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Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses
Renal fibrosis (RF) is the common pathological manifestation and central treatment target of multiple chronic kidney diseases with high morbidity and mortality. Currently, the molecular mechanisms underlying RF remain poorly understood, and exploration of RF-related hub targets and pathways is urgen...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9682235/ https://www.ncbi.nlm.nih.gov/pubmed/36438657 http://dx.doi.org/10.3389/fmolb.2022.1035772 |
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author | Cai, Yueqin Chen, Jingan Liu, Jingyan Zhu, Keyan Xu, Zhixing Shen, Jianan Wang, Dejun Chu, Lisheng |
author_facet | Cai, Yueqin Chen, Jingan Liu, Jingyan Zhu, Keyan Xu, Zhixing Shen, Jianan Wang, Dejun Chu, Lisheng |
author_sort | Cai, Yueqin |
collection | PubMed |
description | Renal fibrosis (RF) is the common pathological manifestation and central treatment target of multiple chronic kidney diseases with high morbidity and mortality. Currently, the molecular mechanisms underlying RF remain poorly understood, and exploration of RF-related hub targets and pathways is urgently needed. In this study, two classical RF rat models (adenine and UUO) were established and evaluated by HE, Masson and immunohistochemical staining. To clear molecular mechanisms of RF, differentially expressed genes (DEGs) were identified using RNA-Seq analysis, hub targets and pathways were screened by bioinformatics (functional enrichment analyses, PPI network, and co-expression analysis), the screening results were verified by qRT-PCR, and potential drugs of RF were predicted by network pharmacology and molecular docking. The results illustrated that renal structures were severely damaged and fibrotic in adenine- and UUO-induced models, as evidenced by collagen deposition, enhanced expressions of biomarkers (TGF-β1 and α-SMA), reduction of E-cadherin biomarker, and severe renal function changes (significantly decreased UTP, CREA, Ccr, and ALB levels and increased UUN and BUN levels), etc. 1189 and 1253 RF-related DEGs were screened in the adenine and UUO models, respectively. Two key pathways (AGE-RAGE and NOD-like receptor) and their hub targets (Tgfb1, Col1a1, Nlrc4, Casp4, Trpm2, and Il18) were identified by PPI networks, co-expressed relationships, and qRT-PCR verification. Furthermore, various reported herbal ingredients (curcumin, resveratrol, honokiol, etc.) were considered as important drug candidates due to the strong binding affinity with these hub targets. Overall, this study mainly identified two key RF-related pathways (AGE-RAGE and NOD-like receptor), screened hub targets (Tgfb1, Col1a1, Nlrc4, Casp4, Trpm2, and Il18) that involved inflammation, ECM formation, myofibroblasts generation, and pyroptosis, etc., and provided referable drug candidates (curcumin, resveratrol, honokiol, etc.) in basic research and clinical treatment of RF. |
format | Online Article Text |
id | pubmed-9682235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96822352022-11-24 Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses Cai, Yueqin Chen, Jingan Liu, Jingyan Zhu, Keyan Xu, Zhixing Shen, Jianan Wang, Dejun Chu, Lisheng Front Mol Biosci Molecular Biosciences Renal fibrosis (RF) is the common pathological manifestation and central treatment target of multiple chronic kidney diseases with high morbidity and mortality. Currently, the molecular mechanisms underlying RF remain poorly understood, and exploration of RF-related hub targets and pathways is urgently needed. In this study, two classical RF rat models (adenine and UUO) were established and evaluated by HE, Masson and immunohistochemical staining. To clear molecular mechanisms of RF, differentially expressed genes (DEGs) were identified using RNA-Seq analysis, hub targets and pathways were screened by bioinformatics (functional enrichment analyses, PPI network, and co-expression analysis), the screening results were verified by qRT-PCR, and potential drugs of RF were predicted by network pharmacology and molecular docking. The results illustrated that renal structures were severely damaged and fibrotic in adenine- and UUO-induced models, as evidenced by collagen deposition, enhanced expressions of biomarkers (TGF-β1 and α-SMA), reduction of E-cadherin biomarker, and severe renal function changes (significantly decreased UTP, CREA, Ccr, and ALB levels and increased UUN and BUN levels), etc. 1189 and 1253 RF-related DEGs were screened in the adenine and UUO models, respectively. Two key pathways (AGE-RAGE and NOD-like receptor) and their hub targets (Tgfb1, Col1a1, Nlrc4, Casp4, Trpm2, and Il18) were identified by PPI networks, co-expressed relationships, and qRT-PCR verification. Furthermore, various reported herbal ingredients (curcumin, resveratrol, honokiol, etc.) were considered as important drug candidates due to the strong binding affinity with these hub targets. Overall, this study mainly identified two key RF-related pathways (AGE-RAGE and NOD-like receptor), screened hub targets (Tgfb1, Col1a1, Nlrc4, Casp4, Trpm2, and Il18) that involved inflammation, ECM formation, myofibroblasts generation, and pyroptosis, etc., and provided referable drug candidates (curcumin, resveratrol, honokiol, etc.) in basic research and clinical treatment of RF. Frontiers Media S.A. 2022-11-09 /pmc/articles/PMC9682235/ /pubmed/36438657 http://dx.doi.org/10.3389/fmolb.2022.1035772 Text en Copyright © 2022 Cai, Chen, Liu, Zhu, Xu, Shen, Wang and Chu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Cai, Yueqin Chen, Jingan Liu, Jingyan Zhu, Keyan Xu, Zhixing Shen, Jianan Wang, Dejun Chu, Lisheng Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title | Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title_full | Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title_fullStr | Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title_full_unstemmed | Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title_short | Identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and RNA-seq transcriptome analyses |
title_sort | identification of six hub genes and two key pathways in two rat renal fibrosis models based on bioinformatics and rna-seq transcriptome analyses |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9682235/ https://www.ncbi.nlm.nih.gov/pubmed/36438657 http://dx.doi.org/10.3389/fmolb.2022.1035772 |
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