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Slow phosphorylation of a tyrosine residue in LAT optimizes T cell ligand discrimination

Abstract

Self–non-self discrimination is central to T cell-mediated immunity. The kinetic proofreading model can explain T cell antigen receptor (TCR) ligand discrimination; however, the rate-limiting steps have not been identified. Here, we show that tyrosine phosphorylation of the T cell adapter protein LAT at position Y132 is a critical kinetic bottleneck for ligand discrimination. LAT phosphorylation at Y132, mediated by the kinase ZAP-70, leads to the recruitment and activation of phospholipase C-γ1 (PLC-γ1), an important effector molecule for T cell activation. The slow phosphorylation of Y132, relative to other phosphosites on LAT, is governed by a preceding glycine residue (G131) but can be accelerated by substituting this glycine with aspartate or glutamate. Acceleration of Y132 phosphorylation increases the speed and magnitude of PLC-γ1 activation and enhances T cell sensitivity to weaker stimuli, including weak agonists and self-peptides. These observations suggest that the slow phosphorylation of Y132 acts as a proofreading step to facilitate T cell ligand discrimination.

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Fig. 1: Mammalian LAT has a glycine preceding Y132 that decreases the phosphorylation efficiency of Y132.
Fig. 2: Mutation of LAT G131 to an aspartate or glutamate facilitates calcium responses by augmenting PLC-γ1 signaling.
Fig. 3: Enhanced Y132 phosphorylation allows T cells to react with low-affinity ligands.
Fig. 4: Substitution of G131D or G131E in LAT promotes ERK activation and calcium increase in response to weak ligand or self-peptide stimulation.
Fig. 5: The G135D mutation in LAT promotes primary mouse T cells to respond to low-affinity antigen or self-peptide stimulation.
Fig. 6: LAT Y132 probably represents a conserved kinetic proofreading step in tetrapodal T cells.
Fig. 7: Cold temperature does not impair the ability of zebrafish thymocytes to trigger calcium flux in response to stimulation.
Fig. 8: Expression of LAT G131D endows T cells with the zebrafish thymocyte-like ability to promote calcium mobilization at reduced temperature.

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Acknowledgements

We thank A. Roque (University of California, San Francisco) for animal husbandry, S. Muratcioglu (University of California, Berkeley) for providing the GFP-labeled PLC-γ1 tandem N-SH2 protein, the NIH Tetramer Core Facility for providing the OVA and APL peptide-loaded H-2Kb monomers or OVA-loaded H-2Ab tetramers, the UCSF Parnassus Flow Cytometry Core for maintaining the BD FACSAria II, R. Mathieu (Boston Children’s Hospital) and the BCH Department of Hematology/Oncology Flow Cytometry Research Facility for technical assistance, B. Au-Yeung (Emory University), P. Allen and D. Donermeyer (Washington University in St. Louis), and G. Morris and L.-F. Lu (University of California, San Diego) for critical feedback on the manuscript. The work was supported by the Jane Coffin Childs Fund 61–1560 (to W.-L.L.), the Damon Runyon Cancer Research Foundation DRG 2198-14 and DFS 31-18 (to N.H.S.), the Czech Science Foundation 19-03435Y (to O.S.), the Howard Hughes Medical Institute (to A.W. and J.K.) and NIH, NIAID P01 AI091580-06 (to A.W. and J.K.), 1R37AI114575 (to A.W.), and DRC Center Grant P30 DK063720 (UCSF Parnassus Flow Cytometry Core). All data to understand and access the conclusions of this study are available in the main text, the supplementary materials, and the indicated repositories.

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W-L.L, N.H.S., J.K., and A.W were responsible for conceptualization; W-L.L, N.H.S., S.A.R., L.I.Z., J.K., and A.W. were responsible for the methodology; W-L.L, N.H.S, S.A.R., and I.R.F. carried out the investigations; W-L.L, N.H.S., S.A.R., and A.W. wrote the original draft; W-L.L, N.H.S., S.A.R., V.H., I.R.F., W.Z., O.S., L.I.Z., J.K., and A.W. reviewed and edited the manuscript; W.Z., V.H., and O.S. provided resources; L.I.Z., J.K., and A.W. supervised the study; and W-L.L, N.H.S., W.Z., O.S., L.I.Z., J.K., and A.W acquired funding.

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Correspondence to Arthur Weiss.

