Cooperative enhancement of specificity in a lattice of T cell receptors

Tuning the potency and selectivity of ImmTAC molecules by affinity modulation

T-cell-engaging bispecifics have great clinical potential for the treatment of cancer and infectious diseases. The binding affinity and kinetics of a bispecific molecule for both target and T-cell CD3 have substantial effects on potency and specificity, but the rules governing these relationships are not fully understood. Using immune mobilizing monoclonal TCRs against cancer (ImmTAC) molecules as a model, we explored the impact of altering affinity for target and CD3 on the potency and specificity of the redirected T-cell response. This class of bispecifics binds specific target peptides presented by human leukocyte antigen on the cell surface via an affinity-enhanced T-cell receptor and can redirect T-cell activation with an anti-CD3 effector moiety. The data reveal that combining a strong affinity TCR with an intermediate affinity anti-CD3 results in optimal T-cell activation, while strong affinity of both targeting and effector domains significantly reduces maximum cytokine release. Moreover, by optimizing the affinity of both parts of the molecule, it is possible to improve the selectivity. These results could be effectively modelled based on kinetic proofreading with limited signalling. This model explained the experimental observation that strong binding at both ends of the molecules leads to reduced activity, through very stable target-bispecific-effector complexes leading to CD3 entering a non-signalling dark state. These findings have important implications for the design of anti-CD3-based bispecifics with optimal biophysical parameters for both activity and specificity.

COMPARISON OF A DUAL STRATEGY FOR T-CELL ACTIVATION UNDER INHIBITION OF THE CD4 RECEPTOR

We consider a stochastic model for T-cell activation proposed in Refs. [1] and [2] to compare the specificity and sensitivity of two different strategies for T-cell activation that utilize the history of phosphorylation of T-cell receptor (TCR). We compare these two strategies when the temporal signals/events that are essential for progressive T-cell activation are suppressed by blockade of CD4 receptor that may have caused by disease or therapeutic effects.3–6 We show that under these conditions, a threshold-strategy which is capable of maintaining a threshold (for total number of phosphorylated TCRs by time [Formula: see text]) for a further duration [Formula: see text] performs better in discriminating agonist peptides than a single-threshold strategy (reached by time [Formula: see text]) leading to T-cell activation using the Wentzell-Friedlin theory for large deviations for stochastic processes.7,8

A model of cell surface receptor aggregation

In this paper we construct and analyze a model of cell receptor aggregation. Experiments have shown that receptors in an aggregated state have greatly reduced mobility. We model the effects of this reduced mobility with a density dependent diffusion and study the impact of density dependent diffusion on aggregate formation in a one-dimensional domain. Critical values of receptor diffusivity and receptor activation are found and compared with numerical simulations. We find that the role of density dependant diffusion is quite limited in the formation of aggregate structures. In the case of receptor activation, the analytical results agree very well with the numerical calculations. Finally, we consider our model in higher dimensional domains. In this case our analysis is primarily numerical.

TCR/pMHC Interaction: Phenotypic Model for an Unsolved Enigma

TCR-pMHC interaction is the keystone of the adaptive immune response. This process exhibits an impressive capacity of speed, sensitivity, and discrimination that allows detecting foreign pMHCs at very low concentration among much more abundant self-pMHC ligands. However, and despite over three decades of intensive research, the mechanisms by which this remarkable discrimination and sensitivity is attained remain controversial. In kinetic proofreading mechanisms (KPR), an increase of specificity occurs by reducing the sensitivity. To overcome this difficulty, more elaborate models including feedback processes or induced rebinding have been incorporated into the KPR scheme. Here a new approach based on the assumption that the proofreading chain behaves differently for foreign- and self-pMHC complexes has been integrated into a phenotypic model in which the complexes responsible for T cell activation stabilize (for foreign peptides) or weaken (for foreign peptides), resulting in a dramatic increase in sensitivity and specificity. Stabilization and destabilization of complexes may be caused by conformational changes, rebinding, or any other process leading to variations in the dissociation rate constants of the complexes transmitting the activation. The numerical solution and the analytical expression for the steady-state response as a function of k_off(i) (i = 0, 1, …, N, where C₀, C₁, …, C_N are the complexes in the proofreading chain) are provided. The activation chain speeds up, and larger increases in sensitivity and discrimination are obtained if the rate of activation along the proofreading chain increases for foreign pMHCs and decreases for self-ligands. Experimental implications and comparison with current models are discussed.

