BACKGROUND: Nickel is the most frequent cause of T cell-mediated allergic contact dermatitis worldwide. In vitro, CD4+ T cells from all donors respond to nickel but the involved αβ T cell receptor (TCR) repertoire has not been comprehensively analyzed. METHODS: We introduce CD154 (CD40L) upregulation as a fast, unbiased, and quantitative method to detect nickel-specific CD4+ T cells ex vivo in blood of clinically characterized allergic and non allergic donors. Naïve (CCR7+ CD45RA+) and memory (not naïve) CD154+ CD4+ T cells were analyzed by flow cytometry after 5 hours of stimulation with 200 µmol/L NiSO4 ., TCR α- and β-chains of sorted nickel-specific and control cells were studied by high-throughput sequencing. RESULTS: Stimulation of PBMCs with NiSO4 induced CD154 expression on ~0.1% (mean) of naïve and memory CD4+ T cells. In allergic donors with recent positive patch test, memory frequencies further increased ~13-fold and were associated with markers of in vivo activation. CD154 expression was TCR-mediated since single clones could be specifically restimulated. Among nickel-specific CD4+ T cells of allergic and non allergic donors, TCRs expressing the α-chain segment TRAV9-2 or a histidine in their α- or β-chain complementarity determining region 3 (CDR3) were highly overrepresented. CONCLUSIONS: Induced CD154 expression represents a reliable method to study nickel-specific CD4+ T cells. TCRs with particular features respond in all donors, while strongly increased blood frequencies indicate nickel allergy for some donors. Our approach may be extended to other contact allergens for the further development of diagnostic and predictive in vitro tests.
Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
- MeSH
- Adaptive Immunity genetics MeSH
- Antigens, Viral MeSH
- Antigens MeSH
- Complementarity Determining Regions genetics physiology MeSH
- Immunotherapy MeSH
- Humans MeSH
- Receptors, Antigen, T-Cell immunology metabolism physiology MeSH
- Sequence Analysis, DNA methods MeSH
- Cluster Analysis MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The B cell receptor immunoglobulin (Ig) gene repertoires of marginal zone (MZ) lymphoproliferations were analyzed in order to obtain insight into their ontogenetic relationships. Our cohort included cases with MZ lymphomas (n = 488), i.e. splenic (SMZL), nodal (NMZL) and extranodal (ENMZL), as well as provisional entities (n = 76), according to the WHO classification. The most striking Ig gene repertoire skewing was observed in SMZL. However, restrictions were also identified in all other MZ lymphomas studied, particularly ENMZL, with significantly different Ig gene distributions depending on the primary site of involvement. Cross-entity comparisons of the MZ Ig sequence dataset with a large dataset of Ig sequences (MZ-related or not; n = 65 837) revealed four major clusters of cases sharing homologous ('public') heavy variable complementarity-determining region 3. These clusters included rearrangements from SMZL, ENMZL (gastric, salivary gland, ocular adnexa), chronic lymphocytic leukemia, but also rheumatoid factors and non-malignant splenic MZ cells. In conclusion, different MZ lymphomas display biased immunogenetic signatures indicating distinct antigen exposure histories. The existence of rare public stereotypes raises the intriguing possibility that common, pathogen-triggered, immune-mediated mechanisms may result in diverse B lymphoproliferations due to targeting versatile progenitor B cells and/or operating in particular microenvironments. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
- MeSH
- Gene Rearrangement, B-Lymphocyte genetics MeSH
- Genes, Immunoglobulin genetics MeSH
- Genes, Immunoglobulin Heavy Chain genetics MeSH
- Complementarity Determining Regions genetics MeSH
- Humans MeSH
- Lymphoma, B-Cell, Marginal Zone genetics MeSH
- Mutation genetics MeSH
- Tumor Microenvironment MeSH
- Receptors, Antigen, B-Cell genetics MeSH
- Immunoglobulin Variable Region genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
For understanding the rules and laws of adaptive immunity, high-throughput profiling of T-cell receptor (TCR) repertoires becomes a powerful tool. The structure of TCR repertoires is instructive even before the antigen specificity of each particular receptor becomes available. It embodies information about the thymic and peripheral selection of T cells; the readiness of an adaptive immunity to withstand new challenges; the character, magnitude and memory of immune responses; and the aetiological and functional proximity of T-cell subsets. Here, we describe our current analytical approaches for the comparative analysis of murine TCR repertoires, and show several examples of how these approaches can be applied for particular experimental settings. We analyse the efficiency of different metrics used for estimation of repertoire diversity, repertoire overlap, V-gene and J-gene segments usage similarity, and amino acid composition of CDR3. We discuss basic differences of these metrics and their advantages and limitations in different experimental models, and we provide guidelines for choosing an efficient way to lead a comparative analysis of TCR repertoires. Applied to the various known and newly developed mouse models, such analysis should allow us to disentangle multiple sophisticated puzzles in adaptive immunity.
Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCR[Formula: see text] sequences .
