Peptide exchange on MHC-I by TAPBPR is driven by a negative allostery release cycle.

Chaperones TAPBPR and tapasin associate with class I major histocompatibility complexes (MHC-I) to promote optimization (editing) of peptide cargo. Here, we use solution NMR to investigate the mechanism of peptide exchange. We identify TAPBPR-induced conformational changes on conserved MHC-I molecular surfaces, consistent with our independently determined X-ray structure of the complex. Dynamics present in the empty MHC-I are stabilized by TAPBPR and become progressively dampened with increasing peptide occupancy. Incoming peptides are recognized according to the global stability of the final pMHC-I product and anneal in a native-like conformation to be edited by TAPBPR. Our results demonstrate an inverse relationship between MHC-I peptide occupancy and TAPBPR binding affinity, wherein the lifetime and structural features of transiently bound peptides control the regulation of a conformational switch located near the TAPBPR binding site, which triggers TAPBPR release. These results suggest a similar mechanism for the function of tapasin in the peptide-loading complex

Molecular determinants of chaperone interactions on MHC-I for folding and antigen repertoire selection.

The interplay between a highly polymorphic set of MHC-I alleles and molecular chaperones shapes the repertoire of peptide antigens displayed on the cell surface for T cell surveillance. Here, we demonstrate that the molecular chaperone TAP-binding protein related (TAPBPR) associates with a broad range of partially folded MHC-I species inside the cell. Bimolecular fluorescence complementation and deep mutational scanning reveal that TAPBPR recognition is polarized toward the α2 domain of the peptide-binding groove, and depends on the formation of a conserved MHC-I disulfide epitope in the α2 domain. Conversely, thermodynamic measurements of TAPBPR binding for a representative set of properly conformed, peptide-loaded molecules suggest a narrower MHC-I specificity range. Using solution NMR, we find that the extent of dynamics at "hotspot" surfaces confers TAPBPR recognition of a sparsely populated MHC-I state attained through a global conformational change. Consistently, restriction of MHC-I groove plasticity through the introduction of a disulfide bond between the α1/α2 helices abrogates TAPBPR binding, both in solution and on a cellular membrane, while intracellular binding is tolerant of many destabilizing MHC-I substitutions. Our data support parallel TAPBPR functions of 1) chaperoning unstable MHC-I molecules with broad allele-specificity at early stages of their folding process, and 2) editing the peptide cargo of properly conformed MHC-I molecules en route to the surface, which demonstrates a narrower specificity. Our results suggest that TAPBPR exploits localized structural adaptations, both near and distant to the peptide-binding groove, to selectively recognize discrete conformational states sampled by MHC-I alleles, toward editing the repertoire of displayed antigens

T-Cell activation: a queuing theory analysis at low agonist density

We analyze a simple linear triggering model of the T-cell receptor (TCR) within the framework of queuing theory, in which TCRs enter the queue upon full activation and exit by downregulation. We fit our model to four experimentally characterized threshold activation criteria and analyze their specificity and sensitivity: the initial calcium spike, cytotoxicity, immunological synapse formation, and cytokine secretion. Specificity characteristics improve as the time window for detection increases, saturating for time periods on the timescale of downregulation; thus, the calcium spike (30 s) has low specificity but a sensitivity to single-peptide MHC ligands, while the cytokine threshold (1 h) can distinguish ligands with a 30% variation in the complex lifetime. However, a robustness analysis shows that these properties are degraded when the queue parameters are subject to variation—for example, under stochasticity in the ligand number in the cell-cell interface and population variation in the cellular threshold. A time integration of the queue over a period of hours is shown to be able to control parameter noise efficiently for realistic parameter values when integrated over sufficiently long time periods (hours), the discrimination characteristics being determined by the TCR signal cascade kinetics (a kinetic proofreading scheme). Therefore, through a combination of thresholds and signal integration, a T cell can be responsive to low ligand density and specific to agonist quality. We suggest that multiple threshold mechanisms are employed to establish the conditions for efficient signal integration, i.e., coordinate the formation of a stable contact interface

The case for absolute ligand discrimination : modeling information processing and decision by immune T cells

Some cells have to take decision based on the quality of surroundings ligands, almost irrespective of their quantity, a problem we name "absolute discrimination". An example of absolute discrimination is recognition of not-self by immune T Cells. We show how the problem of absolute discrimination can be solved by a process called "adaptive sorting". We review several implementations of adaptive sorting, as well as its generic properties such as antagonism. We show how kinetic proofreading with negative feedback implements an approximate version of adaptive sorting in the immune context. Finally, we revisit the decision problem at the cell population level, showing how phenotypic variability and feedbacks between population and single cells are crucial for proper decision

Cellular-level versus receptor-level response threshold hierarchies in T-Cell activation

Peptide-MHC (pMHC) ligand engagement by T-cell receptors (TCRs) elicits a variety of cellular responses, some of which require substantially more TCR-mediated stimulation than others. This threshold hierarchy could reside at the receptor level, where different response pathways branch off at different stages of the TCR/CD3 triggering cascade, or at the cellular level, where the cumulative TCR signal registered by the T-cell is compared to different threshold values. Alternatively, dual-level thresholds could exist. In this study, we show that the cellular hypothesis provides the most parsimonious explanation consistent with data obtained from an in-depth analysis of distinct functional responses elicited in a clonal T-cell system by a spectrum of biophysically defined altered peptide ligands across a range of concentrations. Further, we derive a mathematical model that describes how ligand density, affinity, and off-rate all affect signaling in distinct ways. However, under the kinetic regime prevailing in the experiments reported here, the TCR/pMHC class I (pMHCI) dissociation rate was found to be the main governing factor. The CD8 coreceptor modulated the TCR/pMHCI interaction and altered peptide ligand potency. Collectively, these findings elucidate the relationship between TCR/pMHCI kinetics and cellular function, thereby providing an integrated mechanistic understanding of T-cell response profiles