The principle of conformational signaling

Specific conformations of signaling proteins can serve as “signals” in signal transduction by being recognized by receptors.

An induced rebinding model of antigen discrimination

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We propose that pMHC binding to TCR can increase (induce) pMHC rebinding.

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Published studies are consistent with an induced rebinding model.

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Induced rebinding improves the ability of T cells to discriminate antigens.

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Induced rebinding relates 3D to 2D TCR–pMHC binding parameters.

T cells have to detect rare high-affinity ‘foreign’ peptide MHC (pMHC) ligands among abundant low-affinity ‘self’-peptide MHC ligands. It remains unclear how this remarkable discrimination is achieved. Kinetic proofreading mechanisms can provide the required specificity but only at the expense of much reduced sensitivity. A number of recent observations suggest that pMHC engagement of T cell receptors (TCRs) induces changes such as clustering and/or conformational alterations that enhance subsequent rebinding. We show that inclusion of induced rebinding to the same pMHC in kinetic proofreading models enhances the sensitivity of TCR recognition while retaining specificity. Moreover, induced rebinding is able to reproduce the striking, and hitherto unexplained, 2D membrane-binding properties recently reported for the TCR.

Activated PLC-γ1 is catalytically induced at LAT but activated PLC-γ1 is localized at both LAT- and TCR-containing complexes

Phospholipase C-γ1 (PLC-γ1) is a key regulator of T cell receptor (TCR)-induced signaling. Activation of the TCR enhances PLC-γ1 enzymatic function, resulting in calcium influx and the activation of PKC family members and RasGRP. The current model is that phosphorylation of LAT tyrosine 132 facilitates the recruitment of PLC-γ1, leading to its activation and function at the LAT complex. In this study, we examined the phosphorylation kinetics of LAT and PLC-γ1 and the cellular localization of activated PLC-γ1. We observed that commencement of the phosphorylation of LAT tyrosine 132 and PLC-γ1 tyrosine 783 occurred simultaneously, supporting the current model. However, once begun, PLC-γ1 activation occurred more rapidly than LAT tyrosine 132. The association of LAT and PLC-γ1 was more transient than the interaction of LAT and Grb2 and a pool of activated PLC-γ1 translocated away from LAT to cellular structures containing the TCR. These studies demonstrate that LAT and PLC-γ1 form transient interactions that catalyze the activation of PLC-γ1, but that activated PLC-γ1 resides in both LAT and TCR clusters. Together, this work highlights that our current model is incomplete and the activation and function of PLC-γ1 in T cells is highly complex.

Systems biology in immunology: a computational modeling perspective

Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and to conduct simulations of immune function. We provide descriptions of the key data-gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and the reasons why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease.

A mathematical framework for analyzing T cell receptor scanning of peptides

T cells continuously search for antigenic peptides presented on major histocompatibility complexes expressed on nearly all nucleated cells. Because only a few antigenic peptides are presented in a sea of thousands of self-peptides, the T cells have a critical task in discriminating between self- and nonself-peptides. This search process for antigens must be performed with sufficient speed in order to induce a fast response against invading pathogens. This study presents a mathematical framework for analyzing the scanning process of peptides. The framework includes analytic expressions for calculating the sampling rate as well as continuous-systems- and stochastic-agent-based models. The results show that the scanning of self-peptides is a very fast process due to fast off-rates. The simulations also predict the existence of an optimal sampling rate for a certain range of on-rates based on the recently proposed confinement time model. Calculations reveal that most of the self-peptides located within a microdomain are scanned within just a few seconds, and that the T cell receptors have kinetics for self-peptides, facilitating fast scanning. The derived mathematical expressions within this study provide conceptual calculations for further investigations of how the T cell discriminates between self- and nonself-peptides.