- MeSH
- Adaptive Immunity genetics MeSH
- Cytomegalovirus immunology MeSH
- Diabetes Mellitus genetics immunology MeSH
- Genetic Variation immunology MeSH
- Complementarity Determining Regions genetics MeSH
- Humans MeSH
- Receptors, Antigen, B-Cell genetics MeSH
- Receptors, Antigen, T-Cell genetics immunology MeSH
- Receptors, Antigen genetics immunology MeSH
- Receptors, Immunologic genetics immunology MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
γδ T cells are considered to be innate-like lymphocytes that respond rapidly to stress without clonal selection and differentiation. Here we use next-generation sequencing to probe how this paradigm relates to human Vδ2neg T cells, implicated in responses to viral infection and cancer. The prevalent Vδ1 T cell receptor (TCR) repertoire is private and initially unfocused in cord blood, typically becoming strongly focused on a few high-frequency clonotypes by adulthood. Clonal expansions have differentiated from a naive to effector phenotype associated with CD27 downregulation, retaining proliferative capacity and TCR sensitivity, displaying increased cytotoxic markers and altered homing capabilities, and remaining relatively stable over time. Contrastingly, Vδ2+ T cells express semi-invariant TCRs, which are present at birth and shared between individuals. Human Vδ1+ T cells have therefore evolved a distinct biology from the Vδ2+ subset, involving a central, personalized role for the γδ TCR in directing a highly adaptive yet unconventional form of immune surveillance.
- MeSH
- Tumor Necrosis Factor Receptor Superfamily, Member 7 metabolism MeSH
- Biomarkers metabolism MeSH
- Cell Differentiation MeSH
- Clone Cells cytology MeSH
- CX3C Chemokine Receptor 1 metabolism MeSH
- Cytotoxicity, Immunologic MeSH
- Tissue Donors MeSH
- Adult MeSH
- Phenotype MeSH
- Genetic Variation MeSH
- Complementarity Determining Regions genetics MeSH
- Immunologic Surveillance * MeSH
- Interleukin-15 pharmacology MeSH
- Humans MeSH
- Cell Proliferation MeSH
- Receptors, Antigen, T-Cell, gamma-delta metabolism MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
PURPOSE: Prompted by the extensive biases in the immunoglobulin (IG) gene repertoire of splenic marginal-zone lymphoma (SMZL), supporting antigen selection in SMZL ontogeny, we sought to investigate whether antigen involvement is also relevant post-transformation. EXPERIMENTAL DESIGN: We conducted a large-scale subcloning study of the IG rearrangements of 40 SMZL cases aimed at assessing intraclonal diversification (ID) due to ongoing somatic hypermutation (SHM). RESULTS: ID was identified in 17 of 21 (81%) rearrangements using the immunoglobulin heavy variable (IGHV)1-2*04 gene versus 8 of 19 (40%) rearrangements utilizing other IGHV genes (P= 0.001). ID was also evident in most analyzed IG light chain gene rearrangements, albeit was more limited compared with IG heavy chains. Identical sequence changes were shared by subclones from different patients utilizing the IGHV1-2*04 gene, confirming restricted ongoing SHM profiles. Non-IGHV1-2*04 cases displayed both a lower number of ongoing SHMs and a lack of shared mutations (per group of cases utilizing the same IGHV gene). CONCLUSIONS: These findings support ongoing antigen involvement in a sizable portion of SMZL and further argue that IGHV1-2*04 SMZL may represent a distinct molecular subtype of the disease.
- MeSH
- Alleles * MeSH
- Amino Acid Motifs MeSH
- Antigens immunology MeSH
- Models, Biological MeSH
- Complementarity Determining Regions chemistry genetics MeSH
- Humans MeSH
- Lymphoma, B-Cell, Marginal Zone genetics immunology pathology MeSH
- Mutation MeSH
- Splenic Neoplasms genetics immunology pathology MeSH
- Gene Rearrangement, B-Lymphocyte, Heavy Chain MeSH
- Receptors, Antigen, B-Cell genetics MeSH
- Amino Acid Sequence MeSH
- Gene Expression Profiling MeSH
- Amino Acid Substitution MeSH
- Immunoglobulin Heavy Chains chemistry genetics MeSH
- Transcriptome MeSH
- Immunoglobulin Variable Region chemistry genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Edukační publikace popisuje strukturu protilátek, jednotlivé fragmenty, prostorovou fixaci domén, panty, úlohu disulfidi-ckých můstků, β-vláken a hypervariabilních smyček, rozdíly mezi jednotlivými imunoglobuliny a jejich izotypy. Reakce antigenu a protilátky je vysvětlována jak z hlediska komplementarity reaktantů, tak různých vazebných sil, které se na energii imunochemické vazby podílejí. Jsou uvedeny rozdíly mezi vazbou protilátky s imunogenem anebo haptenem a vlastnosti, které přispívají k imunogenicitě antigenu. Je objasněn vztah mezi afinitou a specifitou imunochemické reakce, jakož i reaktivita zárodečných a zralých protilátek.
