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Proteomic Analysis Reveals Differential Expression Profiles in Idiopathic Pulmonary Fibrosis Cell Lines
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, irreversible lung disorder of unknown cause. This disease is characterized by profibrotic activation of resident pulmonary fibroblasts resulting in aberrant deposition of extracellular matrix (ECM) proteins. However, although much is kno...
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Published in: | International journal of molecular sciences 2022-05, Vol.23 (9), p.5032 |
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creator | Velázquez-Enríquez, Juan Manuel Ramírez-Hernández, Alma Aurora Navarro, Luis Manuel Sánchez Reyes-Avendaño, Itayetzi González-García, Karina Jiménez-Martínez, Cristian Castro-Sánchez, Luis Sánchez-Chino, Xariss Miryam Vásquez-Garzón, Verónica Rocío Baltiérrez-Hoyos, Rafael |
description | Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, irreversible lung disorder of unknown cause. This disease is characterized by profibrotic activation of resident pulmonary fibroblasts resulting in aberrant deposition of extracellular matrix (ECM) proteins. However, although much is known about the pathophysiology of IPF, the cellular and molecular processes that occur and allow aberrant fibroblast activation remain an unmet need. To explore the differentially expressed proteins (DEPs) associated with aberrant activation of these fibroblasts, we used the IPF lung fibroblast cell lines LL97A (IPF-1) and LL29 (IPF-2), compared to the normal lung fibroblast cell line CCD19Lu (NL-1). Protein samples were quantified and identified using a label-free quantitative proteomic analysis approach by liquid chromatography-tandem mass spectrometry (LC-MS/MS). DEPs were identified after pairwise comparison, including all experimental groups. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network construction were used to interpret the proteomic data. Eighty proteins expressed exclusively in the IPF-1 and IPF-2 clusters were identified. In addition, 19 proteins were identified up-regulated in IPF-1 and 10 in IPF-2; 10 proteins were down-regulated in IPF-1 and 2 in IPF-2 when compared to the NL-1 proteome. Using the search tool for retrieval of interacting genes/proteins (STRING) software, a PPI network was constructed between the DEPs and the 80 proteins expressed exclusively in the IPF-2 and IPF-1 clusters, containing 115 nodes and 136 edges. The 10 hub proteins present in the IPP network were identified using the CytoHubba plugin of the Cytoscape software. GO and KEGG pathway analyses showed that the hub proteins were mainly related to cell adhesion, integrin binding, and hematopoietic cell lineage. Our results provide relevant information on DEPs present in IPF lung fibroblast cell lines when compared to the normal lung fibroblast cell line that could play a key role during IPF pathogenesis. |
doi_str_mv | 10.3390/ijms23095032 |
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This disease is characterized by profibrotic activation of resident pulmonary fibroblasts resulting in aberrant deposition of extracellular matrix (ECM) proteins. However, although much is known about the pathophysiology of IPF, the cellular and molecular processes that occur and allow aberrant fibroblast activation remain an unmet need. To explore the differentially expressed proteins (DEPs) associated with aberrant activation of these fibroblasts, we used the IPF lung fibroblast cell lines LL97A (IPF-1) and LL29 (IPF-2), compared to the normal lung fibroblast cell line CCD19Lu (NL-1). Protein samples were quantified and identified using a label-free quantitative proteomic analysis approach by liquid chromatography-tandem mass spectrometry (LC-MS/MS). DEPs were identified after pairwise comparison, including all experimental groups. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network construction were used to interpret the proteomic data. Eighty proteins expressed exclusively in the IPF-1 and IPF-2 clusters were identified. In addition, 19 proteins were identified up-regulated in IPF-1 and 10 in IPF-2; 10 proteins were down-regulated in IPF-1 and 2 in IPF-2 when compared to the NL-1 proteome. Using the search tool for retrieval of interacting genes/proteins (STRING) software, a PPI network was constructed between the DEPs and the 80 proteins expressed exclusively in the IPF-2 and IPF-1 clusters, containing 115 nodes and 136 edges. The 10 hub proteins present in the IPP network were identified using the CytoHubba plugin of the Cytoscape software. GO and KEGG pathway analyses showed that the hub proteins were mainly related to cell adhesion, integrin binding, and hematopoietic cell lineage. Our results provide relevant information on DEPs present in IPF lung fibroblast cell lines when compared to the normal lung fibroblast cell line that could play a key role during IPF pathogenesis.