Biology subjects

Van Deuren, V. M. L.

Publications and source records attributed to Van Deuren, V. M. L..

4 recordsLinked to original sources

bioRxiv2025

Clonal overlap and convergent clustering of T-cell receptor signatures in Crohn's disease in monozygotic twins

IntroductionThe dysregulated immune-response in Crohns disease might result from disturbances in the T-cell receptor (TCR) repertoire. To investigate this hypothesis, we compared the peripheral TCR repertoire within T-cell subsets in twin pairs, concordant and discordant for Crohns disease. MethodsWe performed TCR and TCR{beta} sequencing on peripheral flow-sorted CD4+ memory gut- homing (integrin4{beta}7+), non-gut-homing (integrin4{beta}7-), and regulatory T-cells (Tregs) from Dutch monozygotic Crohns disease concordant twins (N=8), monozygotic Crohns disease discordant twins (N=8), and healthy controls (N=4). TCR diversity and clonality, overlap between individuals, convergence and enrichment, and clustering of the TCR repertoire was studied and compared to previously reported Crohns disease-related TCRs. ResultsOverall diversity and clonality was comparable between Crohns disease patients, healthy cotwins and healthy controls. Comparing T-cell subsets, a decreased diversity and increased clonality was observed for Tregs. Concordant Crohns disease twins had an increased overlap in TCRs for Tregs and CD4+ memory gut-homing T-cells. Using TCR convergence, enrichment and subsequent clustering analyses, we identified eight clusters of TCRs potentially related with Crohns disease. The identified Crohns disease-related TCR signatures have not previously been described in relation to Crohns disease, and have thus far mostly unknown antigen specificity. ConclusionsIncreased overlap in the TCR repertoires of monozygotic twin pairs concordant for Crohns disease suggest that (antigen-driven) skewing of the TCR repertoire could play a role in the pathophysiology of Crohns disease. The identified TCR-based Crohns disease signatures are prime targets for further study into the pathogenesis of Crohns disease.

immunology↗

bioRxiv2025

T cell-microbiome associations captured through T cell receptor convergence analysis

The gut microbiome modulates mucosal immunity, yet how specific bacterial taxa shape the diversity and specificity of T cell receptor (TCR) repertoires remains poorly understood. Existing approaches emphasize single-species effects or broad immune features, without pinpointing which microbes drive specific T cell clonotypes. We present AIRRWAS, a computational framework that integrates TCR-microbiome interaction analysis with targeted in vitro validation to detect genus-level TCR convergence. Applied to three independent cohorts, AIRRWAS identified reproducible associations between convergent TCR clusters and 21 bacterial genera spanning core commensals, probiotics and taxa with immunomodulatory roles. Predicted clonotypes were enriched within the TCR-microbiome interaction network and preferentially activated by genus-matched stimuli, eliciting different functional T cell responses. These findings demonstrate that distinct repertoires can share genus-specific TCR motifs, enabling detection of shared immune signatures. AIRRWAS can map these TCR- microbiome interactions, laying the groundwork for biomarker discovery immune monitoring and the development of microbiome-targeted therapies.

bioinformatics↗

bioRxiv2025

Generation of a T cell receptor, cytokine and cell repertoire synovial fluid atlas to define commonalities and dissimilarities between arthritic diseases through systems immunology approaches

Although different chronic arthritic diseases are defined by clinical factors like gender, psoriasis and auto-antibodies, the biology of inflamed joints while comparing the different diseases remains neglected. Here, after curating an inflamed joint derived T-cell receptor (TCR) database, our new TRIASSIC tool identified 66303 significantly convergent TCR clonotypes. Clustering TCR clonotypes showed that synovial fluid convergence clusters (SFCCs) characterized HLA-B27+ mediated diseases (spondyloarthritis, SpA, and enthesitis-related juvenile idiopathic arthritis, JIA-ERA), Lyme arthritis and oligoarticular JIA. Single-cell transcriptomics and bulk proteomics showed upregulated interferon type I and II and TNF- pathways in oJIA. Adult and juvenile psoriatic arthritis, (JIA-)PsA, was characterized by upregulated HSP expression in monocytes and TXNIP in T-cells. We discovered an abundance of CCL5 expressing CD8+ T-cells in SF from HLA-B27+ JIA-ERA and SpA patients. JIA-ERA patients showed upregulation of CD74 and LGALS1 in Th1 and Th17 cells and IGHV7-4.1 in B-cells. oJIA patients shared a TRBV28 RG-motif on CXCL13 producing helper T-cells. Rheumatoid arthritis and (JIA-)PsA patients carried EBV-reactive cytotoxic CD8+ T-cells. Annexin signalling was shown to be important in the intercellular communication for all arthritis groups. Collectively, our work showed that chronic arthritis is characterized by both disease-specific and broadly shared mechanisms.

immunology↗

bioRxiv2023

RapTCR: Rapid exploration and visualization of T-cell receptor repertoires

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSThe acquisition of T-cell receptor (TCR) repertoire sequence data has become faster and cheaper due to advancements in high-throughput sequencing. However, fully exploiting the diagnostic and clinical potential within these TCR repertoires requires a thorough understanding of the inherent repertoire structure. Hence, visualizing the full space of TCR sequences could be a key step towards enabling exploratory analysis of TCR repertoire, driving their enhanced interrogation. Nonetheless, current methods remain limited to rough profiling of TCR V and J gene distributions. Addressing this need, we developed RapTCR, a tool for rapid visualization and post-analysis of TCR repertoires. ApproachTo overcome computational complexity, RapTCR introduces a novel, simple embedding strategy that represents TCR amino acid sequences as short vectors while retaining their pairwise alignment similarity. RapTCR then applies efficient algorithms for indexing these vectors and constructing their nearest neighbor network. It provides multiple visualization options to map and interactively explore a TCR network as a two-dimensional representation. Benchmarking analyses using epitope-annotated datasets demonstrate that these RapTCR visualizations capture TCR similarity features on a global level (e.g., J gene) and locally (e.g., epitope reactivity). RapTCR is available as a Python package, implementing the intuitive scikit-learn syntax to easily generate insightful, publication-ready figures for TCR repertoires of any size. Availability and ImplementationRapTCR was written in Python 3. It is available as an anaconda package (https://anaconda.org/vincentvandeuren/raptcr), and on github (https://github.com/vincentvandeuren/RapTCR). Documentation and example notebooks are available at vincentvandeuren.github.io/rapTCR_docs/. Contactpieter.meysman@uantwerpen.be

bioinformatics↗