Direct single molecule measurement of TCR triggering by agonist pMHC in living primary T cells

1An essential aspect of adaptive immunity is the ability of T cells to discriminate between structurally similar agonist and non-stimulatory self peptides bound to major histocompatibility complex (pMHC) molecules presented on the surface of antigen-presenting cells (APCs). Fewer than 10 agonist pMHC molecules can trigger T cells, and the signaling response occurs on a timescale of seconds. It has been recognized for decades that subtle, peptide-specific differences in binding parameters, especially kinetic rates for the pMHC and T cell receptor (TCR) reaction, seem to be the basis of antigen recognition. Experimental correlations between molecular pMHC:TCR binding kinetics, typically determined from solution assays of soluble extracellular domains and bulk measurements of T cell activity, have provided the foundation for much of this understanding.

2From a physical point of view, the extreme sensitivity, selectivity, and apparent immunity to stochastic noise exhibited by TCR antigen recognition pose challenges to classical notions of ligand-receptor signaling. For example, the maximum affinity a TCR can have for self pMHC ligands (non-triggering) is sharply defined and close to the affinity threshold for foreign pMHC (triggering). Consequently, every TCR is likely to bind a subset of the ever-present self pMHC molecules with affinities differing only slightly from genuine foreign agonist pMHC. If TCR triggering and signaling were simply proportional to TCR occupancy by ligand, then the abundance of self pMHC could easily overwhelm genuine agonist signals, rendering this as an ineffective discriminatory mechanism. Alternatively, each engagement of pMHC with TCR (serial triggering; ), perhaps with some minimum engagement time (kinetic proof reading;; ), might define the threshold for TCR triggering. Other proposed mechanisms elaborate further, suggesting (pseudo) heterodimers of self and agonist pMHC molecules or pMHC-independent forms of trans activation of multiple TCR by a single agonist pMHC may be at work. Proving or disproving any of these various possibilities based on current data is confounded by the vast difference between ensemble biochemical measurements and cell population behavior. Substantial ambiguity with respect to the actual molecular mechanisms responsible for antigen triggering of T cells remains. A physically accurate understanding of this remarkable process will require simultaneous observations of the molecular binding kinetics, stoichiometry, and movement of individual signaling complexes in living T cells.

3Here, we characterize the molecular interactions between pMHC and TCR, at the single molecule level, while simultaneously monitoring the local membrane recruitment of cytosolic Zeta-chain-associated protein kinase 70 (ZAP70) in live primary T cells. Every pMHC can be individually resolved and tracked for up to minutes before photobleaching by using a multi-timescale single molecule fluorescence imaging approach. Key to this strategy is the variable control of excitation light dose and exposure time to achieve hardware discrimination of molecular species with different mobilities. The pMHC molecules fall into two unambiguously distinguished classes: one undergoing fast random motion and the second moving slowly along linear trajectories. These slow moving pMHC are the bound pMHC:TCR complexes; they are only observed with agonist peptide and they spatially correlate with both TCR and recruitment of ZAP70. The linear trajectories of the pMHC:TCR complexes match the well-characterized cytoskeleton-driven movement of TCR during the formation of the immunological synapse. Thus a lone agonist pMHC bound to TCR leads to stable engagement of the resulting complex with the cytoskeleton. Single molecule intensity calibration of the number of ZAP70 recruited to the vicinity of each agonist pMHC indicates that TCR are triggered in a 1:1 stoichiometry with pMHC.