Theories and quantification of thymic selection

The peripheral T cell repertoire is sculpted from prototypic T cells in the thymus bearing randomly generated T cell receptors (TCR) and by a series of developmental and selection steps that remove cells that are unresponsive or overly reactive to self-peptide–MHC complexes. The challenge of understanding how the kinetics of T cell development and the statistics of the selection processes combine to provide a diverse but self-tolerant T cell repertoire has invited quantitative modeling approaches, which are reviewed here

Regulation of T cell expansion by antigen presentation dynamics

An essential feature of the adaptive immune system is the proliferation of antigen-specific lymphocytes during an immune reaction to form a large pool of effector cells. This proliferation must be regulated to ensure an effective response to infection while avoiding immunopathology. Recent experiments in mice have demonstrated that the expansion of a specific clone of T cells in response to cognate antigen obeys a striking inverse power law with respect to the initial number of T cells. Here, we show that such a relationship arises naturally from a model in which T cell expansion is limited by decaying levels of presented antigen. The same model also accounts for the observed dependence of T cell expansion on affinity for antigen and on the kinetics of antigen administration. Extending the model to address expansion of multiple T cell clones competing for antigen, we find that higher affinity clones can suppress the proliferation of lower affinity clones, thereby promoting the specificity of the response. Employing the model to derive optimal vaccination protocols, we find that exponentially increasing antigen doses can achieve a nearly optimized response. We thus conclude that the dynamics of presented antigen is a key regulator of both the size and specificity of the adaptive immune response

Computational modeling of cell mechanics and binding kinetics at T-cell interfaces

T cells orchestrate adaptive immunity, yet how they recognize and respond to small numbers of antigenic ligands remains an open question. T cells use surface receptors (TCRs) to engage membrane-presented ligands (pMHCs) on antigen-presenting cells (APCs). Recent experiments have illuminated the significance of mechanical forces, spatial organization, and dynamics of key proteins at cell-cell interfaces in immunology. For example, studies have shown T cells use actin-based microvillar protrusions to actively search APCs and stimulatory TCR-pMHC bonds exhibit catch-bond behavior, with an average bond lifetime that initially increases with increasing tensile force. It is unclear how mechanical forces at the cell-cell interface and force-dependent TCR-pMHC dissociation kinetics regulate antigen discrimination. Experimental observations raise the interesting question of whether T cells can exploit catch-bond behavior of stimulatory bonds as a physical mechanism in the search of rare antigenic ligands.In this dissertation, we employ computational methods to explore (i) the impact of TCR-pMHC bond formation on the spatial organization and shape of membranes at the cell-cell interface, (ii) the dynamics of TCR cluster formation, and (iii) the mechanical feedback between receptor-ligand binding and active force generation by scanning T-cell microvilli. We find the formation of individual TCR-pMHC bonds drives changes in the membrane organization and shape, leading to time-dependent forces on TCR-pMHC bonds. Using force-dependent lifetime data for TCRs bound to various ligands, we show that stimulatory catch bonds have a markedly enhanced average lifetime compared with non-stimulatory pMHCs. By varying the fraction and density of agonist pMHC on APCs, we demonstrate that stimulatory pMHC molecules play a central role in the formation of TCR clusters, and that TCR-pMHC clustering drives longer surface molecules away from regions of close apposition. Lastly, we find that a small number of catch bonds can initially immobilize T-cell microvilli, after which additional bonds accumulate and increase the cumulative receptor-engagement time. Thus, catch bonds can selectively slow and stabilize scanning microvilli, suggesting a physical mechanism that may contribute to antigen discrimination by T cells. Taken together, our results highlight the importance of force-dependent binding kinetics and cell mechanics for antigen discrimination at the T-cell-APC interface

Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection

Conventional and regulatory T cells develop in the thymus where they are exposed to samples of self-peptide MHC (pMHC) ligands. This probabilistic process selects for cells within a range of responsiveness that allows the detection of foreign antigen without excessive responses to self. Regulatory T cells are thought to lie at the higher end of the spectrum of acceptable self-reactivity and play a crucial role in the control of autoimmunity and tolerance to innocuous antigens. While many studies have elucidated key elements influencing lineage commitment, we still lack a full understanding of how thymocytes integrate signals obtained by sampling self-peptides to make fate decisions. To address this problem, we apply stochastic models of signal integration by T cells to data from a study quantifying the development of the two lineages using controllable levels of agonist peptide in the thymus. We find two models are able to explain the observations; one in which T cells continually re-assess fate decisions on the basis of multiple summed proximal signals from TCR-pMHC interactions; and another in which TCR sensitivity is modulated over time, such that contact with the same pMHC ligand may lead to divergent outcomes at different stages of development. Neither model requires that T and T are differentially susceptible to deletion or that the two lineages need qualitatively different signals for development, as have been proposed. We find additional support for the variable-sensitivity model, which is able to explain apparently paradoxical observations regarding the effect of partial and strong agonists on T and T development