Immunologic balance of regulatory T cell/T helper 17 responses in gastrointestinal infectious diseases: Role of miRNAs

miR-137 regulates autophagy and apoptosis in duodenal ulcer by targeting BNIP3L

BACKGROUND

Duodenal ulcer (DU) represents a clinical manifestation and disease state that occurs when the mucosal surface of the duodenum is damaged. The processes of autophagy and apoptosis have been linked to the development of DU, yet the precise roles they play remain unclear. This study aimed to investigate the expression and mechanism of action of microRNAs (miRNA)-137 (miR-137) in DU.

METHODS

Dysregulated miRNAs and targeted genes were identified from the Gene Expression Omnibus database, and the immune cell infiltration levels were analyzed using CIBERSORT. To confirm the targeting of the miRNAs, we conducted dual luciferase reporter assays in vitro. The detection of cell apoptosis was conducted using flow cytometry. Moreover, quantitative reverse transcription polymerase chain reaction, cell counting kit-8, and Western blot were employed to ascertain the levels of autophagy- and apoptosis-related proteins.

RESULTS

Bioinformatics analysis identified 5 miRNAs, with miR-137 showing the most pronounced dysregulation. Its target gene, BNIP3L, was subsequently identified. In vitro experiments confirmed that miR-137 targeted BNIP3L. The upregulation of miR-137 expression in HIEC-6 cells resulted in the inhibition of BNIP3L expression, a reduction in autophagy, and an increase in apoptosis. A reduction in the expression of miR-137 would have the opposite effect.

CONCLUSIONS

miR-137 is upregulated in DU patients and contributes to ulcer progression by inhibiting BNIP3L, reducing autophagy, and promoting apoptosis. Targeting miR-137 could provide a novel therapeutic strategy for DU management.

Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction

Increasing research has shown that the abnormal expression of microRNA (miRNA) is associated with many complex diseases. However, biological experiments have many limitations in identifying the potential disease-miRNA associations. Therefore, we developed a computational model of Three-Layer Heterogeneous Network based on the Integration of CircRNA information for MiRNA-Disease Association prediction (TLHNICMDA). In the model, a disease-miRNA-circRNA heterogeneous network is built by known disease-miRNA associations, known miRNA-circRNA interactions, disease similarity, miRNA similarity, and circRNA similarity. Then, the potential disease-miRNA associations are identified by an update algorithm based on the global network. Finally, based on global and local leave-one-out cross validation (LOOCV), the values of AUCs in TLHNICMDA are 0.8795 and 0.7774. Moreover, the mean and standard deviation of AUC in 5-fold cross-validations is 0.8777+/-0.0010. Especially, the two types of case studies illustrated the usefulness of TLHNICMDA in predicting disease-miRNA interactions.

Targeting regulatory T cells for cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of death and disability worldwide. The CVDs are accompanied by inflammatory progression, resulting in innate and adaptive immune responses. Regulatory T cells (Tregs) have an immunosuppressive function and are one of the subsets of CD4⁺T cells that play a crucial role in inflammatory diseases. Whether using Tregs as a biomarker for CVDs or targeting Tregs to exert cardioprotective functions by regulating immune balance, suppressing inflammation, suppressing cardiac and vascular remodeling, mediating immune tolerance, and promoting cardiac regeneration in the treatment of CVDs has become an emerging research focus. However, Tregs have plasticity, and this plastic Tregs lose immunosuppressive function and produce toxic effects on target organs in some diseases. This review aims to provide an overview of Tregs' role and related mechanisms in CVDs, and reports on the research of plasticity Tregs in CVDs, to lay a foundation for further studies targeting Tregs in the prevention and treatment of CVDs.

Predicting miRNA-disease associations based on multi-view information fusion

MicroRNAs (miRNAs) play an important role in various biological processes and their abnormal expression could lead to the occurrence of diseases. Exploring the potential relationships between miRNAs and diseases can contribute to the diagnosis and treatment of complex diseases. The increasing databases storing miRNA and disease information provide opportunities to develop computational methods for discovering unobserved disease-related miRNAs, but there are still some challenges in how to effectively learn and fuse information from multi-source data. In this study, we propose a multi-view information fusion based method for miRNA-disease association (MDA)prediction, named MVIFMDA. Firstly, multiple heterogeneous networks are constructed by combining the known MDAs and different similarities of miRNAs and diseases based on multi-source information. Secondly, the topology features of miRNAs and diseases are obtained by using the graph convolutional network to each heterogeneous network view, respectively. Moreover, we design the attention strategy at the topology representation level to adaptively fuse representations including different structural information. Meanwhile, we learn the attribute representations of miRNAs and diseases from their similarity attribute views with convolutional neural networks, respectively. Finally, the complicated associations between miRNAs and diseases are reconstructed by applying a bilinear decoder to the combined features, which combine topology and attribute representations. Experimental results on the public dataset demonstrate that our proposed model consistently outperforms baseline methods. The case studies further show the ability of the MVIFMDA model for inferring underlying associations between miRNAs and diseases.