4Associations of pMHC with TCR exhibited molecular binding dwell times with mean durations of 53.8 ± 12.2 s and 5.2 ± 0.2 s for AND and 5c.c7 TCRs, respectively. Individual dwell times are roughly exponentially distributed and are in general agreement with bulk solution measurements of pMHC:TCR kinetic off-rates for both TCRs. However, dwell times measured from tracking experiments specifically correspond to spatial entrapment of pMHC with a TCR, or cluster of TCRs, on the T cell surface. They do not necessarily correspond to individual molecular binding events with a single TCR. Indeed, recent studies (e.g., by FRET) have suggested that pMHC:TCR kinetic off-rates may be accelerated in living cells relative to in vitro measurements, possibly as a result of actively applied forces from the cytoskeleton. We explore the possibility that individual dwell times observed by tracking experiments could be composed of rapid unbinding and serial rebinding of pMHC to multiple TCR within a cluster. Results from a stochastic reaction-diffusion analysis, covering a wide range of parameter space, indicate that serial rebinding alone is unlikely to sustain entrapment. If pMHC thoroughly disengages from TCR, it will most likely escape. Structural flexibility within the pMHC:TCR complex could give rise to apparently fast kinetics (e.g., in FRET measurements) without actual unbinding of pMHC from TCR. The tracking observations reported here directly reveal that the functional interaction between agonist pMHC and TCR is long-lived in living cells and that triggered TCR remain localized with the same pMHC.

5We probe agonist pMHC:TCR complex dynamics in hybrid live cell—supported membrane junctions (Figure 1A). The supported membrane is functionalized with MHC (IEk) and intercellular adhesion molecule-1 fusion with a blue fluorescent protein (ICAM1-TagBFP), both linked to the membrane via C-terminal poly-His tag binding to Ni-chelating lipids. The MHC is loaded with peptide (moth cytochrome c [MCC] agonist or null), which is covalently coupled in a 1:1 stoichiometry (verified by HPLC) to the photostable fluorophores Atto647N or Atto488 using maleimide-thiol chemistry. Upon contact between the T cell and the supported membrane, Leukocyte function-associated antigen 1 (LFA1)-ICAM1 binding leads to rapid cell spreading and formation of an essentially planar interface between the T cell and supported membrane, within which pMHC:TCR interactions occur.

6At fast exposure times (17.5 ms) and high excitation powers (0.2 W/cm2), all pMHC molecules are readily resolved (Figure 1B, left panel). The pMHC move as individual molecules, as identified by single-step photobleaching, and can be continuously tracked for up to hundreds of frames (Figure 1C). In regions without a cell, pMHC exclusively exhibit random diffusive motion. The step-size distribution from these trajectories corresponds to a single lateral diffusion coefficient of 0.44 (SEM = 0.002) µm2/s, which is typical for supported membranes. Within the T cell junction, the step-size distribution becomes bimodal (Figure 1D). In addition to a fast component from freely diffusing pMHC, a distinct slow-moving component also appears.

7At long exposure times (500 ms) and low excitation powers (0.02 W/cm2), the fast moving pMHC fraction in Figure 1D is averaged over several pixels to form a relatively homogenous background. The slow moving molecules remain highly localized and can be unambiguously tracked for longer than a minute, using 1–10 s time-lapses (Figure 1B, right panel; Video 1). The slow moving pMHC molecules colocalize with TCR (Figure 2) and move in linear trajectories toward the geometric center of the live cell-supported membrane junction; these are the pMHC:TCR complexes. When MHC is loaded with a mixture of agonist and null peptides, with different fluorescent labels, only the agonist peptides are observed in the slow-moving complexes (Figure 3). The result is identical when the fluorophores are reversed, excluding the possibility that fluorophore effects could be responsible for binding.

8The agonist pMHC densities used in these experiments range from 0.2 to 100 molecules/µm2. The lowest densities are near thresholds for triggering Ca2+ flux and below levels where stable TCR microclusters are readily visible (Figure 2), whereas the higher densities are well above the densities at which microclusters are observed. Nonetheless, the observed single molecule pMHC motion at all densities is reminiscent of the well-characterized actomyosin-driven TCR microcluster radial transport in cells that are activated.

