Single-cell transcriptional gene signature analysis identifies IL-17 signaling pathway as the key pathway in sepsis

Immunobiology. 2023 Nov;228(6):152763. doi: 10.1016/j.imbio.2023.152763. Epub 2023 Nov 24.

Abstract

Sepsis is a multiple dysregulated systemic inflammatory response with high mortality and leads to public concern. This study was designed to identify possible critical pathways associated with sepsis clinical severity and outcome, which offer potential biomarkers and therapeutic targets for sepsis diagnosis and treatment. Single-cell transcriptome profiles of human peripheral blood mononuclear (PBMC) in the healthy control population and sepsis patients were downloaded from the sepsis database GSE167363 and performed quality control before subsequent analysis. The bulk-RNA sequencing of blood samples in the sepsis-associated databases GSE100159 and GSE133822 was also used to confirm the association between critical pathways and sepsis pathology after processing raw data. We found there was a total of 18 distinct clusters in PBMC of sepsis, which was identified by the t-SNE and UMAP dimension reduction analysis. Meanwhile, the main cell types including B, NK, T, and monocyte cells were identified via the cell maker website and the "Single R" package cell-type annotation analysis. Subsequently, GO and KEGG enrichment analysis of differential expression genes in each cluster found that DEGs between healthy control and sepsis patients were significantly enriched in the IL-17 signaling pathway in monocyte, NK, and T cells. Finally, GSE100159 and GSE133822 confirmed IL-17 signaling pathway-associated genes including IL-17R, TRAF6, RELB, TRAF5, CEBPB, JUNB, CXCL1, CXCL3, CXCL8, CXCR1, and CXCR2 were significantly up-regulated in sepsis blood samples compared with the age-matched healthy control population. Taken together, we concluded that the IL-17 signaling pathway serves as a significant potential mechanism of sepsis and provides a promising therapeutic target for sepsis treatment. This research will further deepen our understanding of sepsis development.

Keywords: Gene expression omnibus; Interleukins; Sepsis; single-cell RNA-sequencing.

MeSH terms

  • Computational Biology / methods
  • Gene Expression Profiling / methods
  • Humans
  • Interleukin-17 / metabolism
  • Leukocytes, Mononuclear / metabolism
  • Protein Interaction Maps* / genetics
  • Sepsis* / genetics
  • Signal Transduction / genetics
  • Transcriptome

Substances

  • Interleukin-17