ABIN1 is a negative regulator of effector functions in cytotoxic T cells.

T cells are pivotal in the adaptive immune defense, necessitating a delicate balance between robust response against infections and self-tolerance. Their activation involves intricate cross-talk among signaling pathways triggered by the T-cell antigen receptors (TCR) and co-stimulatory or inhibitory receptors. The molecular regulation of these complex signaling networks is still incompletely understood. Here, we identify the adaptor protein ABIN1 as a component of the signaling complexes of GITR and OX40 co-stimulation receptors. T cells lacking ABIN1 are hyper-responsive ex vivo, exhibit enhanced responses to cognate infections, and superior ability to induce experimental autoimmune diabetes in mice. ABIN1 negatively regulates p38 kinase activation and late NF-κB target genes. P38 is at least partially responsible for the upregulation of the key effector proteins IFNG and GZMB in ABIN1-deficient T cells after TCR stimulation. Our findings reveal the intricate role of ABIN1 in T-cell regulation.

Bystander activation in memory and antigen-inexperienced memory-like CD8 T cells.

Antigen-induced memory T cells undergo counterintuitive activation in an antigen-independent manner, which is called bystander response. Although it is well documented that memory CD8+ T cells produce IFNγ and upregulate the cytotoxic program upon the stimulation with inflammatory cytokines, there is only rare evidence that this provides an actual protection against pathogens in immunocompetent individuals. One of the reasons might be numerous antigen-inexperienced memory-like T cells that are also capable of the bystander response. Little is known about the bystander protection of memory and memory-like T cells and their redundancies with innate-like lymphocytes in humans because of the interspecies differences and the lack of controlled experiments. However, it has been proposed that IL-15/NKG2D-driven bystander activation of memory T cells drives protection or immunopathology in particular human diseases.

Regulatory T cells suppress the formation of potent KLRK1 and IL-7R expressing effector CD8 T cells by limiting IL-2.

Regulatory T cells (Tregs) are indispensable for maintaining self-tolerance by suppressing conventional T cells. On the other hand, Tregs promote tumor growth by inhibiting anticancer immunity. In this study, we identified that Tregs increase the quorum of self-reactive CD8+ T cells required for the induction of experimental autoimmune diabetes in mice. Their major suppression mechanism is limiting available IL-2, an essential T-cell cytokine. Specifically, Tregs inhibit the formation of a previously uncharacterized subset of antigen-stimulated KLRK1+ IL-7R+ (KILR) CD8+ effector T cells, which are distinct from conventional effector CD8+ T cells. KILR CD8+ T cells show superior cell-killing abilities in vivo. The administration of agonistic IL-2 immunocomplexes phenocopies the absence of Tregs, i.e., it induces KILR CD8+ T cells, promotes autoimmunity, and enhances antitumor responses in mice. Counterparts of KILR CD8+ T cells were found in the human blood, revealing them as a potential target for immunotherapy.

As well as protecting us from invading pathogens, like bacteria or viruses, our immune system can also identify dangerous cells of our own that may cause the body harm, such as cancer cells. Once detected, a population of immune cells called cytotoxic T cells launch into action to kill the potentially harmful cell. However, sometimes the immune system makes mistakes and attacks healthy cells which it misidentifies as being dangerous, leading to autoimmune diseases. Special immune cells called T regulatory lymphocytes, or 'Tregs', can suppress the activity of cytotoxic T cells, preventing them from hurting the body's own cells. While this can have a positive impact and reduce the effects of autoimmunity, Tregs can also make the immune system less responsive to cancer cells and allow tumors to grow. But how Tregs alter the behavior of cytotoxic T cells during autoimmune diseases and cancer is poorly understood. While multiple mechanisms have been proposed, none of these have been tested in living animal models of these diseases. To address this, Tsyklauri et al. studied Tregs in laboratory mice which had been modified to have autoimmune diabetes, which is when the body attacks the cells responsible for producing insulin. The experiments revealed that Tregs take up a critical signaling molecule called IL-2 which cytotoxic T cells need to survive and multiply. As a result, there is less IL-2 molecules available in the environment, inhibiting the cytotoxic T cells' activity. Furthermore, if Tregs are absent and there is an excess of IL-2, this causes cytotoxic T cells to transition into a previously unknown subset of T cells with superior killing abilities. Tsyklauri et al. were able to replicate these findings in two different groups of laboratory mice which had been modified to have cancer. This suggests that Tregs suppress the immune response to cancer cells and prevent autoimmunity using the same mechanism. In the future, this work could help researchers to develop therapies that alter the behavior of cytotoxic T cells and/or Tregs to either counteract autoimmune diseases, or help the body fight off cancer.

Self-reactivity of CD8 T-cell clones determines their differentiation status rather than their responsiveness in infections.

Mature T cells are selected for recognizing self-antigens with low to intermediate affinity in the thymus. Recently, the relative differences in self-reactivity among individual T-cell clones were appreciated as important factors regulating their fate and immune response, but the role of self-reactivity in T-cell biology is incompletely understood. We addressed the role of self-reactivity in T-cell diversity by generating an atlas of mouse peripheral CD8+ T cells, which revealed two unconventional populations of antigen-inexperienced T cells. In the next step, we examined the steady-state phenotype of monoclonal T cells with various levels of self-reactivity. Highly self-reactive clones preferentially differentiate into antigen-inexperienced memory-like cells, but do not form a population expressing type I interferon-induced genes, showing that these two subsets have unrelated origins. The functional comparison of naïve monoclonal CD8+ T cells specific to the identical model antigen did not show any correlation between the level of self-reactivity and the magnitude of the immune response.

