T-cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages experimentally inferred antigen-associated TCRs to form meta-clonotypes – groups of biochemically similar TCRs – that can be used to robustly quantify functionally similar TCRs in bulk repertoires across individuals. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the SARS-CoV-2 antigen-associated TCRs that have strong evidence of restriction to patients with a specific human leukocyte antigen (HLA) genotype. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (false discovery rate [FDR]<0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.
As the mechanistic basis of adaptive cellular antigen recognition, T cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages antigen-enriched repertoires to form meta-clonotypes – groups of biochemically similar TCRs – that can be used to robustly quantify functionally similar TCRs in bulk repertoires. We apply the framework to TCR data from COVID-19 patients, generating 1,915 public TCR meta-clonotypes from the 18 SARS-CoV-2 antigen-enriched repertoires with the strongest evidence of HLA-restriction. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 44% (845/1915) were significantly enriched among COVID-19 patients that expressed the putative restricting HLA allele, demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates workflows for distance-based TCR repertoire analysis.
If viral strains are sufficiently similar in their immunodominant epitopes, then populations of cross-reactive T cells may be boosted by exposure to one strain and provide protection against infection by another at a later date. This type of pre-existing immunity may be important in the adaptive immune response to influenza and to coronaviruses. Patterns of recognition of epitopes by T cell clonotypes (a set of cells sharing the same T cell receptor) are represented as edges on a bipartite network. We describe different methods of constructing bipartite networks that exhibit cross-reactivity, and the dynamics of the T cell repertoire in conditions of homeostasis, infection and re-infection. Cross-reactivity may arise simply by chance, or because immunodominant epitopes of different strains are structurally similar. We introduce a circular space of epitopes, so that T cell cross-reactivity is a quantitative measure of the overlap between clonotypes that recognize similar (that is, close in epitope space) epitopes.
The T cell receptor (TCR) repertoire is extremely diverse and plays an instrumental role in fighting off pathogens individuals encounter in a lifetime. A key aspect of the immune system combatting the diverse array of pathogens an individual sees may be TCR cross-reactivity, where a TCR can recognize more than one peptide displayed on an MHC-I molecule. The number of possible peptides presented to the immune system exceeds 1015, and this number is greater than the number of possible T cells the immune system can generate and sustain. Thus, a certain portion of the T cells in an immune system must be cross-reactive. Specifically, cross-reactive TCRs may play a key role in allowing the immune system to adapt to rapidly evolving pathogens, such as influenza A virus (IAV). Utilizing 8 variant influenza viruses for priming and secondary challenge, our preliminary data has shown that cross-reactive TCRs seen in primary infection with one IAV can mount a robust and effective memory response to a different IAV, across a range of mutations. However, selection for cross-reactive receptors may create a narrowed repertoire consisting of a few clonotypes over the course of many repeated heterosubtypic IAV infections, covering a narrow range of antigenic space representing the mutant epitopes encountered. Paradoxically, this selection for cross-reactivity may provide a substantial escape opportunity with future antigenic variations. Ongoing work focuses on how repeated IAV challenges shape the repertoire, and how previous infections inform future responses by selected cross-reactive T cell pools.
Supported by grants from NIH (R01 112404040) and the St. Jude Children's Research Hospital Graduate School
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