ArticlePloS one2026
Integration of single-cell and bulk RNA sequencing reveals programmed cell death-associated transcriptional programs in sepsis-induced acute lung injury.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSepsis-induced acute lung injury (ALI) is a frequent and life-threatening complication of sepsis, yet clinically actionable transcriptomic biomarkers remain limited. Regulated/programmed cell death (PCD) pathways shape inflammatory injury and barrier dysfunction, but their cell-type-specific transcriptional signatures in sepsis-induced ALI are incompletely defined.
methodsBulk transcriptomes from E-MTAB-5273 (training; sepsis-induced ALI vs sepsis) and E-MTAB-5274 (external validation) and scRNA-seq data from GSE207651 (CLP vs sham) were analyzed. Thirteen curated PCD gene sets were scored by ssGSEA, and differential PCD pathways were identified using the Wilcoxon rank-sum test with multiple-testing correction. WGCNA and differential expression analysis (limma) were integrated to obtain differentially expressed PCD-related genes (DE-PCDRGs). We benchmarked 113 machine-learning model combinations (12 algorithms) under cross-validation to select an optimal classifier, and interpreted predictions using SHAP and LIME. Associations between the PCD score and immune/metabolic signatures were assessed by ssGSEA. Cell types enriched for model-gene expression were localized in scRNA-seq, and key genes were validated in a CLP-induced ALI rat model using Western blot and immunohistochemistry.
resultsFive PCD processes differed between sepsis-induced ALI and sepsis, including increased apoptosis and pyroptosis and decreased lysosome-dependent cell death, NETosis, and alkaliptosis. Twelve DE-PCDRGs were identified, and an 8-gene signature (PADI4, IFI6, POLB, IFI27, GZMB, CD3E, CRIP1, CASP5) yielded the best performance (glmBoost feature selection + random forest classifier; AUC 0.988 in training and 0.817 in validation). Enrichment analyses linked model genes to ribosome-related pathways, cell adhesion molecules, and the intestinal immune network for IgA production. High vs low PCD score groups differed in 11 immune-cell signatures and 23 metabolic pathways. Single-cell analyses highlighted endothelial cells as a major compartment expressing multiple model genes. In vivo experiments confirmed differential protein abundance of PADI4, POLB, and IFI27 in CLP-induced ALI lungs, supporting their potential as biomarkers.
conclusionIntegrating bulk and single-cell transcriptomes delineated PCD-associated molecular features in sepsis-induced ALI and identified an externally validated 8-gene classifier signature. These results nominate endothelial-cell-linked PCD programs and the PADI4/POLB/IFI27 axis for further mechanistic studies and biomarker development.
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