031589/full |
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