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Integrated supplementary information

Supplementary Figure 1 ZAP-70-mediated phosphorylation of LAT Y132 is a slow signal event.

a. J.CskAS Jurkat cells were treated with the PP1 analog, 3-iodo-benzyl-PP1, for various periods (sec) of time. Lysates were subjected to immunoblot analysis of p-Y171, p-Y132 of LAT or p-Y783 of PLC-γ1. Total LAT is used as a loading control. Note the same lysates were run on two separate gels to blot for p-Y171 and p-Y132. b. The relevant bands in each immunoblot were quantified by Image Lab. The signal intensity was normalized to the 0 sec time point first and then further normalized as the fraction of maximal responses. The experiments were performed seven times. The brackets represent the standard deviation (mean ± s.d; n = 7). c. Representative bar graphs of phosphorylation of Y132 by ZAP-70. Data are derived from a high-throughput phosphorylation screen using the ZAP-70 kinase domain and a peptide library spanning LAT residues 120-139, in a Y127F background, as reported in previously (Shah et al., 2016). This subset of the data from the full screen shows the impact of every amino acid substitution at residues 131 (-1 position) and 135 (+3 position) on the ability of ZAP-70 to phosphorylate Y132. Data are shown on a log10-scale relative to the parent (“wild-type”) sequence (glycine at 131 and valine at 135). A positive value indicates enhancement of phosphorylation relative to the parent sequence, a value close to zero indicates no impact on phosphorylation efficiency, and a negative value indicates that the substitution reduced the efficiency of phosphorylation. The screen shows that most -1 substitutions enhance phosphorylation by ZAP-70, relative to a -1 glycine, and that ZAP-70 strongly prefers to phosphorylate substrates with a +3 hydrophobic residue. The average effect of mutations at Y132 are shown by a red dotted horizontal line to demonstrate the magnitude of the most negatively-perturbing substitutions (that is the signal floor of the assay). This high-throughput screen was done once. d. CRISPR-Cas9 was used to generate ZAP-70-deficient Jurkat cells (J.Zap70.KO) or ITK-deficient Jurkat cells (J.Itk.KO). Cells were stimulated with anti-TCR mAb (C305) at 37oC for a time course of 1, 2, or 5 min. Lysates were then subjected to immunoblot analysis as indicated. Data are representative of four independent experiments.

Supplementary Figure 2 G131–p-Y132 exhibits comparable binding affinity to the PLC-γ1 N-SH2 domain as does a peptide with aspartate preceding p-Y132.

a. Graphs showing the raw data and binding isotherms from isothermal titration calorimetry for representative measurements of LAT p-Y132 peptides binding to the PLC-γ1 N-terminal SH2 domain. The calorimeter cell contained the SH2 domain at a concentration of 3 μM, and the peptide (30 μM) was delivered in 16 injections. Peptide sequences are given above the graphs. b. Bar graph showing the mean binding affinities from three independent experiments as in (a). Each symbol represents one independent experimental result. ns, not significant; two-tailed Mann-Whitney test. The center values presented the mean. c. Data derived from a high-throughput binding screen using the PLC-γ1 N-terminal SH2 domain and a phospho-peptide library containing all single point mutations in LAT residues 120-139, in a Y127F background and with a phosphorylated Y132 residue. This subset of the data from the full screen shows the impact of every amino acid substitution at residues 131 (-1 position) and 135 (+3 position) on the ability of the PLC-γ1 N-terminal SH2 domain to bind to p-Y132. Data are shown on a log10-scale relative to the parent (“wild-type”) sequence. A positive value indicates enhancement in binding relative to the parent sequence, a value close to zero indicates no impact on binding affinity, and a negative value indicates that the substitution reduced the binding affinity. The average effect of mutations at Y132 is shown by a red dotted horizontal line to demonstrate the magnitude of the most negatively-perturbing substitutions (that is the signal floor of the assay). The screen shows that binding to the PLC-γ1 N-terminal SH2 domain is largely unaffected by the identity of the -1 residue, whereas it has a strong preference for hydrophobic residues at the +3 position, as described previously (Songyang et al., 1995). This high-throughput screen was done once.

Supplementary Figure 3 G131D or E does not impact activation of ZAP-70 and Lck.

