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

Developmental epigenetic programming by Tet1/3 determines peripheral CD8 T cell fate

In response to infections, naive CD8 T cells give rise to effector and memory T cells. However, eliciting long-lived memory CD8 T cells remains a challenge for many infections. DNA demethylation of cytosines within CpG dinucleotides by Tet enzymes is a key epigenetic mechanism that regulates short- and long-term transcriptional programs in cells. Currently, their roles in modulating CD8 T-cell effector and memory differentiation are unclear. Here, we report that developing CD8 T cells lacking Tet1/3 preferentially differentiate into short-lived effector and effector memory cells following acute infection. Using genome-wide analyses, mice in which Tet1/3 were ablated during T-cell development and mature CD8 T cells, respectively, we show that Tet1/3 regulates these cell fates by licensing the chromatin landscape of genes downstream of T-cell receptor activation during thymic T-cell maturation. However, in mature CD8 T cells, Tet1/3 are dispensable for effector and memory cell fates. These findings unveil context-specific roles of DNA demethylation, which are essential for defining pathways that contribute to CD8 memory T-cell generation in response to infections.

T-cell receptor specificity landscape revealed through de novo peptide design

T-cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. An effective binding between T-cell receptors (TCRs) and pathogen-derived peptides presented on Major Histocompatibility Complexes (MHCs) mediate an immune response. However, predicting these interactions remains challenging due to limited functional data on T-cell reactivities. Here, we introduce a computational approach to predict TCR interactions with peptides presented on MHC class I alleles, and to design novel immunogenic peptides for specified TCR-MHC complexes. Our method leverages HERMES, a structure-based, physics-guided machine learning model trained on the protein universe to predict amino acid preferences based on local structural environments. Despite no direct training on TCR-pMHC data, the implicit physical reasoning in HERMES enables us to make accurate predictions of both TCR-pMHC binding affinities and T-cell activities across diverse viral epitopes and cancer neoantigens, achieving up to 72% correlation with experimental data. Leveraging our TCR recognition model, we develop a computational protocol for de novo design of immunogenic peptides. Through experimental validation in three TCR-MHC systems targeting viral and cancer peptides, we demonstrate that our designs-with up to five substitutions from the native sequence-activate T-cells at success rates of up to 50%. Lastly, we use our generative framework to quantify the diversity of the peptide recognition landscape for various TCR-MHC complexes, offering key insights into T-cell specificity in both humans and mice. Our approach provides a platform for immunogenic peptide and neoantigen design, opening new computational paths for T-cell vaccine development against viruses and cancer.

Ligand-induced receptor multimerization achieves specificity enhancement of kinetic proofreading without associated costs

Kinetic proofreading (KPR) is a commonly invoked mechanism for specificity enhancement of receptor signaling. However, specificity enhancement comes at a cost of nonequilibrium energy input and signal attenuation. We show that ligand-induced multimeric receptor assembly can enhance receptor specificity to the same degree as KPR, yet without the need for out-of-equilibrium energy expenditure and signal loss. We show how multimeric receptor specificity enhancement arises from the amplification of affinity differences via sequential progression down a free energy landscape. We also show that multimeric receptor ligand recognition is more robust to stochastic fluctuations and molecular noise than KPR receptors. Finally, we show that multimeric receptors perform signaling tasks beyond specificity enhancement like absolute discrimination and aspects of ligand antagonism. Our results suggest that multimeric receptors may serve as a potent mechanism of ligand discrimination comparable to and potentially with more advantages than traditional proofreading.

IL-2 amplifies quantitative TCR signalling inputs to drive Th1 and Th2 differentiation

The activation of CD4+ T-cells in a T cell receptor (TCR)-dependent antigen-specific manner is a central characteristic of the adaptive immune response. In addition to ensuring that CD4+ T-cells recognise their cognate antigen during activation, TCR-mediated signalling can also direct the outcome of differentiation. In both in vivo and in vitro model systems, strong TCR signalling has been demonstrated to drive Th1 differentiation, whereas weak TCR signalling drives Th2 responses. During the process of differentiation, TCR signal strength acts as a quantitative component in combination with the qualitative effects imparted by cytokines to polarise distinct T-helper lineages. Here, we investigated the role of interleukin 2 (IL-2) signalling in determining the outcome of TCR-dependent differentiation. IL-2 production was initiated as an early response to TCR-induced activation and was regulated by the strength of TCR signalling initially received. In the absence of IL-2, TCR dependent differentiation was found to be abolished. However, proliferative responses and early markers of activation were maintained, including the upregulation of GATA3, Tbet and Foxp3 at 24 h post-stimulation. Demonstrating that IL-2 signalling has a key role in stabilising and amplifying lineage-specific transcirption factor expression during differentiation. Further, activation of IL-2-deficient T-cells in the presence of exogenous cytokines was sufficient to restore differentiation whilst maintaining transcriptional signatures imparted during initial TCR signalling. Combined, our data demonstrate that the integration of quantitative TCR-dependent signalling and qualitative IL-2 signalling is essential for determining the fate of CD4+ T-cells during differentiation.

Mechanistic modeling of cell viability assays with in silico lineage tracing

Data from cell viability assays, which measure cumulative division and death events in a population and reflect substantial cellular heterogeneity, are widely available. However, interpreting such data with mechanistic computational models is hindered because direct model/data comparison is often muddled. We developed an algorithm that tracks simulated division and death events in mechanistically detailed single-cell lineages to enable such a model/data comparison and suggest causes of cell-cell drug response variability. Using our previously developed model of mammalian single-cell proliferation and death signaling, we simulated drug dose response experiments for four targeted anti-cancer drugs (alpelisib, neratinib, trametinib and palbociclib) and compared them to experimental data. Simulations are consistent with data for strong growth inhibition by trametinib (MEK inhibitor) and overall lack of efficacy for alpelisib (PI-3K inhibitor), but are inconsistent with data for palbociclib (CDK4/6 inhibitor) and neratinib (EGFR inhibitor). Model/data inconsistencies suggest (i) the importance of CDK4/6 for driving the cell cycle may be overestimated, and (ii) that the cellular balance between basal (tonic) and ligand-induced signaling is a critical determinant of receptor inhibitor response. Simulations show subpopulations of rapidly and slowly dividing cells in both control and drug-treated conditions. Variations in mother cells prior to drug treatment all impinging on ERK pathway activity are associated with the rapidly dividing phenotype and trametinib resistance. This work lays a foundation for the application of mechanistic modeling to large-scale cell viability assay datasets and better understanding determinants of cellular heterogeneity in drug response.

trans-Interacting Plasma Membrane Proteins and Binding Partner Identification

Plasma membrane proteins (PMPs) play critical roles in a myriad of physiological and disease conditions. A unique subset of PMPs functions through interacting with each other in trans at the interface between two contacting cells. These trans-interacting PMPs (tiPMPs) include adhesion molecules and ligands/receptors that facilitate cell-cell contact and direct communication between cells. Among the tiPMPs, a significant number have apparent extracellular binding domains but remain orphans with no known binding partners. Identification of their potential binding partners is therefore important for the understanding of processes such as organismal development and immune cell activation. While a number of methods have been developed for the identification of protein binding partners in general, very few are applicable to tiPMPs, which interact in a two-dimensional fashion with low intrinsic binding affinities. In this review, we present the significance of tiPMP interactions, the challenges of identifying binding partners for tiPMPs, and the landscape of method development. We describe current avidity-based screening approaches for identifying novel tiPMP binding partners and discuss their advantages and limitations. We conclude by highlighting the importance of developing novel methods of identifying new tiPMP interactions for deciphering the complex protein interactome and developing targeted therapeutics for diseases.

Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages

Macrophages sense pathogens and orchestrate specific immune responses. Stimulus specificity is thought to be achieved through combinatorial and dynamical coding by signaling pathways. While NFκB dynamics are known to encode stimulus information, dynamical coding in other signaling pathways and their combinatorial coordination remain unclear. Here, we established live-cell microscopy to investigate how NFκB and p38 dynamics interface in stimulated macrophages. Information theory and machine learning revealed that p38 dynamics distinguish cytokine TNF from pathogen-associated molecular patterns and high doses from low, but contributed little to information-rich NFκB dynamics when both pathways are considered. This suggests that immune response genes benefit from decoding immune signaling dynamics or combinatorics, but not both. We found that the heterogeneity of the two pathways is surprisingly uncorrelated. Mathematical modeling revealed potential sources of uncorrelated heterogeneity in the branched pathway network topology and predicted it to drive gene expression variability. Indeed, genes dependent on both p38 and NFκB showed high scRNAseq variability and bimodality. These results identify combinatorial signaling as a mechanism to restrict NFκB-AND-p38-responsive inflammatory cytokine expression to few cells.

Mathematical models of TCR initial triggering

T cell receptors (TCRs) play crucial roles in regulating T cell response by rapidly and accurately recognizing foreign and non-self antigens. The process involves multiple molecules and regulatory mechanisms, forming a complex network to achieve effective antigen recognition. Mathematical modeling techniques can help unravel the intricate network of TCR signaling and identify key regulators that govern it. In this review, we introduce and briefly discuss relevant mathematical models of TCR initial triggering, with a focus on kinetic proofreading (KPR) models with different modified structures. We compare the topology structures, biological hypotheses, parameter choices, and simulation performance of each model, and summarize the advantages and limitations of them. Further studies on TCR modeling design, aiming for an optimized balance of specificity and sensitivity, are expected to contribute to the development of new therapeutic strategies.

Bimodality in Ras signaling originates from processivity of the Ras activator SOS without deterministic bistability

Ras is a small GTPase that is central to important functional decisions in diverse cell types. An important aspect of Ras signaling is its ability to exhibit bimodal or switch-like activity. We describe the total reconstitution of a receptor-mediated Ras activation-deactivation reaction catalyzed by SOS and p120-RasGAP on supported lipid membrane microarrays. The results reveal a bimodal Ras activation response, which is not a result of deterministic bistability but is rather driven by the distinct processivity of the Ras activator, SOS. Furthermore, the bimodal response is controlled by the condensation state of the scaffold protein, LAT, to which SOS is recruited. Processivity-driven bimodality leads to stochastic bursts of Ras activation even under strongly deactivating conditions. This behavior contrasts deterministic bistability and may be more resistant to pharmacological inhibition.

Reliable ligand discrimination in stochastic multistep kinetic proofreading: First passage time vs. product counting strategies

Cellular signaling, crucial for biological processes like immune response and homeostasis, relies on specificity and fidelity in signal transduction to accurately respond to stimuli amidst biological noise. Kinetic proofreading (KPR) is a key mechanism enhancing signaling specificity through time-delayed steps, although its effectiveness is debated due to intrinsic noise potentially reducing signal fidelity. In this study, we reformulate the theory of kinetic proofreading (KPR) by convolving multiple intermediate states into a single state and then define an overall "processing" time required to traverse these states. This simplification allows us to succinctly describe kinetic proofreading in terms of a single waiting time parameter, facilitating a more direct evaluation and comparison of KPR performance across different biological contexts such as DNA replication and T cell receptor (TCR) signaling. We find that loss of fidelity for longer proofreading steps relies on the specific strategy of information extraction and show that in the first-passage time (FPT) discrimination strategy, longer proofreading steps can exponentially improve the accuracy of KPR at the cost of speed. Thus, KPR can still be an effective discrimination mechanism in the high noise regime. However, in a product concentration-based discrimination strategy, longer proofreading steps do not necessarily lead to an increase in performance. However, by introducing activation thresholds on product concentrations, can we decompose the product-based strategy into a series of FPT-based strategies to better resolve the subtleties of KPR-mediated product discrimination. Our findings underscore the importance of understanding KPR in the context of how information is extracted and processed in the cell.

Antigen perception in T cells by long-term Erk and NFAT signaling dynamics

Immune system threat detection hinges on T cells' ability to perceive varying peptide-major histocompatibility complex (pMHC) antigens. As the Erk and NFAT pathways link T cell receptor engagement to gene regulation, their signaling dynamics may convey information about pMHC inputs. To test this idea, we developed a dual reporter mouse strain and a quantitative imaging assay that, together, enable simultaneous monitoring of Erk and NFAT dynamics in live T cells over day-long timescales as they respond to varying pMHC inputs. Both pathways initially activate uniformly across various pMHC inputs but diverge only over longer (9+ h) timescales, enabling independent encoding of pMHC affinity and dose. These late signaling dynamics are decoded via multiple temporal and combinatorial mechanisms to generate pMHC-specific transcriptional responses. Our findings underscore the importance of long timescale signaling dynamics in antigen perception and establish a framework for understanding T cell responses under diverse contexts.

A guide to ERK dynamics, part 1: mechanisms and models

Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.

TCR ligand potency differentially impacts PD-1 inhibitory effects on diverse signaling pathways

Checkpoint blockade revolutionized cancer therapy, but we still lack a quantitative, mechanistic understanding of how inhibitory receptors affect diverse signaling pathways. To address this issue, we developed and applied a fluorescent intracellular live multiplex signal transduction activity reporter (FILMSTAR) system to analyze PD-1-induced suppressive effects. These studies identified pathways triggered solely by TCR or requiring both TCR and CD28 inputs. Using presenting cells differing in PD-L1 and CD80 expression while displaying TCR ligands of distinct potency, we found that PD-1-mediated inhibition primarily targets TCR-linked signals in a manner highly sensitive to peptide ligand quality. These findings help resolve discrepancies in existing data about the site(s) of PD-1 inhibition in T cells while emphasizing the importance of neoantigen potency in controlling the effects of checkpoint therapy.