9Two-color single molecule tracking is used to quantitatively monitor membrane recruitment of cytosolic ZAP70-EGFP (incorporated by retroviral transfection) to the locations of the pMHC:TCR complexes. Using a dual-view system in which chromatic aberrations have been mapped (Figure 4—figure supplement 1), spatial colocalization between the two channels to less than 105 nm is achieved. Immediately after cell landing, ZAP70 localizes to and moves together with the pMHC:TCR complexes (Figure 4A; Videos 2 and 3). For each frame in a tracking sequence, fluorescence intensity in the ZAP70-EGFP channel is integrated over a 315 nm square region centered on each pMHC:TCR complex (Figure 4B). The resulting intensity traces reveal discrete changes in average intensity, which we attribute to the binding of one ZAP70-EGFP to the phosphorylated ITAM domains on the cytoplasmic side of TCR engaged with pMHC. Representative traces of colocalized ZAP70-EGFP intensity along with the corresponding intensity trace from the pMHC are illustrated in Figure 4C. Stochastic transitions are identified using a change-point algorithm and results from this analysis are superimposed on the raw intensity traces. Observed molecular binding dwell times of individual ZAP70-EGFP, as resolved by the stochastic transitions, range from 12 to 107 s. The majority of single molecule ZAP70-EGFP traces exhibit intensity fluctuations consistent with background (Figure 4—figure supplement 2A), which would not be expected if cytosolic ZAP70-EGFP exchanged during exposure time. These dwell times are slightly longer than estimates of ∼10 s obtained from bulk fluorescence recovery after photobleaching (FRAP) experiments. However, those experiments also identified a slower-exchanging fraction of ZAP70 that was not included in the average.

10ZAP70-EGFP features brighter than single molecules are also observed and we calibrate their stoichiometries using single molecule ZAP70-EGFP intensities from the same cell. For example, the average ZAP70-EGFP feature intensity per frame (136.0 counts ± 0.04 SEM, integrated over a 315 nm square area for each feature) for the cell shown in Figure 4D corresponds to 2.9 ± 0.04 SEM ZAP70-EGFP per feature, given that the single molecule intensity is 47 ± 2 counts (SEM; n = 6) in that cell. Each feature therefore contains on average ∼6 ZAP70 molecules, since ZAP70-EGFP was expressed in a roughly 1:1 ratio with endogenous ZAP70 (selected by FACS and confirmed by western blotting) in these experiments. Each TCR complex has 10 ITAM domains that, when phosphorylated, can bind one ZAP70 each. Thus observation of ∼6 ZAP70 per agonist pMHC suggests only a single TCR is triggered.

11Brighter ZAP70-EGFP features tend to be located towards the geometric center of the cell at later time points (>5–10 min after T cell landing). These can be tracked for tens to hundreds of seconds, indicating that recruited ZAP70-EGFP remain stably associated with the pMHC:TCR complex while traveling along the same linear trajectories (Figure 4A; Videos 2 and 3). The observation of a range of ZAP70-EGFP stoichiometries (from 1 to ∼10 ZAP70-EGFP per pMHC:TCR complex) implies that some time-dependent accumulation of ZAP70 is likely to occur, although we have not definitively observed ZAP70-EGFP accumulation over time within individual intensity traces. Taken together, these observations demonstrate that engagement of TCR with an individual agonist pMHC molecule leads to stable association with the actin cytoskeleton, one-to-one TCR triggering (ITAM phosphorylation), and subsequent ZAP70 recruitment. Moreover, since every pMHC:TCR:ZAP70 complex is individually resolved in these experiments, we demonstrate that a single pMHC:TCR complex can lead to TCR triggering without molecular-scale association with other MHC molecules.