Perspectives for computer modeling in the study of T cell activation

The T cell receptor (TCR) is responsible for discriminating between self- and foreign-derived peptides, translating minute differences in amino-acid sequence into large differences in response. Because of the great variability in the TCR and its ligands, activation of T cells by foreign peptides is a quantitative process, dependent on a mix of upstream signals and downstream integration. Accordingly, quantitative data and computational models have shed light on many important aspects of this process: molecular noise in ligand recognition, spatial dynamics in T cell-APC (antigen presenting cell) interactions, graded versus all-or-none decision making by the TCR apparatus, mechanisms of peptide antagonism and synergism, and the tunability and robustness of activation thresholds. Though diverse in their formalism, these studies together paint a picture of how modeling has shaped and will continue to shape understanding of T cell immunobiology.

A role for rebinding in rapid and reliable T cell responses to antigen

Experimental work has shown that T cells of the immune system rapidly and specifically respond to antigenic molecules presented on the surface of antigen-presenting-cells and are able to discriminate between potential stimuli based on the kinetic parameters of the T cell receptor-antigen bond. These antigenic molecules are presented among thousands of chemically similar endogenous peptides, raising the question of how T cells can reliably make a decision to respond to certain antigens but not others within minutes of encountering an antigen presenting cell. In this theoretical study, we investigate the role of localized rebinding between a T cell receptor and an antigen. We show that by allowing the signaling state of individual receptors to persist during brief unbinding events, T cells are able to discriminate antigens based on both their unbinding and rebinding rates. We demonstrate that T cell receptor coreceptors, but not receptor clustering, are important in promoting localized rebinding, and show that requiring rebinding for productive signaling reduces signals from a high concentration of endogenous pMHC. In developing our main results, we use a relatively simple model based on kinetic proofreading. However, we additionally show that all our results are recapitulated when we use a detailed T cell receptor signaling model. We discuss our results in the context of existing models and recent experimental work and propose new experiments to test our findings.

Elucidation of T cell signalling models

A potential mechanism that allows T cells to reliably discriminate pMHC ligands involves an interplay between kinetic proofreading, negative feedback and a destruction of this negative feedback. We analyse a detailed model of these mechanisms which involves the TCR, SHP1 and ERK. We discover that the behaviour of pSHP1 negative feedback is of primary importance, and particularly the influence of a kinetic proofreading base negative feedback state on pSHP1 dynamics. The CD8 co-receptor is shown to benefit from a kinetic proofreading locking mechanism and is able to overcome pSHP1 negative influences to sensitise a T cell.

Tailoring T-cell receptor signals by proximal negative feedback mechanisms

The T-cell receptor (TCR) signalling machinery is central in determining the response of a T cell (establishing immunity or tolerance) following exposure to antigen. This process is made difficult by the narrow margin of self and non-self discrimination, and by the complexity of the genetic programmes that are induced for each outcome. Recent studies have identified novel negative feedback mechanisms that are rapidly induced by TCR engagement and that have key roles in the regulation of signal triggering and propagation. In vitro and in vivo data suggest that they are important in determining ligand discrimination by the TCR and in regulating signal output in response to antigen.

Stochastic effects and bistability in T cell receptor signaling

The stochastic dynamics of T cell receptor (TCR) signaling are studied using a mathematical model intended to capture kinetic proofreading (sensitivity to ligand-receptor binding kinetics) and negative and positive feedback regulation mediated, respectively, by the phosphatase SHP1 and the MAP kinase ERK. The model incorporates protein-protein interactions involved in initiating TCR-mediated cellular responses and reproduces several experimental observations about the behavior of TCR signaling, including robust responses to as few as a handful of ligands (agonist peptide-MHC complexes on an antigen-presenting cell), distinct responses to ligands that bind TCR with different lifetimes, and antagonism. Analysis of the model indicates that TCR signaling dynamics are marked by significant stochastic fluctuations and bistability, which is caused by the competition between the positive and negative feedbacks. Stochastic fluctuations are such that single-cell trajectories differ qualitatively from the trajectory predicted in the deterministic approximation of the dynamics. Because of bistability, the average of single-cell trajectories differs markedly from the deterministic trajectory. Bistability combined with stochastic fluctuations allows for switch-like responses to signals, which may aid T cells in making committed cell-fate decisions.