Mesenchymal Stem Cell-Secreted TGF-β1 Restores Treg/Th17 Skewing Induced by Lipopolysaccharide and Hypoxia Challenge via miR-155 Suppression

Background. Regulatory T cell (Treg)/T helper (Th) 17 skewing is important in the development of acute respiratory distress syndrome (ARDS). Immunomodulatory effects of mesenchymal stem cell- (MSC-) secreted transforming growth factor- (TGF-) β1 on CD4+ T cells are environment-sensitive and lack discussion in hypoxic and inflammatory conditions. Methods. Mouse splenic CD4+ T cells were precoated with anti-CD3 (5 μg/ml) and anti-CD28 (2 μg/ml) overnight. RAW264.7 cells were added as antigen-presenting cells (APCs). T cells with and without RAW264.7 cells were treated with various LPS concentrations of 0, 10, 100, and 1000 ng/ml or/and at hypoxia condition of 5% O2. Based on LPS (100 ng/ml) and hypoxia conditions (5% O2) as stimuli, MSCs were set as direct coculture or indirect coculture by transwell system. Anti-TGF-β1 neutralization antibody was added to explore the role of TGF-β1 among the soluble factors secreted by MSCs; miR-155 overexpression of CD4+ T cells was performed by transfection, and then, cells were added to the MSC-CD4+ T cell coculture system in hypoxic- and LPS-stimulated condition. After 48 hours, cells or supernatants were collected for detection of frequency of Treg and Th17 subsets, CD4+ T cell apoptosis and proliferation capacity assay by flow cytometry, secretion of INF-γ, IL-17A, IL-21, TGF-β1, and IL-10 by ELISA, and levels of miR-155, Rorc, Foxp3, and Ptpn2 mRNA expression of CD4+ T cells by RT-PCR. Results. MSCs could restore skewed Treg/Th17 induced by LPS and hypoxia compared to groups without MSCs with increased secretion of TGF-β1, IL-10, and IL-17A ( $P<0.05$ ) and attenuate the increased expression of miR-155 in CD4+ T cells via cell-to-cell contact mechanism while TGF-β1 neutralization significantly inhibited the effects of MSCs restoring skewed Treg/Th17 and abolished its effect on miR-155 expression in CD4+ T cells. Conclusions. These findings suggested miR-155 suppression of CD4+ T cells mediated MSC-secreted TGF-β1 modulating skewed Treg/Th17 induced by LPS-hypoxia challenge, providing evidence when proposing future T lymphocyte-targeted cell therapy in a specific condition.

Crosstalk of Microorganisms and Immune Responses in Autoimmune Neuroinflammation: A Focus on Regulatory T Cells

Regulatory T cells (Tregs) are the major determinant of peripheral immune tolerance. Many Treg subsets have been described, however thymus-derived and peripherally induced Tregs remain the most important subpopulations. In multiple sclerosis, a prototypical autoimmune disorder of the central nervous system, Treg dysfunction is a pathogenic hallmark. In contrast, induction of Treg proliferation and enhancement of their function are central immune evasion mechanisms of infectious pathogens. In accordance, Treg expansion is compartmentalized to tissues with high viral replication and prolonged in chronic infections. In friend retrovirus infection, Treg expansion is mainly based on excessive interleukin-2 production by infected effector T cells. Moreover, pathogens seem also to enhance Treg functions as shown in human immunodeficiency virus infection, where Tregs express higher levels of effector molecules such as cytotoxic T-lymphocyte-associated protein 4, CD39 and cAMP and show increased suppressive capacity. Thus, insights into the molecular mechanisms by which intracellular pathogens alter Treg functions might aid to find new therapeutic approaches to target central nervous system autoimmunity. In this review, we summarize the current knowledge of the role of pathogens for Treg function in the context of autoimmune neuroinflammation. We discuss the mechanistic implications for future therapies and provide an outlook for new research directions.

A comprehensive review of online resources for microRNA-diseases associations: the state of the art

MicroRNAs (miRNAs) as small 19- to 24-nucleotide noncoding RNAs regulate several mRNA targets and signaling pathways. Therefore, miRNAs are considered key regulators in cellular pathways as well as various pathologies. There is substantial interest in the relationship between disease and miRNAs, which made that one of the important research topics. Interestingly, miRNAs emerged as an attractive approach for clinical application, not only as biomarkers for diagnosis and prognosis or in the prediction of therapy response but also as therapeutic tools. For these purposes, the identification of crucial miRNAs in disease is very important. Databases provided valuable experimental and computational miRNAs-disease information in an accessible and comprehensive manner, such as miRNA target genes, miRNA related in signaling pathways and miRNA involvement in various diseases. In this review, we summarized miRNAs-disease databases in two main categories based on the general or specific diseases. In these databases, researchers could search diseases to identify critical miRNAs and developed that for clinical applications. In another way, by searching particular miRNAs, they could recognize in which disease these miRNAs would be dysregulated. Despite the significant development that has been done in these databases, there are still some limitations, such as not being updated and not providing uniform and detailed information that should be resolved in future databases. This survey can be helpful as a comprehensive reference for choosing a suitable database by researchers and as a guideline for comparing the features and limitations of the database by developer or designer. Short abstract We summarized miRNAs-disease databases that researchers could search disease to identify critical miRNAs and developed that for clinical applications. This survey can help choose a suitable database for researchers.