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The T cell receptor (TCR) interacts with peptide-major histocompatibility complexes (pMHC) to discriminate pathogens from self-antigens and trigger adaptive immune responses. Direct physical contact is required between the T cell and the antigen-presenting cell (APC) for cross-junctional binding where the TCR and pMHC are anchored on two-dimensional (2D) membranes of the apposing cells1. Despite their 2D nature, TCR-pMHC binding kinetics have only been analyzed three-dimensionally (3D) with a varying degree of correlation with the T cell responsiveness2-4. Here we use two mechanical assays5,6 to show high 2D affinities between a TCR and its antigenic pMHCs driven by rapid on-rates. Compared to their 3D counterparts, 2D affinities and on-rates of the TCR for a panel of pMHC ligands possess far broader dynamic ranges that match that of their corresponding T cell responses. The best 3D predictor of response is the off-rate, with agonist pMHC dissociating the slowest2-4. In contrast, 2D off-rates are up to 8,300-fold faster, with the agonist pMHC dissociating the fastest. Our 2D data suggest rapid antigen sampling by T cells and serial engagement of a few agonist pMHCs by TCRs in a large self pMHC background. Thus, the cellular environment amplifies the TCR-pMHC binding to generate broad affinities and rapid kinetics that determine T-cell responsiveness.
The sustained interest in the kinetic analysis of TCR-pMHC interactions stems from a fundamental hypothesis that the interaction parameters play a central role in determining the subsequent T cell response. We analyzed 2D TCR-pMHC interactions on naïve CD8+ OT1 T cells with the adhesion frequency5,7 and thermal fluctuation6,8 assays using a micropipette (Fig. 1a) and a biomembrane force probe (BFP, Fig. 1b). Both employ a red blood cell (RBC) as an adhesion sensor but the BFP also attaches a bead to the RBC. RBC or bead was functionalized with pMHC mutated to abrogate CD8 binding9 (Fig. 1c) (Methods).
In the adhesion frequency assay5,7, a T cell (Fig. 1a and b, right) was micro-manipulated to touch the RBC or bead with a controlled contact area and time. TCR-pMHC binding (if present) was observed visually by the RBC elongation (Movie M1) or detected by the bead displacement (Movie M2) on T cell retraction. To determine the likelihood of adhesion, the cell pair was moved repeatedly in and out of contact for a given contact time (tc) to yield an adhesion frequency (Pa), i.e. the number of adhesions divided by the number of total contacts. The adhesion frequencies were specific because binding was abolished unless OT1 TCR and antigenic pMHC were used (Fig. 1d). Using a divalent straptavidin10 (Di-SA) to ensure monomeric pMHC presentation (Fig. 1c) produced similar adhesion frequency as using a tetravalent wildtype streptavidin (WT-SA) to couple pMHC on RBCs (Fig. 1e), ruling out multimeric pMHC as the cause for high affinity binding (see below).
The 2D kinetic information is extracted by fitting an adhesion frequency curve measured using multiple cell pairs over a range of contact times with a mathematical model5 (Fig. 2a-c), which derives separately two parameters (mrmlAcKa and koff) with good accuracy (Methods, Fig. S1). The 2D affinity Ka has a unit of area rather than volume, the unit of 3D affinity. We report the effective 2D affinity (AcKa, in μm4) as it is evaluated together with the contact area Ac (a few percent of 3 μm2 for micropipette or of 1 μm2 for BFP). Adhesion frequency depends on the receptor (mr) and ligand (ml) densities. For example, three different OVA pMHC densities yielded three distinct adhesion levels (Fig. 2a) but the same affinity is derived (Fig. S2). The weaker ligands R4 (Fig. 2b) and G4 (Fig. 2c) required higher densities than OVA (Fig. 2a and c) yet still generated lower adhesion levels, indicating far lower affinities. The 2D off-rate koff is not affected by the contact area or protein densities and is inversely proportional to the time t1/2 required to reach half-maximal Pa level5 (Method). The OVA curves in Fig. 2a reached equilibrium very rapidly, indicating a fast off-rate that required the BFP to measure accurately (Fig. 2c). The R4 (Fig. 2b) and G4 (Fig. 2c) curves rose more slowly, indicating slower off-rates. The effective 2D on-rate Ackon (= AcKa × koff) equals the initial slope of the adhesion curve divided by the receptor and ligand densities. The much steeper initial slopes yet lower pMHC densities of the adhesion curves for OVA (Fig. 2a and c) than R4 (Fig. 2b) and G4 (Fig. 2c) indicate a much faster association of TCR with OVA.