12Since the slow-moving pMHC can be clearly resolved from the fast moving component, the lifetime of molecules in this bound state is directly observable. The minimum detectable lifetime is limited by the fastest frame rate (17.5 ms per frame) and the maximum measureable lifetime is limited by photobleaching. For these single molecule tracking experiments, the temporal dynamic range spans from ∼50 ms to ∼5 min. Unbinding and photobleaching are indistinguishable in fluorescence methods such as this. For molecular binding, characterized by a constant kinetic off-rate, the distribution of observed dwell times,, is described bywhere is the photobleaching rate (kb), is the unbinding rate (koff), and is the observed mean dwell time in this experiment. The observed dwell time distributions are roughly exponential, as is expected for molecular binding. Thus by measuring both kbl and it is possible to determine as long as. We determine to be 53.8 ± 12.2 s for AND and 5.2 ± 0.2 s for 5c.c7 TCRs for Atto488-labeled peptide agonist with of 300 and 30 s respectively (Figure 5A,B). While fluorescent labels can affect binding kinetics, we measure similar values of with both Atto647N and Atto488 labeled peptides (see, e.g., Figures 1C, 3, and 4A,C). is also relatively unchanged at high agonist pMHC density (100 molecules/µm2), which is far above minimal levels required for T cell activation and observation of stable TCR microclusters (Figure 5C). We observe that cytoskeleton disruption by the actin-binding molecule, Latrunculin A, moderately increases with the AND TCR and had no significant effect on 5c.c7 kinetics (Figure 5C). Similarly, the dwell time distribution was only modestly affected by anti-CD4 (data not shown); however, the total number of TCR:pMHC complexes per cell was smaller in the anti-CD4 experiments, suggesting that the antibody interfered with pMHC:TCR binding.

13Tracking observations reveal the time intervals over which individual agonist pMHC molecules remain physically trapped within the immediate vicinity of the same TCR. Thus, although our measured dwell times in live cells are in general agreement with bulk solution measurements of pMHC:TCR kinetic off-rates for both TCRs (Figure 5C), this may not result from the same reasons in each case. Unbinding of pMHC from TCR followed by rapid rebinding to the same TCR or another TCR within the same signaling cluster could conceivably lead to entrapment of pMHC for timescales longer than the lifetime of the molecular interaction. This has been hypothesized as a potential mode by which a small number of agonist pMHC could trigger a larger number of TCR. Furthermore, recently reported single molecule measurements of pMHC:TCR binding kinetics in live cells, by force probe and by FRET, have suggested accelerated kinetic-off rates. We investigate this further below.

14We quantitatively assess the possibility of serial rebinding of agonist pMHC to multiple TCR within a TCR cluster using a stochastic reaction-diffusion simulation over a large range of and TCR cluster size. The total time to escape for an individual molecule, which is the parameter directly measured in pMHC tracking experiments, is given by:

15In this representation, and are the individual dwell times in the bound and unbound configurations, n is the number of rebinding events, and is the duration of the final unbound period prior to ultimate escape. For the stochastic simulation, and are treated as random variables with exponential distributions defined by the in situ measured values of koff and kon for pMHC:TCR binding, respectively. If the pMHC diffuses out of the TCR cluster prior to rebinding, it has escaped. Otherwise, the pMHC rebinds and the cycle repeats. Using the fastest kon (0.17 µm2s−1molecule−1) observed in similar hybrid live cell-SLB systems and the measured diffusion coefficient of pMHC in our supported membranes, we find that for TCR clusters of the sizes observed experimentally (≤100 TCR molecules) (Figure 6). Only for unrealistically large TCR clusters (∼1000 TCR molecules) could rebinding within the same cluster lead to appreciable entrapment (Figure 6—figure supplement 1).

16These simulations indicate that the observed values of are unlikely to be the result of rapid serial rebinding of one pMHC with many TCR within a TCR cluster. We note that although TCR clusters are not readily visible at the low antigen densities in these experiments, low level TCR clustering has been reported in the resting state by other methods. Even with a very fast kon, if pMHC completely disengages from TCR for long enough to diffuse to an adjacent TCR, then the probability of complete escape from the TCR cluster is high. Only in the extreme limit, where kon is so fast that pMHC unbinding is predominantly followed by rebinding to the same TCR, is the escape time appreciably longer than the individual molecular dwell times. The distinction between rapidly rebinding the same TCR and a single engagement is largely semantic. However, it may reveal something about the mechanical stability of pMHC:TCR interactions, and could account for the apparently accelerated koff observed in other types of experiments.