Phenotypic and Clonal Stability of Antigen-Inexperienced Memory-like T Cells across the Genetic Background, Hygienic Status, and Aging.

Ag-inexperienced memory-like T (AIMT) cells are functionally unique T cells, representing one of the two largest subsets of murine CD8+ T cells. However, differences between laboratory inbred strains, insufficient data from germ-free mice, a complete lack of data from feral mice, and an unclear relationship between AIMT cells formation during aging represent major barriers for better understanding of their biology. We performed a thorough characterization of AIMT cells from mice of different genetic background, age, and hygienic status by flow cytometry and multiomics approaches, including analyses of gene expression, TCR repertoire, and microbial colonization. Our data showed that AIMT cells are steadily present in mice, independent of their genetic background and hygienic status. Despite differences in their gene expression profiles, young and aged AIMT cells originate from identical clones. We identified that CD122 discriminates two major subsets of AIMT cells in a strain-independent manner. Whereas thymic CD122LOW AIMT cells (innate memory) prevail only in young animals with high thymic IL-4 production, peripheral CD122HIGH AIMT cells (virtual memory) dominate in aged mice. Cohousing with feral mice changed the bacterial colonization of laboratory strains but had only minimal effects on the CD8+ T cell compartment, including AIMT cells.

Norine: update of the nonribosomal peptide resource.

Norine, the unique resource dedicated to nonribosomal peptides (NRPs), is now updated with a new pipeline to automate massive sourcing and enhance annotation. External databases are mined to extract NRPs that are not yet in Norine. To maintain a high data quality, successive filters are applied to automatically validate the NRP annotations and only validated data is inserted in the database. External databases were also used to complete annotations of NRPs already in Norine. Besides, annotation consistency inside Norine and between Norine and external sources have reported annotation errors. Some can be corrected automatically, while others need manual curation. This new approach led to the insertion of 539 new NRPs and the addition or correction of annotations of nearly all Norine entries. Two new tools to analyse the chemical structures of NRPs (rBAN) and to infer a molecular formula from the mass-to-charge ratio of an NRP (Kendrick Formula Predictor) were also integrated. Norine is freely accessible from the following URL: https://bioinfo.cristal.univ-lille.fr/norine/.

CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins.

CRISPR (clustered regularly interspaced short palindromic repeats) arrays and their associated (Cas) proteins confer bacteria and archaea adaptive immunity against exogenous mobile genetic elements, such as phages or plasmids. CRISPRCasFinder allows the identification of both CRISPR arrays and Cas proteins. The program includes: (i) an improved CRISPR array detection tool facilitating expert validation based on a rating system, (ii) prediction of CRISPR orientation and (iii) a Cas protein detection and typing tool updated to match the latest classification scheme of these systems. CRISPRCasFinder can either be used online or as a standalone tool compatible with Linux operating system. All third-party software packages employed by the program are freely available. CRISPRCasFinder is available at https://crisprcas.i2bc.paris-saclay.fr.

Efficient approximations of RNA kinetics landscape using non-redundant sampling.

MOTIVATION: Kinetics is key to understand many phenomena involving RNAs, such as co-transcriptional folding and riboswitches. Exact out-of-equilibrium studies induce extreme computational demands, leading state-of-the-art methods to rely on approximated kinetics landscapes, obtained using sampling strategies that strive to generate the key landmarks of the landscape topology. However, such methods are impeded by a large level of redundancy within sampled sets. Such a redundancy is uninformative, and obfuscates important intermediate states, leading to an incomplete vision of RNA dynamics. RESULTS: We introduce RNANR, a new set of algorithms for the exploration of RNA kinetics landscapes at the secondary structure level. RNANR considers locally optimal structures, a reduced set of RNA conformations, in order to focus its sampling on basins in the kinetic landscape. Along with an exhaustive enumeration, RNANR implements a novel non-redundant stochastic sampling, and offers a rich array of structural parameters. Our tests on both real and random RNAs reveal that RNANR allows to generate more unique structures in a given time than its competitors, and allows a deeper exploration of kinetics landscapes. AVAILABILITY AND IMPLEMENTATION: RNANR is freely available at https://project.inria.fr/rnalands/rnanr . CONTACT: yann.ponty@lix.polytechnique.fr.

Norine, the knowledgebase dedicated to non-ribosomal peptides, is now open to crowdsourcing.

Since its creation in 2006, Norine remains the unique knowledgebase dedicated to non-ribosomal peptides (NRPs). These secondary metabolites, produced by bacteria and fungi, harbor diverse interesting biological activities (such as antibiotic, antitumor, siderophore or surfactant) directly related to the diversity of their structures. The Norine team goal is to collect the NRPs and provide tools to analyze them efficiently. We have developed a user-friendly interface and dedicated tools to provide a complete bioinformatics platform. The knowledgebase gathers abundant and valuable annotations on more than 1100 NRPs. To increase the quantity of described NRPs and improve the quality of associated annotations, we are now opening Norine to crowdsourcing. We believe that contributors from the scientific community are the best experts to annotate the NRPs they work on. We have developed MyNorine to facilitate the submission of new NRPs or modifications of stored ones. This article presents MyNorine and other novelties of Norine interface released since the first publication. Norine is freely accessible from the following URL: http://bioinfo.lifl.fr/NRP.