Expression changes of CD177 and MPO as novel biomarkers in lung tissue of CLP model rats

Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study

Background

Septic shock occurs when sepsis is related to severe hypotension and leads to a remarkable high number of deaths. The early diagnosis of septic shock is essential to reduce mortality. High-quality biomarkers can be objectively measured and evaluated as indicators to accurately predict disease diagnosis. However, single-gene prediction efficiency is inadequate; therefore, we identified a risk-score model based on gene signature to elevate predictive efficiency.

Methods

The gene expression profiles of GSE33118 and GSE26440 were downloaded from the Gene Expression Omnibus (GEO) database. These two datasets were merged, and the differentially expressed genes (DEGs) were identified using the limma package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed. Subsequently, Lasso regression and Boruta feature selection algorithm were combined to identify the hub genes of septic shock. GSE9692 was then subjected to weighted gene co-expression network analysis (WGCNA) to identify the septic shock-related gene modules. Subsequently, the genes within such modules that matched with septic shock-related DEGs were identified as the hub genes of septic shock. To further understand the function and signaling pathways of hub genes, we performed gene set variation analysis (GSVA) and then used the CIBERSORT tool to analyze the immune cell infiltration pattern of diseases. The diagnostic value of hub genes in septic shock was determined using receiver operating characteristic (ROC) analysis and verified using quantitative PCR (qPCR) and Western blotting in our hospital patients with septic shock.

Results

A total of 975 DEGs in the GSE33118 and GSE26440 databases were obtained, of which 30 DEGs were remarkably upregulated. With the use of Lasso regression and Boruta feature selection algorithm, six hub genes (CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4) with expression differences in septic shock were screened as potential diagnostic markers for septic shock among the significant DEGs and were further validated in the GSE9692 dataset. WGCNA was used to identify the co-expression modules and module-trait correlation. Enrichment analysis showed significant enrichment in the reactive oxygen species pathway, hypoxia, phosphatidylinositol 3-kinases (PI3K)/Protein Kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, nuclear factor-κβ/tumor necrosis factor alpha (NF-κβ/TNF-α), and interleukin-6 (IL-6)/Janus Kinase (JAK)/Signal Transducers and Activators of Transcription 3 (STAT3) signaling pathways. The receiver operating characteristic curve (ROC) of these signature genes was 0.938, 0.914, 0.939, 0.956, 0.932, and 0.914, respectively. In the immune cell infiltration analysis, the infiltration of M0 macrophages, activated mast cells, neutrophils, CD8 T cells, and naive B cells was more significant in the septic shock group. In addition, higher expression levels of CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 messenger RNA (mRNA) were observed in peripheral blood mononuclear cells (PBMCs) isolated from septic shock patients than from healthy donors. Higher expression levels of CD177 and MMP8 proteins were also observed in the PBMCs isolated from septic shock patients than from control participants.

Conclusions

CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 were identified as hub genes, which were of considerable value in the early diagnosis of septic shock patients. These preliminary findings are of great significance for studying immune cell infiltration in the pathogenesis of septic shock, which should be further validated in clinical studies and basic studies.

Endogenous Sulfur Dioxide Improves the Survival Rate of Sepsis by Improving the Oxidative Stress Response during Lung Injury

Objective

To explore the regulation of endogenous sulfur dioxide on oxidative stress in lung injury induced by sepsis.

Method

Forty male Sprague Dawley rats were divided into control, sepsis, sepsis + SO2, and SO2 group randomly used to observe survival rate. The other group of twenty-eight rats were randomly divided as the same manner for mechanism research. The number of WBCS and the percentage of PMN cells were calculated. The microphotographs of morphological changes and the index of quantitative assessment (IQA) of lung tissues were calculated. The ratio of wet/dry (W/D) of lung tissues was calculated. Levels of H2O2, MDA, NO, MPO, SOD, GSH-px, and TNF-α in plasma and lung tissues were measured.