A hybrid deterministic-stochastic algorithm for modeling cell signaling dynamics in spatially inhomogeneous environments and under the influence of external fields

Cell signaling dynamics mediate myriad processes in biology. It has become increasingly clear that inter- and intracellular signaling reactions often occur in a spatially inhomogeneous environment and that it is important to account for stochastic fluctuations of certain species involved in signaling reactions. The importance of these effects enhances the difficulty of gleaning mechanistic information from observations of a few experimental reporters and highlights the significance of synergistic experimental and computational studies. When both stochastic fluctuations and spatial inhomogeneity must be included in a model simultaneously, however, the resulting computational demands quickly become overwhelming. In many situations the failure of standard coarse-graining methods (i.e., ignoring spatial variation or stochastic fluctuations) when applied to all components of a complex system does not exclude the possibility of successfully applying such coarse-graining to some components of the system. Following this approach alleviates computational cost but requires "hybrid" algorithms where some variables are treated at a coarse-grained level while others are not. We present an efficient algorithm for simulation of stochastic, spatially inhomogeneous reaction-diffusion kinetics coupled to coarse-grained fields described by (stochastic or deterministic) partial differential equations (PDEs). The PDEs could represent mean-field descriptions of reactive species present in large copy numbers or evolution of hydrodynamic variables that influence signaling (e.g., membrane shape or cytoskeletal motion). We discuss the approximations made to derive our algorithm and test its efficacy by applying it to problems that include many features typical of realistic cell signaling processes.

Spatial and temporal dynamics of T cell receptor signaling with a photoactivatable agonist

The precise timing of signals downstream of the T cell receptor (TCR) is poorly understood. To address this problem, we prepared major histocompatibility complexes containing an antigenic peptide that is biologically inert until exposed to ultraviolet (UV) light. UV irradiation of these complexes in contact with cognate T cells enabled the high-resolution temporal analysis of signaling. Phosphorylation of the LAT adaptor molecule was observed in 4 s, and diacylglycerol production and calcium flux was observed in 6-7 s. TCR activation also induced cytoskeletal polarization within 2 min. Antibody blockade of CD4 reduced the intensity of LAT phosphorylation and the speed of calcium flux. Furthermore, strong desensitization of diacylglycerol production, but not LAT phosphorylation, occurred shortly after TCR activation, suggesting that different molecular events play distinct signal-processing roles. These results establish the speed and localization of early signaling steps, and have important implications regarding the overall structure of the network.

Molecular mechanisms involved in T cell receptor triggering

Despite intensive investigation we still do not understand how the T cell antigen receptor (TCR) tranduces signals across the plasma membrane, a process referred to as TCR triggering. Three basic mechanisms have been proposed, involving aggregation, conformational change, or segregation of the TCR upon binding pMHC ligand. Given the low density of pMHC ligand it remains doubtful that TCR aggregation initiates triggering, although it is likely to enhance subsequent signalling. Structural studies to date have not provided definitive evidence for or against a conformational change mechanism, but they have ruled out certain types of conformational change. Size-induced segregation of the bound TCR from inhibitory membrane tyrosine phosphatases seems to be required, but is probably not the only mechanism. Current evidence suggests that TCR triggering is initiated by a combination of segregation and conformational change, with subsequent aggregation contributing to amplification of the signal.