17All evidence reported here suggests that individual agonist pMHC remain bound to the same TCR for at least several seconds for the 5c.c7 TCR and for approximately one minute for the AND TCR in live cells. Subsequent recruitment of ZAP70 indicates TCR are triggered and movement of the complexes along linear trajectories confirms stable association with the actin cytoskeleton. All of this occurs as a result of a lone agonist pMHC binding TCR, without involvement of other MHC. The measured average pMHC:TCR:ZAP70 stoichiometry indicates TCR triggering is most likely 1:1 with agonist pMHC. Supernumerary triggering of multiple TCR by a single pMHC is not observed on the timescales of minutes investigated in these experiments. The original serial triggering model drew its conclusions from the extent of TCR down regulation measured 5 hr after exposure of T cells to antigen-pulsed APCs. Additionally, the lack of molecular-scale cooperativity in TCR triggering by agonist pMHC indicates that observed cooperativity at the level of cellular calcium response, at similar ligand densities and timescales, is most likely due to intracellular feedback mechanisms.

18The timescales of the pMHC:TCR interactions we observe in live cells are consistent with SPR measurements of koff for the 5c.c7 TCR and 226 TCR, which is nearly identical to AND (Figure 5C and Figure 7). They are also consistent with reports of a ∼2 s kinetic threshold for thymic selection determined in vivo. Stochastic reaction-diffusion analysis of the measured kinetic and mobility parameters indicates that rapid serial rebinding of agonist pMHC to multiple TCRs in a signaling cluster is unlikely to be a universal mechanism for ligand discrimination and rapid signal amplification in T cells.

19The intercellular geometry as well as active processes within the T cell have long been suspected to influence pMHC:TCR interactions. Direct in situ measurements of individual pMHC:TCR binding kinetics, such as we report here, are extremely limited but informative comparisons can be made. Notably, a recent intramolecular FRET study of the 5c.c7 TCR binding MCC pMHC reports short (∼150 ms) in situ 2D dwell times, nearly 35 times faster than the = 5.2 ± 0.2 s we measured by tracking. This same study measures 25 times longer under conditions of cytoskeleton disruption, essentially in agreement with tracking observations. This result has been interpreted to mean that the actin cytoskeleton actively destabilizes agonist pMHC:TCR complexes. In contrast, we observe very small effects of actin disruption on agonist pMHC dwell times for AND and essentially no effect with 5c.c7 TCR (Figure 5C).

20It is conceivable that the agonist pMHC:TCR complex does not remain bound in the same structural configuration for the duration of engagement. If mechanical coupling to actin significantly reduces the apparent in a single molecule FRET measurement, but not in a single molecule tracking experiment, this raises the possibility that mechanical forces can induce conformational alterations in agonist pMHC:TCR without complete disengagement of the complex. Recent structural studies of pMHC:TCR indicate the possibility of such flexibility. While putative conformational changes would not affect single-molecule tracking measurements, they could produce a FRET signature. Under such a scenario, apparently fast observed by FRET imaging may not correspond to actual molecular unbinding and escape of agonist pMHC from TCR.

21In the aggregate, the data reported here indicate that spatially discrete pMHC:TCR:ZAP70 complexes form according to molecular mass action laws with relatively predictable chemical kinetics and stoichiometry in living cells. The observed pMHC:TCR molecular binding kinetics mirror solution measurements and we observe no evidence for molecular scale cooperativity in the triggering of TCR by agonist pMHC (at low agonist density). Thus any amplification or other form of signal processing must occur downstream of TCR triggering.

22A plasmid containing enhanced green fluorescent protein fused to CD3 zeta-chain-associated protein of 70 kDa (Zap70-EGFP) was a gift of Takashi Saito, RIKEN Research Center for Allergy and Immunology, Yokohama, Japan. The Zap70-EGFP gene was amplified by PCR and subcloned into a murine stem cell virus parent vector (pMSCV).