a. Immunoblot analysis of J.LAT.WT, J.LAT.G131D, or J.LAT.G131E cells stimulated with a range of titrated anti-CD3 for one minute at 37oC. Lysates were prepared and run on 12% NuPage Bis-Tris protein gels, and subjected to immunoblot analysis with various anti-pY or anti-total protein as indicated. Data are representative of at least six independent experiments. b. Bar graphs depicting the fold change of phospho-tyrosines of specific proteins (as indicated) of J.LAT.WT, J.LAT.G131D, or J.LAT.G131E cells following stimulation with titrated concentrations of anti-CD3. Each symbol represents the analysis of one experiment. The lines above the bar graphs represent the significance of standard deviations (mean; n = 6 for Lck p-Y394, ZAP-70 p-Y319, LAT p-Y191, LAT p-Y226; n =7 for ZAP-70 Y493; n = 8 for LAT p-Y171; n = 4 for ζ p-Y142). ns = not significant. For Lck p-Y394, WT vs D from left to right: P = 0.2751; P = 0.9989; P = 0.9923; P = 0.9933; P > 0.9999; WT vs E from left to right: P > 0.9999; P = 0.9847; P = 0.9565; P = 0.9933; P > 0.9999; P = 0.9987; For ζ p-Y412, WT vs D from left to right: P > 0.9999; P = 0.9378; P = 0.9988; P = 0.9996; P = 0.9932; WT vs E from left to right: P > 0.9999; P = 0.9119; P > 0.9999; P > 0.9999; P > 0.9999; For ZAP-70 p-Y319, WT vs D from left to right: P > 0.9999; P = 0.9958; P = 0.7575; P = 0.6990; P = 0.1022; WT vs E from left to right: P = 0.5233; P = 0.5144; P = 0.4558; P = 0.3149; P = 0.9968; For ZAP-70 p-Y493, WT vs D from left to right: P > 0.9999; P = 0.9180; P = 0.4685; P = 0.3701; P = 0.9789; WT vs E from left to right: P = 0.8176; P > 0.9999; P = 0.9429; P = 0.7203; P > 0.9999; For LAT p-Y171, WT vs D from left to right: P = 0.2263; P > 0.9999; P = 0.9997; P = 0.9986; P = 0.7571; WT vs E from left to right: P = 0.9852; P = 0.9801; P > 0.9999; P = 0.9994; P = 0.9983; For LAT p-Y191, WT vs D, from left to right: P = 0.9995; P = 0.6763; P = 0.9994; P = 0.9999; P > 0.9999; WT vs E, from left to right: P = 0.9998; P = 0.9996; P > 0.9999; P = 0.9998; P = 0.9998; For LAT p-Y226, WT vs D, from left to right: P > 0.9999; P = 0.9984; P > 0.9999; P > 0.9999; P = 0.9869; WT vs E, from left to right: P = 0.3200; P = 0.9887; P = 0.9985; P > 0.9999; P > 0.9999. One-way ANOVA test. c. Bar graphs depicting the fold change of LAT p-Y132 or PLC-γ1 p-Y783 of J.LAT.WT, J.LAT.G131D, or J.LAT.G131E cells following stimulation with titrated concentrations of anti-CD3. The relevant bands in each immunoblot were quantified by Image Lab. The signal intensity of LAT p-Y132 or PLC-γ1 p-Y783 was normalized to the total protein (LAT or PLC-γ1) first and then normalized to the 0 sec time point of J.LAT.WT cells’ response. The experiments were performed at least six times. Each symbol represents the analysis of one experiment. The lines above the bar graphs represent the significance of the standard deviations (mean; n = 10 for LAT p-Y132; n = 7 for PLC-γ1 p-Y783). For LAT p-Y132 statistical analysis: **P = 0.0098 (WT vs D at 0.06 μg/ml); *P = 0.0305 (WT vs D at 0.13 μg/ml); *P = 0.0121 (WT vs D at 0.25 μg/ml); *P = 0.0359 (WT vs D at 0.5 μg/ml); **P = 0.0036 (WT vs E at 0.06 μg/ml); *P = 0.0420 (WT vs E at 0.13 μg/ml); **P = 0.0022 (WT vs E at 0.5 μg/ml); ns = not significant: P > 0.9999 (WT vs D at 0 μg/ml); P = 0.8161 (WT vs E at 0 μg/ml); P = 0.2517 (WT vs E at 0.06 μg/ml). For PLC-γ1 p-Y783 statistical analysis: **P = 0.00206 (WT vs D at 0.13 μg/ml); ***P = 0.0005 (WT vs D at 0.25 μg/ml); *P = 0.0305 (WT vs D at 0.5 μg/ml); *P = 0.0483 (WT vs E at 0.25 μg/ml); ***P = 0.0026 (WT vs E at 0.5 μg/ml); ns = not significant: P > 0.9999 (WT vs D at 0 μg/ml); P > 0.9999 (WT vs E at 0 μg/ml); P = 0.2593 (WT vs D at 0.06 μg/ml); P > 0.9999 (WT vs E at 0.06 μg/ml); P = 0.2843 (WT vs E at 0.13 μg/ml); One-way ANOVA test.

