Quorum sensing allows T cells to discriminate between self and nonself

The quantum model of T-cell activation: Revisiting immune response theories

Our understanding of the immune response is far from complete, missing out on more detailed explanations that could be provided by molecular insights. To bridge this gap, we introduce the quantum model of T-cell activation. This model suggests that the transfer of energy during protein phosphorylation within T cells is not a continuous flow but occurs in discrete bursts, or 'quanta', of phosphates. This quantized energy transfer is mediated by oscillating cycles of receptor phosphorylation and dephosphorylation, initiated by dynamic 'catch-slip' pulses in the peptide-major histocompatibility complex-T-cell receptor (pMHC-TcR) interactions. T-cell activation is predicated upon achieving a critical threshold of catch-slip pulses at the pMHC-TcR interface. Costimulation is relegated to a secondary role, becoming crucial only when the frequency of pMHC-TcR catch-slip pulses does not meet the necessary threshold for this quanta-based energy transfer. Therefore, our model posits that it is the quantum nature of energy transfer-not the traditional signal I or signal II-that plays the decisive role in T-cell activation. This paradigm shift highlights the importance of understanding T-cell activation through a quantum lens, offering a potentially transformative perspective on immune response regulation.

A journey to your self: The vague definition of immune self and its practical implications

The identification of immunogenic peptides has become essential in an increasing number of fields in immunology, ranging from tumor immunotherapy to vaccine development. The nature of the adaptive immune response is shaped by the similarity between foreign and self-protein sequences, a concept extensively applied in numerous studies. Can we precisely define the degree of similarity to self? Furthermore, do we accurately define immune self? In the current work, we aim to unravel the conceptual and mechanistic vagueness hindering the assessment of self-similarity. Accordingly, we demonstrate the remarkably low consistency among commonly employed measures and highlight potential avenues for future research.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

Exploring new perspectives in immunology

Several conceptual pillars form the foundation of modern immunology, including the clonal selection theory, antigen receptor diversity, immune memory, and innate control of adaptive immunity. However, some immunological phenomena cannot be explained by the current framework. Thus, we still do not know how to design vaccines that would provide long-lasting protective immunity against certain pathogens, why autoimmune responses target some antigens and not others, or why the immune response to infection sometimes does more harm than good. Understanding some of these mysteries may require that we question existing assumptions to develop and test alternative explanations. Immunology is increasingly at a point when, once again, exploring new perspectives becomes a necessity.

How persistent infection overcomes peripheral tolerance mechanisms to cause T cell-mediated autoimmune disease

T cells help orchestrate immune responses to pathogens, and their aberrant regulation can trigger autoimmunity. Recent studies highlight that a threshold number of T cells (a quorum) must be activated in a tissue to mount a functional immune response. These collective effects allow the T cell repertoire to respond to pathogens while suppressing autoimmunity due to circulating autoreactive T cells. Our computational studies show that increasing numbers of pathogenic peptides targeted by T cells during persistent or severe viral infections increase the probability of activating T cells that are weakly reactive to self-antigens (molecular mimicry). These T cells are easily re-activated by the self-antigens and contribute to exceeding the quorum threshold required to mount autoimmune responses. Rare peptides that activate many T cells are sampled more readily during severe/persistent infections than in acute infections, which amplifies these effects. Experiments in mice to test predictions from these mechanistic insights are suggested.

Systems immunology of regulatory T cells: can one circuit explain it all?

Regulatory T (Treg) cells play vital roles in immune homeostasis and response, including discrimination between self- and non-self-antigens, containment of immunopathology, and inflammation resolution. These diverse functions are orchestrated by cellular circuits involving Tregs and other cell types across space and time. Despite dramatic progress in our understanding of Treg biology, a quantitative framework capturing how Treg-containing circuits give rise to these diverse functions is lacking. Here, we propose that different facets of Treg function can be interpreted as distinct operating regimes of the same underlying circuit. We discuss how a systems immunology approach, involving quantitative experiments, computational modeling, and machine learning, can advance our understanding of Treg function, and help identify general operating and design principles underlying immune regulation.

CTLA4 depletes T cell endogenous and trogocytosed B7 ligands via cis-endocytosis

CD28 and CTLA4 are T cell coreceptors that competitively engage B7 ligands CD80 and CD86 to control adaptive immune responses. While the role of CTLA4 in restraining CD28 costimulatory signaling is well-established, the mechanism has remained unclear. Here, we report that human T cells acquire antigen-presenting-cell (APC)-derived B7 ligands and major histocompatibility complex (MHC) via trogocytosis through CD28:B7 binding. Acquired MHC and B7 enabled T cells to autostimulate, and this process was limited cell-intrinsically by CTLA4, which depletes B7 ligands trogocytosed or endogenously expressed by T cells through cis-endocytosis. Extending this model to the previously proposed extrinsic function of CTLA4 in human regulatory T cells (Treg), we show that blockade of either CD28 or CTLA4 attenuates Treg-mediated depletion of APC B7, indicating that trogocytosis and CTLA4-mediated cis-endocytosis work together to deplete B7 from APCs. Our study establishes CTLA4 as a cell-intrinsic molecular sink that limits B7 availability on the surface of T cells, with implications for CTLA4-targeted therapy.

