Of friends and foes - how to educate the immune system

The overarching objective of my lab’s research program is to understand T cell tolerance induction in the thymus and its functional consequences. We approach this question in a multi-faceted manner, leveraging in silico and statistical models, genomics and advanced imaging technologies. In this talk, I will focus on our work using hierarchical models and in silico simulations to understand the interactions that drive thymic T cell selection and the interactions that govern these processes.

A T cell’s ability to act as a potent fighter against infection is initiated by its T cell receptor (TCR) binding to foreign peptide:MHC complexes. Large TCR repertoire diversity enables the orchestration of antigen-specific immune responses against the vast space of possible peptides. I will describe two complimentary approaches that we developed to study TCR/peptide:MHC pairs from the large TCR repertoire and antigen space, which is crucial in biomedical research. Our open-access tool copepodTCR facilitates the design and interpretation of high-throughput experimental assays to determine TCR specificity. While copepodTCR aids with assay design, the space of all possible TCR/peptide:MHC pairs is too vast to experimentally test. Therefore, we developed BATMAN, an open-access tool for predicting TCR peptide:MHC interactions which had remained a fundamental challenge.



Using predictions that we gained from these models, I will present a perspective of how thymic selection can be viewed as a learning algorithm that the immune system uses to teach developing T cells to distinguish self from nonself, thereby solving two the crucial tasks of generalisation and discrimination.