</description><identifier>ISSN: 1422-0067</identifier><identifier>ISSN: 1661-6596</identifier><identifier>EISSN: 1422-0067</identifier><identifier>DOI: 10.3390/ijms23095032</identifier><identifier>PMID: 35563422</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Biomarkers ; Cell adhesion ; Cell adhesion & migration ; Cell cycle ; Cell Line ; Cell lineage ; Cell lines ; Chromatography, Liquid ; Disease ; Encyclopedias ; Extracellular matrix ; Extracellular Matrix Proteins - metabolism ; Fibroblasts ; Fibroblasts - metabolism ; Fibrosis ; Genes ; Genomes ; Humans ; Idiopathic Pulmonary Fibrosis - metabolism ; Liquid chromatography ; Lung diseases ; Lungs ; Mass spectrometry ; Mass spectroscopy ; Metabolism ; Metabolites ; Protein expression ; Proteins ; Proteome - metabolism ; Proteomes ; Proteomics ; Proteomics - methods ; Pulmonary fibrosis ; Scientific imaging ; Signal transduction ; Software ; Tandem Mass Spectrometry - methods</subject><ispartof>International journal of molecular sciences, 2022-05, Vol.23 (9), p.5032</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-6ef5ee8cb4a42d11b1b184175a4366ab2a625ac2d9886aa06aad473998fd99633</citedby><cites>FETCH-LOGICAL-c412t-6ef5ee8cb4a42d11b1b184175a4366ab2a625ac2d9886aa06aad473998fd99633</cites><orcidid>0000-0002-4861-8235 ; 0000-0003-3416-6917 ; 0000-0002-7761-0136 ; 0000-0001-8249-3571 ; 0000-0002-8599-8150 ; 0000-0002-7262-5419</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2663062086/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2663062086?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25732,27903,27904,36991,36992,38495,43874,44569,53769,53771,74158,74872</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35563422$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Velázquez-Enríquez, Juan Manuel</creatorcontrib><creatorcontrib>Ramírez-Hernández, Alma Aurora</creatorcontrib><creatorcontrib>Navarro, Luis Manuel Sánchez</creatorcontrib><creatorcontrib>Reyes-Avendaño, Itayetzi</creatorcontrib><creatorcontrib>González-García, Karina</creatorcontrib><creatorcontrib>Jiménez-Martínez, Cristian</creatorcontrib><creatorcontrib>Castro-Sánchez, Luis</creatorcontrib><creatorcontrib>Sánchez-Chino, Xariss Miryam</creatorcontrib><creatorcontrib>Vásquez-Garzón, Verónica Rocío</creatorcontrib><creatorcontrib>Baltiérrez-Hoyos, Rafael</creatorcontrib><title>Proteomic Analysis Reveals Differential Expression Profiles in Idiopathic Pulmonary Fibrosis Cell Lines</title><title>International journal of molecular sciences</title><addtitle>Int J Mol Sci</addtitle><description>Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, irreversible lung disorder of unknown cause. This disease is characterized by profibrotic activation of resident pulmonary fibroblasts resulting in aberrant deposition of extracellular matrix (ECM) proteins. However, although much is known about the pathophysiology of IPF, the cellular and molecular processes that occur and allow aberrant fibroblast activation remain an unmet need. To explore the differentially expressed proteins (DEPs) associated with aberrant activation of these fibroblasts, we used the IPF lung fibroblast cell lines LL97A (IPF-1) and LL29 (IPF-2), compared to the normal lung fibroblast cell line CCD19Lu (NL-1). Protein samples were quantified and identified using a label-free quantitative proteomic analysis approach by liquid chromatography-tandem mass spectrometry (LC-MS/MS). DEPs were identified after pairwise comparison, including all experimental groups. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network construction were used to interpret the proteomic data. Eighty proteins expressed exclusively in the IPF-1 and IPF-2 clusters were identified. In addition, 19 proteins were identified up-regulated in IPF-1 and 10 in IPF-2; 10 proteins were down-regulated in IPF-1 and 2 in IPF-2 when compared to the NL-1 proteome. Using the search tool for retrieval of interacting genes/proteins (STRING) software, a PPI network was constructed between the DEPs and the 80 proteins expressed exclusively in the IPF-2 and IPF-1 clusters, containing 115 nodes and 136 edges. The 10 hub proteins present in the IPP network were identified using the CytoHubba plugin of the Cytoscape software. GO and KEGG pathway analyses showed that the hub proteins were mainly related to cell adhesion, integrin binding, and hematopoietic cell lineage. Our results provide relevant information on DEPs present in IPF lung fibroblast cell lines when compared to the normal lung fibroblast cell line that could play a key role during IPF pathogenesis.