Architecture of a minimal signalling pathway explains the T cell response to a 1,000,000-fold variation in antigen affinity and dose

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map pMHC affinity onto T cell responses have produced inconsistent patterns of responses preventing formulations of canonical models of T cell signalling. Here, a systematic analysis of T cell responses to 1,000,000fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signalling incorporating kinetic proofreading with limited signalling coupled to an incoherent feed forward loop (KPL-IFF), that reproduces these observations. We show that the KPL-IFF model correctly predicts the T cell response to antigen co-presentation. Our work offers a general approach for studying cellular signalling that does not require full details of biochemical pathways. Significance statement T cells initiate and regulate adaptive immune responses when their T cell antigen receptors recognise antigens. The T cell response is known to depend on the antigen affinity/dose but the precise relationship, and the mechanisms underlying it, are debated. To resolve the debate, we stimulated T cells with antigens spanning a 1,000,000-fold range in affinity/dose. We found that a different antigen (and hence different affinity) produced the largest T cell response at different doses. Using model identification algorithms, we report a simple mechanistic model that can predict the T cell response from the physiological low affinity regime into the high affinity regime applicable to therapeutic receptors. 1 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/071878 doi: bioRxiv preprint first posted online Aug. 27, 2016;