Quantitative theories of T-cell responsiveness

We review recent advances toward a comprehensive mathematical theory of T-cell immunity. A key insight is that the efficacy of the T-cell response is best analyzed in terms of T-cell receptor (TCR) avidity and the distribution of this avidity across the TCR repertoire (the 'avidity spectrum'). Modification of this avidity spectrum by a wide range of tuning and tolerance mechanisms allows the system to adapt cross-reactivity and specificity to the challenge at hand while avoiding inappropriate responses against non-pathogenic cells and tissues. Theoretical models relate molecular kinetic parameters and cellular properties to systemic level statistics such as avidity spectra. Such bridge equations are crucial for rational clinical manipulation of T cells at the molecular level.

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.

Ligand detection and discrimination by spatial relocalization: A kinase-phosphatase segregation model of TCR activation

We develop a model of tyrosine phosphorylation and activation of the T-cell receptor (TCR) by localization to regions of close membrane-membrane proximity (close contact) that physically exclude tyrosine phosphatases such as CD45. Phosphatase exclusion generates regions of low phosphatase and high kinase activity and thus our model provides a framework to examine the kinetic segregation model of TCR activation. We incorporate a sequence of activation steps modeling the construction of the signalosome with a final sequestered, or high-stability, signaling state. The residence time of unbound TCRs in tyrosine kinase-rich domains is shown to be too short for accumulation of activation steps, whereas binding to an agonist lengthens the localization time and leads to generation of fully active TCRs. Agonist detection depends only on this localization, and therefore kinetic segregation represents a viable ligand detection mechanism, or signal transduction mechanism across membranes, distinct from receptor oligomerization and conformational change. We examine the degree of discrimination of agonists from a background of null (self) peptides, and from weak agonists achievable by this mechanism.

Synthetic multivalent ligands as probes of signal transduction

Cell-surface receptors acquire information from the extracellular environment and coordinate intracellular responses. Many receptors do not operate as individual entities, but rather as part of dimeric or oligomeric complexes. Coupling the functions of multiple receptors may endow signaling pathways with the sensitivity and malleability required to govern cellular responses. Moreover, multireceptor signaling complexes may provide a means of spatially segregating otherwise degenerate signaling cascades. Understanding the mechanisms, extent, and consequences of receptor co-localization and interreceptor communication is critical; chemical synthesis can provide compounds to address the role of receptor assembly in signal transduction. Multivalent ligands can be generated that possess a variety of sizes, shapes, valencies, orientations, and densities of binding elements. This Review focuses on the use of synthetic multivalent ligands to characterize receptor function.

Agent-based modeling of the context dependency in T cell recognition

Antigen recognition by T cells is a key event in the adaptive immune response. T cells scan the surface of antigen-presenting cells (APCs) or target cells for specific peptides bound to MHC molecules. In the physiological setting, a typical APC presents tens of thousands of diverse endogenous self-derived peptides complexed to MHC (pMHC complexes). When 'foreign' peptides are presented, they constitute a small fraction of the total surface peptide repertoire. As T cells seem to be capable of discerning minute amounts of 'foreign' peptides among a complex background of self-peptides, endogenous peptides are generally assumed to play no role in recognition. However, recent results suggest that these background peptides may alter the sensitivity of T cells to foreign peptides. Current experimental limitations preclude analysis of peptide mixtures approaching physiological complexity, making it difficult to further address the role of complex background peptides. In this paper, we present a computational model to test how complex, varied peptide populations on an APC could potentially modulate a T cell's ability to detect the presence of small numbers of agonist peptides among a diverse population. We use the model to investigate the notion that under physiological conditions, T cell recognition of foreign peptides is context dependent, that is, T cells process signals gathered from all pMHC interactions, not just from a few agonist peptides while ignoring all others.

