Thymic selection is crucial for forming a pool of T-cells that can efficiently discriminate self from non-self using their T-cell receptors (TCRs) to develop adaptive immunity. In the present study we analyzed how a diverse set of physicochemical and sequence features of a TCR can affect the chances of successfully passing the selection. On a global scale we identified differences in selection probabilities based on CDR3 loop length, hydrophobicity, and residue sizes depending on variable genes and TCR chain context. We also observed a substantial decrease in N-glycosylation sites and other short sequence motifs for both alpha and beta chains. At the local scale we used dedicated statistical and machine learning methods coupled with a probabilistic model of the V(D)J rearrangement process to infer patterns in the CDR3 region that are either enriched or depleted during the course of selection. While the abundance of patterns containing poly-Glycines can improve CDR3 flexibility in selected TCRs, the "holes" in the TCR repertoire induced by negative selection can be related to Arginines in the (N)-Diversity (D)-N-region (NDN) region. Corresponding patterns were stored by us in a database available online. We demonstrated how TCR sequence composition affects lineage commitment during thymic selection. Structural modeling reveals that TCRs with "flat" and "bulged" CDR3 loops are more likely to commit T-cells to the CD4+ and CD8+ lineage respectively. Finally, we highlighted the effect of an individual MHC haplotype on the selection process, suggesting that those "holes" can be donor-specific. Our results can be further applied to identify potentially self-reactive TCRs in donor repertoires and aid in TCR selection for immunotherapies.

• Keywords
• HLA alleles, T-cell immunity, T-cell receptor repertoire, immune repertoire analysis, immune repertoire sequencing, thymic selection,
• MeSH
• Complementarity Determining Regions genetics   immunology   chemistry   MeSH
• Humans MeSH
• Receptors, Antigen, T-Cell, alpha-beta * genetics   immunology   chemistry   MeSH
• Thymus Gland * immunology   cytology   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Complementarity Determining Regions MeSH
• Receptors, Antigen, T-Cell, alpha-beta * MeSH

Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.

• MeSH
• Adult MeSH
• Jurkat Cells MeSH
• Middle Aged MeSH
• Humans MeSH
• Computer Simulation MeSH
• Receptors, Antigen, T-Cell, alpha-beta genetics   MeSH
• Receptors, Antigen, T-Cell genetics   MeSH
• Reproducibility of Results MeSH
• High-Throughput Nucleotide Sequencing methods   MeSH
• Bias MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Intramural MeSH
• Names of Substances
• Receptors, Antigen, T-Cell, alpha-beta MeSH
• Receptors, Antigen, T-Cell 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.

• Keywords
• COVID-19, RepSeq, SARS-CoV-2, TCR, computational biology, human, immunology, inflammation, systems biology,
• MeSH
• COVID-19 immunology   physiopathology   MeSH
• Gene Library MeSH
• Immunologic Memory * MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Epitope Mapping MeSH
• Receptors, Antigen, T-Cell chemistry   genetics   MeSH
• SARS-CoV-2 physiology   MeSH
• Amino Acid Sequence MeSH
• Severity of Illness Index MeSH
• T-Lymphocytes immunology   MeSH
• Histocompatibility Testing MeSH
• Cross Reactions MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Receptors, Antigen, T-Cell MeSH

The diverse repertoire of T-cell receptors (TCR) plays a key role in the adaptive immune response to infections. Using TCR alpha and beta repertoire sequencing for T-cell subsets, as well as single-cell RNAseq and TCRseq, we track the concentrations and phenotypes of individual T-cell clones in response to primary and secondary yellow fever immunization - the model for acute infection in humans - showing their large diversity. We confirm the secondary response is an order of magnitude weaker, albeit ∼10 days faster than the primary one. Estimating the fraction of the T-cell response directed against the single immunodominant epitope, we identify the sequence features of TCRs that define the high precursor frequency of the two major TCR motifs specific for this particular epitope. We also show the consistency of clonal expansion dynamics between bulk alpha and beta repertoires, using a new methodology to reconstruct alpha-beta pairings from clonal trajectories.

• Keywords
• TCR, computational biology, human, immunology, inflammation, single-cell, systems biology, vaccination, yellow fever,
• MeSH
• Time Factors MeSH
• Adult MeSH
• Epitopes immunology   MeSH
• Phenotype MeSH
• Immunologic Memory MeSH
• Humans MeSH
• Lymphocyte Subsets immunology   physiology   MeSH
• Receptors, Antigen, T-Cell genetics   immunology   physiology   MeSH
• T-Lymphocytes immunology   physiology   virology   MeSH
• Transcriptome MeSH
• Yellow Fever Vaccine immunology   pharmacology   MeSH
• Yellow fever virus immunology   MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Yellow Fever immunology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Epitopes MeSH
• Receptors, Antigen, T-Cell MeSH
• Yellow Fever Vaccine 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
• Adaptive Immunity genetics   MeSH
• Antigens, Viral MeSH
• Antigens MeSH
• Complementarity Determining Regions genetics   physiology   MeSH
• Immunotherapy MeSH
• Humans MeSH
• Receptors, Antigen, T-Cell immunology   metabolism   physiology   MeSH
• Sequence Analysis, DNA methods   MeSH
• Cluster Analysis MeSH
• High-Throughput Nucleotide Sequencing methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antigens, Viral MeSH
• Antigens MeSH
• Complementarity Determining Regions MeSH
• Receptors, Antigen, T-Cell MeSH