Evolution of T cell responses in the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

Abstract T cells contribute to immune protection and pathogenesis in tuberculosis, but measurements of polyclonal responses have failed resolve correlates outcome. We report the first temporal evaluation human vivo clonal repertoire Mtb-reactive cell responses, by receptor (TCR) sequencing at site a standardised antigenic challenge. Initial recruitment non-Mtb reactive is followed enrichment clones arising from oligoclonal proliferation. introduce modular computational pipeline, Metaclonotypist, sensitively cluster distinct TCRs with shared epitope specificity, which we apply here establish catalogue public HLA-restricted metaclones. Although most are private, 10 metaclones were sufficient identify Mtb-T reactivity across our study population (N≥128), indicating striking level immunodominance specific TCR-peptide interactions that may offer novel approaches patient stratification vaccine development.

Language: Английский

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TCREMP: a bioinformatic pipeline for efficient embedding of T-cell receptor sequences from immune repertoire and single-cell sequencing data

Journal of Molecular Biology, Journal Year: 2025, Volume and Issue: unknown, P. 169205 - 169205

Published: May 1, 2025

Language: Английский

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Designing meaningful continuous representations of T cell receptor sequences with deep generative models

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: May 20, 2024

T Cell Receptor (TCR) antigen binding underlies a key mechanism of the adaptive immune response yet vast diversity TCRs and complexity protein interactions limits our ability to build useful low dimensional representations TCRs. To address current limitations in TCR analysis we develop capacity-controlled disentangling variational autoencoder trained using dataset approximately 100 million sequences, that name TCR-VALID. We design TCR-VALID such model are low-dimensional, continuous, disentangled, sufficiently informative provide high-quality sequence de novo generation. thoroughly quantify these properties representations, providing framework for future representation learning dimensions. The continuity allows fast accurate clustering is benchmarked against other state-of-the-art tools pre-trained language models.

Language: Английский

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TCR clustering by contrastive learning on antigen specificity

Briefings in Bioinformatics, Journal Year: 2024, Volume and Issue: 25(5)

Published: July 25, 2024

Effective clustering of T-cell receptor (TCR) sequences could be used to predict their antigen-specificities. TCRs with highly dissimilar can bind the same antigen, thus making into a common antigen group central challenge. Here, we develop TouCAN, method that relies on contrastive learning and pretrained protein language models perform TCR sequence antigen-specificity predictions. Following training, TouCAN demonstrates ability cluster groups. Additionally, performance predictions comparable other leading methods in field.

Language: Английский

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T cell receptor-centric perspective to multimodal single-cell data analysis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 29, 2023

Abstract The T-cell receptor (TCR) carries critical information regarding functionality. TCR, despite its importance, is underutilized in single cell transcriptomics, with gene expression (GEx) features solely driving current analysis strategies. Here, we argue for a switch to TCR-first approach, which would uncover unprecedented insights into T and TCR repertoire mechanics. To this end, curated large atlas from 12 prominent human studies, containing total 500,000 cells spanning multiple diseases, including melanoma, head-and-neck cancer, lung transplantation. Herein, identified severe limitations cell-type annotation using unsupervised approaches propose more robust standard semi-supervised method or the arrangement. We then showcase utility of approach through application novel STEGO.R tool successful identification hyperexpanded clones reveal treatment-specific changes. Additionally, meta-analysis based on neighbor enrichment revealed previously unknown public clusters potential antigen-specific properties as well highlighting additional common arrangements. Therefore, paradigm shift highlights often overlooked by conventional GEx-focused methods, enabled that have improvements immunotherapy diagnostics. One Sentence Summary Revamping interrogation strategies single-cell data be centered rather than generic improved capacity find relevant disease specific TCR. Key Points captures dynamic features, even within clonal population. A ∼500,000 enhance analysis, especially restricted populations. Novel program pipeline allows consistent reproducible interrogating scTCR-seq GEx.

Language: Английский

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The differential immunological impact of photon vs proton radiation therapy in high grade lymphopenia

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 28, 2024

Abstract Radiation therapy has long been a cornerstone of cancer treatment. More recently, immune checkpoint blockade also applied across variety cancers, often leading to remarkable response rates. However, photon-based radiotherapy – which accounts for the vast majority is known frequently induce profound lymphopenia, might limit efficacy system based combinations. Proton beam produce less drastic raises possibility greater synergy with immunotherapy. In this study we aimed explore exact nature differential impact two radiation modalities upon system. We used multiparametric flow cytometry and deep sequencing rearranged TCRb loci investigate cohort 20 patients gastrointestinal tumors who received either therapy. Proton-treated remained relatively stable throughout treatment most metrics considered, whereas those photons saw depletion in naïve T cells, increase effector/memory populations, loss TCR diversity. The repertoires photon-treated underwent oligoclonal expansion after their lymphocyte count nadirs, particularly CD8+ Temra driving reduction Across entire cohort, post-nadir diversity inversely correlated overall survival time died. This that increased adoption proton-based or other sparing regimes may lead better patients.

Language: Английский

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Tricked by Edge Cases: Can Current Approaches Lead to Accurate Prediction of T-Cell Specificity with Machine Learning?

Published: Oct. 28, 2024

Abstract The ability to predict T-cell receptor (TCR) specificity computationally could revolutionize personalized immunotherapies, vaccine development, and the understanding of immunology autoimmune diseases. While progress depends on obtaining training data that represent vast range possible TCR-ligand pairs, systematic assessment modeling assumptions is equally important can begin with existing data. We illustrate this by evaluating two ideas currently present in field 1,2 : treating TCR T cell activation as distinct tasks, using unsupervised models based sequence similarity for prediction. Although presented general strategies, we argue these are exceptions rather than universally applicable principles.

Language: Английский

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T cell receptor–centric perspective to multimodal single-cell data analysis

Science Advances, Journal Year: 2024, Volume and Issue: 10(48)

Published: Nov. 29, 2024

The T cell receptor (TCR), despite its importance, is underutilized in single-cell analysis, with gene expression features solely driving current strategies. Here, we argue for a TCR-first approach, more suited toward repertoires. To this end, curated large atlas from 12 prominent human studies, containing total 500,000 cells spanning multiple diseases, including melanoma, head and neck cancer, blood lung transplantation. identified severe limitations cell-type annotation using unsupervised approaches propose robust standard semi-supervised method or the TCR arrangement. We showcase utility of approach through application STEGO.R tool identification treatment-related dynamics previously unknown public clusters potential antigen-specific properties. Thus, paradigm shift to can highlight overlooked key that have improvements immunotherapy diagnostics.

Language: Английский

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