Biology subjects

Howie, B.

Publications and source records attributed to Howie, B..

5 recordsLinked to original sources

bioRxiv2025

Multi-centered T cell repertoire profiling identifies novel alterations in the immune repertoire of individuals with inflammatory bowel disease and validates previous findings

IntroductionIBD is an incurable immune-mediated inflammatory disease (IMID), affecting the gut with a high rate of primary- and secondary-loss-of-response to therapy. By investigating the T cell receptor repertoire of individuals with IBD, novel therapeutic and preventive strategies can be identified, and a better understanding of IBD can be obtained. MethodsWhereas most studies have so far focused on the more diverse T cell receptor beta (TRB) repertoire, we here profiled the alpha (TRA) repertoire of three cohorts containing treatment-naive and treated individuals in addition to individuals living with the disease for >20 years, resulting in an exhaustive dataset containing the TRA repertoire of 2,151 individuals. ResultsUsing the generated datasets, we were able to replicate previous findings describing the expansion of Crohns-associated invariant T (CAIT) cells in individuals with Crohns disease (CD) in the three cohorts. Using a hypothesis-free statistical testing framework, we identified clonotypes that were associated with the disease at its different stages, e.g., at the time of diagnosis and decades post-diagnosis. By conducting a meta-analysis across the three cohorts, we were able to identify a set of clonotypes that were associated with the disease regardless of its stage. We validated our findings in a previously published independent test dataset from a German cohort, showing the robustness of the identified sets of clonotypes. ConclusionThe identified clonotypes are potential novel therapeutic targets to treat IBD, e.g., through targeted depletion. These clonotypes are also of major interest as they can be investigated in a targeted fashion to identify culprit antigen(s) in IBD.

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

A Catalog of the Public T-cell Response to Cytomegalovirus

ECOclusters (Exposure Co-Occurrence clusters) are previously described groups of public T-cell receptors (TCRs) that tend to co-occur across T-cell repertoires from tens of thousands of donors. Each ECOcluster putatively represents the public T-cell response to a different prevalent immune exposure. We previously associated a 26,106-member ECOcluster with exposure to cytomegalovirus (CMV) and used it to define a sensitive, specific classifier for CMV seropositivity. Here, we provide the CMV-associated ECOcluster TCRs, describe the ECOcluster and explore some types of analysis that it enables. We assess the CMV specificity of its component HLA-COclusters (subgroups of co-occurring TCRs associated with the same HLA). We use TCR sequence similarity within HLA-ECOclusters to identify groups of TCRs putatively responding to the same antigen, and we find suggestions of different subgroups of CMV-exposed donors responding to different antigens. The CMV ECOcluster is the most complete catalog of the public T-cell response to CMV to date. We provide the CMV ECOcluster TCRs as a resource for research community use and exploration.

immunology↗

bioRxiv2024

Identifying immune signatures of common exposures through co-occurrence of T-cell receptors in tens of thousands of donors

BackgroundMemory T cells are records of clonal expansion from prior immune exposures such as infections, vaccines and chronic diseases. Some of the receptors of these expanded T cell clones in a typical immune repertoire are highly public (present in many individuals) because they respond to the same peptide from a prevalent immune exposure, presented by the same Human Leukocyte Antigen (HLA) allele. Only a tiny fraction of public T-cell receptor {beta} sequences (TCRs) have known associations with exposures or specific peptides. MethodsWe mined the TCR repertoires of tens of thousands of donors to define "ECOclusters": clusters of public TCRs that tend to occur in the same donors. First, we built models to infer donor HLA type from the TCR repertoire, then associated public TCRs with HLA alleles. Next, we derived co-occurrence clusters of TCRs responding to antigens presented by the same HLA allele, then combined those clusters by co-occurrence across HLA alleles. Each such cross-HLA ECOcluster putatively represents a public TCR signature of a single exposure. ResultsWe constructed sensitive, specific models to predict the presence of 220 HLA alleles from TCR repertoires and clustered 8,618,285 HLA allele-associated TCRs to define 11,058 ECOclusters. Using serologically labeled repertoires, we identified ECOclusters associated with HSV-1, HSV-2, EBV, Parvovirus, Toxoplasma gondii, Cytomegalovirus and SARS-CoV-2, and constructed sensitive, specific classifiers of exposure. ECOclusters represent a step toward deciphering the ledger of immune exposure history encoded by the T-cell repertoire.

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↗