Veronika I. Zarnitsyna

The kinetics of two-dimensional TCR and pMHC interactions determine T-cell responsiveness

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 for cross-junctional binding where the TCR and pMHC are anchored on two-dimensional (2D) membranes of the apposing cells. Despite their 2D nature, TCR–pMHC binding kinetics have only been analysed three-dimensionally (3D) with a varying degree of correlation with the T-cell responsiveness. Here we use two mechanical assays to show high 2D affinities between a TCR and its antigenic pMHC 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 slowest. 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 intrinsic TCR–pMHC binding to generate broad affinities and rapid kinetics that determine T-cell responsiveness.

Flow-enhanced adhesion regulated by a selectin interdomain hinge.

L-selectin requires a threshold shear to enable leukocytes to tether to and roll on vascular surfaces. Transport mechanisms govern flow-enhanced tethering, whereas force governs flow-enhanced rolling by prolonging the lifetimes of L-selectin–ligand complexes (catch bonds). Using selectin crystal structures, molecular dynamics simulations, site-directed mutagenesis, single-molecule force and kinetics experiments, Monte Carlo modeling, and flow chamber adhesion studies, we show that eliminating a hydrogen bond to increase the flexibility of an interdomain hinge in L-selectin reduced the shear threshold for adhesion via two mechanisms. One affects the on-rate by increasing tethering through greater rotational diffusion. The other affects the off-rate by strengthening rolling through augmented catch bonds with longer lifetimes at smaller forces. By forcing open the hinge angle, ligand may slide across its interface with L-selectin to promote rebinding, thereby providing a mechanism for catch bonds. Thus, allosteric changes remote from the ligand-binding interface regulate both bond formation and dissociation.

Mechanisms for Flow-Enhanced Cell Adhesion

Cell adhesion is mediated by specific receptor–ligand bonds. In several biological systems, increasing flow has been observed to enhance cell adhesion despite the increasing dislodging fluid shear forces. Flow-enhanced cell adhesion includes several aspects: flow augments the initial tethering of flowing cells to a stationary surface, slows the velocity and increases the regularity of rolling cells, and increases the number of rollingly adherent cells. Mechanisms for this intriguing phenomenon may include transport-dependent acceleration of bond formation and force-dependent deceleration of bond dissociation. The former includes three distinct transport modes: sliding of cell bottom on the surface, Brownian motion of the cell, and rotational diffusion of the interacting molecules. The latter involves a recently demonstrated counterintuitive behavior called catch bonds where force prolongs rather than shortens the lifetimes of receptor–ligand bonds. In this article, we summarize our recently published data that used dimensional analysis and mutational analysis to elucidate the above mechanisms for flow-enhanced leukocyte adhesion mediated by L-selectin-ligand interactions.

Measuring Diffusion and Binding Kinetics by Contact Area FRAP

The immunological synapse is a stable intercellular structure that specializes in substance and signal transfer from one immune cell to another. Its formation is regulated in part by the diffusion of adhesion and signaling molecules into, and their binding of countermolecules in the contact area. The stability of immunological synapses allows receptor-ligand interactions to approximate chemical equilibrium despite other dynamic aspects. We have developed a mathematical model that describes the coupled reaction-diffusion process in an established immunological synapse. In this study, we extend a previously described contact area fluorescence recovery after photobleaching (FRAP) experiment to test the validity of the model. The receptor binding activity and lateral mobility of fluorescently labeled, lipid-anchored ligands in the bilayer resulted in their accumulation, as revealed by a much higher fluorescence intensity inside the contact area than outside. After complete photobleaching of the synapse, fluorescence recovery requires ligands to dissociate and rebind, and to diffuse in and out of the contact area. Such a FRAP time course consequently provides information on reaction and diffusion, which can be extracted by fitting the model solution to the data. Surprisingly, reverse rates in the two-dimensional contact area were at least 100-fold slower than in three-dimensional solution. As previously reported in immunological synapses, a significant nonrecoverable fraction of fluorescence was observed with one of two systems studied, suggesting some ligands either dissociated or diffused much more slowly compared with other ligands in the same synapse. The combined theory and experiment thus provides a new method for in situ measurements of kinetic rates, diffusion coefficients, and nonrecoverable fractions of interacting molecules in immunological synapses and other stable cell-bilayer junctions.

Estimating the Diversity, Completeness, and Cross-Reactivity of the T Cell Repertoire

In order to recognize and combat a diverse array of pathogens the immune system has a large repertoire of T cells having unique T cell receptors (TCRs) with only a few clones specific for any given antigen. We discuss how the number of different possible TCRs encoded in the genome (the potential repertoire) and the number of different TCRs present in an individual (the realized repertoire) can be measured. One puzzle is that the potential repertoire greatly exceeds the realized diversity of naïve T cells within any individual. We show that the existing hypotheses fail to explain why the immune system has the potential to generate far more diversity than is used in an individual, and propose an alternative hypothesis of “evolutionary sloppiness.” Another immunological puzzle is why mice and humans have similar repertoires even though humans have over 1000-fold more T cells. We discuss how the idea of the “protecton,” the smallest unit of protection, might explain this discrepancy and estimate the size of “protecton” based on available precursor frequencies data. We then consider T cell cross-reactivity – the ability of a T cell clone to respond to more than one epitope. We extend existing calculations to estimate the extent of expected cross-reactivity between the responses to different pathogens. Our results are consistent with two observations: a low probability of observing cross-reactivity between the immune responses to two randomly chosen pathogens; and the ensemble of memory cells being sufficiently diverse to generate cross-reactive responses to new pathogens.