The educational publication describes the antibody structure, various fragments, three-dimensional fixation of domains, the function of disulfide bridges, β-strands and hypervariable loops. It also deals with differences between individual immunoglobulins and their isotypes. The antigen-antibody reaction is interpreted in the aspect of complementarity of reactants, as well as various binding forces participating in the energy of the immunochemical bond. Differences between the antibody bond to immunogen or to hapten and characteristics supporting the immunogenicity of antigen are given as well. Both the relation between the affinity and specifity of immunochemical reaction and the reactivity of naive and mature antibodies are demonstrated.
- Keywords
- specifita, imunogenicita,
- MeSH
- Antibody Affinity MeSH
- Antigens * immunology MeSH
- Epitopes MeSH
- Haptens MeSH
- Complementarity Determining Regions immunology MeSH
- Immunoglobulin A immunology MeSH
- Immunoglobulin D immunology MeSH
- Immunoglobulin E immunology MeSH
- Immunoglobulin G immunology MeSH
- Immunoglobulin M immunology MeSH
- Immunoglobulins immunology MeSH
- Antibodies * immunology MeSH
BACKGROUND: The repertoire of T- and B-cell receptor sequences encodes the antigen specificity of adaptive immunity system, determines its present state and guides its ability to mount effective response against encountered antigens in future. High throughput sequencing of immune repertoires (Rep-Seq) is a promising technique that allows to profile millions of antigen receptors of an individual in a single experiment. While a substantial number of tools for mapping and assembling Rep-Seq data were published recently, the field still lacks an intuitive and flexible tool that can be used by researchers with little or no computational background for in-depth analysis of immune repertoire profiles. RESULTS: Here we report VDJviz, a web tool that can be used to browse, analyze and perform quality control of Rep-Seq results generated by various pre-processing software. On a set of real data examples we show that VDJviz can be used to explore key repertoire characteristics such as spectratype, repertoire clonality, V-(D)-J recombination patterns and to identify shared clonotypes. We also demonstrate the utility of VDJviz in detection of critical Rep-Seq biases such as artificial repertoire diversity and cross-sample contamination. CONCLUSIONS: VDJviz is a versatile and lightweight tool that can be easily employed by biologists, immunologists and immunogeneticists for routine analysis and quality control of Rep-Seq data. The software is freely available for non-commercial purposes, and can be downloaded from: https://github.com/antigenomics/vdjviz .
- MeSH
- B-Lymphocytes immunology metabolism MeSH
- Genomics methods standards MeSH
- Complementarity Determining Regions genetics MeSH
- Web Browser MeSH
- Clonal Evolution genetics MeSH
- Humans MeSH
- Cluster Analysis MeSH
- Software * MeSH
- T-Lymphocytes immunology metabolism MeSH
- V(D)J Recombination * MeSH
- Computational Biology methods standards MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
We report on markedly different frequencies of genetic lesions within subsets of chronic lymphocytic leukemia patients carrying mutated or unmutated stereotyped B-cell receptor immunoglobulins in the largest cohort (n=565) studied for this purpose. By combining data on recurrent gene mutations (BIRC3, MYD88, NOTCH1, SF3B1 and TP53) and cytogenetic aberrations, we reveal a subset-biased acquisition of gene mutations. More specifically, the frequency of NOTCH1 mutations was found to be enriched in subsets expressing unmutated immunoglobulin genes, i.e. #1, #6, #8 and #59 (22-34%), often in association with trisomy 12, and was significantly different (P<0.001) to the frequency observed in subset #2 (4%, aggressive disease, variable somatic hypermutation status) and subset #4 (1%, indolent disease, mutated immunoglobulin genes). Interestingly, subsets harboring a high frequency of NOTCH1 mutations were found to carry few (if any) SF3B1 mutations. This starkly contrasts with subsets #2 and #3 where, despite their immunogenetic differences, SF3B1 mutations occurred in 45% and 46% of cases, respectively. In addition, mutations within TP53, whilst enriched in subset #1 (16%), were rare in subsets #2 and #8 (both 2%), despite all being clinically aggressive. All subsets were negative for MYD88 mutations, whereas BIRC3 mutations were infrequent. Collectively, this striking bias and skewed distribution of mutations and cytogenetic aberrations within specific chronic lymphocytic leukemia subsets implies that the mechanisms underlying clinical aggressiveness are not uniform, but rather support the existence of distinct genetic pathways of clonal evolution governed by a particular stereotyped B-cell receptor selecting a certain molecular lesion(s).
- MeSH
- Leukemia, Lymphocytic, Chronic, B-Cell genetics metabolism mortality MeSH
- Cytogenetic Analysis MeSH
- Gene Frequency MeSH
- Gene Rearrangement, B-Lymphocyte MeSH
- Genes, Immunoglobulin MeSH
- Complementarity Determining Regions genetics MeSH
- Immunoglobulin Joining Region genetics MeSH
- Polymorphism, Single Nucleotide MeSH
- Humans MeSH
- Mutation * MeSH
- Biomarkers, Tumor * MeSH
- Prognosis MeSH
- Receptors, Antigen, B-Cell genetics metabolism MeSH
- Immunoglobulin Heavy Chains genetics MeSH
- Immunoglobulin Variable Region genetics MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
