RT Journal Article SR Electronic T1 Architecture of a minimal signalling pathway explains the T cell response to a 1,000,000-fold variation in antigen affinity and dose JF bioRxiv FD Cold Spring Harbor Laboratory SP 071878 DO 10.1101/071878 A1 Melissa Lever A1 Hong-Sheng Lim A1 Philipp Kruger A1 John Nguyen A1 Nicola Trendel A1 Enas Abu-Shah A1 Philip K. Maini A1 P. Anton van der Merwe A1 Omer Dushek YR 2016 UL http://biorxiv.org/content/early/2016/08/27/071878.abstract AB 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 1,000,000-fold 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.