Memory in receptor–ligand-mediated cell adhesion

Single-molecule biomechanical measurements, such as the force to unfold a protein domain or the lifetime of a receptor–ligand bond, are inherently stochastic, thereby requiring a large number of data for statistical analysis. Sequentially repeated tests are generally used to obtain a data ensemble, implicitly assuming that the test sequence consists of independent and identically distributed (i.i.d.) random variables, i.e., a Bernoulli sequence. We tested this assumption by using data from the micropipette adhesion frequency assay that generates sequences of two random outcomes: adhesion and no adhesion. Analysis of distributions of consecutive adhesion events revealed violation of the i.i.d. assumption, depending on the receptor–ligand systems studied. These include Markov sequences with positive (T cell receptor interacting with antigen peptide bound to a major histocompatibility complex) or negative (homotypic interaction between C-cadherins) feedbacks, where adhesion probability in the next test was increased or decreased, respectively, by adhesion in the immediate past test. These molecular interactions mediate cell adhesion and cell signaling. The ability to “remember” the previous adhesion event may represent a mechanism by which the cell regulates adhesion and signaling.

Insights from in situ analysis of TCR-pMHC recognition: response of an interaction network.

Recognition of peptide presented by the major histocompatibility complex (pMHC) molecule by the T‐cell receptor (TCR) determines T‐cell selection, development, differentiation, fate, and function. Despite intensive studies on the structures, thermodynamic properties, kinetic rates, and affinities of TCR–pMHC interactions in the past two decades, questions regarding the functional outcome of these interactions, i.e. how binding of the αβ TCR heterodimer with distinct pMHCs triggers different intracellular signals via the adjacent CD3 components to produce different T‐cell responses, remain unclear. Most kinetic measurements have used surface plasmon resonance, a three‐dimensional (3D) technique in which fluid‐phase receptors and ligands are removed from their cellular environment. Recently, several two‐dimensional (2D) techniques have been developed to analyze molecular interactions on live T cells with pMHCs presented by surrogate antigen‐presenting cells or supported planar lipid bilayers. The insights from these in situ analyses have provided a sharp contrast of the 2D network biology approach to the 3D reductionist approach and prompted rethinking of our current views of T‐cell triggering. Based on these insights, we propose a mechanochemical coupled triggering hypothesis to explain why the in situ kinetic parameters differ so much from their 3D counterparts, yet correlate so much better with T‐cell functional responses.

Regulation of catch bonds by rate of force application

The current paradigm for receptor-ligand dissociation kinetics assumes off-rates as functions of instantaneous force without impact from its prior history. This a priori assumption is the foundation for predicting dissociation from a given initial state using kinetic equations. Here we have invalidated this assumption by demonstrating the impact of force history with single-bond kinetic experiments involving selectins and their ligands that mediate leukocyte tethering and rolling on vascular surfaces during inflammation. Dissociation of bonds between L-selectin and P-selectin glycoprotein ligand-1 (PSGL-1) loaded at a constant ramp rate to a constant hold force behaved as catch-slip bonds at low ramp rates that transformed to slip-only bonds at high ramp rates. Strikingly, bonds between L-selectin and 6-sulfo-sialyl Lewis X were impervious to ramp rate changes. This ligand-specific force history effect resembled the effect of a point mutation at the L-selectin surface (L-selectinA108H) predicted to contact the former but not the latter ligand, suggesting that the high ramp rate induced similar structural changes as the mutation. Although the A108H substitution in L-selectin eliminated the ramp rate responsiveness of its dissociation from PSGL-1, the inverse mutation H108A in P-selectin acquired the ramp rate responsiveness. Our data are well explained by the sliding-rebinding model for catch-slip bonds extended to incorporate the additional force history dependence, with Ala-108 playing a pivotal role in this structural mechanism. These results call for a paradigm shift in modeling the mechanical regulation of receptor-ligand bond dissociation, which includes conformational coupling between binding pocket and remote regions of the interacting molecules.

A coupled diffusion-kinetics model for analysis of contact-area FRAP experiment.

Kinetic rates and binding affinity of receptor-ligand interactions are important determinants of cell adhesion. Measurements of these parameters in fluid phase using soluble molecules (i.e., three-dimensionial parameters) do not necessarily correlate with their counterparts measured when both binding partners are respectively anchored to two apposing surfaces (i.e., two-dimensional (2D) parameters). Moreover, 2D affinities measured by different methods can differ by orders of magnitude. Here we describe a coupled diffusion-reaction model for the fluorescence recovery after photobleaching experiment previously used to demonstrate the dynamics of adhesive bonds in the contact area. Applying the mathematical model to the contact area fluorescence recovery after photobleaching experiment enables in situ measurements of 2D kinetic rates of the adhesion molecules and their retarded diffusion in a stable contact area. The mathematical properties of the model are characterized in this article and its experimental validation will be presented in the companion article.

T cell triggering: insights from 2D kinetics analysis of molecular interactions

Interaction of the T cell receptor (TCR) with pathogen-derived peptide presented by the major histocompatibility complex (pMHC) molecule is central to adaptive immunity as it initiates intracellular signaling to trigger T cell response to infection. Kinetic parameters of this interaction have been under intensive investigation for more than two decades using soluble pMHCs and/or TCRs with at least one of them in the solution (three-dimensional (3D) methods). Recently, several techniques have been developed to enable kinetic analysis on live T cells with pMHCs presented by surrogate antigen presenting cells (APCs) or supported planar lipid bilayers (two-dimensional (2D) methods). Comparison of 2D versus 3D parameters reveals drastic differences with broader ranges of 2D affinities and on-rates and orders of magnitude faster 2D off-rates for functionally distinct pMHCs. Here we review new 2D data and discuss how it may impact previously developed models of T cell discrimination between pMHCs of different potencies.