Dataset Information

B-1a Cells Protect Mice from Sepsis: Critical Role of CREB.

ABSTRACT: Bacterial sepsis is a serious life-threatening condition caused by an excessive immune response to infection. B-1 cells differ from conventional B-2 cells by their distinct phenotype and function. A subset of B-1 cells expressing CD5, known as B-1a cells, exhibits innate immune activity. Here we report that B-1a cells play a beneficial role in sepsis by mitigating exaggerated inflammation through a novel mechanism. Using a mouse model of bacterial sepsis, we found that the numbers of B-1a cells in various anatomical locations were significantly decreased. Adoptive transfer of B-1a cells into septic mice significantly attenuated systemic inflammation and improved survival, whereas B-1a cell-deficient CD19-/- mice were more susceptible to infectious inflammation and mortality. We also demonstrated B-1a cells produced ample amounts of IL-10 which controlled excessive inflammation and the mice treated with IL-10-deficient B-1a cells were not protected against sepsis. Moreover, we identified a novel intracellular signaling molecule, cAMP-response element binding protein (CREB), which serves as a pivotal transcription factor for upregulating IL-10 production by B-1a cells in sepsis through its nuclear translocation and binding to putative responsive elements on IL-10 promoter. Thus, the benefit of B-1a cells in bacterial sepsis is mediated by CREB and the identification of CREB in B-1a cells reveals a potential avenue for treatment in bacterial sepsis.

SUBMITTER: Aziz M

PROVIDER: S-EPMC5531203 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

B-1a Cells Protect Mice from Sepsis: Critical Role of CREB.

Aziz Monowar M Holodick Nichol E NE Rothstein Thomas L TL Wang Ping P

Journal of immunology (Baltimore, Md. : 1950) 20170619 2

Bacterial sepsis is a serious life-threatening condition caused by an excessive immune response to infection. B-1 cells differ from conventional B-2 cells by their distinct phenotype and function. A subset of B-1 cells expressing CD5, known as B-1a cells, exhibits innate immune activity. Here we report that B-1a cells play a beneficial role in sepsis by mitigating exaggerated inflammation through a novel mechanism. Using a mouse model of bacterial sepsis, we found that the numbers of B-1a cells ...[more]

PMID: 28630091

Similar Datasets

Project description:Background: Innate immune memory, also termed "trained immunity", is thought to protect against experimental models of infection, including sepsis. Trained immunity via reprogramming monocytes/macrophages has been reported to result in enhanced inflammatory status and antimicrobial activity against infection in sepsis. However, a safe and efficient way to induce trained immunity remains unclear. Methods: β-glucan is a prototypical agonist for inducing trained immunity. Ferumoxytol, superparamagnetic iron oxide (SPIO) with low cytotoxicity, has been approved by FDA for clinical use. We synthesized novel nanoparticles BSNPs by coupling β-glucan with SPIO. BSNPs were further conjugated with fluorescein for quantitative analysis and trace detection of β-glucan on BSNPs. Inflammatory cytokine levels were measured by ELISA and qRT-PCR, and the phagocytosis of macrophages was detected by flow cytometry and confocal microscopy. The therapeutic effect of BSNPs was evaluated on the well-established sepsis mouse model induced by both clinical Escherichia coli (E. coli) and cecal ligation and puncture (CLP). Results: BSNPs were synthesized successfully with a 3:20 mass ratio of β-glucan and SPIO on BSNPs, which were mainly internalized by macrophages and accumulated in the lungs and livers of mice. BSNPs effectively reprogrammed macrophages to enhance the production of trained immunity markers and phagocytosis toward bacteria. BSNP-induced trained immunity protected mice against sepsis caused by E. coli and CLP and also against secondary infection. We found that BSNP treatment elevated Akt, S6, and 4EBP phosphorylation, while mTOR inhibitors decreased the trained immunity markers and phagocytosis enhanced by BSNPs. Furthermore, the PCR Array analysis revealed Igf1, Sesn1, Vegfa, and Rps6ka5 as possible key regulators of mTOR signaling during trained immunity. BSNP-induced trained immunity mainly regulated cellular signal transduction, protein modification, and cell cycle by modulating ATP binding and the kinase activity. Our results indicated that BSNPs induced trained immunity in an mTOR-dependent manner. Conclusion: Our data highlight that the trained immunity of macrophages is an effective strategy against sepsis and suggest that BSNPs are a powerful tool for inducing trained immunity to prevent and treat sepsis and secondary infections.

Project description:IntroductionSepsis is intricately linked to intestinal damage and barrier dysfunction. At present times, there is a growing interest in a metabolite-based therapy for multiple diseases.MethodsSerum samples from septic patients and healthy individuals were collected and their metabonomics profiling assessed using Ultra-Performance Liquid Chromatography-Time of Flight Mass Spectrometry (UPLC-TOFMS). The eXtreme Gradient Boosting algorithms (XGBOOST) method was used to screen essential metabolites associated with sepsis, and five machine learning models, including Logistic Regression, XGBoost, GaussianNB(GNB), upport vector machines(SVM) and RandomForest were constructed to distinguish sepsis including a training set (75%) and validation set(25%). The area under the receiver-operating characteristic curve (AUROC) and Brier scores were used to compare the prediction performances of different models. Pearson analysis was used to analysis the relationship between the metabolites and the severity of sepsis. Both cellular and animal models were used to HYPERLINK "javascript:;" assess the function of the metabolites.ResultsThe occurrence of sepsis involve metabolite dysregulation. The metabolites mannose-6-phosphate and sphinganine as the optimal sepsis-related variables screened by XGBOOST algorithm. The XGBoost model (AUROC=0.956) has the most stable performance to establish diagnostic model among the five machine learning methods. The SHapley Additive exPlanations (SHAP) package was used to interpret the XGBOOST model. Pearson analysis reinforced the expression of Sphinganine, Mannose 6-phosphate were positively associated with the APACHE-II, PCT, WBC, CRP, and IL-6. We also demonstrated that sphinganine strongly diminished the LDH content in LPS-treated Caco-2 cells. In addition, using both in vitro and in vivo examination, we revealed that sphinganine strongly protects against sepsis-induced intestinal barrier injury.DiscussionThese findings highlighted the potential diagnostic value of the ML, and also provided new insight into enhanced therapy and/or preventative measures against sepsis.

Dataset Information

B-1a Cells Protect Mice from Sepsis: Critical Role of CREB.

Publications

B-1a Cells Protect Mice from Sepsis: Critical Role of CREB.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets