Robust and Accurate Discrimination of Self/Non-Self Antigen Presentations by Regulatory T Cell Suppression.
Ontology highlight
ABSTRACT:
SUBMITTER: Furusawa C
PROVIDER: S-EPMC5036821 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Publications
Robust and Accurate Discrimination of Self/Non-Self Antigen Presentations by Regulatory T Cell Suppression.
Furusawa Chikara C Yamaguchi Tomoyuki T
PloS one 20160926 9
The immune response by T cells usually discriminates self and non-self antigens, even though the negative selection of self-reactive T cells is imperfect and a certain fraction of T cells can respond to self-antigens. In this study, we construct a simple mathematical model of T cell populations to analyze how such self/non-self discrimination is possible. The results demonstrate that the control of the immune response by regulatory T cells enables a robust and accurate discrimination of self and ...[more]
Similar Datasets
Project description:Down Syndrome cell adhesion molecule (Dscam) genes encode neuronal cell recognition proteins of the immunoglobulin superfamily. In Drosophila, Dscam1 generates 19,008 different ectodomains by alternative splicing of three exon clusters, each encoding half or a complete variable immunoglobulin domain. Identical isoforms bind to each other, but rarely to isoforms differing at any one of the variable immunoglobulin domains. Binding between isoforms on opposing membranes promotes repulsion. Isoform diversity provides the molecular basis for neurite self-avoidance. Self-avoidance refers to the tendency of branches from the same neuron (self-branches) to selectively avoid one another. To ensure that repulsion is restricted to self-branches, different neurons express different sets of isoforms in a biased stochastic fashion. Genetic studies demonstrated that Dscam1 diversity has a profound role in wiring the fly brain. Here we show how many isoforms are required to provide an identification system that prevents non-self branches from inappropriately recognizing each other. Using homologous recombination, we generated mutant animals encoding 12, 24, 576 and 1,152 potential isoforms. Mutant animals with deletions encoding 4,752 and 14,256 isoforms were also analysed. Branching phenotypes were assessed in three classes of neurons. Branching patterns improved as the potential number of isoforms increased, and this was independent of the identity of the isoforms. Although branching defects in animals with 1,152 potential isoforms remained substantial, animals with 4,752 isoforms were indistinguishable from wild-type controls. Mathematical modelling studies were consistent with the experimental results that thousands of isoforms are necessary to ensure acquisition of unique Dscam1 identities in many neurons. We conclude that thousands of isoforms are essential to provide neurons with a robust discrimination mechanism to distinguish between self and non-self during self-avoidance.
| S-EPMC2836808 | biostudies-literature
Project description:All immune systems must distinguish self from non-self to repel invaders without inducing autoimmunity. Clustered, regularly interspaced, short palindromic repeat (CRISPR) loci protect bacteria and archaea from invasion by phage and plasmid DNA through a genetic interference pathway. CRISPR loci are present in approximately 40% and approximately 90% of sequenced bacterial and archaeal genomes, respectively, and evolve rapidly, acquiring new spacer sequences to adapt to highly dynamic viral populations. Immunity requires a sequence match between the invasive DNA and the spacers that lie between CRISPR repeats. Each cluster is genetically linked to a subset of the cas (CRISPR-associated) genes that collectively encode >40 families of proteins involved in adaptation and interference. CRISPR loci encode small CRISPR RNAs (crRNAs) that contain a full spacer flanked by partial repeat sequences. CrRNA spacers are thought to identify targets by direct Watson-Crick pairing with invasive 'protospacer' DNA, but how they avoid targeting the spacer DNA within the encoding CRISPR locus itself is unknown. Here we have defined the mechanism of CRISPR self/non-self discrimination. In Staphylococcus epidermidis, target/crRNA mismatches at specific positions outside of the spacer sequence license foreign DNA for interference, whereas extended pairing between crRNA and CRISPR DNA repeats prevents autoimmunity. Hence, this CRISPR system uses the base-pairing potential of crRNAs not only to specify a target, but also to spare the bacterial chromosome from interference. Differential complementarity outside of the spacer sequence is a built-in feature of all CRISPR systems, indicating that this mechanism is a broadly applicable solution to the self/non-self dilemma that confronts all immune pathways.
| S-EPMC2813891 | biostudies-literature
Project description:Regulatory T cells (T(reg) cells) suppress autoreactive immune responses and limit the efficacy of tumor vaccines; however, it remains a challenge to selectively eliminate or inhibit T(reg) cells. In this study, the zinc-finger A20, a negative regulator of the Toll-like receptor and tumor necrosis factor receptor signaling pathways, was found to play a crucial part in controlling the maturation, cytokine production and immunostimulatory potency of dendritic cells (DCs). A20-silenced DCs showed spontaneous and enhanced expression of costimulatory molecules and proinflammatory cytokines and had different effects on T cell subsets: they inhibited T(reg) cells and hyperactivated tumor-infiltrating cytotoxic T lymphocytes and T helper cells that produced interleukin-6 and tumor necrosis factor-alpha and were refractory to T(reg) cell-mediated suppression. Hence, this study identifies A20 as an antigen presentation attenuator in control of antitumor immune responses during both the priming and the effector phases and provides a strategy to overcome T(reg) cell-mediated suppression in an antigen-specific manner, reducing the need to directly target T(reg) cells.
