Integrated analysis of multi-omics data reveals T cell exhaustion in sepsis

Hospital Acquired Sepsis, Disease Prevalence, and Recent Advances in Sepsis Mitigation

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, commonly associated with nosocomial transmission. Gram-negative bacterial species are particularly problematic due to the release of the lipopolysaccharide toxins upon cell death. The lipopolysaccharide toxin of E. coli has a greater immunogenic potential than that of other Gram-negative bacteria. The resultant dysregulation of the immune system is associated with organ failure and mortality, with pregnant women, ICU patients, and neonates being particularly vulnerable. Additionally, sepsis recovery patients have an increased risk of re-hospitalisation, chronic illness, co-morbidities, organ damage/failure, and a reduced life expectancy. The emergence and increasing prevalence of antimicrobial resistance in bacterial and fungal species has impacted the treatment of sepsis patients, leading to increasing mortality rates. Multidrug resistant pathogens including vancomycin-resistant Enterococcus, beta lactam-resistant Klebsiella, and carbapenem-resistant Acinetobacter species are associated with an increased risk of mortality. To improve the prognosis of sepsis patients, predominantly high-risk neonates, advances must be made in the early diagnosis, triage, and control of sepsis. The identification of suitable biomarkers and biomarker combinations, coupled with machine learning and artificial intelligence, show promise in early detection protocols. Rapid diagnosis of sepsis in patients is essential to inform on clinical treatment, especially with resistant infectious agents. This timely review aims to discuss sepsis prevalence, aetiology, and recent advances towards disease mitigation and control.

Endothelial cell dynamics in sepsis-induced acute lung injury and acute respiratory distress syndrome: pathogenesis and therapeutic implications

Sepsis, a prevalent critical condition in clinics, continues to be the leading cause of death from infections and a global healthcare issue. Among the organs susceptible to the harmful effects of sepsis, the lungs are notably the most frequently affected. Consequently, patients with sepsis are predisposed to developing acute lung injury (ALI), and in severe cases, acute respiratory distress syndrome (ARDS). Nevertheless, the precise mechanisms associated with the onset of ALI/ARDS remain elusive. In recent years, there has been a growing emphasis on the role of endothelial cells (ECs), a cell type integral to lung barrier function, and their interactions with various stromal cells in sepsis-induced ALI/ARDS. In this comprehensive review, we summarize the involvement of endothelial cells and their intricate interplay with immune cells and stromal cells, including pulmonary epithelial cells and fibroblasts, in the pathogenesis of sepsis-induced ALI/ARDS, with particular emphasis placed on discussing the several pivotal pathways implicated in this process. Furthermore, we discuss the potential therapeutic interventions for modulating the functions of endothelial cells, their interactions with immune cells and stromal cells, and relevant pathways associated with ALI/ARDS to present a potential therapeutic strategy for managing sepsis and sepsis-induced ALI/ARDS.

Bovine lactoferrin inhibits inflammatory response and apoptosis in lipopolysaccharide-induced acute lung injury by targeting the PPAR-γ pathway

BACKGROUND

Lactoferrin (LF) is an iron-binding multifunctional cationic glycoprotein. Previous studies have demonstrated that LF may be a potential drug for treating acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). In this study, we explored the anti-inflammatory effect and mechanism of bovine lactoferrin (bLF) in ALI using the RNA sequencing (RNA-seq) technology and transcriptome analysis.

METHODS AND RESULTS

Based on the differentially expressed genes (DEGs) obtained from RNA-seq of the Lung from mouse model, the bioinformatics workflow was implemented using the BGISEQ-500 platform. The protein-protein interaction (PPI) network was obtained using STRING, and the hub gene was screened using Cytoscape. To verify the results of transcriptome analysis, the effects of bLF on Lipopolysaccharide (LPS)-induced BEAS-2B cells and its anti-reactive oxygen species (ROS), anti-inflammatory, and antiapoptotic effects were studied via Cell Counting Kit-8 (CCK-8) test, active oxygen detection test, ELISA, and western blot assay. Transcriptome analysis revealed that two hub gene modules of DEGs were screened via PPI analysis using the STRING and MCODE plug-ins of Cytoscape. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that these core modules are enriched in the PPAR (peroxisome proliferator-activated receptor) and AMPK (AMP-activated protein kinase) signaling pathways. Through cell experiments, our study shows that bLF can inhibit ROS, inflammatory reaction, and LPS-induced BEAS-2B cell apoptosis, which are significantly antagonized by the PPAR-γ inhibitor GW9662.

CONCLUSION

This study has suggested that the PPAR-γ pathway is the critical target of bLF in anti-inflammatory reactions and apoptosis of ALI, which provides a direction for further research.

Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis

BACKGROUND

Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted.

OBJECTIVES

This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value.

METHODS

Sepsis transcriptome data sets were downloaded from the NCBI GEO database. The immunedeconv R package was employed to analyze the abundance of immune cells in sepsis patients and calculate the ratios of different immune cell types. Differential analysis of immune cell ratios was performed using the t test. The Spearman rank correlation coefficient was utilized to find the relationships between immune cell abundance and pathways. The prognostic significance of immune cell ratios for patient survival probability was assessed using the log-rank test. In addition, differential gene expression was performed using the limma package, and gene co-expression analysis was executed using the WGCNA package.

RESULTS

We found significant changes in immune cell ratios between sepsis patients and healthy controls. Some of these ratios were associated with 28-day survival. Certain pathways showed significant correlations with immune cell ratios. Notably, six immune cell ratios demonstrated discriminative ability for patients with systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis, with an Area Under the Curve (AUC) larger than 0.84. Patients with a high eosinophil/B.cell.memory ratio exhibited poor survival outcomes. A total of 774 differential genes were identified in sepsis patients with a high eosinophil/B.cell.memory ratio compared to those with a low ratio. These genes were organized into seven co-expression modules associated with relevant pathways, including interferon signaling, T-cell receptor signaling, and specific granule pathways.

CONCLUSIONS

Immune cell ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting in sepsis patients can be utilized for disease subtyping, prognosis, and diagnosis. The proposed cell ratios may have higher prognostic values than the neutrophil-to-lymphocyte ratio (NLR).

Classification of subtypes and identification of dysregulated genes in sepsis

Background

Sepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis.

Methods

The datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples.

Results

A total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients.

Conclusion

This study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.