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Van Deuren, V. M. L.

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

2 recordsLinked to original sources

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↗

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↗