| S-EPMC3684168 | biostudies-literature
Project description:MotivationTranscriptional regulation mechanisms allow cells to adapt and respond to external stimuli by altering gene expression. The possible cell transcriptional states are determined by the underlying gene regulatory network (GRN), and reliably inferring such network would be invaluable to understand biological processes and disease progression.ResultsIn this article, we present a novel method for the inference of GRNs, called PORTIA, which is based on robust precision matrix estimation, and we show that it positively compares with state-of-the-art methods while being orders of magnitude faster. We extensively validated PORTIA using the DREAM and MERLIN+P datasets as benchmarks. In addition, we propose a novel scoring metric that builds on graph-theoretical concepts.Availability and implementationThe code and instructions for data acquisition and full reproduction of our results are available at https://github.com/AntoinePassemiers/PORTIA-Manuscript. PORTIA is available on PyPI as a Python package (portia-grn).Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9113237 | biostudies-literature
Project description:Immune homeostasis in tissues is achieved through a delicate balance between pathogenic T-cell responses directed at tissue-specific antigens and the ability of the tissue to inhibit these responses. The mechanisms by which tissues and the immune system communicate to establish and maintain immune homeostasis are currently unknown. Clinical evidence suggests that chronic or repeated exposure to self antigen within tissues leads to an attenuation of pathological autoimmune responses, possibly as a means to mitigate inflammatory damage and preserve function. Many human organ-specific autoimmune diseases are characterized by the initial presentation of the disease being the most severe, with subsequent flares being of lesser severity and duration. In fact, these diseases often spontaneously resolve, despite persistent tissue autoantigen expression. In the practice of antigen-specific immunotherapy, allergens or self antigens are repeatedly injected in the skin, with a diminution of the inflammatory response occurring after each successive exposure. Although these findings indicate that tissues acquire the ability to attenuate autoimmune reactions upon repeated responses to antigens, the mechanism by which this occurs is unknown. Here we show that upon expression of self antigen in a peripheral tissue, thymus-derived regulatory T cells (T(reg) cells) become activated, proliferate and differentiate into more potent suppressors, which mediate resolution of organ-specific autoimmunity in mice. After resolution of the inflammatory response, activated T(reg) cells are maintained in the target tissue and are primed to attenuate subsequent autoimmune reactions when antigen is re-expressed. Thus, T(reg) cells function to confer 'regulatory memory' to the target tissue. These findings provide a framework for understanding how T(reg) cells respond when exposed to self antigen in peripheral tissues and offer mechanistic insight into how tissues regulate autoimmunity.
| S-EPMC3263357 | biostudies-literature
Project description:RIG-I-like receptors (RLRs) are cytosolic innate immune sensors that detect pathogenic RNA and induce a systemic antiviral response. During the last decade, many studies focused on their molecular characterization and the identification of RNA agonists. Therefore, it became more and more clear that RLR activation needs to be carefully regulated, because constitutive signaling or detection of endogenous RNA through loss of specificity is detrimental. Here, we review the current understanding of RLR activation and selectivity. We specifically focus upon recent findings on the function of the helicase domain in discriminating between different RNAs, and whose malfunctioning causes serious autoimmune diseases.
| S-EPMC5454087 | biostudies-literature
Project description:UNLABELLED:Many RNA viruses are detected by retinoic acid-inducible gene i (RIG-I), a cytoplasmic sensor that triggers an antiviral response upon binding non-self-RNA that contains a stretch of double-stranded RNA (dsRNA) bearing a base-paired 5' ppp nucleotide. To gain insight into how RIG-I discriminates between self-RNA and non-self-RNA, we used duplexes whose complementary bottom strand contained both ribo- and deoxynucleotides. These duplexes were examined for their binding to RIG-I and their relative abilities to stimulate ATPase activity, to induce RIG-I dimerization on the duplex, and to induce beta interferon (IFN-?) expression. We show that the chemical nature of the bottom strand is not critical for RIG-I binding. However, two key ribonucleotides, at positions 2 and 5 on the bottom strand, are minimally required for the RIG-I ATPase activity, which is necessary but not sufficient for IFN-? stimulation. We find that duplexes with shorter stretches of dsRNA, as model self-RNAs, bind less stably to RIG-I but nevertheless have an enhanced ability to stimulate the ATPase. Moreover, ATPase activity promotes RIG-I recycling on RIG-I/dsRNA complexes. Since pseudo-self-RNAs bind to RIG-I less stably, they are preferentially recycled by ATP hydrolysis that weakens the helicase domain binding of dsRNA. Our results suggest that one function of the ATPase is to restrict RIG-I signaling to its interaction with non-self-RNA. A model of how this discrimination occurs as a function of dsRNA length is presented. IMPORTANCE:The innate immune response to pathogens is based on the discrimination between self-RNA and non-self-RNA. The main determinants of this detection for RNA viruses are specific pathogen-associated molecular patterns (PAMPs) of RNA, which are detected by dedicated cytoplasmic pattern recognition receptors (PRRs). RIG-I is a PRR that specifically detects short viral dsRNAs amid a sea of cellular RNAs. Here we study the determinants of this discrimination and how RIG-I ATPase activity, the only enzymatic activity of this sensor, contributes to its activation in a manner restricted to its interaction with non-self-RNAs. We also show how the innate immune response evolves during infection via IFN expression, from a state in which discrimination of self-RNA from non-self-RNA is most important to one in which this discrimination is sacrificed for the effectiveness of the antiviral response.