CD3ζ ITAMs enable ligand discrimination and antagonism by inhibiting TCR signaling in response to low-affinity peptides

The T cell antigen receptor (TCR) contains ten immunoreceptor tyrosine-based activation motif (ITAM) signaling sequences distributed within six CD3 subunits; however, the reason for such structural complexity and multiplicity is unclear. Here we evaluated the effect of inactivating the three CD3ζ chain ITAMs on TCR signaling and T cell effector responses using a conditional 'switch' mouse model. Unexpectedly, we found that T cells expressing TCRs containing inactivated (non-signaling) CD3ζ ITAMs (6F-CD3ζ) exhibited reduced ability to discriminate between low- and high-affinity ligands, resulting in enhanced signaling and cytokine responses to low-affinity ligands because of a previously undetected inhibitory function of CD3ζ ITAMs. Also, 6F-CD3ζ TCRs were refractory to antagonism, as predicted by a new in silico adaptive kinetic proofreading model that revises the role of ITAM multiplicity in TCR signaling. Finally, T cells expressing 6F-CD3ζ displayed enhanced cytolytic activity against solid tumors expressing low-affinity ligands, identifying a new counterintuitive approach to TCR-mediated cancer immunotherapy.

Quantitative approaches for decoding the specificity of the human T cell repertoire

T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) interactions play a vital role in initiating immune responses against pathogens, and the specificity of TCRpMHC interactions is crucial for developing optimized therapeutic strategies. The advent of high-throughput immunological and structural evaluation of TCR and pMHC has provided an abundance of data for computational approaches that aim to predict favorable TCR-pMHC interactions. Current models are constructed using information on protein sequence, structures, or a combination of both, and utilize a variety of statistical learning-based approaches for identifying the rules governing specificity. This review examines the current theoretical, computational, and deep learning approaches for identifying TCR-pMHC recognition pairs, placing emphasis on each method's mathematical approach, predictive performance, and limitations.

Modulation of antigen discrimination by duration of immune contacts in a kinetic proofreading model of T cell activation with extreme statistics

T cells form transient cell-to-cell contacts with antigen presenting cells (APCs) to facilitate surface interrogation by membrane bound T cell receptors (TCRs). Upon recognition of molecular signatures (antigen) of pathogen, T cells may initiate an adaptive immune response. The duration of the T cell/APC contact is observed to vary widely, yet it is unclear what constructive role, if any, such variations might play in immune signaling. Modeling efforts describing antigen discrimination often focus on steady-state approximations and do not account for the transient nature of cellular contacts. Within the framework of a kinetic proofreading (KP) mechanism, we develop a stochastic First Receptor Activation Model (FRAM) describing the likelihood that a productive immune signal is produced before the expiry of the contact. Through the use of extreme statistics, we characterize the probability that the first TCR triggering is induced by a rare agonist antigen and not by that of an abundant self-antigen. We show that defining positive immune outcomes as resilience to extreme statistics and sensitivity to rare events mitigates classic tradeoffs associated with KP. By choosing a sufficient number of KP steps, our model is able to yield single agonist sensitivity whilst remaining non-reactive to large populations of self antigen, even when self and agonist antigen are similar in dissociation rate to the TCR but differ largely in expression. Additionally, our model achieves high levels of accuracy even when agonist positive APCs encounters are rare. Finally, we discuss potential biological costs associated with high classification accuracy, particularly in challenging T cell environments.

Bimodality in Ras signaling originates from processivity of the Ras activator SOS without classic kinetic bistability

Ras is a small GTPase that is central to important functional decisions in diverse cell types. An important aspect of Ras signaling is its ability to exhibit bimodal, or switch-like activity. We describe the total reconstitution of a receptor-mediated Ras activation-deactivation reaction catalyzed by SOS and p120-RasGAP on supported lipid membrane microarrays. The results reveal a bimodal Ras activation response, which is not a result of classic kinetic bistability, but is rather driven by the distinct processivity of the Ras activator, SOS. Furthermore, the bimodal response is controlled by the condensation state of the scaffold protein, LAT, to which SOS is recruited. Processivity-driven bimodality leads to stochastic bursts of Ras activation even under strongly deactivating conditions. This behavior contrasts classic kinetic bistability and is distinctly more resistant to pharmacological inhibition.

Simulating the Evolution of Signaling Signatures During CART-Cell and Tumor Cell Interactions

Immunotherapies have been proven to have significant therapeutic efficacy in the treatment of cancer. The last decade has seen adoptive cell therapies, such as chimeric antigen receptor T-cell (CART-cell) therapy, gain FDA approval against specific cancers. Additionally, there are numerous clinical trials ongoing investigating additional designs and targets. Nevertheless, despite the excitement and promising potential of CART-cell therapy, response rates to therapy vary greatly between studies, patients, and cancers. There remains an unmet need to develop computational frameworks that more accurately predict CART-cell function and clinical efficacy. Here we present a coarse-grained model simulated with logical rules that demonstrates the evolution of signaling signatures following the interaction between CART-cells and tumor cells and allows for in silico based prediction of CART-cell functionality prior to experimentation.Clinical Relevance- Analysis of CART-cell signaling signatures can inform future CAR receptor design and combination therapy approaches aimed at improving therapy response.

Non-coding sequence variation reveals fragility within interleukin 2 feedback circuitry and shapes autoimmune disease risk

Genetic variants associated with human autoimmune diseases commonly map to non-coding control regions, particularly enhancers that function selectively in immune cells and fine-tune gene expression within a relatively narrow range of values. How such modest, cell-type-selective changes can meaningfully shape organismal disease risk remains unclear. To explore this issue, we experimentally manipulated species-conserved enhancers within the disease-associated IL2RA locus and studied accompanying changes in the progression of autoimmunity. Perturbing distinct enhancers with restricted activity in conventional T cells (Tconvs) or regulatory T cells (Tregs)-two functionally antagonistic T cell subsets-caused only modest, cell-type-selective decreases in IL2ra expression parameters. However, these same perturbations had striking and opposing effects in vivo , completely preventing or severely accelerating disease in a murine model of type 1 diabetes. Quantitative tissue imaging and computational modelling revealed that each enhancer manipulation impinged on distinct IL-2-dependent feedback circuits. These imbalances altered the intracellular signaling and intercellular communication dynamics of activated Tregs and Tconvs, producing opposing spatial domains that amplified or constrained ongoing autoimmune responses. These findings demonstrate how subtle changes in gene regulation stemming from non-coding variation can propagate across biological scales due to non-linearities in intra- and intercellular feedback circuitry, dramatically shaping disease risk at the organismal level.