23Bi-hexahistidine-tagged major histocompatibility complex (MHC) class II I-Ek protein was produced and purified as previously described. A decahistidine-tagged ICAM1-TagBFP fusion protein was generated by PCR amplifying the TagBFP sequence (Evrogen Inc., Moscow, Russia) and subcloning it into a pN1-ICAM1 vector. The entire Icam1-TagBFP gene was then further subcloned into the pFastBac1 vector (Invitrogen Inc., Carlsbad, CA), which was used to generate baculovirus for infection of High Five cells (Invitrogen Inc.). The ICAM1-TagBFP was subsequently purified on a Ni-NTA-agarose affinity column, eluted with an imidazole gradient, dialyzed, and stored in Tris buffer containing 10% glycerol. AND CD4+ T cells and 5 c.c7 CD4+ T cells were harvested and cultured essentially as previously described.

24T cells were transduced with Zap70-EGFP and sorted using fluorescence-activated cell sorting (FACS) according to viability and EGFP expression. The population of transduced cells that was used expressed EGFP at no more than 50% of the highest EGFP level in the overall EGFP-positive population.

25Using the basic sequence of moth cytochrome c (amino acids 88–103) and previously described variants, the following peptides were synthesized by David King at the HHMI Mass Spectrometry Laboratory at UC Berkeley and/or commercially (Elim Biopharmaceuticals, Hayward, CA): MCC (ANERADLIAYLKQATK), MCC(C) (ANERADLIAYLKQATKGGSC), MCC-null(C) (ANERAELIAYLTQAAKGGSC). For fluorophore labeling, cysteine-containing peptides were dissolved in a small amount of phosphate buffer and mixed in a 1:2 molar ratio with Atto 647N resuspended in a small amount of 1-propanol or lyophilized Atto 488 (Atto-Tec GmbH, Siegen, Germany) and labeled using maleimide-thiol chemistry. The peptides were then incubated at room temperature for at least 1 hr and purified on a C18 reverse phase column (Grace–Vydac, Deerfield, IL) and H2O:acetonitrile gradient using ÄKTA explorer 100 FPLC system (Amersham Pharmacia Biotech, Piscataway, NJ). Peptide identity was confirmed after purification using mass spectrometry.

26TIRF experiments were performed on an inverted microscope (Nikon Eclipse Ti; Technical Instruments, Burlingame, CA) using a custom-built laser launch with 488 nm (Sapphire HP; Coherent Inc., Santa Clara, CA) and 640 nm (Cube; Coherent Inc.) diode lasers, as described previously. Laser powers measured at the sample were 0.8 mW (640 nm) and 0.5 mW (488 nm) for 500 ms exposures and 4.4 mW (640 nm) for 17.5 ms exposures. A dichroic beamsplitter (z488/647rpc; Chroma Technology Corp., Bellows Falls, VT) reflected the laser light through the objective lens (Nikon 1.49 NA TIRF; Technical Instruments, Burlingame, CA) and fluorescence images were recorded using an EM-CCD (iXon 597DU; Andor Inc., South Windsor, CT) after passing through a laser-blocking filter (Z488/647 M; Chroma Technology Corp., Bellows Falls, VT). Bandpass filters (FF03 525/50; Semrock Inc., Rochester, NY and ET 700/75, Chroma Technology Corp., Bellows Falls, VT) were placed in a DualView 2 Simultaneous Imaging System (Photometrics, Tuscon, AZ). Colors were registered before every two-color experiment by imaging 100 nm Tetraspec beads (Invitrogen Inc.) deposited on a coverslip patterned with a Cr grid with ∼80 nm width and 3–4 μm pitch Cr lines, since the Tetraspec beads preferentially bind the regular Cr pattern. Exposure times and time-lapse periods for most experiments were set using image collection software (MetaMorph 7.5; Molecular Devices Inc., Downingtown, PA), which drives an external shutter (Uniblitz LS6; Vincent Associates, Rochester, NY). Exposure time and Fast Kinetics Mode for short (17.5 ms) integration time experiments were set using Andor Solis (Andor Inc., South Windsor, CT). Exposure times were measured directly from the Fire output of the EM-CCD using an oscilloscope (TDS 210; Tektronix, Inc., Beaverton, OR).