Result

The number of WBCS and the percentage of PMN cells decreased in sepsis (p all < 0.05), and rebound in sepsis+SO2 (p all < 0.05). The IQA and W/D of lung tissues increased in sepsis (p for W/D < 0.05), and decreased in sepsis+SO2 (p all < 0.05). H2O2 and MDA of plasma and lung tissues increased in sepsis (p all < 0.05) and rebound in sepsis+SO2 (p for H2O2 of plasma and lung tissues <0.05). NO and MPO of plasma and lung tissues increased in sepsis (p for NO and MPO of lung tissues <0.05) and rebound in sepsis+SO2 (p all < 0.05). SOD of plasma and lung tissues in sepsis group decreased (p all <0.05) and increased in sepsis+SO2 (p all < 0.05). GSH-px of plasma and lung tissues decreased in sepsis (p for plasma <0.05) and increased in sepsis+SO2 (p for GSH-px of lung tissues <0.05). TNF-α of plasma and lung tissues increased in sepsis (p all<0.05) and decreased in sepsis+SO2 (p for lung tissue <0.05).

Conclusion

Endogenous sulfur dioxide improves the survival rate of sepsis by improving the oxidative stress response during lung injury.

Identification of a Four-Gene Signature for Diagnosing Paediatric Sepsis

Aim

Early diagnosis of paediatric sepsis is crucial for the proper treatment of children and reduction of hospitalization and mortality. Biomarkers are a convenient and effective method for diagnosing any disease. However, huge differences among the studies reporting biomarkers for diagnosing sepsis have limited their clinical application. Therefore, in this study, we aimed to evaluate the diagnostic value of key genes involved in paediatric sepsis based on the data of the Gene Expression Omnibus database.

Methods

We used the GSE119217 dataset to identify differentially expressed genes (DEGs) between patients with and without paediatric sepsis. The most relevant gene modules of paediatric sepsis were screened through the weighted gene coexpression network analysis (WGCNA). Common genes (CGs) were found between DEGs and WGCNA. Genes with a potential diagnostic value in paediatric sepsis were selected from the CGs using least absolute shrinkage and selection operator regression and support vector machine recursive feature elimination. The principal component analysis, receiver operating characteristic curves, and C-index were used to verify the diagnostic value of the identified genes in six other independent sepsis datasets. Subsequently, a meta-analysis of the selected genes was performed to evaluate the value of these genes as biomarkers in paediatric sepsis.

Results

A total of 41 CGs were selected from the GSE119217 dataset. A four-gene signature composed of ANXA3, CD177, GRAMD1C, and TIGD3 effectively distinguished patients with paediatric sepsis from those in the control group. The signature was verified using six other independent datasets. In addition, the meta-analysis results showed that the pooled sensitivity, specificity, and area under the curve values were 1.00, 0.98, and 1.00, respectively.

Conclusion

The four-gene signature can be used as new biomarkers to distinguish patients with paediatric sepsis from healthy individuals.

Identification of potential biomarkers and immune infiltration in pediatric sepsis via multiple-microarray analysis

Immune adjustment has become a sepsis occurring in the development of an important mechanism that cannot be ignored. This article from the perspective of immune infiltration of pediatric sepsis screening markers, and promote the understanding of disease mechanisms. Bioinformatics integrated six data sets of pediatric sepsis by using the surrogate variable analysis package and then analyzed differentially expressed genes (DEGs), immune infiltration and weighted gene co-expression network analysis of characteristics (WGCNA) of immune infiltration between pediatric sepsis and the control. Common genes of WGCNA and DEGs were used to functional annotation, pathway enrichment analysis and protein-protein interaction network. Support vector machine (SVM), least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to confirm the key genes for the diagnosis of pediatric sepsis. Receiver operating characteristic (ROC) curve, C index, principal component analysis (PCA) and GiViTi calibration band were used to evaluate the diagnostic performance of key genes. Decision curve analysis (DCA) was used to evaluate the clinical application value of key genes. Lastly, the correlation between key genes and immune cells was analyze. NK cells Resting and NK cell activated in pediatric sepsis during immune infiltration were significantly lower than those in the control group, while M1 Macrophages were higher than those in the control group. ROC, C-index, PCA, GiViTi calibration band and DCA indicated that MCEMP1, CD177, MMP8 and OLFM4 had high diagnostic performance for pediatric sepsis. There is a negative correlation between 4 key genes and NK cells resting, NK cells activated. Except for MCEMP1, the other 3 genes were positively correlated with M1 Macrophages. This study revealed differences in immune responses in pediatric sepsis and identified four key genes as potential biomarkers. Pediatric sepsis in pathology maybe understood better by learning about how it develops.