Antigen perception in T cells by long-term Erk and NFAT signaling dynamics

Immune system threat detection hinges on T cells' ability to perceive varying peptide major-histocompatibility complex (pMHC) antigens. As the Erk and NFAT pathways link T cell receptor engagement to gene regulation, their signaling dynamics may convey information about pMHC inputs. To test this idea, we developed a dual reporter mouse strain and a quantitative imaging assay that, together, enable simultaneous monitoring of Erk and NFAT dynamics in live T cells over day-long timescales as they respond to varying pMHC inputs. Both pathways initially activate uniformly across various pMHC inputs, but diverge only over longer (9+ hrs) timescales, enabling independent encoding of pMHC affinity and dose. These late signaling dynamics are decoded via multiple temporal and combinatorial mechanisms to generate pMHC-specific transcriptional responses. Our findings underscore the importance of long timescale signaling dynamics in antigen perception, and establish a framework for understanding T cell responses under diverse contexts.

SIGNIFICANCE STATEMENT

To counter diverse pathogens, T cells mount distinct responses to varying peptide-major histocompatibility complex ligands (pMHCs). They perceive the affinity of pMHCs for the T cell receptor (TCR), which reflects its foreignness, as well as pMHC abundance. By tracking signaling responses in single living cells to different pMHCs, we find that T cells can independently perceive pMHC affinity vs dose, and encode this information through the dynamics of Erk and NFAT signaling pathways downstream of the TCR. These dynamics are jointly decoded by gene regulatory mechanisms to produce pMHC-specific activation responses. Our work reveals how T cells can elicit tailored functional responses to diverse threats and how dysregulation of these responses may lead to immune pathologies.

Proofreading does not result in more reliable ligand discrimination in receptor signaling due to its inherent stochasticity

Kinetic proofreading (KPR) has been used as a paradigmatic explanation for the high specificity of ligand discrimination by cellular receptors. KPR enhances the difference in the mean receptor occupancy between different ligands compared to a nonproofread receptor, thus potentially enabling better discrimination. On the other hand, proofreading also attenuates the signal and introduces additional stochastic receptor transitions relative to a nonproofreading receptor. This increases the relative magnitude of noise in the downstream signal, which can interfere with reliable ligand discrimination. To understand the effect of noise on ligand discrimination beyond the comparison of the mean signals, we formulate the task of ligand discrimination as a problem of statistical estimation of the receptor affinity of ligands based on the molecular signaling output. Our analysis reveals that proofreading typically worsens ligand resolution compared to a nonproofread receptor. Furthermore, the resolution decreases further with more proofreading steps under most commonly biologically considered conditions. This contrasts with the usual notion that KPR universally improves ligand discrimination with additional proofreading steps. Our results are consistent across a variety of different proofreading schemes and metrics of performance, suggesting that they are inherent to the KPR mechanism itself rather than any particular model of molecular noise. Based on our results, we suggest alternative roles for KPR schemes such as multiplexing and combinatorial encoding in multi-ligand/multi-output pathways.

Regulation of Cx43 Gap Junction Intercellular Communication by Bruton's Tyrosine Kinase and Interleukin-2-Inducible T-Cell Kinase

T and B cell receptor signaling involves the activation of Akt, MAPKs, and PKC as well as an increase in intracellular Ca²⁺ and calmodulin activation. While these coordinate the rapid turnover of gap junctions, also implicated in this process is Src, which is not activated as part of T and B cell receptor signaling. An in vitro kinase screen identified that Bruton's tyrosine kinase (BTK) and interleukin-2-inducible T-cell kinase (ITK) phosphorylate Cx43. Mass spectroscopy revealed that BTK and ITK phosphorylate Cx43 residues Y247, Y265, and Y313, which are identical to the residues phosphorylated by Src. Overexpression of BTK or ITK in the HEK-293T cells led to increased Cx43 tyrosine phosphorylation as well as decreased gap junction intercellular communication (GJIC) and Cx43 membrane localization. In the lymphocytes, activation of the B cell receptor (Daudi cells) or T cell receptor (Jurkat cells) increased the BTK and ITK activity, respectively. While this led to increased tyrosine phosphorylation of Cx43 and decreased GJIC, the cellular localization of Cx43 changed little. We have previously identified that Pyk2 and Tyk2 also phosphorylate Cx43 at residues Y247, Y265, and Y313 with a similar cellular fate to that of Src. With phosphorylation critical to Cx43 assembly and turnover, and kinase expression varying between different cell types, there would be a need for different kinases to achieve the same regulation of Cx43. The work presented herein suggests that in the immune system, ITK and BTK have the capacity for the tyrosine phosphorylation of Cx43 to alter the gap junction function in a similar manner as Pyk2, Tyk2, and Src.

Simulating the Evolution of Signaling Signatures during CART-Cell - Tumor Cell Interactions

Immunotherapies have been proven to have significant therapeutic efficacy in the treatment of cancer. The last decade has seen adoptive cell therapies, such as chimeric antigen receptor T-cell (CART-cell) therapy, gain FDA approval against specific cancers. Additionally, there are numerous clinical trials ongoing investigating additional designs and targets. Nevertheless, despite the excitement and promising potential of CART-cell therapy, response rates to therapy vary greatly between studies, patients, and cancers. There remains an unmet need to develop computational frameworks that more accurately predict CART-cell function and clinical efficacy. Here we present a coarse-grained model simulated with logical rules that demonstrates the evolution of signaling signatures following the interaction between CART-cells and tumor cells and allows for in silico based prediction of CART-cell functionality prior to experimentation.

Time required for commitment to T cell proliferation depends on TCR affinity and cytokine response

T cell activation and effector functions are determined by the affinity of the interaction between T cell receptor (TCR) and its antigenic peptide MHC (pMHC) ligand. A better understanding of the quantitative aspects of TCR-pMHC affinity-dependent T cell activation is critical for the development of new immunotherapeutic strategies. However, the role of TCR-pMHC affinity in regulating the kinetics of CD8+ T cell commitment to proliferation and differentiation is unknown. Here, we show that the stronger the TCR-pMHC affinity, the shorter the time of T cell-APC co-culture required to commit CD8+ T cells to proliferation. The time threshold for T cell cytokine production is much lower than that for cell proliferation. There is a strong correlation between affinity-dependent differences in AKT phosphorylation and T cell proliferation. The cytokine IL-15 increases the poor proliferation of T cells stimulated with low affinity pMHC, suggesting that pro-inflammatory cytokines can override the affinity-dependent features of T cell proliferation.