27Single unilamellar vesicles (SUVs) were formed by tip sonication of a solution composed of 98 mol % 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and 2 mol % 1,2-dioleoyl-sn-glycero-3-[(N-(5-amino-1-carboxypentyl) iminodiacetic acid) succinyl] (nickel salt) (Ni2+-NTA-DOGS) (Avanti Polar Lipids, Alabaster, AL) in Mill-Q water (EMD Millipore, Billerica, MA). Tip sonication was preferred to vesicle extrusion due to the introduction of significant levels of fluorescent impurities into the SUVs during extrusion. Prior to experiments, #2 40 mm diameter round coverslips were ultrasonicated for 30 min in 50:50 isopropyl alcohol:water, rinsed thoroughly in Milli-Q water (EMD Millipore, Billerica, MA), etched for 5 min in piranha solution (3:1 sulfuric acid:hydrogen peroxide), and again rinsed thoroughly in Milli-Q water. The coverslips were used in the assembly of FCS2 Closed Chamber Systems (flow cells; Bioptechs, Butler, PA), which were pre-filled with Tris-buffered saline (TBS; 19.98 mM Tris, 136 mM NaCl, pH 7.4; Mediatech Inc., Herndon, VA). SUVs were then flowed into the chambers, and bilayers were allowed to form for at least 30 min. The bilayers were rinsed once with TBS, incubated for 5 min with 100 mM NiCl2 in TBS, rinsed with TBS, and then rinsed with a T cell imaging buffer composed of 1 mM CaCl2, 2 mM MgCl2, 20 mM HEPES, 137 mM NaCl, 5 mM KCl, 0.7 mM Na2HPO4, 6 mM d-glucose, and 1% wt/vol bovine serum albumin. 48 hr prior to experiments, MHC was loaded with peptide at 37°C in a buffer composed of 1% wt/vol bovine serum albumin in phosphate-buffered saline and brought to pH 4.5 with citric acid. Unbound peptide was separated from peptide loaded MHC (pMHC) using 10k spin concentrators (Amicon Ultra, Cork, Ireland) and then pMHC was diluted in imaging buffer. ICAM1-TagBFP and pMHC were further diluted with imaging buffer, introduced into the flow cells, and incubated for 35 min followed by a rinse with imaging buffer. T cells resuspended in imaging buffer and added to the flow cells 35 min after the final rinse and imaged immediately for 30–60 min. To visualize TCR, T cells were incubated in a solution of 1 μl Alexa 647 (Invitrogen Inc.)-labeled H57 anti-TCR Fab and 100 μl imaging buffer for 20 min at 4°C prior to the regular imaging buffer resuspension. All other incubations during this protocol were performed at room temperature, and imaging experiments were performed at 37°C.

28Single molecule diffraction-limited spots were detected in raw.tif image stacks of agonist pMHC labeled with MCC-Atto488 and MCC-647N molecules by filtering for both size and intensity and linked into tracks using published particle detection and tracking algorithms adapted for MATLAB (The Mathworks; Natick, MA) by Daniel Blair and Eric Dufresne (http://physics.georgetown.edu/matlab/; accessed 16 August 2012). Size and intensity thresholds were first determined by eye using a test data set and then applied uniformly to all data collected with the same exposure time and incident laser intensities. Single molecules were identified by step photobleaching detected in an automated way using a Bayesian change point detection algorithm.