Transcriptome Meta-Analysis Deciphers a Dysregulation in Immune Response-Associated Gene Signatures during Sepsis

Sepsis is a life-threatening disease induced by a systemic inflammatory response, which leads to organ dysfunction and mortality. In sepsis, the host immune response is depressed and unable to cope with infection; no drug is currently available to treat this. The lungs are frequently the starting point for sepsis. This study aimed to identify potential genes for diagnostics and therapeutic purposes in sepsis by a comprehensive bioinformatics analysis. Our criteria are to unravel sepsis-associated signature genes from gene expression datasets. Differentially expressed genes (DEGs) were identified from samples of sepsis patients using a meta-analysis and then further subjected to functional enrichment and protein‒protein interaction (PPI) network analysis for examining their potential functions. Finally, the expression of the topmost upregulated genes (ARG1, IL1R2, ELANE, MMP9) was quantified by reverse transcriptase-PCR (RT-PCR), and myeloperoxidase (MPO) expression was confirmed by immunohistochemistry (IHC) staining in the lungs of a well-established sepsis mouse model. We found that all the four genes were upregulated in semiquantitative RT-PCR studies; however, MMP9 showed a nonsignificant increase in expression. MPO staining showed strong immunoreactivity in sepsis as compared to the control. This study demonstrates the role of significant and widespread immune activation (IL1R2, MMP9), along with oxidative stress (ARG1) and the recruitment of neutrophils, in sepsis (ELANE, MPO).

Fermented soybean meal extract improves oxidative stress factors in the lung of inflammation/infection animal model

Context

Fermented soybean products have been used in various ways, and more research is being conducted on them to reveal their benefit.

Objective

The objective of this study was to evaluate the antioxidative activity of fermented soybean meal extract by Lactobacillus plantarum in vitro and in vivo tests.

Materials and methods

A Lactobacillus plantarum strain RM10 was selected through plate and fermentation experiment, which increased the degree of protein hydrolysis (1.015 μg/mL) and antioxidant activity in soybean meal fermented by selected bacteria (FSBM). In vivo study was done on septic rats as an inflammation/infection model, and then the trial groups were treated with different concentrations of fermented soybean meal extracts (FSBM, 5, 10, and 20%).

Results

DPPH radical-scavenging and ferrozine ion-chelating activity enhanced (P < 0.05) after fermentation of soybean meal compared to control group. Reduced (P < 0.05) expression of inflammatory genes and enzymes was detected in the lungs of rats treated with fermented soybean meal extract.

Discussion and conclusions

These results demonstrated that a diet containing fermented soybean meal extract improved extreme inflammatory response in an infectious disease like sepsis by reducing inflammatory factors.

Data on changes of NF-κB gene expression in liver and lungs as a biomarker and hepatic injury in CLP-induced septic rats

Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a ubiquitous transcription factor, which plays a key role in regulating immune response against infection. Increased and/or prolonged activation of NF-κB has been linked to cancer, inflammatory, autoimmune diseases and viral infection. The purpose of this set of data was to evaluate NF-κB gene expression in cecal ligation and puncture (CLP)- induced septic rats and associated hepatic cell changes. Here, we provide the information about the evaluation of NF-κB gene expression using Real-time PCR and histopathological data of liver-related to our study published in the Turkish Journal of Medical Sciences [1]. Also, the information of the primers and more details about gene expression evaluation by real-time PCR of the targeted gene is provided. The data present here introduced another biomarker in liver and lung of CLP- induced septic rats and also confirmed hepatic dysfunction based on the pathological data. The histopathologic assessment showed normal condition in control group, mild infiltration of neutrophils in the liver parenchyma and portal tracts in LAP group (laparotomy) but severe congestion, severe neutrophil infiltration in the liver parenchyma and portal tracts in the CLP group. The data from real-time PCR showed that NF-κB expression was significantly increased in the CLP group compared with the control and LAP group, so it can be a biomarker for (CLP)- induced sepsis. This set of data and our previous study underscored the powerful potential of using the real-time PCR method to determine the involvement of genes such as MPO, CD177, and NF-κB in infectious diseases like sepsis.