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Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing

BACKGROUND: Sepsis can result in acute lung injury (ALI). Studies have shown that pharmacological inhibition of ferroptosis can treat ALI. However, the regulatory mechanisms of ferroptosis in sepsis-induced ALI remain unclear. METHODS: Transcriptome sequencing was performed on lung tissue samples fr...

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Autores principales: Hu, Wen, Wu, Zhen, Zhang, Mei, Yu, Shilin, Zou, Xiaohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116744/
https://www.ncbi.nlm.nih.gov/pubmed/37081490
http://dx.doi.org/10.1186/s12890-023-02361-3
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author Hu, Wen
Wu, Zhen
Zhang, Mei
Yu, Shilin
Zou, Xiaohua
author_facet Hu, Wen
Wu, Zhen
Zhang, Mei
Yu, Shilin
Zou, Xiaohua
author_sort Hu, Wen
collection PubMed
description BACKGROUND: Sepsis can result in acute lung injury (ALI). Studies have shown that pharmacological inhibition of ferroptosis can treat ALI. However, the regulatory mechanisms of ferroptosis in sepsis-induced ALI remain unclear. METHODS: Transcriptome sequencing was performed on lung tissue samples from 10 sepsis-induced mouse models of ALI and 10 control mice. After quality control measures, clean data were used to screen for differentially expressed genes (DEGs) between the groups. The DEGs were then overlapped with ferroptosis-related genes (FRGs) to obtain ferroptosis-related DEGs (FR-DEGs). Subsequently, least absolute shrinkage and selection operator (Lasso) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were used to obtain key genes. In addition, Ingenuity Pathway Analysis (IPA) was employed to explore the disease, function, and canonical pathways related to the key genes. Gene set enrichment analysis (GSEA) was used to investigate the functions of the key genes, and regulatory miRNAs of key genes were predicted using the NetworkAnalyst and StarBase databases. Finally, the expression of key genes was validated with the GSE165226 and GSE168796 datasets sourced from the Gene Expression Omnibus (GEO) database and using quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: Thirty-three FR-DEGs were identified between 1843 DEGs and 259 FRGs. Three key genes, Ncf2, Steap3, and Gclc, were identified based on diagnostic models established by the two machine learning methods. They are mainly involved in infection, immunity, and apoptosis, including lymphatic system cell migration and lymphocyte and T cell responses. Additionally, the GSEA suggested that Ncf2 and Steap3 were similarly enriched in mRNA processing, response to peptides, and leukocyte differentiation. Furthermore, a key gene-miRNA network including 2 key genes (Steap3 and Gclc) and 122 miRNAs, and a gene-miRNA network with 1 key gene (Steap3) and 3 miRNAs were constructed using NetworkAnalyst and StarBase, respectively. Both databases predicted that mmu-miR-15a-5p was the target miRNA of Steap3. Finally, Ncf2 expression was validated using both datasets and qRT-PCR, and Steap3 was validated using GSE165226 and qRT-PCR. CONCLUSIONS: This study identified two FR-DEGs (Ncf2 and Steap3) associated with sepsis-induced ALI via transcriptome analyses, as well as their functional and metabolic pathways. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02361-3.
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spelling pubmed-101167442023-04-21 Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing Hu, Wen Wu, Zhen Zhang, Mei Yu, Shilin Zou, Xiaohua BMC Pulm Med Research BACKGROUND: Sepsis can result in acute lung injury (ALI). Studies have shown that pharmacological inhibition of ferroptosis can treat ALI. However, the regulatory mechanisms of ferroptosis in sepsis-induced ALI remain unclear. METHODS: Transcriptome sequencing was performed on lung tissue samples from 10 sepsis-induced mouse models of ALI and 10 control mice. After quality control measures, clean data were used to screen for differentially expressed genes (DEGs) between the groups. The DEGs were then overlapped with ferroptosis-related genes (FRGs) to obtain ferroptosis-related DEGs (FR-DEGs). Subsequently, least absolute shrinkage and selection operator (Lasso) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were used to obtain key genes. In addition, Ingenuity Pathway Analysis (IPA) was employed to explore the disease, function, and canonical pathways related to the key genes. Gene set enrichment analysis (GSEA) was used to investigate the functions of the key genes, and regulatory miRNAs of key genes were predicted using the NetworkAnalyst and StarBase databases. Finally, the expression of key genes was validated with the GSE165226 and GSE168796 datasets sourced from the Gene Expression Omnibus (GEO) database and using quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: Thirty-three FR-DEGs were identified between 1843 DEGs and 259 FRGs. Three key genes, Ncf2, Steap3, and Gclc, were identified based on diagnostic models established by the two machine learning methods. They are mainly involved in infection, immunity, and apoptosis, including lymphatic system cell migration and lymphocyte and T cell responses. Additionally, the GSEA suggested that Ncf2 and Steap3 were similarly enriched in mRNA processing, response to peptides, and leukocyte differentiation. Furthermore, a key gene-miRNA network including 2 key genes (Steap3 and Gclc) and 122 miRNAs, and a gene-miRNA network with 1 key gene (Steap3) and 3 miRNAs were constructed using NetworkAnalyst and StarBase, respectively. Both databases predicted that mmu-miR-15a-5p was the target miRNA of Steap3. Finally, Ncf2 expression was validated using both datasets and qRT-PCR, and Steap3 was validated using GSE165226 and qRT-PCR. CONCLUSIONS: This study identified two FR-DEGs (Ncf2 and Steap3) associated with sepsis-induced ALI via transcriptome analyses, as well as their functional and metabolic pathways. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02361-3. BioMed Central 2023-04-20 /pmc/articles/PMC10116744/ /pubmed/37081490 http://dx.doi.org/10.1186/s12890-023-02361-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hu, Wen
Wu, Zhen
Zhang, Mei
Yu, Shilin
Zou, Xiaohua
Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title_full Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title_fullStr Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title_full_unstemmed Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title_short Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
title_sort identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116744/
https://www.ncbi.nlm.nih.gov/pubmed/37081490
http://dx.doi.org/10.1186/s12890-023-02361-3
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