Gpx3 and Egr1 Are Involved in Regulating the Differentiation Fate of Cardiac Fibroblasts under Pressure Overload.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35799890", "kind": "science-record", "revision": 3, "content_hash": "sha256:d87946c049bbb2c73d6be4242660e8d329250f7abe02c907f41a3952d4480910", "created_at": "2026-11-01T18:14:51Z", "updated_at": "2026-11-01T21:28:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Gpx3 and Egr1 Are Involved in Regulating the Differentiation Fate of Cardiac Fibroblasts under Pressure Overload.", "doi": "10.1155/2022/3235250", "pmid": "35799890", "authors": ["Guoxing Li", "Yuhong Qin", "Zhe Cheng", "Xiaocheng Cheng", "Ruiyu Wang", "Xuexiu Luo", "Yipin Zhao", "Dongying Zhang", "Gang Li"], "journal": "Oxidative medicine and cellular longevity", "year": 2022, "abstract": "Objectives: Although myocardial fibrosis is a common pathophysiological process associated with many heart diseases, the molecular mechanisms regulating the development of fibrosis have not been fully determined. Recently, single cell RNA sequencing (scRNA-seq) analysis has been used to examine cellular fate and function during cellular differentiation and has contributed to elucidating the mechanisms of various diseases. The main purpose of this study was to characterize the fate of cardiac fibroblasts (CFs) and the dynamic gene expression patterns in a model of cardiac pressure overload using scRNA-seq analysis.\nMethods: The public scRNA-seq dataset of the transverse aortic coarctation (TAC) model in mice was downloaded from the GEO database, GSE155882. First, we performed quality control, dimensionality reduction, clustering, and annotation of the data through the Seurat R package (v4.0.5). Then, we constructed the pseudotime trajectory of cell development and identified key regulatory genes using the Monocle R package (v2.22.0). Different cell fates and groups were fully characterized by Gene Set Enrichment Analysis (GSEA) analysis and Transcription factor (TF) activity analysis. Finally, we used Cytoscape (3.9.1) to extensively examine the gene regulatory network related to cell fate.\nResults: Pseudotime analysis showed that CFs differentiated into two distinct cell fates, one of which produced activated myofibroblasts, and the other which produced protective cells that were associated with reduced fibrosis levels, increased antioxidative stress responses, and the ability to promote angiogenesis. In the TAC model, activated CFs were significantly upregulated, while protective cells were downregulated. Treatment with the bromodomain inhibitor JQ1 reversed this change and improved fibrosis. Analysis of dynamic gene expression revealed that Gpx3 was significantly upregulated during cell differentiation into protective cells. Gpx3 expression was affected by JQ1 treatment. Furthermore, Gpx3 expression levels were negatively correlated with the different levels of fibrosis observed in the various treatment groups. Finally, we found that transcription factors Jun, Fos, Atf3, and Egr1 were upregulated in protective cells, especially Egr1 was predicted to be involved in the regulation of genes related to antioxidant stress and angiogenesis, suggesting a role in promoting differentiation into this cell phenotype.\nConclusions: The scRNA-seq analysis was used to characterize the dynamic changes associated with fibroblast differentiation and identified Gpx3 as a factor that might be involved in the regulation of myocardial fibrosis under cardiac pressure overload. These findings will help to further understanding of the mechanism of fibrosis and provide potential intervention targets.", "claims": [{"id": "claim-method", "statement": "Monocle2 was used for pseudotime analysis [22].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35799890", "locator": "sections[4] \"2.2. 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Conclusions: The scRNA-seq analysis was used to characterize the dynami"], "order_basis": "paper_text_order:320", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["he transverse aortic coarctation (TAC) model in mice was downloaded from the GEO database, GSE155", "le BET bromodomain inhibitor, 18 days later. Mice were treated with JQ1 for one month, then JQ1 tre", "et al. [17] established TAC and Sham models in mice and administered JQ1 [28], a small molecule"], "order_basis": "paper_text_order:778", "id": "assay:3"}]}