Towards a quantitative theory of tolerance

A cornerstone of the classical view of tolerance is the elimination of self-reactive T cells via negative selection in the thymus. However, high-throughput T cell receptor (TCR) sequencing data have so far failed to detect substantial signatures of negative selection in the observed repertoires. In addition, quantitative estimates as well as recent experiments suggest that the elimination of self-reactive T cells is at best incomplete. We discuss several recent theoretical ideas that might explain tolerance while being consistent with these observations, including collective decision-making through quorum sensing, and sensitivity to change through dynamic tuning and adaptation. We propose that a unified quantitative theory of tolerance should combine these elements to help to explain the plasticity of the immune system and its robustness to autoimmunity.

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.

The Adaptation Model of Immunity: Signal IV Matters Most in Determining the Functional Outcomes of Immune Responses

Current research in immunology and immunotherapy is fully influenced by the self-nonself model of immunity. This theoretical model suggests that alloreactivity results in graft rejection, whereas tolerance toward self-antigens expressed by malignant cells facilitates cancer development. Similarly, breakage of immunological tolerance toward self-antigens results in autoimmune diseases. Accordingly, immune suppression is recommended for the management of autoimmune diseases, allergy, and organ transplantation, whereas immune inducers are used for the treatment of cancers. Although the danger model, the discontinuity model, and the adaptation model are proposed for a better understanding of the immune system, the self-nonself model continues to dominate the field. Nevertheless, a cure for these human diseases remains elusive. This essay discusses current theoretical models of immunity, as well as their impacts and limitations, and expands on the adaptation model of immunity to galvanize a new direction for the treatment of autoimmune diseases, organ transplantation, and cancer.

Retina-arrestin specific CD8+ T cells are not implicated in HLA-A29-positive birdshot chorioretinitis

BACKGROUND

HLA-A29-positive birdshot chorioretinitis (BCR) is an inflammatory eye disorder that is generally assumed to be caused by an autoimmune response to HLA-A29-presented peptides from retinal arrestin (SAG), yet the epitopes recognized by CD8+ T cells from patients remain to be identified.

OBJECTIVES

The identification of natural ligands of SAG presented by HLA-A29. To quantify CD8+ T cells reactive to antigenic SAG peptides presented by HLA-A29 in patients and controls.

METHODS

We performed mass-spectrometry based immunopeptidomics of HLA-A29 of antigen-presenting cell lines from patients engineered to express SAG. MHC-I Dextramer technology was utilised to determine expansion of antigen-specific CD8+ T cells reactive to SAG peptides in complex with HLA-A29 in a cohort of BCR patients, HLA-A29-positive controls, and HLA-A29-negative controls.

RESULTS

We report on the naturally presented antigenic SAG peptides identified by sequencing the HLA-A29 immunopeptidome of antigen-presenting cells of patients. We show that the N-terminally extended SAG peptide precursors can be trimmed in vitro by the antigen-processing aminopeptidases ERAP1 and ERAP2. Unexpectedly, no enhanced antigen engagement by CD8+ T cells upon stimulation with SAG peptides was observed in patients or HLA-A29-positive controls. Multiplexed HLA-A29-peptide dextramer profiling of a case-control cohort revealed that CD8+ T cells specific for these SAG peptides were neither detectable in peripheral blood nor in eye biopsies of patients.

CONCLUSIONS

Collectively, these findings demonstrate that SAG is not a CD8+ T cell autoantigen and sharply contrast the paradigm in the pathogenesis of BCR. Therefore, the mechanism by which HLA-A29 is associated with BCR does not involve SAG.

Quantifying changes in the T cell receptor repertoire during thymic development

One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4⁺ and CD8⁺ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.

Immunoregulation via Cell Density and Quorum Sensing-like Mechanisms: An Underexplored Emerging Field with Potential Translational Implications

Quorum sensing (QS) was historically described as a mechanism by which bacteria detect and optimize their population density via gene regulation based on dynamic environmental cues. Recently, it was proposed that QS or similar mechanisms may have broader applications across different species and cell types. Indeed, emerging evidence shows that the mammalian immune system can also elicit coordinated responses on a population level to regulate cell density and function, thus suggesting that QS-like mechanisms may also be a beneficial trait of the immune system. In this review, we explore and discuss potential QS-like mechanisms deployed by the immune system to coordinate cellular-level responses, such as T cell responses mediated via the common gamma chain (γc) receptor cytokines and the aryl hydrocarbon receptors (AhRs). We present evidence regarding a novel role of QS as a multifunctional mechanism coordinating CD4⁺ and CD8⁺ T cell behavior during steady state and in response to infection, inflammatory diseases, and cancer. Successful clinical therapies such as adoptive cell transfer for cancer treatment may be re-evaluated to harness the effects of the QS mechanism(s) and enhance treatment responsiveness. Moreover, we discuss how signaling threshold perturbations through QS-like mediators may result in disturbances of the complex crosstalk between immune cell populations, undesired T cell responses, and induction of autoimmune pathology. Finally, we discuss the potential therapeutic role of modulating immune-system-related QS as a promising avenue to treat human diseases.