Modeling T cell antigen discrimination based on feedback control of digital ERK responses

T-lymphocyte activation displays a remarkable combination of speed, sensitivity, and discrimination in response to peptide-major histocompatibility complex (pMHC) ligand engagement of clonally distributed antigen receptors (T cell receptors or TCRs). Even a few foreign pMHCs on the surface of an antigen-presenting cell trigger effective signaling within seconds, whereas 1 x 10(5)-1 x 10(6) self-pMHC ligands that may differ from the foreign stimulus by only a single amino acid fail to elicit this response. No existing model accounts for this nearly absolute distinction between closely related TCR ligands while also preserving the other canonical features of T-cell responses. Here we document the unexpected highly amplified and digital nature of extracellular signal-regulated kinase (ERK) activation in T cells. Based on this observation and evidence that competing positive- and negative-feedback loops contribute to TCR ligand discrimination, we constructed a new mathematical model of proximal TCR-dependent signaling. The model made clear that competition between a digital positive feedback based on ERK activity and an analog negative feedback involving SH2 domain-containing tyrosine phosphatase (SHP-1) was critical for defining a sharp ligand-discrimination threshold while preserving a rapid and sensitive response. Several nontrivial predictions of this model, including the notion that this threshold is highly sensitive to small changes in SHP-1 expression levels during cellular differentiation, were confirmed by experiment. These results combining computation and experiment reveal that ligand discrimination by T cells is controlled by the dynamics of competing feedback loops that regulate a high-gain digital amplifier, which is itself modulated during differentiation by alterations in the intracellular concentrations of key enzymes. The organization of the signaling network that we model here may be a prototypic solution to the problem of achieving ligand selectivity, low noise, and high sensitivity in biological responses.

Understanding specificity and sensitivity of T-cell recognition

The response of T cells to antigen shows an amazing degree of both sensitivity and specificity, with a cell responding to 1-10 peptide-MHC complexes and being sensitive to single amino acid substitutions. Kinetic proofreading or feedback pathways achieve specificity at the level of the receptor, whereas serial engagement of receptors by ligand molecules enhances sensitivity. Crosstalk between receptors, integration of signals and/or tuning of responses is important at the level of the cell. Induction of anergic or regulatory cells by suboptimal stimuli prevents cell activation by multiple encounters with weak ligands. Thus, for optimal sensitivity and specificity, it is necessary to have mechanisms that operate at the level of the receptor, the cell and finally, the population of responding cells.

Frequency encoding of T-cell receptor engagement dynamics in calcium time series

The sustained increase of the cytosolic calcium concentration ([Ca2+]i) plays a central role in T-cell receptor (TCR)-mediated T-cell activation. Previous experiments using a [Ca2+]i clamp technique have demonstrated that specificity is encoded by the [Ca2+]i oscillation frequency since cytokine transcription factors are activated in a frequency-dependent manner. An outstanding question is how encoding of specific activation occurs under physiological conditions. In this case, continuous TCR interactions with specific peptides bound to cell surface-associated major histocompatibility complexes are driving the sustained [Ca2+]i increase. Addressing this question, we analyzed [Ca2+]i time series from individual T-cells mathematically. We are able to identify signal fluctuations associated with the TCR-triggering dynamics. We also find that [Ca2+]i time series associated with T-cells activated to IFN-gamma production exhibit oscillations with higher frequencies than the time series corresponding to T-cells not activated to IFN-gamma production. We show that signal autocorrelations are a means to distinguish functional signals according to their associated cytokine production. The signal level, however, allows for the distinction of nonfunctional from functional signals. These findings provide strong evidence for specificity encoding of biological functions in intracellular signals via signal level and signal correlations.

Strong and durable TCR clustering at the T/dendritic cell immune synapse is not required for NFAT activation and IFN-gamma production in human CD4+ T cells

The exact function of TCR clustering and organized macromolecular patterns at the immune synapse between APCs and T lymphocytes is unclear. Using human immature or mature dendritic cells (DCs) and autologous CD4(+) effector T cells, we demonstrate that, within a given conjugate, mature DCs induce strong and long-lasting TCR clustering and protein kinase C-theta translocation in a superantigen dose-dependent manner. Moreover, mature DCs promote CD43 exclusion in a dose-independent manner. In contrast, immature DCs are less potent at inducing these molecular rearrangements. Using these models to correlate T cell functions with the frequency, the intensity, and the duration of TCR clustering, we show, in Jurkat T cells, that weak and transient TCR clustering is sufficient to promote TCR down-modulation, protein kinase C-theta translocation at the synapse, and substantial NFAT transcriptional activation. Moreover, we show, in CD4(+) T cell blasts, that strong TCR clustering is required for neither TCR down-modulation nor optimal IFN-gamma production. Together, our results demonstrate that some CD4(+) functional responses, such as cytokine production, are independent of central supramolecular activation cluster formation.

