Women represent about 80% of patients with autoimmune diseases. This may partly result from sex-based differences in T cell receptor (TCR) selection during thymocyte development, potentially influenced by hormones and the lower expression of the Autoimmune Regulator (AIRE) transcription factor in females. To investigate this, we analyzed sex-specific differences in TCR generation and selection. We examined TCR repertoires in double-positive thymocytes and single-positive thymic cells, including CD8⁺ and CD4⁺ effector T cells and regulatory T cells (Tregs), derived from male and female organ donors. Minimal sex-based differences were observed in V and J gene usage, and there were no notable differences in TCR repertoire diversity, complementarity-determining region 3 (CDR3) length, amino acid composition, or network structure. No TCR sequences were exclusive to either sex. However, female effector T cells exhibited a significantly higher prevalence of TCRs specific to self-antigens implicated in autoimmunity compared to males, while female Tregs showed a reduced frequency of such TCRs. These differences were not observed for TCRs targeting self-antigens unrelated to autoimmunity or antigens associated with cancer or viruses. Our findings highlight a sex-specific imbalance in thymic selection of TCRs with autoimmunity-associated specificities, providing mechanistic insight into the increased susceptibility of women to autoimmune diseases.
Accurate characterization and comparison of T cell receptor (TCR) repertoires from small biological samples present significant challenges. The main challenge is the low material input, which compromises the quality of bulk sequencing and hinders the recovery of sufficient TCR sequences for robust analyses. We aimed to address this limitation by implementing a strategic approach to pool homologous biological samples. Our findings demonstrate that such pooling indeed enhances the TCR repertoire coverage, particularly for cell subsets of constrained sizes, and enables accurate comparisons of TCR repertoires at different levels of complexity across T cell subsets with different sizes. This methodology holds promise for advancing our understanding of T cell repertoires in scenarios where sample size constraints are a prevailing concern.
In the version of the article initially published, there were errors in Figs.1234.In Fig. 1, in the upper box, "CDR3" initially appeared as "CDR2" and "IGLJ(10)" read "IGLV( 10)".In the lower box, "TRBD" was missing from above "CDR3".In Fig. 2a, "class-switch recombination" originally read "class switching".In Fig. 3d, the uppermost arrow, " + /-UMI" and the lower "MTPX PCR" were all missing, and the second instance of " + /-UMI" appeared as "UMI".In Fig. 4c, the AIRR 1 image was missing the TCR from the surface of one of the cells.
Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community's Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.
Abstract T cell receptors (TCRs) are formed by stochastic gene rearrangements, theoretically generating >10 19 sequences. They are selected during thymopoiesis, which releases a repertoire of about 10 8 unique TCRs per individual. How evolution shaped a process that produces TCRs that can effectively handle a countless and evolving set of infectious agents is a central question of immunology. The paradigm is that a diverse enough repertoire of TCRs should always provide a proper, though rare, specificity for any given need. Expansion of such rare T cells would provide enough fighters for an effective immune response and enough antigen-experienced cells for memory. We show here that human thymopoiesis releases a large population of CD8 + T cells harboring α/β paired TCRs that (i) have high generation probabilities and (ii) a preferential usage of some V and J genes, (iii) are shared between individuals and (iv) can each recognize and be activated by multiple unrelated viral peptides, notably from EBV, CMV and influenza. These polyspecific T cells may represent a first line of defense that is mobilized in response to infections before a more specific response subsequently ensures viral elimination. Our results support an evolutionary selection of polyspecific α/β TCRs for broad antiviral responses and heterologous immunity.
Abstract A high density of resident memory T cells (T RM ) in tumors correlates with improved clinical outcomes in immunotherapy-treated patients. However, in preclinical models, only some subpopulations of T RM are associated with cancer vaccine efficacy. We identified two main T RM subpopulations in tumor-infiltrating lymphocytes derived from non-small cell lung cancer (NSCLC) patients: one co-expressing CD103 and CD49a (DP), and the other expressing only CD49a (MP); both exhibiting additional T RM surface markers like CD69. DP T RM exhibited greater functionality compared to MP T RM . Analysis of T-cell receptor (TCR) repertoire and of the stemness marker TCF-1 revealed shared TCRs between populations, with the MP subset appearing more progenitor-like phenotype. In two NSCLC patient cohorts, only DP T RM predicted PD-1 blockade response. Multivariate analysis, including various biomarkers (CD8, TCF1 + CD8 + T cells, and PD-L1) associated with responses to anti-PD(L)1, showed that only intra-tumoral infiltration by DP T RM remained significant. This study highlights the non-equivalence of T RM populations and emphasizes the importance of distinguishing between them to better define their role in antitumor immunity and as a biomarker of response to immunotherapy.