The Enigmatic Nature of the TCR-pMHC Interaction: Implications for CAR-T and TCR-T Engineering

The interaction of the T-cell receptor (TCR) with a peptide in the major histocompatibility complex (pMHC) plays a central role in the adaptive immunity of higher chordates. Due to the high specificity and sensitivity of this process, the immune system quickly recognizes and efficiently responds to the appearance of foreign and altered self-antigens. This is important for ensuring anti-infectious and antitumor immunity, in addition to maintaining self-tolerance. The most common parameter used for assessing the specificity of TCR-pMHC interaction is affinity. This thermodynamic characteristic is widely used not only in various theoretical aspects, but also in practice, for example, in the engineering of various T-cell products with a chimeric (CAR-T) or artificial (TCR-engineered T-cell) antigen receptor. However, increasing data reveal the fact that, in addition to the thermodynamic component, the specificity of antigen recognition is based on the kinetics and mechanics of the process, having even greater influence on the selectivity of the process and T lymphocyte activation than affinity. Therefore, the kinetic and mechanical aspects of antigen recognition should be taken into account when designing artificial antigen receptors, especially those that recognize antigens in the MHC complex. This review describes the current understanding of the nature of the TCR-pMHC interaction, in addition to the thermodynamic, kinetic, and mechanical principles underlying the specificity and high sensitivity of this interaction.

The immune synapses reveal aberrant functions of CD8 T cells during chronic HIV infection

Chronic HIV infection causes persistent low-grade inflammation that induces premature aging of the immune system including senescence of memory and effector CD8 T cells. To uncover the reasons of gradually diminished potency of CD8 T cells from people living with HIV, here we expose the T cells to planar lipid bilayers containing ligands for T-cell receptor and a T-cell integrins and analyze the cellular morphology, dynamics of synaptic interface formation and patterns of the cellular degranulation. We find a large fraction of phenotypically naive T cells from chronically infected people are capable to form mature synapse with focused degranulation, a signature of a differentiated T cells. Further, differentiation of aberrant naive T cells may lead to the development of anomalous effector T cells undermining their capacity to control HIV and other pathogens that could be contained otherwise.

Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design

BACKGROUND

Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.

METHODS

We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.

RESULTS

In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation.

CONCLUSIONS

Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter. Video Abstract.

Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

In recent decades, chimeric antigen receptors (CARs) have been successfully used to generate engineered T cells capable of recognizing and eliminating cancer cells. The structure of CARs typically includes costimulatory domains, which enhance the T-cell response upon antigen encounter. However, it is not fully known how those co-stimulatory domains influence cell activation in the presence of biological variability. In this work, we used mathematical modelling to elucidate how the inclusion of one such costimulatory molecule, CD28, impacts the response of a population of CAR T cells under different sources of variability. Particularly, we demonstrate that CD28-bearing CARs mediate a faster and more consistent population response under both target antigen variability and kinetic rate variability. Next, we identify kinetic parameters that have the most impact on cell response time. Finally, based on our findings, we propose that enhancing the catalytic activity of lymphocyte-specific protein tyrosine kinase can result in drastically reduced and more consistent response times among heterogeneous CAR T-cell populations.

Generation of Allogeneic CAR T Cells through Specific Degradation of the T Cell Antigen Receptor by E3 Ubiquitin Ligase Fusion Proteins

Receptor downregulation is instrumental for many therapeutic interventions. Receptor knockout through gene-editing technologies is efficient but can introduce off-target mutations and chromothripsis. Regulation of gene expression at the protein level is a promising alternative. Here, we present results showing the targeted T cell antigen receptor (TCR) degradation using chimeric E3 fusion proteins that we call Receptor Targeting Chimeras (ReceptorTAC). We show that TCR degradation is dependent on enzymatically active, membrane-anchored E3 ligase variants. TCR specificity was achieved by direct fusion of an E3 domain to the CD3ζ transmembrane sequence. Jurkat and primary T cells stably expressing the ReceptorTAC constructs showed significantly reduced responses to TCR stimulation. We also used our ReceptorTAC technology to generate TCR-deficient, claudin18.2-specific CAR T cells, where the activity of the CAR was unaffected by the expression of the ReceptorTAC. These data indicate that our ReceptorTAC molecule can be used to generate allogeneic CAR T cells.

T-cell Receptor Is a Threshold Detector: Sub- and Supra-Threshold Stochastic Resonance in TCR-MHC Clusters on the Cell Surface

Stochastic resonance in clusters of major histocompatibility molecules is extended by a more detailed description of adaptive thresholding and by applying the notion of suprathreshold stochastic resonance as a stochastically quantizing encoder of transmembrane signaling downstream of major histocompatibility molecules and T-cell receptors on the side of presenting and recognizing cells, respectively. The adaptive nature of thresholding is partly explained by a mirroring of the noncognate–cognate dichotomy shown by the T-cell receptor structure and the kinetic-segregation model of the onset of T-cell receptor triggering. Membrane clusters of major histocompatibility molecules and T-cell receptors on their host cells are envisioned as places of the temporal encoding of downstream signals via the suprathreshold stochastic resonance process. The ways of optimization of molecular prostheses, such as chimeric antigen receptors against cancer in transmembrane signaling, are suggested in the framework of suprathreshold stochastic resonance. The analogy between Förster resonance energy transfer and suprathreshold stochastic resonance for information transfer is also discussed. The overlap integral for energy transfer parallels the mutual information transferred by suprathreshold stochastic resonance.

Dephosphorylation accelerates the dissociation of ZAP70 from the T cell receptor

Protein-protein binding domains are critical in signaling networks. Src homology 2 (SH2) domains are binding domains that interact with sequences containing phosphorylated tyrosines. A subset of SH2 domain-containing proteins has tandem domains, which are thought to enhance binding affinity and specificity. However, a trade-off exists between long-lived binding and the ability to rapidly reverse signaling, which is a critical requirement of noise-filtering mechanisms such as kinetic proofreading. Here, we use modeling to show that the unbinding rate of tandem, but not single, SH2 domains can be accelerated by phosphatases. Using surface plasmon resonance, we show that the phosphatase CD45 can accelerate the unbinding rate of zeta chain-associated protein kinase 70 (ZAP70), a tandem SH2 domain-containing kinase, from biphosphorylated peptides from the T cell receptor (TCR). An important functional prediction of accelerated unbinding is that the intracellular ZAP70-TCR half-life in T cells will not be fixed but rather, dependent on the extracellular TCR-antigen half-life, and we show that this is the case in both cell lines and primary T cells. The work highlights that tandem SH2 domains can break the trade-off between signal fidelity (requiring long half-life) and signal reversibility (requiring short half-life), which is a key requirement for T cell antigen discrimination mediated by kinetic proofreading.