Feedback control of T-cell receptor activation

The specificity and sensitivity of T-cell recognition is vital to the immune response. Ligand engagement with the T-cell receptor (TCR) results in the activation of a complex sequence of signalling events, both on the cell membrane and intracellularly. Feedback is an integral part of these signalling pathways, yet is often ignored in standard accounts of T-cell signalling. Here we show, using a mathematical model, that these feedback loops can explain the ability of the TCR to discriminate between ligands with high specificity and sensitivity, as well as provide a mechanism for sustained signalling. The model also explains the recent counter-intuitive observation that endogenous 'null' ligands can significantly enhance T-cell signalling. Finally, the model may provide an archetype for receptor switching based on kinase-phosphatase switches, and thus be of interest to the wider signalling community.

Conformational spread: the propagation of allosteric states in large multiprotein complexes

The phenomenon of allostery is conventionally described for small symmetrical oligomeric proteins such as hemoglobin. Here we review experimental evidence from a variety of systems-including bacterial chemotaxis receptors, muscle ryanodine receptors, and actin filaments-showing that conformational changes can also propagate through extended lattices of protein molecules. We explore the statistical mechanics of idealized linear and two-dimensional arrays of allosteric proteins and show that, as in the analogous Ising models, arrays of closely packed units can show large-scale integrated behavior. We also discuss proteins that undergo conformational changes driven by the hydrolysis of ATP and give examples in which these changes propagate through linear chains of molecules. We suggest that conformational spread could provide the basis of a solid-state "circuitry" in a living cell, able to integrate biochemical and biophysical events over hundreds of protein molecules.

T cell receptor-ligand interactions: a conformational preequilibrium or an induced fit

Kinetic parameters of T cell receptor (TCR) interactions with its ligand have been proposed to control T cell activation. Analysis of kinetic data obtained has so far produced conflicting insights; here, we offer a consideration of this problem. As a model system, association and dissociation of a soluble TCR (sT1) and its specific ligand, an azidobenzoic acid derivative of the peptide SYIPSAEK-(ABA)I (residues 252-260 from Plasmodium berghei circumsporozoite protein), bound to class I MHC H-2K(d)-encoded molecule (MHCp) were studied by surface plasmon resonance. The association time courses exhibited biphasic patterns. The fast and dominant phase was assigned to ligand association with the major fraction of TCR molecules, whereas the slow component was attributed to the presence of traces of TCR dimers. The association rate constant derived for the fast phase, assuming a reversible, single-step reaction mechanism, was relatively slow and markedly temperature-dependent, decreasing from 7.0 x 10(3) at 25 degrees C to 1.8 x 10(2) M(-1).s(-1) at 4 degrees C. Hence, it is suggested that these observed slow rate constants are the result of unresolved elementary steps of the process. Indeed, our analysis of the kinetic data shows that the time courses of TCR-MHCp interaction fit well to two different, yet closely related mechanisms, where an induced fit or a preequilibrium of two unbound TCR conformers are operational. These mechanisms may provide a rationale for the reported conformational flexibility of the TCR and its unusual ligand recognition properties, which combine high specificity with considerable crossreactivity.

The Immunological Synapse Balances T Cell Receptor Signaling and Degradation

The immunological synapse is a specialized cell-cell junction between T cell and antigen-presenting cell surfaces. It is characterized by a central cluster of antigen receptors, a ring of integrin family adhesion molecules, and temporal stability over hours. The role of this specific organization in signaling for T cell activation has been controversial. We use in vitro and in silico experiments to determine that the immunological synapse acts as a type of adaptive controller that both boosts T cell receptor triggering and attenuates strong signals.

