Progressive enhancement of kinetic proofreading in T cell antigen discrimination from receptor activation to DAG generation

Abstract

T cells use kinetic proofreading to discriminate antigens by converting small changes in antigen binding lifetime into large differences in cell activation, but where in the signaling cascade this computation is performed is unknown. Previously, we developed a light-gated immune receptor to probe the role of ligand kinetics in T cell antigen signaling. We found significant kinetic proofreading at the level of the signaling lipid diacylglycerol (DAG) but lacked the ability to determine where the multiple signaling steps required for kinetic discrimination originate in the upstream signaling cascade (Tischer and Weiner, 2019). Here we uncover where kinetic proofreading is executed by adapting our optogenetic system for robust activation of early signaling events. We find the strength of kinetic proofreading progressively increases from Zap70 recruitment to LAT clustering to downstream DAG generation. Leveraging the ability of our system to rapidly disengage ligand binding, we also measure slower reset rates for downstream signaling events. These data suggest a distributed kinetic proofreading mechanism, with proofreading steps both at the receptor and at slower resetting downstream signaling complexes that could help balance antigen sensitivity and discrimination.

A new, all‐encompassing aetiology of type 1 diabetes

“…Therefore, the association between TCR and self-peptide-HLA complex is short, preventing T-cell activation. The current model of T-cell activation suggests that multiple proof-reading steps consisting of multiple rounds of tyrosine phosphorylation need to occur before full T-cell activation occurs [70,71]. This time-consuming process requires continuous binding of peptide-HLA complex; therefore, low affinity ligands do not cause T-cell activation.…”

“…A single amino acid change in the self-peptide or epitope-binding groove of the HLA protein can significantly increase binding affinity. As most of the peptides in the epitope-binding groove are self-peptides, the simultaneous signal from all TCRs of a T-cell due to a seemingly minor self-peptide-HLA complex mutation may be sufficient to cause T-cell activation, assuming the mutation does not affect HLA-TCR affinity or co-stimulatory signals, for example, HLA with CD4, CD80 or CD86 with CD28 or CTLA4 [70,71]. The T-cells that encounter the self-peptide-HLA complex mutation have successfully completed cellular positive, negative, and agonist selection in the thymus; because the HLA-TCR binding is not altered by the HLA mutation affecting the epitope-binding groove, there is no down-regulation of the erroneous, non-self-signal due to normal insulin peptide presented in a mutated epitope-binding groove of an otherwise normal HLA protein.…”

Flexibility and sensitivity in gene regulation out of equilibrium

“…In this work, we use tools from 34 graph theory (15, 16) to explore the full space of transcrip-35 tional steady-state outputs available for this system under 36 different energetic drives, compared to equilibrium control. 37 We find that all equilibrium responses must be monotonic 38 (with one inflection point) as a function of control variables, 39 such as the concentration of transcription factor, measured 40 in a conventional logarithmic scale. In contrast, we discover 41 that nonequilibrium models can exhibit three types of output: 42 an "equilibrium-like," monotonic response with one inflection 43 point, potentially displaced from equilibrium; a new -but 44 still-monotonic-shape with three inflection points; and a new, 45 surprising non-monotonic shape with two inflection points, 46 where, for instance, increasing a control variable can change 47 its effect from repression to activation.…”

“…We found that investing energy along more than one rate at once was capable of achieving more dramatic response curves more economically. This finding may help explain the many observations in biological systems where energy is independently injected along multiple steps (36)(37)(38)(39)(40)(41). However, since each independently-regulated injection of energy may also be accompanied by architectural costs, not all examples of biological regulation may contain the distributed dissipation machinery required to make novel nonequilibrium response signatures conspicuous.…”

“…the fraction of rate space manifesting said phenotype-varies 489 markedly across the rates. For instance, the two-inflection- recognized that many steps could each be driven independently 507 (36), as has later been repeatedly observed in the multistep ways that T-cell or MAPK activation implement kinetic proofreading (37)(38)(39)(40) or in mechanochemical operation of myosin motors (41). How do such distributed investments of energy afford expanded control of response functions?…”