The expanding role of systems immunology in decoding the T cell receptor repertoire

Abstract

T cells play a crucial role in the immune system’s defense against many infectious diseases, including persistent infections for which no effective vaccines currently exist. The T cell component of the adaptive immune system is highly complex involving a constantly evolving landscape of various inter-related T cell populations. These T cell populations are characterized by their phenotypic and functional properties as well as the collection, or repertoire, of T cell receptors (TCR) that mediate T cell recognition of antigenic peptides derived from pathogens. Understanding the various processes and factors that impact the development and evolution of the broader T cell repertoire available to recognize and respond to pathogens and the characteristics of antigen-experienced T cell repertoires associated with effective immune control of pathogens is critical to the rational design of T cell-based vaccines and therapies. In this article we discuss, using examples of recent research, the promise that systems immunology approaches, involving quantitative analysis and mathematical and computational modeling of immunological data, hold for decoding the complex TCR repertoire system in the current era of advancing technologies.

A statistical modelling reveals bi-directional chromatin scanning by RAG in the human TCR-α locus

“…In conclusion, this study applies the quantitative statistical method to modelling of V(D)J recombination in human TCRs and provides evidence that RAG chromatin scanning plays a critical role in pairing TRAV and TRAJ segments. With increasing scale and complexity of TCR sequence data, statistical modelling becomes a powerful tool for advancing our understanding of TCR biology including the recombination process (DeWitt et al, 2018;Venturi and Thomas, 2018; assumed in this study are still simplified mechanistically (Murugan et al, 2012;Marcou et al, 2018), however, our findings need to be further validated with experimental approaches. Such an interdisciplinary effort will make it possible to test hypotheses and improve models in more efficient and interactive ways than ever as seen in emerging fields of immunogenomics (Zewde et al, 2018) and systems immunology (Venturi and Thomas, 2018).…”