In the thermal fluctuation assay6,8 (Methods), association/dissociation events of TCR-pMHC bonds were identified by reduction/resumption of thermal fluctuations of the BFP bead because bond formation anchored the bead to the T cell, restricting its movements (Fig. S3 and Movie M3). The time from association to dissociation is bond lifetime tb whose distributions line up in semi-log plots that linearize exponential decays, suggesting first-order dissociation of single-bonds for both OVA and G4 (Fig. 2d). Their respective off-rates equal the negative slope of the lines (Fig. 2d), which agree with the corresponding values from the adhesion curves (Fig. 2c). These results confirm that both assays measure stress-free kinetics despite the use of force to break any bond present at the end of each contact cycle5-8.
We compared 2D parameters of the OT1 TCR binding to a panel of pMHCs with increasing potencies3 to the published 3D results11,12 (Fig. 3). Regardless of receptor and ligand densities, the same monomeric binding model5 fits adhesion curves at both 25 and 37 °C equally well for all ligands (Fig. S2) with higher temperature yielding higher affinities (Table 1). The effective 2D affinities from antagonist to agonist pMHC spanned three logs from 10-6–10-3 μm4, whereas that of null (VSV) pMHC was below 10-8 μm4, the assay’s detection limit7 (Fig. 3a). In sharp contrast, the 3D affinities differ by only one log for the same ligand set (Fig. 3d), making it difficult to resolve ligand potencies from TCR kinetics. Further, the micromolar 3D KD conveys an impression that TCR-pMHC binding is of low affinity; however, the OT1 (and F5, Fig. S4) TCR on naïve (and activated, Fig. S5) T cells have effective 2D affinities for agonist pMHCs similar to that of high affinity lymphocyte function-associated antigen (LFA)-1 for intercellular adhesion molecule (ICAM)-113, an interaction that provides strong adhesion for many immune functions.
The high 2D affinities of TCR for agonist pMHCs were driven by rapid 2D on-rates, which were even faster than that of P-selectin associating with P-selectin glycoprotein ligand (PSGL)-114, an interaction that requires a rapid on-rate to capture flowing leukocytes to inflamed vascular surfaces. Unlike the P-selectin-PSGL-1 interaction, however, the fast 2D on-rates for TCR-pMHC do not translate to fast 3D on-rates. In fact, the 3D TCR-pMHC on-rates11,12 are >200-fold slower than the P-selectin-PSGL-1 3D on-rate15. The 3D TCR-pMHC on-rates are insensitive to the different peptides (Fig. 3e), suggesting that TCR binding is initiated by MHC contact16. By comparison, the 2D on-rates spanned four logs for the same ligand set (Fig. 3b), indicating the critical contribution of peptide contact to TCR-pMHC association. Thus, an important attribute of our measurements is their high sensitivity to discriminate binding kinetics for a range of closely related ligands.
The 2D off-rates (Fig. 3c) were 30-8300 fold faster than the corresponding 3D off-rates (Fig. 3f), with the value for TCR dissociating from OVA:H-2Kb (7.2 and 10.8 s-1 at 25 and 37 °C, respectively) comparable to that for L-selectin dissociating from PSGL-1 (10.2 s-1 at 25 °C), the most rapid selectin-ligand off-rate in both 2D and 3D, which is required for mediating fast rolling of leukocytes on vascular surfaces6,17. Again, the fast 2D off-rates for TCR-pMHC did not translate to fast 3D off-rates. In fact, OVA:H-2Kb dissociates from the OT1 TCR in a single step at 25 °C with a 3D off-rate of 0.022 s-1 but in two steps (i.e. requiring dimer formation) at 37 °C with a 3D off-rate of 0.0012 s-1 for the second step11,12. Most telling, the off-rates of stronger ligands are progressively faster in 2D but slower in 3D, displaying opposite trends (compare Fig. 3c and f). Thus, the TCR-pMHC off-rates and their relationships to ligand potency differ substantially between 2D and 3D.
To further test the hypothesis that TCR-pMHC kinetics determines T cell responsiveness, we measured the peptide concentration required to stimulate half-maximal T cell proliferation (EC50)18 and plotted it vs. the 2D TCR binding parameters measured at 25 °C (Fig. 4a-c) and 37 °C (Fig. 4d-f). A strong correlation was found between 1/EC50 and all metrics of 2D kinetics, especially the affinities and on-rates, for their broad dynamic ranges better match the wide range of functional responses. This is the first demonstration of the relevance of 2D TCR-pMHC binding kinetics to the functional response of T cells19. Besides T cell proliferation, a late-stage response assessed after three days of APC stimulation, the more proximal TCR downregulation response used in the previous 3D studies3 also correlated well with our 2D parameters (Fig. S6).
