T cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remains a major challenge. Here we developed a statistical framework to detect TCR clone proliferation and contraction from longitudinal repertoire data. We applied this framework to data from three pairs of identical twins immunized with the yellow fever vaccine. We identified 600 to 1,700 responding TCRs in each donor and validated them using three independent assays. While the responding TCRs were mostly private, albeit with higher overlap between twins, they could be well-predicted using a classifier based on sequence similarity. Our method can also be applied to samples obtained postinfection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic.

• Klíčová slova
• RepSeq, T cell receptor, high-throughput sequencing, twins, vaccination,
• MeSH
• antigeny virové imunologie   MeSH
• dárci tkání MeSH
• dvojčata monozygotní MeSH
• imunizace metody   MeSH
• lidé MeSH
• receptory antigenů T-buněk imunologie   MeSH
• T-lymfocyty imunologie   MeSH
• vakcína proti žluté zimnici imunologie   MeSH
• vakcinace metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antigeny virové MeSH
• receptory antigenů T-buněk MeSH
• vakcína proti žluté zimnici MeSH

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.

• MeSH
• adaptivní imunita genetika   MeSH
• antigeny virové MeSH
• antigeny MeSH
• hypervariabilní oblasti genetika   fyziologie   MeSH
• imunoterapie MeSH
• lidé MeSH
• receptory antigenů T-buněk imunologie   metabolismus   fyziologie   MeSH
• sekvenční analýza DNA metody   MeSH
• shluková analýza MeSH
• vysoce účinné nukleotidové sekvenování metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antigeny virové MeSH
• antigeny MeSH
• hypervariabilní oblasti MeSH
• receptory antigenů T-buněk MeSH

COVID-19 is a global pandemic caused by the SARS-CoV-2 coronavirus. T cells play a key role in the adaptive antiviral immune response by killing infected cells and facilitating the selection of virus-specific antibodies. However, neither the dynamics and cross-reactivity of the SARS-CoV-2-specific T-cell response nor the diversity of resulting immune memory is well understood. In this study, we use longitudinal high-throughput T-cell receptor (TCR) sequencing to track changes in the T-cell repertoire following two mild cases of COVID-19. In both donors, we identified CD4+ and CD8+ T-cell clones with transient clonal expansion after infection. We describe characteristic motifs in TCR sequences of COVID-19-reactive clones and show preferential occurrence of these motifs in publicly available large dataset of repertoires from COVID-19 patients. We show that in both donors, the majority of infection-reactive clonotypes acquire memory phenotypes. Certain T-cell clones were detected in the memory fraction at the pre-infection time point, suggesting participation of pre-existing cross-reactive memory T cells in the immune response to SARS-CoV-2.

• Klíčová slova
• COVID-19, RepSeq, SARS-CoV-2, TCR, computational biology, human, immunology, inflammation, systems biology,
• MeSH
• COVID-19 imunologie   patofyziologie   MeSH
• genová knihovna MeSH
• imunologická paměť * MeSH
• lidé MeSH
• longitudinální studie MeSH
• mapování epitopu MeSH
• receptory antigenů T-buněk chemie   genetika   MeSH
• SARS-CoV-2 fyziologie   MeSH
• sekvence aminokyselin MeSH
• stupeň závažnosti nemoci MeSH
• T-lymfocyty imunologie   MeSH
• testování histokompatibility MeSH
• zkřížené reakce MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• receptory antigenů T-buněk MeSH

The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.

• MeSH
• analýza jednotlivých buněk MeSH
• anotace sekvence * MeSH
• antigeny chemie   imunologie   metabolismus   MeSH
• databáze proteinů * MeSH
• hlavní histokompatibilní komplex genetika   imunologie   MeSH
• interakční proteinové domény a motivy MeSH
• internet MeSH
• lidé MeSH
• Macaca mulatta MeSH
• molekulární modely MeSH
• myši MeSH
• receptory antigenů T-buněk chemie   imunologie   metabolismus   MeSH
• sekundární struktura proteinů MeSH
• sekvence aminokyselin MeSH
• sekvenční homologie aminokyselin MeSH
• sekvenční seřazení MeSH
• software * MeSH
• T-lymfocyty cytologie   imunologie   MeSH
• vazba proteinů MeSH
• vazebná místa MeSH
• vysoce účinné nukleotidové sekvenování MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antigeny MeSH
• receptory antigenů T-buněk MeSH