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The generation of regulatory T (T(Reg)) cells in the thymus is crucial for immune homeostasis and self-tolerance. Recent discoveries have revealed the cellular and molecular mechanisms that govern the differentiation of a subset of developing thymocytes into natural T(Reg) cells. Several models, centred on the self-reactivity of the T cell receptor (TCR), have been proposed to explain the generation of a T(Reg) cell population that is cognizant of self. Several molecular pathways link TCR and cytokine signalling with the expression of the T(Reg) cell-associated transcription factor forkhead box P3 (FOXP3). Moreover, interplay between thymocytes and thymic antigen-presenting cells is also involved in T(Reg) cell generation.

Summary The degree of T cell self-reactivity considered dangerous by the immune system, thereby requiring thymic selection processes to prevent autoimmunity, is unknown. Here, we analyzed a panel of T cell receptors (TCRs) with a broad range of reactivity to ovalbumin (OVA323-339) in the rat insulin promoter (RIP)-mOVA self-antigen model for their ability to trigger thymic self-tolerance mechanisms. Thymic regulatory T (Treg) cell generation in vivo was directly correlated with in vitro TCR reactivity to OVA-peptide in a broad ~1,000-fold range. Interestingly, higher TCR affinity was associated with a larger Treg cell developmental “niche” size, even though the amount of antigen should remain constant. The TCR-reactivity threshold to elicit thymic negative selection and peripheral T cell responses was ~100 fold higher than that of Treg cell differentiation. Thus, these data suggest that the broad range of self-reactivity that elicits thymic Treg cell generation is tuned to secure peripheral tolerance to self.

Reciprocal interactions between B and follicular T helper (Tfh) cells orchestrate the germinal center (GC) reaction, a hallmark of humoral immunity. Abnormal GC responses could lead to the production of pathogenic autoantibodies and the development of autoimmunity. Here we show that miR-146a controls GC responses by targeting multiple CD40 signaling pathway components in B cells; by contrast, loss of miR-146a in T cells does not alter humoral responses. However, specific deletion of both miR-146a and its paralog, miR-146b, in T cells increases Tfh cell numbers and enhanced GC reactions. Thus, our data reveal differential cell-intrinsic regulations of GC B and Tfh cells by miR-146a and miR-146b. Together, members of the miR-146 family serve as crucial molecular brakes to coordinately control GC reactions to generate protective humoral responses without eliciting unwanted autoimmunity.

MicroRNAs (miRNAs) are 19–24 nucleotide long non-coding RNA species that regulate the expression of multiple target genes at the post-transcriptional level. They are required for normal immune system development and function, and their expression is dynamically regulated in different immune cell subsets during lineage differentiation and immune response. Aberrant expression of miRNAs results in dysregulated innate and adaptive immunity. This in turn can lead to failure to fight against invading pathogens and the development of autoimmune diseases and hematopoietic malignancies. In this article, we review current progress in miRNA research in immunity in both physiological and pathological settings. We also discuss research limitations and challenges that researchers are just beginning to solve.

Background: Drug candidates often cause an unwanted blockage of the potassium ion channel of the human ether-ago go related gene (hERG). The blockage leads to long QT syndrome (LQTS), which is a severe life-threatening cardiac side effect. Therefore, a virtual screening method to predict drug-induced hERG-related cardiotoxicity could facilitate drug discovery by filtering out toxic drug candidates. Result: In this study, we generated a reliable hERG-related cardiotoxicity dataset composed of 2130 compounds, which were carried out under constant conditions. Based on our dataset, we developed a computational hERG-related cardiotoxicity prediction model. The neural network model achieved an area under the receiver operating characteristic curve (AUC) of 0.764, with an accuracy of 90.1%, a Matthews correlation coefficient (MCC) of 0.368, a sensitivity of 0.321, and a specificity of 0.967, when tenfold cross-validation was performed. The model was further evaluated using ten drug compounds tested on guinea pigs and showed an accuracy of 80.0%, an MCC of 0.655, a sensitivity of 0.600, and a specificity of 1.000, which were better than the performances of existing hERG-toxicity prediction models. Conclusion: The neural network model can predict hERG-related cardiotoxicity of chemical compounds with a high accuracy. Therefore, the model can be applied to virtual high-throughput screening for drug candidates that do not cause cardiotoxicity. The prediction tool is available as a web-tool at http://ssbio.cau.ac.kr/CardPred.

IFNγ signaling drives dendritic cells (DCs) to promote type I T cell (Th1) immunity. Here, we show that activation of DCs by IFNγ is equally crucial for the differentiation of a population of T-bet+ regulatory T (Treg) cells specialized to inhibit Th1 immune responses. Conditional deletion of IFNγ receptor in DCs but not in Treg cells resulted in a severe defect in this specific Treg cell subset, leading to exacerbated immune pathology during parasitic infections. Mechanistically, IFNγ-unresponsive DCs failed to produce sufficient amount of IL-27, a cytokine required for optimal T-bet induction in Treg cells. Thus, IFNγ signalling endows DCs with the ability to efficiently control a specific type of T cell immunity through promoting a corresponding Treg cell population.

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