NMI Functions as Immuno-regulatory Molecule in Sepsis by Regulating Multiple Signaling Pathways

Single-cell RNA sequencing reveals cell-cell communication and potential biomarker in sepsis and septic shock patients

BACKGROUND

Sepsis is a disease characterized by infection-induced multiorgan dysfunction, which can progress to septic shock if not promptly treated. Early identification of sepsis is crucial for its treatment. However, there are currently limited specific biomarkers for sepsis or septic shock. This study aims to identify potential biomarkers for sepsis and septic shock.

METHODS

We analyzed single-cell transcriptomic data of peripheral blood mononuclear cells (PBMCs) from healthy individuals, sepsis and septic shock patients, identified differences in gene expression and cell-cell communication between different cell types during disease progression. Moreover, our analyses were further validated with flow cytometry and bulk RNA-seq data.

RESULTS

Our study elucidates the alterations in cellular proportions and cell-cell communication among healthy controls, sepsis, and septic shock patients. We identified a specific augmentation in the Resistin signaling within sepsis monocytes, mediated via RETN-CAP1 ligand-receptor pairs. Additionally, we observed enhanced IL16 signaling within monocytes from septic shock patients, mediated through IL16-CD4 ligand-receptor pairs. Subsequently, we confirmed our findings by validating the increase in CAP-1+ monocytes in sepsis and IL16+ monocytes in septic shock in mouse models. And a significant upregulation of CAP-1 and IL16 was also observed in the bulk RNA-seq data from patients with sepsis and septic shock. Furthermore, we identified four distinct clusters of CD14+ monocytes, highlighting the heterogeneity of monocytes in the progress of sepsis.

CONCLUSIONS

In summary, our work demonstrates changes in cell-cell communication of healthy controls, sepsis and septic shock, confirming that the molecules CAP-1 and IL16 on monocytes may serve as potential diagnostic markers for sepsis and septic shock, respectively. These findings provide new insights for early diagnosis and stratified treatment of the disease.

Cuproptosis-Related Biomarkers and Characterization of Immune Infiltration in Sepsis

Introduction

Sepsis is a worldwide epidemic, with high morbidity and mortality. Cuproptosis is a form of cell death that is associated with a wide range of diseases. This study aimed to explore genes associated with cuproptosis in sepsis, construct predictive models and screen for potential targets.

Methods

The LASSO algorithm and SVM-RFE model has been analysed the expression of cuproptosis-related genes in sepsis and immune infiltration characteristics and identified the marker genes under a diagnostic model. Gene-drug networks, mRNA-miRNA networks and PPI networks were constructed to screen for potential biological targets. The expression of marker genes was validated based on the GSE57065 dataset. Consensus clustering method was used to classify sepsis samples.

Results

We found 381 genes associated with the development of sepsis and discovered significantly differentially expressed cuproptosis-related genes of 16 cell types in sepsis and immune infiltration with CD8/CD4 T cells being lower. NFE2L2, NLRP3, SLC31A1, DLD, DLAT, PDHB, MTF1, CDKN2A and DLST were identified as marker genes by the LASSO algorithm and the SVM-RFE model. AUC > 0.9 was constructed for PDHB and MTF1 alone respectively. The validation group data for PDHB (P=0.00099) and MTF1 (P=7.2e-14) were statistically significant. Consistent clustering analysis confirmed two subtypes. The C1 subtype may be more relevant to cellular metabolism and the C2 subtype has some relevance to immune molecules.The results of animal experiments showed that the gene expression was consistent with the bioinformatics analysis.

Discussion

Our study systematically explored the relationship between sepsis and cuproptosis and constructed a diagnostic model. And, several cuproptosis-related genes may interfere with the progression of sepsis through immune cell infiltration.

Integrated Analysis of the Transcriptome and Microbial Diversity in the Intestine of Miniature Pig Obesity Model

Obesity, a key contributor to metabolic disorders, necessitates an in-depth understanding of its pathogenesis and prerequisites for prevention. Guangxi Bama miniature pig (GBM) offers an apt model for obesity-related studies. In this research, we used transcriptomics and 16S rRNA gene sequencing to discern the differentially expressed genes (DEGs) within intestinal (jejunum, ileum, and colon) tissues and variations in microbial communities in intestinal contents of GBM subjected to normal diets (ND) and high-fat, high-carbohydrate diets (HFHCD). After a feeding duration of 26 weeks, the HFHCD-fed experimental group demonstrated notable increases in backfat thickness, BMI, abnormal blood glucose metabolism, and blood lipid levels alongside the escalated serum expression of pro-inflammatory factors and a marked decline in intestinal health status when compared to the ND group. Transcriptomic analysis revealed a total of 1669 DEGs, of which 27 had similar differences in three intestinal segments across different groups, including five immune related genes: COL6A6, CYP1A1, EIF2AK2, NMI, and LGALS3B. Further, we found significant changes in the microbiota composition, with a significant decrease in beneficial bacterial populations within the HFHCD group. Finally, the results of integrated analysis of microbial diversity with transcriptomics show a positive link between certain microbial abundance (Solibacillus, norank_f__Saccharimonadaceae, Candidatus_Saccharimonas, and unclassified_f__Butyricicoccaceae) and changes in gene expression (COL6A6 and NMI). Overall, HFHCD appears to co-contribute to the initiation and progression of obesity in GBM by aggravating inflammatory responses, disrupting immune homeostasis, and creating imbalances in intestinal flora.