A spatially extended stochastic model of the bacterial chemotaxis signalling pathway

We have combined two distinct but related stochastic approaches to model the Escherichia coli chemotaxis pathway. Reactions involving cytosolic components of the pathway were assumed to obey the laws of conventional stochastic chemical kinetics, while the clustered membrane receptors were represented in two-dimensional arrays similar to the Ising model. Receptors were assumed to flip between an active and an inactive state with probabilities dependent upon three energy inputs: ligand binding, methylation level due to adaptation, and the activity of neighbouring receptors. Examination of models with different lattice size and geometry showed that the sensitivity to stimuli increases with lattice size and the nearest-neighbour coupling strength up to a critical point, but this amplification was also accompanied by a proportional increase in steady-state noise. Multiple methylation of receptors resulted in diminished signal-to-noise ratio, but showed improved stability to variation in the coupling strength and increased gain. Under the best conditions the simulated output of a coupled lattice of receptors closely matched the time-course and amplitude found experimentally in living bacteria. The model also has some of the properties of a cellular automaton and shows an unexpected emergence of spatial patterns of methylation within the receptor lattice.

TCR ligand discrimination is enforced by competing ERK positive and SHP-1 negative feedback pathways

Functional discrimination between structurally similar self and foreign antigens is a main attribute of adaptive immunity. Here we describe two feedback mechanisms in T lymphocytes that together sharpen and amplify initial signaling differences related to the quality of T cell receptor (TCR) engagement. Weakly binding ligands predominantly trigger a negative feedback loop leading to rapid recruitment of the tyrosine phosphatase SHP-1, followed by receptor desensitization through inactivation of Lck kinase. In contrast, strongly binding ligands efficiently activate a positive feedback circuit involving Lck modification by ERK, preventing SHP-1 recruitment and allowing the long-lasting signaling necessary for gene activation. The characteristics of these pathways suggest that they constitute an important part of the mechanism allowing T cells to discriminate between self and foreign ligands.

Inter-receptor communication through arrays of bacterial chemoreceptors

The sensing mechanisms of chemotactic bacteria allow them to respond sensitively to stimuli. Escherichia coli, for example, respond to changes in chemoattractant concentration of less than 10% over a range spanning six orders of magnitude. Sensitivity over this range depends on a nonlinear relationship between ligand concentration and output response. At low ligand concentrations, substantial amplification of the chemotactic signal is required; however, the mechanism responsible for this amplification remains unclear. Here we demonstrate that inter-receptor communication within a lattice acts to amplify and integrate sensory information. Synthetic multivalent ligands that interact through the low-abundance, galactose-sensing receptor Trg stabilize large clusters of chemoreceptors and markedly enhance signal output from these enforced clusters. On treatment with multivalent ligands, the response to the attractant serine is amplified by at least 100-fold. This amplification requires a full complement of chemoreceptors; deletion of the aspartate (Tar) or dipeptide (Tap) receptors diminishes the amplification of the serine response. These results demonstrate that the entire array is involved in sensing. This mode of information exchange has general implications for the processing of signals by cellular receptors.

Autoreactivity, dynamic tuning and selectivity

The immune system adjusts its response to the context in which antigens, including self-antigens, are recognized. Recent observations support a conceptual framework for understanding how this may be achieved at the cellular and cell-population levels. At both levels, 'perturbations' elicit competition between excitation and de-excitation, resulting either in adaptation or in various responses. The responsiveness of individual cells is dynamically tuned, reflecting their recent experience. The tuning of T-cell activation thresholds by self-ligands facilitates positive selection and continuously regulates the level of autoreactivity in the periphery. Autoreactivity appears to be involved in regulation of the immune response, homeostasis, maintaining of the functional integrity of naïve and memory cells, and in other physiological functions.