Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of Sepsis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41114487", "kind": "science-record", "revision": 2, "content_hash": "sha256:3da4c2f832300e4ea5f01d1ddc9ea51cff58f94e394ba858711b64d094c5e806", "created_at": "2026-11-01T20:31:10Z", "updated_at": "2026-11-01T21:35:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of Sepsis.", "doi": "10.2174/0118715303425071250925075308", "pmid": "41114487", "authors": ["Liyao Liu", "Lin Zhao", "Jixiang Tan"], "journal": "Endocrine, metabolic & immune disorders drug targets", "year": 2025, "abstract": "INTRODUCTION: Sepsis is a Systemic Inflammatory Response (SIR) caused by invading pathogens. We aimed to characterize infiltrating cells in sepsis and provide novel insight for the treatment of sepsis.\nMATERIALS AND METHODS: Whole-blood scRNA-seq samples from four septic patients and five healthy subjects were collected from the Gene Expression Omnibus (GEO) database (GSE175453). The Seurat R package was used for quality control and cell clustering by scRNA- seq analysis. Gene set enrichment analysis (GSEA) was performed using the clusterProfiler R package for pathway enrichment analysis. Then, the SCENIC analysis was used to identify key transcriptional regulons, and the CellChat R package was used for cell communication analysis.\nRESULTS: We mainly obtained 9 cell clusters, including myeloid cells, T cells, dendritic cells, NKT cells, B cells, plasma B cells, megakaryocytes, mast cells and erythrocytes. Notably, myeloid cells, erythrocytes and mast cells had a higher proportion in sepsis patients. Activated IL-17 and p53 pathways supported anti-infection response in myeloid cells, and JUNB and SPI1 mediated multiple inflammatory pathways, including TNF signaling and neutrophil activation. We also identified that the cell interaction mode of myeloid cells, such as MPZL1-MPZL1 and FASL-FAS, may serve as a potential target for an anti-inflammatory response in sepsis treatment.\nDISCUSSIONS: The scRNA-seq analysis revealed pro-inflammatory pathways (IL-17, p53) and key regulators (JUNB, SPI1) in septic myeloid cells. Receptor genes (MPZL1 and FAS) mediated cell communication, offering potential biomarkers and targets for sepsis therapy.\nCONCLUSION: We characterized the pro-inflammatory immune response pathways, transcriptional regulon and cell interaction modes of myeloid cells in the development of sepsis.", "claims": [{"id": "claim-method", "statement": "We used the R software (version 4.0.5) for data analysis and visualization, and the independent t-test was conducted for significant difference analysis on two continuous variables.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41114487", "locator": "sections[8] \"Statistical Analysis\" paragraph 2", "quote": "We used the R software (version 4.0.5) for data analysis and visualization, and the independent t-test was conducted for significant difference analysis on two continuous variables."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analyzed during this study are included in this published article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41114487", "locator": "sections[24] \"AVAILABILITY OF DATA AND MATERIALS\" paragraph 2", "quote": "All data generated or analyzed during this study are included in this published article."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41114487"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE175453"], "resolved_accessions": ["GSE175453"], "statements": ["All data generated or analyzed during this study are included in this published article."], "basis": "The paper names GSE175453 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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