The substantial differences between 2D and 3D kinetics for TCR-pMHC interactions are not seen in ligand binding of selectins and integrins. In light of the recent reports of TCR clustering on the cell surface in a cholesterol- and/or actin cytoskeleton-dependent fashion20-23, we speculate that the T cell imposes unique regulations on the TCR organization, orientation, and/or conformation, which may affect the availability of TCR to binding or enable cooperative binding. While the 3D assays of purified molecules may measure their intrinsic kinetics independent of these regulatory mechanisms, our 2D assays may capture the impact of the cellular environment on TCR-pMHC interactions, which mimics the physiological situation (Fig. S7). Consistent with this view, we observed reduced effective 2D affinities of the OT1 TCR for OVA and G4 pMHCs by treatment with methyl-beta-cyclodextrin, a water-soluble cyclic heptasaccharide that can extract cholesterol from the plasma membrane24 and alter TCR preclustered structures22 (Fig. S8). Similar effects were observed by treatment with cholesterol oxidase, another cholesterol depletion agent (Fig. S9). Furthermore, the 2D affinities were also reduced by Latrunculin A, an inhibitor of actin polymerization (Fig. S10). Moreover, Monte Carlo simulations showed an increase in apparent affinity by cooperative binding if it is assumed that interaction of a pMHC with one TCR in a cluster increases the binding propensity of all members of the TCR cluster (Fig. S11). This form of cooperation is suggested by the observed memory effects of TCR-pMHC interaction such that adhesion in a past contact increases the likelihood of adhesion in the next contact9.
The insufficient resolution of T cell responsiveness by 3D TCR-pMHC kinetics (e.g. Fig. 3d-f) has generated numerous models to explain the various functional outcomes2-4,12,19,25-28. The kinetic proofreading model proposed a serial scheme to amplify the small differences in the 3D TCR-pMHC off-rates26. Our data suggest that such amplification results in 2D on-rate, off-rate, and affinity that all match the T cell response to a given pMHC. The broad affinities and rapid kinetics of the 2D interactions meet the requirement for the T cell to scan with high speed and sensitivity the numerous self pMHCs on an APC to find, engage, and respond to antigen expressed at low numbers29. The observations of antigen sampling by a T cell from several APC30 and the rapid microcluster formation between TCR and agonist pMHC further enforce how quickly the pMHC is interrogated to accumulate threshold signaling levels20,23. Microclusters of TCR coupled to its rapid 2D kinetics also allow a single pMHC to serially engage many TCRs in a short time. Note that here the term is used differently from the original model where serial engagement led to TCR internalization27. Although the lifetimes of individual TCR-pMHC bonds are brief because they dissociates rapidly, bonds also reform rapidly and frequently. Serial engagement allows both the quality and quantity of pMHC to be measured by the frequency of bond formation as it is proportional to the 2D affinity and the pMHC density. High bond formation frequency also accumulates a large fraction of engagement time. TCR clustering and cooperative binding could amplify serial engagement as it provides a high local concentration of TCRs, thereby generating maximal recognition signal to trigger downstream events for T cell activation. Thus, our 2D TCR-pMHC kinetic data may provide a basis for a comprehensive model to explain self/non-self recognition, ligand discrimination, thymocyte selection, signal accumulation, feedback mechanisms, and TCR antagonism.
We used adhesion frequency assay5 and thermal fluctuation assay6 to measure the 2D kinetics of TCR-pMHC interaction on the cell membrane. The adhesion frequency assay employed a micropipette and a BFP, and the thermal fluctuation assay employed a BFP. T cells expressing monoclonal OTI or F5 TCR were purified from transgenic mice. Human RBCs directly (or indirectly through a glass bead) coated with pMHC via biotin-streptavidin coupling served as both a surrogate APC and a force sensor for detecting the TCR-pMHC interaction. The site densities of TCR and pMHC were measured by flow cytometry7. Monte Carlo simulations and pharmacological treatments were performed to study the effects of T cell membrane environment.
We thank the NIH Tetramer Core Facility at Emory University for providing MHC monomers, J. Altman for providing the H-2Kb mutant construct, G. Bao for providing the divalent streptavdin, as well as M. Davis and H.-T. He for commenting the manuscript. This work was supported by NIH grants AI38282 and AI060799 (to C.Z.) and AI056017 and National Multiple Sclerosis Society Grant RG4047-A-3 (to B.D.E.).
Author contributionsN.J. and C.Z. initiated the kinetic study with F5 T cells; J.H. and C.Z. designed the kinetic study; J.H. and B.L. performed the micropipette experiments; V.I.Z. performed the BFP experiments and Monte Carlo simulations; L.J.E. and B.D.E. provided the T cells and conducted the functional study; J.H., V.I.Z., B.L. and C.Z. analyzed the data; B.D.E. and C.Z. wrote the paper with all authors contributing.
Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests.