Identification of potential characteristic genes in sepsis utilizing RNA sequencing and gene silence.

backgroundSepsis represents a serious condition involving organ dysfunction that can be life-threatening, posing a significant threat to human health. The mortality rate associated with sepsis ranges from 10% to 40%, with severe cases or those involving septic shock exhibiting mortality rates exceeding 50%.

objectiveGene sequencing took place on the blood samples that were collected both healthy volunteers and septic patients in this study. Advanced methodologies, including bioinformatics analysis, quantitative PCR (qPCR), meta-analysis, and single-cell localization analysis, were employed to identify potential biomarkers associated with the immunomodulation of sepsis. The identified molecular markers were further validated through the establishment of a sepsis cell model, gene silence techniques, and an ELISA test experiments to assess inflammatory factors.

methodsIn this study, 23 individuals with sepsis and 10 healthy volunteers as controls, and peripheral blood samples were collected. The blood specimens were processed with the assistance of BGI for comprehensive gene sequencing. Post-sequencing, the data underwent quality control measures and were subsequently analyzed using the online platform iDEP 2.01 ( http://bioinformatics.sdstate.edu/idep/ ) to identify differentially expressed genes. Conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses on the identified differentially expressed genes.To elucidate core genes from multiple perspectives, a PPI network was created with the help of the STRING database ( https://cn.string-db.org/),facilitatin g the examination of gene interactions in terms of protein. Following the recognition of core genes, sepsis-associated data sets were obtained from the Gene Expression Omnibus (GEO) public database. Specifically, the transcriptional expression of the gene S100A11 was analyzed using meta-analysis techniques, and its survival curve was subsequently evaluated.The S100A11 gene, identified through screening, was analyzed using an online visualization system to determine its single-cell localization. Initial findings indicated that the gene is predominantly expressed in macrophages. (THP-1 cells) are known as a human monocytic cell line utilized in studies.We cultured THP-1 cells and differentiated into macrophages, followed by stimulation and transfection with the S100A11 gene. The interference effect of S100A11 was assessed using quantitative fluorescence PCR (qPCR). Subsequently, THP-1 cells were cultured to establish a septic cell model, and S100A11 gene silence experiments were conducted, categorizing the samples into control, sepsis, and gene silence sepsis groups. ELISA was employed to assess the concentrations of the inflammatory cytokine IL-1β, TNF-α, and IL-6.

resultsResults demonstrated that S100A11 is highly expressed in sepsis and is primarily localized in macrophages. The enrichment in signaling pathways, including Th1 and Th2 cell differentiation, Th17 cell differentiation, Staphylococcus aureus infection, and cytokine-cytokine receptor interaction, was uncovered by differential gene expression analysis.S100A11 serves as a critical regulatory node for the inflammatory cytokines IL-1β, TNF-α, and IL-6.

conclusionNotably, S100A11 was found to be highly expressed in patients with sepsis. This gene plays a crucial role in promoting inflammation during the septic inflammatory response and may be involved in macrophage differentiation, immunomodulation, and the inflammatory processes associated with sepsis.