Supplementary Figure 4 The expression of G131D or E promotes the activation of ERK in response to weak OVA APL stimulation.

a. Representative contour plot of ERK phosphorylation of G131D (left population), G131E (middle population), or WT LAT (right population) expressing J.OT-I+hCD8+ Jurkat variants as in Fig. 4a,b. Ligands used for stimulation are indicated above the plots. b. Bar graphs depicting the percent of p-ERK+ cells as shown in Fig. 4b,c. The percent of p-ERK+ cells at peptide concentration at 1000 pM represents the gated population in Fig. 4b. Each symbol represents one experiment (n = 4). Data are compiled from four independent experiments. The statistical analysis for cells stimulated with OVA peptide: ***P = 0.0001 (WT vs E at 100 pM); ***P = 0.0002 (WT vs E at 1000 pM); ****P = <0.0001. For cells stimulated with Q4R7 peptide: *P = 0.0159; **P = 0.0019; ****P = <0.0001; ns, not significant P = 0.0838. For cells stimulated with T4 peptide: *P = 0.0298; ***P = 0.001; ****P = <0.0001; ns, not significant P = 0.1385. For cells stimulated with Q4H7 peptide: ***P = 0.0009; ****P = <0.0001; ns, not significant P = 0.4285 (WT vs D at 1 pM); P = 0.8305 (WT vs E at 1 pM); P = 0.4731 (WT vs E at 10 pM); P = 0.6343 (WT vs E at 100 pM); P = 0.2393 (WT vs E at 1000 pM); For cells stimulated with G4: **P = 0.0035 (WT vs D at 10 pM); **P = 0.0048 (WT vs D at 100 pM); **P = 0.0030 (WT vs D at 1000 pM); *P = 0.0192 (WT vs E at 10 pM); *P = 0.0358 (WT vs E at 1000 pM); ns, not significant: P = 0.9978 (WT vs D at 1 pM); P = 0.2937 (WT vs E at 1 pM); P = 0.3008 (WT vs E at 100 pM). For cells stimulated with Catnb peptide: ****P = <0.0001; ns, not significant P = 0.9967 (WT vs D at 1 pM); P > 0.9999 (WT vs E at 1 pM); P = 0.6354 (WT vs E at 10 pM). For cells stimulated with VSV peptide: ns, not significant: P > 0.9999 (WT vs D at 1 pM); P = 0.8635 (WT vs D at 10 pM); P = 0.9991 (WT vs D at 100 pM); P > 0.9999 (WT vs D at 1000 pM); P = 0.9658 (WT vs E at 1 pM); P > 0.9999 (WT vs E at 10 pM); P = 0.9998 (WT vs E at 100 pM); P = 0.9688 (WT vs E at 1000 pM); One-way ANOVA test.

Supplementary Figure 5 Substitution of G135D in LAT enables the activation of T cells by low-affinity antigen in a gain-of-function manner.

a. Naive OT-I+ CD8 T cells (left panels) were isolated and transduced with retrovirus expressing wild-type LAT-P2A-BFP or G135D LAT-P2A-BFP. Cells were rested for one day before they were subjected to stimulation with various peptides-pulsed TCR Cα-deficient splenocytes over a range of peptide concentrations (10 μM, 3 μM, 1 μM, 0.3 μM, 0.1 μM, 0 μM for OVA or G4 peptide; 10 μM, 1 μM, 0 μM for VSV peptide). Or, naive OT-II+ CD4 T cells were used for experiments. OT-II+ CD4 T cells were stimulated with agonist OVA- or partial agonist E336Q-pulsed splenocytes overnight (10 μM, 3 μM, 1 μM, 0.1 μM, 0 μM for OVA or E336Q peptide; 10 μM, 1 μM, 0 μM for CLIP peptide). Representative histograms are shown. Peptides used for stimulation are indicated at the left. The expression of IRF4 or CD69 was analyzed. Data are representative of three independent experiments. b. Statistical analysis of p-ERK activation for OT-I+ CD8 T cells (left) or OT-II+ CD4 T cells (right) as experiments done in (a). TCR Cα-deficient splenocytes were pulsed with 1 μM of OVA, T4, or G4 peptide, 10 μM of Catnb peptide or 10 μM of VSV peptide. Each symbol represents an independent replicate (mean ± s.d). **P = 0.0043 (OVA); **P = 0.0022 (T4, G4, Catnb); ns: not significant P = 0.3095. Mann-Whitney test. Statistical analysis of p-ERK induction of OT-II+ T cells was shown on right. Each symbol represents an independent replicate (n=6 samples from two independent experiments). **P = 0.0022; ns: not significant P > 0.9999. Two-tailed Mann-Whitney test. c. Cells were prepared as in (a) to retrovirally express wild-type LAT-P2A-BFP or G135D LAT-P2A-BFP, loaded with the calcium-sensitive dye Indo-I, and incubated with 1:100 or 1:200 biotinylated OVA/H-2Kb, or 1:100 T4/H-2Kb, G4/H-2Kb, or VSV/H-2Kb monomers. Cells were then moved to 37oC and subjected to flow cytometry-based calcium assays. Cells were first recorded for 30 sec to obtain a baseline calcium level. Streptavidin (SA) was added at the 30th sec. Ionomycin (Iono) was added at the 240th sec. Representative calcium traces are shown. Monomers used for stimulation are indicated above the calcium plots. Data are representative of two independent experiments.

