Biology subjects

Robins, H.

Publications and source records attributed to Robins, H..

5 recordsLinked to original sources

bioRxiv2025

A Fundamental Relationship between TCR Diversity, Repertoire Size and Systemic Clonal Expansion: Insights from 30,000 TCRβ Repertoires

TCR diversity is essential for immune defense, yet the mechanisms underlying its decline with age, its dependence on sex and its variation among individuals remain poorly understood. These patterns are often attributed to passive loss from factors such as thymic atrophy and cumulative immune exposures but such processes fail to explain the systematic variation observed across populations. Here we challenge this view by analyzing TCR{beta} repertoires from[~] 30, 000 individuals showing that TCR diversity is almost entirely determined by repertoire size and the frequency of the 1,000 most abundant clones. These two intrinsic features of the repertoire explain 96% of the variance in TCR diversity, capturing its dependence on age and sex and defining a robust relationship that holds even under strong immune perturbations such as Cytomegalovirus infection. This relationship arises because the frequency of abundant clones captures a repertoire-wide pattern of coordinated clonal expansion--termed intrinsic clonality--which may be a fundamental, previously unrecognized property of the immune system. We propose that TCR diversity emerges as a system-level property mediated by repertoire size and intrinsic clonality, both of which are likely homeostatically regulated. These findings offer a new conceptual framework for understanding TCR diversity within immune homeostasis which may guide therapies aimed at restoring immune function.

immunology↗

bioRxiv2024

Antigen-driven expansion of public clonal T cell populations in inflammatory bowel diseases

BackgroundInflammatory Bowel Diseases (IBDs), including Crohns disease (CD) and ulcerative colitis (UC), are known to involve shifts in the T-cell repertoires of affected individuals. These include a reduction in regulatory T cells in both diseases, increase in TNF production in CD, expansion of an unconventional T-cell population in CD, and clonal expansion of abundant T-cell populations in CD mucosal tissue. There are also differential HLA risk and protective alleles between CD and UC, implying CD- and UC-specific repertoire changes that have not yet been identified. MethodsWe performed ImmunoSequencing on blood samples from 3,853 CD cases, 1,803 UC cases, and 5,596 healthy controls. For each sample we imputed HLA type and cytomegalovirus (CMV) infection status based on public T-cell receptor {beta} (TCRB) usage and identified public TCRBs enriched in CD or UC cases. FindingsWe determine that there is more expansion across clonotypes in CD, but not UC, compared with healthy controls. We also identify novel interactive effects of HLA-DQ heterodimers with CD and UC risk. Strikingly, from blood we identify public TCRBs specifically expanded in CD or UC. These sequences are more abundant in intestinal mucosal samples, form groups of similar CDR3 sequences, and can be associated to specific HLA alleles. Although the prevalence of these sequences is higher in ileal and ileocolonic CD than colonic CD or UC, the TCRB sequences themselves are shared across CD and not between CD and UC. InterpretationThere are peptide antigens that commonly evoke immune reactions in IBD cases and rarely in non-IBD controls. These antigens differ between CD and UC. CD, particularly ileal CD, also seems to involve more substantial changes in clonal population structure than UC, compared to healthy controls.

immunology↗

bioRxiv2024

Large-scale statistical mapping of T-cell receptor β sequences to Human Leukocyte Antigens

T-cell receptors (TCRs) interacting with peptides presented by human leukocyte antigens (HLAs) are the foundation of the adaptive immune system but population-level analysis of TCR-HLA interactions is lacking. Here we statistically associate[~] 106 public TCRs to specific HLAs using the TCR{beta} repertoires sampled from 4,144 HLA-genotyped subjects. The TCRs we associate are specific to unique HLA allotypes, not allelic groups, and to the paired -{beta} heterodimer of class II HLAs though exceptions are observed. This specificity permits highly accurate imputation of 248 class I and II HLAs from the TCR{beta} repertoire. Notably, 45 HLA-DP and -DQ heterodimers lack associated TCRs because they likely arise from non-functional trans-complementation. The public class I and II HLA-associated TCRs we identify are primarily expressed on CD8+ and CD4+ memory T cells, respectively, which are responding to various common antigens. Our results recapitulate fundamental biology, provide insights into the functionality of HLAs and demonstrate the power and potential of population-level TCR repertoire sequencing.

immunology↗

bioRxiv2024

Seq2MAIT: A Novel Deep Learning Framework for Identifying Mucosal Associated Invariant T (MAIT) Cells

Mucosal-associated invariant T (MAIT) cells are a group of unconventional T cells that mainly recognize bacterial vitamin B metabolites presented on MHC-related protein 1 (MR1). MAIT cells have been shown to play an important role in controlling bacterial infection and in responding to viral infections. Furthermore, MAIT cells have been implicated in different chronic inflammatory diseases such as inflammatory bowel disease and multiple sclerosis. Despite their involvement in different physiological and pathological processes, a deeper understanding of MAIT cells is still lacking. Arguably, this can be attributed to the difficulty of quantifying and measuring MAIT cells in different biological samples which is commonly done using flow cytometry-based methods and single-cell-based RNA sequencing techniques. These methods mostly require fresh samples which are difficult to obtain, especially from tissues, have low to medium throughput, and are costly and labor-intensive. To address these limitations, we developed sequence-to-MAIT (Seq2MAIT) which is a transformer-based deep neural network capable of identifying MAIT cells in bulk TCR-sequencing datasets, enabling the quantification of MAIT cells from any biological materials where human DNA is available. Benchmarking Seq2MAIT across different test datasets showed an average area-under-the-receiver-operator-curve (AU[ROC]) >0.80. In conclusion, Seq2MAIT is a novel, economical, and scalable method for identifying and quantifying MAIT cells in virtually any biological sample.

bioinformatics↗

bioRxiv2022

Perturbations of the T-cell immune repertoire in kidney transplant rejection

In this cross-sectional and longitudinal analysis of mapping the T-cell repertoire in kidney transplant recipients, we have investigated and validated T-cell clonality, immune repertoire chronology at rejection, and contemporaneous allograft biopsy quantitative tissue injury, to better understand the pathobiology of acute T cell and antibody-mediated kidney transplant rejection. To follow the dynamic evolution of T-cell repertoire changes before and after engraftment and during biopsy-confirmed acute rejection, we sequenced 323 peripheral blood samples from 200 unique kidney transplant recipients, with (n=100) and without (n=100) biopsyconfirmed acute rejection. The results of these studies highlight, for the first time, that patients who develop acute allograft rejection, have lower (p=0.01) T cell fraction even before transplantation, followed by its rise after transplantation and at the time of acute rejection accompanied by high TCR repertoire turnover (p=0.004). Acute rejection episodes occurring after the first 6 months post-transplantation, and those with a component of antibody-mediated rejection, had the highest turnover; p=0.0016) of their TCRs. In conclusion, further prospective validation studies are needed to evaluate the clinical utility of peripheral blood TCR analysis for both pre- and post-transplant immune risk assessment and prediction of different mechanisms of graft rejection.

immunology↗