| S-EPMC4358010 | biostudies-literature
Project description:The complement system is part of the innate immune system and plays an important role in the host defense against infectious pathogens. One of the main effects is the opsonization of foreign invaders and subsequent uptake by phagocytosis. Due to the continuous default basal level of active complement molecules, a tight regulation is required to protect the body's own cells (self cells) from opsonization and from complement damage. A major complement regulator is Factor H, which is recruited from the fluid phase and attaches to cell surfaces where it effectively controls complement activation. Besides self cells, pathogens also have the ability to bind Factor H; they can thus escape opsonization and phagocytosis causing severe infections. In order to advance our understanding of the opsonization process at a quantitative level, we developed a mathematical model for the dynamics of the complement system-termed DynaCoSys model-that is based on ordinary differential equations for cell surface-bound molecules and on partial differential equations for concentration profiles of the fluid phase molecules in the environment of cells. This hybrid differential equation approach allows to model the complement cascade focusing on the role of active C3b in the fluid phase and on the cell surface as well as on its inactivation on the cell surface. The DynaCoSys model enables us to quantitatively predict the conditions under which Factor H mediated complement evasion occurs. Furthermore, investigating the quantitative impact of model parameters by a sensitivity analysis, we identify the driving processes of complement activation and regulation in both the self and non-self regime. The two regimes are defined by a critical Factor H concentration on the cell surface and we use the model to investigate the differential impact of complement model parameters on this threshold value. The dynamic modeling on the surface of pathogens are further relevant to understand pathophysiological situations where Factor H mutants and defective Factor H binding to target surfaces results in pathophysiology such as renal and retinal disease. In the future, this DynaCoSys model will be extended to also enable evaluating treatment strategies of complement-related diseases.
| S-EPMC7493836 | biostudies-literature
Project description:BACKGROUND: The conservation of sequences between related genomes has long been recognised as an indication of functional significance and recognition of sequence homology is one of the principal approaches used in the annotation of newly sequenced genomes. In the context of recent findings that the number non-coding transcripts in higher organisms is likely to be much higher than previously imagined, discrimination between conserved coding and non-coding sequences is a topic of considerable interest. Additionally, it should be considered desirable to discriminate between coding and non-coding conserved sequences without recourse to the use of sequence similarity searches of protein databases as such approaches exclude the identification of novel conserved proteins without characterized homologs and may be influenced by the presence in databases of sequences which are erroneously annotated as coding. RESULTS: Here we present a machine learning-based approach for the discrimination of conserved coding sequences. Our method calculates various statistics related to the evolutionary dynamics of two aligned sequences. These features are considered by a Support Vector Machine which designates the alignment coding or non-coding with an associated probability score. CONCLUSION: We show that our approach is both sensitive and accurate with respect to comparable methods and illustrate several situations in which it may be applied, including the identification of conserved coding regions in genome sequences and the discrimination of coding from non-coding cDNA sequences.
| S-EPMC2758873 | biostudies-other
Project description:A major limitation in the study of sleep breathing disorders in mouse models of pathology is the need to combine whole-body plethysmography (WBP) to measure respiration with electroencephalography/electromyography (EEG/EMG) to discriminate wake-sleep states. However, murine wake-sleep states may be discriminated from breathing and body movements registered by the WBP signal alone. Our goal was to compare the EEG/EMG-based and the WBP-based scoring of wake-sleep states of mice, and provide formal guidelines for the latter. EEG, EMG, blood pressure and WBP signals were simultaneously recorded from 20 mice. Wake-sleep states were scored based either on EEG/EMG or on WBP signals and sleep-dependent respiratory and cardiovascular estimates were calculated. We found that the overall agreement between the 2 methods was 90%, with a high Cohen's Kappa index (0.82). The inter-rater agreement between 2 experts and between 1 expert and 1 naïve sleep investigators gave similar results. Sleep-dependent respiratory and cardiovascular estimates did not depend on the scoring method. We show that non-invasive discrimination of the wake-sleep states of mice based on visual inspection of the WBP signal is accurate, reliable and reproducible. This work may set the stage for non-invasive high-throughput experiments evaluating sleep and breathing patterns on mouse models of pathophysiology.
| S-EPMC5282481 | biostudies-literature