T cell receptor (TCR) recognition of a cognate peptide-major histocompatibility complex (pMHC) is central to adaptive immune recognition. Certain features of this interaction are well-understood, including many of the rules governing peptide binding to MHC. However, our ability to model the ternary TCR:pMHC complex remains limited for three primary reasons: (1) Data availability; (2) Binding; and (3) Cross-reactivity. In elucidating the rules by which the TCR:pMHC interface operates, these efforts stand to address fundamental questions at the heart of adaptive immune recognition, with important theoretical and practical implications that include the potential for the forward design of novel receptors with selected specificities, the ?decoding? of the recent influx of TCR sequencing data for specific antigenic targets, and an understanding of the cross-reactive potential of the repertoire. Previously, we developed novel approaches that provided training data for the construction of algorithms that predict various aspects of TCR specificity (1), including an algorithm we call TCRdist - a simple and effective distance measure to compare TCR sequences. TCRdist can be used to cluster antigen-specific TCR sequences and can be incorporated into a distance-based classifier capable of correctly assigning previously unobserved TCRs to characterized repertoires with robust sensitivity and specificity. Taken together, the results of these experiments and the general success of the TCRdist algorithm provide compelling evidence for the central premises of this proposal: Given a sufficient number of experimentally verified epitope- specific TCR sequences, the epitope specificity of a TCR can be predicted from its sequence; furthermore, the generation of epitope-specific TCR sequence data, in combination with structurally informed computational analysis, provides a roadmap for building a predictive model of the TCR:pMHC interaction. While we have made significant progress in this line of inquiry, the largest remaining hurdle is the apparent broad cross-reactivity within the repertoire. In order to fully elucidate the complex network of interactions among TCRs and pMHCs, the questions we must address then are: what do diverse TCRs that see the same pMHC have in common? And what do diverse pMHCs that are seen by the same TCRs have in common? The ultimate consequence of these studies, beyond their immediate biological applications, will be to assist in the development of the next generation of analytical tools for the modeling of TCR:pMHC interaction, leading to the ultimate goal of a true ?decoder? for this essential interface.
The goal of these studies is the development of a robust predictor of peptide:MHC:T cell receptor specificity. It is based on novel technological and conceptual tools we have developed to sequence epitope-specific TCRs at the single cell level and analyze them to identify the key sequence and structural features that confer specificity to the pMHC:TCR interaction. A major hurdle to the development of such a ?decoder? is the phenomenon of cross-reactivity, which we will explore from the perspective of broad TCR cross-reactivity for diverse epitopes, and narrow pMHC diversity recruiting diverse TCR repertoires. These data will provide key insights into the nature of TCR recognition and permit the development of algorithms that capture this complexity.