Supplementary Figure 6 Peripheral T cells ectopically expressing the mutant G135D LAT exhibit a lower responsive threshold while stimulated with weak ligands or self-peptides.

Flow cytometric analysis of CD69 upregulation and mCherry expression in GFP+Vα2+CD8+ T cells after stimulation with different peptide-pulsed splenocytes (as indicated on top of the contour plots) as in Fig. 5. The GFP+ mCherry-negative population did not express the transduced LAT and, thus, did not respond to peptide stimulation. Data are representative of three experiments.

Supplementary Figure 7 T cell ligand discrimination is preferentially regulated at LAT Y132.

a. CD8-negative or positive LAT-deficient J.OT-I+ Jurkat variants were reconstituted with wild-type LAT or G131D LAT (J.OT-I+.hCD8neg.LAT.WT, J.OT-I+.hCD8neg.LAT.G131D, J.OT-I+.hCD8+.LAT.WT, or J.OT-I+.hCD8+.LAT.G131D). Cells were stimulated with T2-Kb antigen-presenting cells pulsed with OVA peptide, OVA APL peptides, self-peptide Catnb, or VSV control peptide over a wide range of peptide concentrations as in Fig. 3. The percentage of cells that are CD69+ is plotted against peptide concentration (mean ± s.d; n = 3 technical replicates). Data are representative of three experiments. b. Statistical analysis of CD69 upregulation as in (a) with the stimulation of 10 nM of each peptide (mean; n = 3 technical replicates). Data are representative of three experiments. c. LogEC50 analysis of CD69 induction assays as in (a). d. LAT-deficient J.OT-I+ hCD8+ Jurkat variants were reconstituted with wild-type LAT or D126G-Y127, D170G-Y171, E190G-Y191, or D225G-Y226 LAT. Cells were subjected to CD69 induction assays as in (a). The percentage of cells that are CD69+ is plotted against peptide concentration (mean ± s.d; n = 3 technical replicates). Data are representative of two experiments.

Supplementary Figure 8 Temperature effect on mouse thymocyte calcium responses.

Con A-induced calcium responses in 5 × 105 mouse thymocytes per well in a 96 well plate. The cells were loaded with the calcium-sensitive dye Indo-I at room temperature, washed and rested, and then used to record calcium responses using a Flex Station II. Indo-1 loaded cells were first analyzed for 30 sec to obtain the baseline ratio of bound to unbound calcium, and then stimulated with various concentrations of Con A (as color-coded; treatment was added at the 30th sec) for 5 min at various temperatures. Representative calcium traces are shown. Data are representative of two independent experiments.

Supplementary Figure 9 Schematic summary depicting the role of LAT residue 131 in controlling T cell signaling.

The top panel builds upon structural and biochemical analyses of ZAP-70 substrate recognition, which revealed that G131 in human LAT attenuates the rate of Y132 phosphorylation relative to that of other tyrosine phosphorylation events on LAT. The bottom panel depicts the implication for T cell ligand selectivity of the naturally slow Y132 phosphorylation found in mammalian T cells relative to more efficient Y132 phosphorylation in G131D/E mutant T cells and some fish T cells. The G131D mutation facilitates Y132 phosphorylation but also promotes self-reactivity. Mammals use G131 to attenuate Y132 phosphorylation for better ligand discrimination. Our results raise the possibility that some fish may utilize different LAT phosphorylation kinetics than most jawed vertebrates to alter the T cell activation threshold and achieve immune-fitness advantages in their environments for better T cell ligand discrimination.

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Lo, WL., Shah, N.H., Rubin, S.A. et al. Slow phosphorylation of a tyrosine residue in LAT optimizes T cell ligand discrimination. Nat Immunol 20, 1481–1493 (2019). https://doi.org/10.1038/s41590-019-0502-2

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