29The brightness of ZAP70-EGFP features varies from a single molecule to several molecules, and different brightness features are detected using slightly different methods, despite the fact that the features are physically similar. Bright ZAP70-EGFP features (as shown in Figure 4A,D) were detected using the same algorithm as is used for single molecule pMHC. The lower signal-to-noise single molecule ZAP70-EGFP intensity traces like those in Figure 4C were obtained by summing the intensity of the ZAP70-EGFP channel using the agonist pMHC (labeled with Atto647N) molecule position as a mask, as is explained in the main text.

30The lifetime of the bright ZAP70-EGFP speckles is difficult to accurately assess due to the fluctuating background and varying speckle intensity (which biases measurement towards brighter, longer-lived fluorescent features), but speckle lifetimes appear to be longer than the single molecule ZAP70-EGFP lifetimes. Single molecule ZAP70-EGFP molecules are uncorrected for photobleaching of both ZAP70-EGFP and agonist pMHC and therefore the range of binding times reported (12–107 s) only serves as a lower bound for the molecular ZAP70 dwell time.

31The agonist pMHC step size distribution at 17.5 ms resolution in Figure 1D is populated using similar particle detection and tracking methods to the 500 ms resolution analysis., Agonist pMHC:TCR binding kinetics cannot be uniquely inferred from the step size distribution, since the step size distribution is a time-independent analysis. For instance, the step size distribution measured over a certain time period with 2kon and 2koff would appear identical to a scenario with kon and koff.

32Lifetime distributions are roughly exponential and of the form, where τobs is the observed dwell time in our experiments. The individual kinetic transitions were derived assuming the following model:where pMHCfree is the fast-mobility state, pMHC:TCR is the slow-mobility state (or the TCR stably bound state), pMHCbleached is the bleached slow-mobility state, koff and kon are the rates of transitions between the bound and the free pMHC, and kbl is the rate of transition from bound pMHC:TCR to photobleached pMHC. We assume that transititions between states follow a Markov memory-less process and derive a probability density function,, for the single molecule dwell time distribution:, where is the observed mean dwell time in our experiments. Agonist pMHC labeled with Atto488 and Atto647N SLB bleaching curves were background subtracted and then fit to an exponential decay function of the form. Fitting was done using MATLAB.

33Simulations were performed using MATLAB. Our simulation models a TCR cluster as a square lattice upon which agonist pMHC molecules bind discrete TCR lattice sites for duration, where is treated as a random variable drawn from an exponential distribution with mean equal to. is varied over several orders of magnitude and is chosen to match measured values from the literature. pMHC are initially placed at a randomly lattice position drawn from a uniform distribution. After each time period (determined by ), the agonist pMHC molecule steps to a new lattice site or stays at the same lattice site (the lattice spacing is set to 10 nm to roughly follow the size of the TCR complex) until the agonist pMHC is no longer on the TCR cluster, such that, where n indicates the number of steps an individual agonist pMHC molecule takes before exiting the TCR cluster, is the time period between unbinding and binding events, and is the time between the last unbinding event and the ultimate exit from the TCR cluster. Step size is treated as a combination of two independent random variables, drawn from Gaussian distributions with mean 0 and standard deviation. The step size is then a random variable and the angle of displacement is drawn from a uniform distribution. The interval between binding events,, is treated as a random variable drawn from an exponential distribution with mean kon where the density of TCR,, is taken to be 10,000 molecules/µm2 (as in the central supramolecular activation cluster). In this way, where k is the number of iterations (100 in the case of Figure 6 and Figure 6—figure supplement 1), is calculated for every combination of, TCR cluster size, and kon. Note that since,, where is equivalent to the TCR cluster size. This relationship between and TCR cluster size can be seen in Figure 6—figure supplement 1. It is possible that agonist pMHC binding interactions with CD4 could slow the mobility of an individual agonist pMHC within a TCR cluster relative to DSLB when the agonist pMHC are unbound from TCR. This could hypothetically lead to entrapment and long single molecule tracks (like those reported here) in the absence of direct, sustained agonist pMHC-TCR interactions. While such a mechanism is conceivable, there is no direct evidence for such a tethering mechanism in the literature.