TCR-induced FOXP3 expression by CD8+ T cells impairs their anti-tumor activity

Adoptive cell transfer therapy using CD8⁺ T lymphocytes showed promising results eradicating metastatic malignancies. However, several regulatory mechanisms limit its efficacy. We studied the role of the expression of the transcription factor FOXP3 on CD8⁺ T cell function and anti-tumor immunity. Here we show that suboptimal T cell receptor stimulation of CD8⁺ T cells upregulates FOXP3 in vitro. Similarly, CD8 T cells transferred into tumor-bearing mice upregulate FOXP3 in vivo. Cell-intrinsic loss of FOXP3 by CD8⁺ T cells resulted in improved functionality after TCR stimulation and better antitumor responses in vivo. Inhibition of the FOXP3/NFAT interaction likewise improved CD8⁺ T cell functionality. Transcriptomic analysis of cells after TCR stimulation revealed an enrichment of genes implicated in the response to IFN-γ, IFN-α, inflammatory response, IL-6/JAK/STAT, G2M checkpoint and IL-2/STAT signaling in FOXP3-deficient CD8⁺ T cells with respect to FOXP3-wt CD8⁺ T cells. Our results suggest that transient expression of FOXP3 by CD8⁺ T cells in the tumor microenvironment restrains their anti-tumor activity, with clear implications for improving T cell responses during immunotherapy.

Supplying the trip to antibody production-nutrients, signaling, and the programming of cellular metabolism in the mature B lineage

The COVID pandemic has refreshed and expanded recognition of the vital role that sustained antibody (Ab) secretion plays in our immune defenses against microbes and of the importance of vaccines that elicit Ab protection against infection. With this backdrop, it is especially timely to review aspects of the molecular programming that govern how the cells that secrete Abs arise, persist, and meet the challenge of secreting vast amounts of these glycoproteins. Whereas plasmablasts and plasma cells (PCs) are the primary sources of secreted Abs, the process leading to the existence of these cell types starts with naive B lymphocytes that proliferate and differentiate toward several potential fates. At each step, cells reside in specific microenvironments in which they not only receive signals from cytokines and other cell surface receptors but also draw on the interstitium for nutrients. Nutrients in turn influence flux through intermediary metabolism and sensor enzymes that regulate gene transcription, translation, and metabolism. This review will focus on nutrient supply and how sensor mechanisms influence distinct cellular stages that lead to PCs and their adaptations as factories dedicated to Ab secretion. Salient findings of this group and others, sometimes exhibiting differences, will be summarized with regard to the journey to a distinctive metabolic program in PCs.

TCR signal strength defines distinct mechanisms of T cell dysfunction and cancer evasion

T cell receptor (TCR) signal strength is a key determinant of T cell responses. We developed a cancer mouse model in which tumor-specific CD8 T cells (TST cells) encounter tumor antigens with varying TCR signal strength. High-signal-strength interactions caused TST cells to up-regulate inhibitory receptors (IRs), lose effector function, and establish a dysfunction-associated molecular program. TST cells undergoing low-signal-strength interactions also up-regulated IRs, including PD1, but retained a cell-intrinsic functional state. Surprisingly, neither high- nor low-signal-strength interactions led to tumor control in vivo, revealing two distinct mechanisms by which PD1hi TST cells permit tumor escape; high signal strength drives dysfunction, while low signal strength results in functional inertness, where the signal strength is too low to mediate effective cancer cell killing by functional TST cells. CRISPR-Cas9-mediated fine-tuning of signal strength to an intermediate range improved anti-tumor activity in vivo. Our study defines the role of TCR signal strength in TST cell function, with important implications for T cell-based cancer immunotherapies.

Antigen and checkpoint receptor engagement recalibrates T cell receptor signal strength

How T cell receptor (TCR) signal strength modulates T cell function and to what extent this is modified by immune checkpoint blockade (ICB) are key questions in immunology. Using Nr4a3-Tocky mice, we characterized early quantitative and qualitative changes that occur in CD4+ T cells in relation to TCR signaling strength. We captured how dose- and time-dependent programming of distinct co-inhibitory receptors rapidly recalibrates T cell activation thresholds and visualized the immediate effects of ICB on T cell re-activation. Our findings reveal that anti-PD1 immunotherapy leads to an increased TCR signal strength. We defined a strong TCR signal metric of five genes upregulated by anti-PD1 in T cells (TCR.strong), which was superior to a canonical T cell activation gene signature in stratifying melanoma patient outcomes to anti-PD1 therapy. Our study therefore reveals how analysis of TCR signal strength-and its manipulation-can provide powerful metrics for monitoring outcomes to immunotherapy.

Dynamic variability in SHP-1 abundance determines natural killer cell responsiveness

[Figure: see text].

Staggered starts in the race to T cell activation

How T lymphocytes tune their responses to different strengths of stimulation is a fundamental question in immunology. Recent work using new optogenetic, single-cell genomic, and live-imaging approaches has revealed that stimulation strength controls the rate of individual cell responses within a population. Moreover, these responses have been found to use shared molecular programs, regardless of stimulation strength. However, additional data indicate that stimulation duration or cytokine feedback can impact later gene expression phenotypes of activated cells. In-depth molecular studies have suggested mechanisms by which stimulation strength might modulate the probability of T cell activation. This emerging model allows activating T cells to achieve a wide range of population responses through probabilistic control within individual cells.

DNA origami patterning of synthetic T cell receptors reveals spatial control of the sensitivity and kinetics of signal activation

Receptor clustering plays a key role in triggering cellular activation, but the relationship between the spatial configuration of clusters and the elicitation of downstream intracellular signals remains poorly understood. We developed a DNA-origami-based system that is easily adaptable to other cellular systems and enables rich interrogation of responses to a variety of spatially defined inputs. Using a chimeric antigen receptor (CAR) T cell model system with relevance to cancer therapy, we studied signaling dynamics at single-cell resolution. We found that the spatial arrangement of receptors determines the ligand density threshold for triggering and encodes the temporal kinetics of signaling activities. We also showed that signaling sensitivity of a small cluster of high-affinity ligands is enhanced when surrounded by nonstimulating low-affinity ligands. Our results suggest that cells measure spatial arrangements of ligands, translate that information into distinct signaling dynamics, and provide insights into engineering immunotherapies.