</description><subject>Biomarkers</subject><subject>Cell adhesion</subject><subject>Cell adhesion & migration</subject><subject>Cell cycle</subject><subject>Cell Line</subject><subject>Cell lineage</subject><subject>Cell lines</subject><subject>Chromatography, Liquid</subject><subject>Disease</subject><subject>Encyclopedias</subject><subject>Extracellular matrix</subject><subject>Extracellular Matrix Proteins - metabolism</subject><subject>Fibroblasts</subject><subject>Fibroblasts - metabolism</subject><subject>Fibrosis</subject><subject>Genes</subject><subject>Genomes</subject><subject>Humans</subject><subject>Idiopathic Pulmonary Fibrosis - metabolism</subject><subject>Liquid chromatography</subject><subject>Lung diseases</subject><subject>Lungs</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Protein expression</subject><subject>Proteins</subject><subject>Proteome - 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This disease is characterized by profibrotic activation of resident pulmonary fibroblasts resulting in aberrant deposition of extracellular matrix (ECM) proteins. However, although much is known about the pathophysiology of IPF, the cellular and molecular processes that occur and allow aberrant fibroblast activation remain an unmet need. To explore the differentially expressed proteins (DEPs) associated with aberrant activation of these fibroblasts, we used the IPF lung fibroblast cell lines LL97A (IPF-1) and LL29 (IPF-2), compared to the normal lung fibroblast cell line CCD19Lu (NL-1). Protein samples were quantified and identified using a label-free quantitative proteomic analysis approach by liquid chromatography-tandem mass spectrometry (LC-MS/MS). DEPs were identified after pairwise comparison, including all experimental groups. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network construction were used to interpret the proteomic data. Eighty proteins expressed exclusively in the IPF-1 and IPF-2 clusters were identified. In addition, 19 proteins were identified up-regulated in IPF-1 and 10 in IPF-2; 10 proteins were down-regulated in IPF-1 and 2 in IPF-2 when compared to the NL-1 proteome. Using the search tool for retrieval of interacting genes/proteins (STRING) software, a PPI network was constructed between the DEPs and the 80 proteins expressed exclusively in the IPF-2 and IPF-1 clusters, containing 115 nodes and 136 edges. The 10 hub proteins present in the IPP network were identified using the CytoHubba plugin of the Cytoscape software. GO and KEGG pathway analyses showed that the hub proteins were mainly related to cell adhesion, integrin binding, and hematopoietic cell lineage. Our results provide relevant information on DEPs present in IPF lung fibroblast cell lines when compared to the normal lung fibroblast cell line that could play a key role during IPF pathogenesis.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35563422</pmid><doi>10.3390/ijms23095032</doi><orcidid>https://orcid.org/0000-0002-4861-8235</orcidid><orcidid>https://orcid.org/0000-0003-3416-6917</orcidid><orcidid>https://orcid.org/0000-0002-7761-0136</orcidid><orcidid>https://orcid.org/0000-0001-8249-3571</orcidid><orcidid>https://orcid.org/0000-0002-8599-8150</orcidid><orcidid>https://orcid.org/0000-0002-7262-5419</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Biomarkers Cell adhesion Cell adhesion & migration Cell cycle Cell Line Cell lineage Cell lines Chromatography, Liquid Disease Encyclopedias Extracellular matrix Extracellular Matrix Proteins - metabolism Fibroblasts Fibroblasts - metabolism Fibrosis Genes Genomes Humans Idiopathic Pulmonary Fibrosis - metabolism Liquid chromatography Lung diseases Lungs Mass spectrometry Mass spectroscopy Metabolism Metabolites Protein expression Proteins Proteome - metabolism Proteomes Proteomics Proteomics - methods Pulmonary fibrosis Scientific imaging Signal transduction Software Tandem Mass Spectrometry - methods |
title | Proteomic Analysis Reveals Differential Expression Profiles in Idiopathic Pulmonary Fibrosis Cell Lines |
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