Background: To identify potential diagnostic and prognostic biomarkers of the early stage of sepsis. Methods: The differentially expressed genes (DEGs) between sepsis and control transcriptomes were screened from GSE65682 and GSE134347 datasets. The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) analyses. The diagnostic and prognostic abilities of the markers were evaluated by plotting receiver operating characteristic (ROC) curves and Kaplan–Meier survival curves. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to further elucidate the molecular mechanisms and immune-related processes. Finally, the potential biomarkers were validated in a septic mouse model by qRT-PCR and western blotting. Results: Eleven DEGs were identified between the sepsis and control samples, including YOD1, GADD45A, BCL11B, IL1R2, UGCG, TLR5, S100A12, ITK, HP, CCR7 and C19orf59 (all AUC>0.9). Furthermore, the survival analysis identified YOD1, GADD45A, BCL11B and IL1R2 as the prognostic biomarkers of sepsis. According to GSEA, four DEGs were significantly associated with immune-related processes. In addition, ssGSEA demonstrated a significant difference in the enriched immune cell populations between the sepsis and control groups (all P < 0.05). Moreover, YOD1, GADD45A and IL1R2 were upregulated, and BCL11B was downregulated in the heart, liver, lungs, and kidneys of the septic mice model. Conclusions: We identified four potential immune-releated diagnostic and prognostic gene markers for sepsis that offer new insights into its underlying mechanisms.

The purpose of this study was to explore the effect and mechanism responsible for how curcumin affects the biofilm formation by Streptococcus mutans (S. mutans). The antibacterial activity of curcumin was evaluated by measuring the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC). The mass of the biofilm was measured by crystal violet staining. Transcriptome sequencing was used to obtain all the transcript information associated with the biological activity of curcumin-treated S. mutans. Real-time quantitative PCR (qRT-PCR) was performed to examine the expression levels of related biofilm formation genes. The MIC value for curcumin was 64 μM. Curcumin inhibited the formation of a biofilm by S. mutans and degraded mature biofilms. A gene ontology enrichment analysis showed that the DEGs were significantly relevant to biofilm formation. In addition, 17 significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways (p ≤ 0.01) were identified and were potentially associated with the biochemical metabolic processes of S. mutans. DEGs associated with the biofilm formation of S. mutants, including gtfB, gtfC, rgpG, spaP, spxA1, spxA2, bacA, lrgB, and gshAB. The qRT-PCR results were consistent with transcriptome sequencing that the expression levels of gtfB, gtfC, rgpG, and spaP significantly decreased in the curcumin-treated group, whereas the expression levels of spx1, spx2, bacA, lrgB, and gshAB were up-regulated. Curcumin showed marked inhibitory effects against the formation of biofilms by S. mutans and degradation of formed biofilms.