Stimulus-specific responses in innate immunity: Multilayered regulatory circuits

Immune sentinel cells initiate immune responses to pathogens and tissue injury and are capable of producing highly stimulus-specific responses. Insight into the mechanisms underlying such specificity has come from the identification of regulatory factors and biochemical pathways, as well as the definition of signaling circuits that enable combinatorial and temporal coding of information. Here, we review the multi-layered molecular mechanisms that underlie stimulus-specific gene expression in macrophages. We categorize components of inflammatory and anti-pathogenic signaling pathways into five layers of regulatory control and discuss unifying mechanisms determining signaling characteristics at each layer. In this context, we review mechanisms that enable combinatorial and temporal encoding of information, identify recurring regulatory motifs and principles, and present strategies for integrating experimental and computational approaches toward the understanding of signaling specificity in innate immunity.

Optimal ligand discrimination by asymmetric dimerization and turnover of interferon receptors

In multicellular organisms, antiviral defense mechanisms evoke a reliable collective immune response despite the noisy nature of biochemical communication between tissue cells. A molecular hub of this response, the interferon I receptor (IFNAR), discriminates between ligand types by their affinity regardless of concentration. To understand how ligand type can be decoded robustly by a single receptor, we frame ligand discrimination as an information-theoretic problem and systematically compare the major classes of receptor architectures: allosteric, homodimerizing, and heterodimerizing. We demonstrate that asymmetric heterodimers achieve the best discrimination power over the entire physiological range of local ligand concentrations. This design enables sensing of ligand presence and type, and it buffers against moderate concentration fluctuations. In addition, receptor turnover, which drives the receptor system out of thermodynamic equilibrium, allows alignment of activation points for ligands of different affinities and thereby makes ligand discrimination practically independent of concentration. IFNAR exhibits this optimal architecture, and our findings thus suggest that this specialized receptor can robustly decode digital messages carried by its different ligands.

Mesoscale T cell antigen discrimination emerges from intercellular feedback

Mature T cells must distinguish between foreign and self-antigens to promote host defense while limiting autoimmunity. How such discrimination occurs reproducibly has been explored extensively regarding mechanisms regulating initial T cell activation at short time and length scales. Here, we suggest that T cells encounter a higher-level discriminatory boundary post-activation, empowering or constraining their responses over greater spatiotemporal scales. This boundary emerges from coordinated communication among at least three cell types, forming a control system governed by intercellular circuits, including negative feedback from regulatory T cells (Tregs). We propose that the nonlinearities inherent to this system can amplify subtle baseline imbalances in a single cell type's functional state, altering the threshold for productive T cell responses and autoimmune disease risk.

Hierarchy of signaling thresholds downstream of the T cell receptor and the Tec kinase ITK

The strength of peptide:MHC interactions with the T cell receptor (TCR) is correlated with the time to first cell division, the relative scale of the effector cell response, and the graded expression of activation-associated proteins like IRF4. To regulate T cell activation programming, the TCR and the TCR proximal interleukin-2-inducible T cell kinase (ITK) simultaneously trigger many biochemically separate signaling cascades. T cells lacking ITK exhibit selective impairments in effector T cell responses after activation, but under the strongest signaling conditions, ITK activity is dispensable. To gain insight into whether TCR signal strength and ITK activity tune observed graded gene expression through the unequal activation of distinct signaling pathways, we examined Erk1/2 phosphorylation or nuclear factor of activated T cells (NFAT) and nuclear factor (NF)-κB translocation in naïve OT-I CD8⁺ cell nuclei. We observed the consistent digital activation of NFAT1 and Erk1/2, but NF-κB displayed dynamic, graded activation in response to variation in TCR signal strength, tunable by treatment with an ITK inhibitor. Inhibitor-treated cells showed the dampened induction of AP-1 factors Fos and Fosb, NF-κB response gene transcripts, and survival factor Il2 transcripts. ATAC sequencing analysis also revealed that genomic regions most sensitive to ITK inhibition were enriched for NF-κB and AP-1 motifs. Specific inhibition of NF-κB during peptide stimulation tuned the expression of early gene products like c-Fos. Together, these data indicate a key role for ITK in orchestrating the optimal activation of separate TCR downstream pathways, specifically aiding NF-κB activation. More broadly, we revealed a mechanism by which variations in TCR signal strength can produce patterns of graded gene expression in activated T cells.

A local regulatory T cell feedback circuit maintains immune homeostasis by pruning self-activated T cells

A fraction of mature T cells can be activated by peripheral self-antigens, potentially eliciting host autoimmunity. We investigated homeostatic control of self-activated T cells within unperturbed tissue environments by combining high-resolution multiplexed and volumetric imaging with computational modeling. In lymph nodes, self-activated T cells produced interleukin (IL)-2, which enhanced local regulatory T cell (Treg) proliferation and inhibitory functionality. The resulting micro-domains reciprocally constrained inputs required for damaging effector responses, including CD28 co-stimulation and IL-2 signaling, constituting a negative feedback circuit. Due to these local constraints, self-activated T cells underwent transient clonal expansion, followed by rapid death ("pruning"). Computational simulations and experimental manipulations revealed the feedback machinery's quantitative limits: modest reductions in Treg micro-domain density or functionality produced non-linear breakdowns in control, enabling self-activated T cells to subvert pruning. This fine-tuned, paracrine feedback process not only enforces immune homeostasis but also establishes a sharp boundary between autoimmune and host-protective T cell responses.

The discriminatory power of the T cell receptor

T cells use their T cell receptors (TCRs) to discriminate between lower-affinity self and higher-affinity non-self peptides presented on major histocompatibility complex (pMHC) antigens. Although the discriminatory power of the TCR is widely believed to be near-perfect, technical difficulties have hampered efforts to precisely quantify it. Here, we describe a method for measuring very low TCR/pMHC affinities and use it to measure the discriminatory power of the TCR and the factors affecting it. We find that TCR discrimination, although enhanced compared with conventional cell-surface receptors, is imperfect: primary human T cells can respond to pMHC with affinities as low as KD ∼ 1 mM. The kinetic proofreading mechanism fit our data, providing the first estimates of both the time delay (2.8 s) and number of biochemical steps (2.67) that are consistent with the extraordinary sensitivity of antigen recognition. Our findings explain why self pMHC frequently induce autoimmune diseases and anti-tumour responses, and suggest ways to modify TCR discrimination.

Pleiotropy enables specific and accurate signaling in the presence of ligand cross talk

Living cells sense their environment through the binding of extracellular molecular ligands to cell surface receptors. Puzzlingly, vast numbers of signaling pathways exhibit a high degree of cross talk between different signals whereby different ligands act through the same receptor or shared components downstream. It remains unclear how a cell can accurately process information from the environment in such cross-wired pathways. We show that a feature which commonly accompanies cross talk-signaling pleiotropy (the ability of a receptor to produce multiple outputs)-offers a solution to the cross-talk problem. In a minimal model we show that a single pleiotropic receptor can simultaneously identify and accurately sense the concentrations of arbitrary unknown ligands present individually or in a mixture. We calculate the fundamental limits of the signaling specificity and accuracy of such signaling schemes. The model serves as an elementary "building block" toward understanding more complex cross-wired receptor-ligand signaling networks.

Signaling through polymerization and degradation: Analysis and simulations of T cell activation mediated by Bcl10

The adaptive immune system serves as a potent and highly specific defense mechanism against pathogen infection. One component of this system, the effector T cell, facilitates pathogen clearance upon detection of specific antigens by the T cell receptor (TCR). A critical process in effector T cell activation is transmission of signals from the TCR to a key transcriptional regulator, NF-κB. The transmission of this signal involves a highly dynamic process in which helical filaments of Bcl10, a key protein constituent of the TCR signaling cascade, undergo competing processes of polymeric assembly and macroautophagy-dependent degradation. Through computational analysis of three-dimensional, super-resolution optical micrographs, we quantitatively characterize TCR-stimulated Bcl10 filament assembly and length dynamics, and demonstrate that filaments become shorter over time. Additionally, we develop an image-based, bootstrap-like resampling method that demonstrates the preferred association between autophagosomes and both Bcl10-filament ends and punctate-Bcl10 structures, implying that autophagosome-driven macroautophagy is directly responsible for Bcl10 filament shortening. We probe Bcl10 polymerization-depolymerization dynamics with a stochastic Monte-Carlo simulation of nucleation-limited filament assembly and degradation, and we show that high probabilities of filament nucleation in response to TCR engagement could provide the observed robust, homogeneous, and tunable response dynamic. Furthermore, we demonstrate that the speed of filament disassembly preferentially at filament ends provides effective regulatory control. Taken together, these data suggest that Bcl10 filament growth and degradation act as an excitable system that provides a digital response mechanism and the reliable timing critical for T cell activation and regulatory processes.

The immune system serves to protect organisms against pathogen-mediated disease. While a strong immune response is needed to eliminate pathogens in host organisms, immune responses that are too robust or too persistent can trigger autoimmune disorders, cancer, and a variety of additional serious human pathologies. Thus, a careful balance of activating and inhibitory mechanisms is necessary to prevent detrimental health outcomes of immune responses. For example, activated effector T cells marshal the immune response and direct killing of pathogen-infected cells; however, effector T cells that are chronically activated can damage and destroy healthy tissue. Here, we study an important internal activation pathway in effector T cells that involves the growth and counterbalancing disassembly (involving a process called macroautophagy) of filamentous cytoplasmic signaling structures. We utilize image analysis of 3-D super-resolution images and Monte Carlo simulations to study a key signal-transduction protein, Bcl10. We found that the speed of filament disassembly has the greatest effect on the magnitude and duration of the response, implying that pharmaceutical interventions aimed at macroautophagy may have substantial impact on effector T cell function. Given that filamentous structures are utilized in numerous immune signaling pathways, our analysis methods could have broad applicability in the signal transduction field.

Cross-TCR Antagonism Revealed by Optogenetically Tuning the Half-Life of the TCR Ligand Binding

Activation of T cells by agonistic peptide-MHC can be inhibited by antagonistic ones. However, the exact mechanism remains elusive. We used Jurkat cells expressing two different TCRs and tested whether stimulation of the endogenous TCR by agonistic anti-Vβ8 antibodies can be modulated by ligand-binding to the second, optogenetic TCR. The latter TCR uses phytochrome B tetramers (PhyBt) as ligand, the binding half-life of which can be altered by light. We show that this half-life determined whether the PhyBt acted as a second agonist (long half-life), an antagonist (short half-life) or did not have any influence (very short half-life) on calcium influx. A mathematical model of this cross-antagonism shows that a mechanism based on an inhibitory signal generated by early recruitment of a phosphatase and an activating signal by later recruitment of a kinase explains the data.

Quantifying persistence in the T-cell signaling network using an optically controllable antigen receptor

T cells discriminate between healthy and infected cells with remarkable sensitivity when mounting an immune response, which is hypothesized to depend on T cells combining stimuli from multiple antigen-presenting cell interactions into a more potent response. To quantify the capacity for T cells to accomplish this, we have developed an antigen receptor that is optically tunable within cell conjugates, providing control over the duration, and intensity of intracellular T-cell signaling. We observe limited persistence within the T-cell intracellular network on disruption of receptor input, with signals dissipating entirely in ~15 min, and directly show sustained proximal receptor signaling is required to maintain gene transcription. T cells thus primarily accumulate the outputs of gene expression rather than integrate discrete intracellular signals. Engineering optical control in a clinically relevant chimeric antigen receptor (CAR), we show that this limited signal persistence can be exploited to increase CAR-T cell activation threefold using pulsatile stimulation. Our results are likely to apply more generally to the signaling dynamics of other cellular networks.

Autophosphorylation and the Dynamics of the Activation of Lck

Lck (lymphocyte-specific protein tyrosine kinase) is an enzyme which plays a number of important roles in the function of immune cells. It belongs to the Src family of kinases which are known to undergo autophosphorylation. It turns out that this leads to a remarkable variety of dynamical behaviour which can occur during their activation. We prove that in the presence of autophosphorylation one phenomenon, bistability, already occurs in a mathematical model for a protein with a single phosphorylation site. We further show that a certain model of Lck exhibits oscillations. Finally, we discuss the relations of these results to models in the literature which involve Lck and describe specific biological processes, such as the early stages of T cell activation and the stimulation of T cell responses resulting from the suppression of PD-1 signalling which is important in immune checkpoint therapy for cancer.

Extracellular signal-regulated kinase (ERK) pathway control of CD8+ T cell differentiation

The integration of multiple signalling pathways that co-ordinate T cell metabolism and transcriptional reprogramming is required to drive T cell differentiation and proliferation. One key T cell signalling module is mediated by extracellular signal-regulated kinases (ERKs) which are activated in response to antigen receptor engagement. The activity of ERKs is often used to report antigen receptor occupancy but the full details of how ERKs control T cell activation is not understood. Accordingly, we have used mass spectrometry to explore how ERK signalling pathways control antigen receptor driven proteome restructuring in CD8⁺ T cells to gain insights about the biological processes controlled by ERKs in primary lymphocytes. Quantitative analysis of >8000 proteins identified 900 ERK regulated proteins in activated CD8⁺ T cells. The data identify both positive and negative regulatory roles for ERKs during T cell activation and reveal that ERK signalling primarily controls the repertoire of transcription factors, cytokines and cytokine receptors expressed by activated T cells. It was striking that a large proportion of the proteome restructuring that is driven by triggering of the T cell antigen receptor is not dependent on ERK activation. However, the selective targets of the ERK signalling module include the critical effector molecules and the cytokines that allow T cell communication with other immune cells to mediate adaptive immune responses.