The perception and response of T cells to a changing environment are based on the law of initial value

αβ T cells are critical components of the adaptive immune system and are capable of inducing sterilizing immunity after pathogen infection and eliminating transformed tumor cells. The development and function of T cells are controlled through the T cell antigen receptor, which recognizes peptides displayed on major histocompatibility complex (MHC) molecules. Here, we review how T cells generate the ability to recognize self-peptide-bound MHC molecules and use signals derived from these interactions to instruct cellular development, activation thresholds, and functional specialization in the steady state and during immune responses. We argue that the basic tenants of T cell development and function follow Weber-Fetcher's law of just noticeable differences and Wilder's law of initial value. Together, these laws argue that the ability of a system to respond and the quality of that response are scalable to the basal state of that system. Manifestation of these laws in T cells generates clone-specific activation thresholds that are based on perceivable differences between homeostasis and pathogen encounter (self versus nonself discrimination), as well as poised states for subsequent differentiation into specific effector cell lineages.

T cell immune responses deciphered

A machine-learning approach reveals antigen encoding that predicts T cell responses.

Defending and Integrating an Organism by the Immune System

The Integrity model proposes that the adaptive immune response defends, protects and keeps vigilance over the unity of an organism. These functions conceptually rely on three signals that can explain them. All signals have a dual character. The signal‐1 is the recognition of antigen or peptide/MHC ligand. The signal‐2 comprises either help and costimulation or suppression and coinhibition. Lastly, the signal‐3 signals tissues' condition, state or integrity. A part overlaps with the Danger‐associated molecular patterns, and the other part should be detected by putative cell‐surface molecules, intracellular factors or epigenetic events. They are called the Integrity‐associated molecular patterns (IAMPs). The IAMPs originate from damaged (positive signal‐3) or undamaged (negative signal‐3) tissues. The positive signal‐3 would induce costimulatory signal‐2, whereas the negative signal‐3 would induce coinhibitory signal‐2 in APCs. However, in analogue reality, we might more likely encounter a range of signals supposedly sensed by a group of responder cells and integrated overtime (quorum sensing). The predominant option would sway the decision of the immune system to perform either defence or protection (active tolerance). Thus, the quorum sensing supposedly delivers two qualitative thresholds for T (and B) cells' decisions to defend or suppress. If these were not attained, the vigilance (anergy) of adaptive immunocytes for T‐dependent antigens would ensue. These functions provide defence against pathogens and preservation of unity/integrity of an organism, which in turn permits protection of commensals.

Non-Stimulatory pMHC Enhance CD8 T Cell Effector Functions by Recruiting Coreceptor-Bound Lck

Under physiological conditions, CD8⁺ T cells need to recognize low numbers of antigenic pMHC class I complexes in the presence of a surplus of non-stimulatory, self pMHC class I on the surface of the APC. Non-stimulatory pMHC have been shown to enhance CD8⁺ T cell responses to low amounts of antigenic pMHC, in a phenomenon called co-agonism, but the physiological significance and molecular mechanism of this phenomenon are still poorly understood. Our data show that co-agonist pMHC class I complexes recruit CD8-bound Lck to the immune synapse to modulate CD8⁺ T cell signaling pathways, resulting in enhanced CD8⁺ T cell effector functions and proliferation, both in vitro and in vivo. Moreover, co-agonism can boost T cell proliferation through an extrinsic mechanism, with co-agonism primed CD8⁺ T cells enhancing Akt pathway activation and proliferation in neighboring CD8⁺ T cells primed with low amounts of antigen.

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.

Tregs self-organize into a computing ecosystem and implement a sophisticated optimization algorithm for mediating immune response

Regulatory T cells (Tregs) play a crucial role in mediating immune response. Yet an algorithmic understanding of the role of Tregs in adaptive immunity remains lacking. Here, we present a biophysically realistic model of Treg-mediated self-tolerance in which Tregs bind to self-antigens and locally inhibit the proliferation of nearby activated T cells. By exploiting a duality between ecological dynamics and constrained optimization, we show that Tregs tile the potential antigen space while simultaneously minimizing the overlap between Treg activation profiles. We find that for sufficiently high Treg diversity, Treg-mediated self-tolerance is robust to fluctuations in self-antigen concentrations but lowering the Treg diversity results in a sharp transition-related to the Gardner transition in perceptrons-to a regime where changes in self-antigen concentrations can result in an autoimmune response. We propose an experimental test of this transition in immune-deficient mice and discuss potential implications for autoimmune diseases.

Learning from HIV-1 to predict the immunogenicity of T cell epitopes in SARS-CoV-2

We describe a physics-based learning model for predicting the immunogenicity of cytotoxic T lymphocyte (CTL) epitopes derived from diverse pathogens including SARS-CoV-2. The model was trained and optimized on the relative immunodominance of CTL epitopes in human immunodeficiency virus infection. Its accuracy was tested against experimental data from patients with COVID-19. Our model predicts that only some SARS-CoV-2 epitopes predicted to bind to HLA molecules are immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but those from the SARS-CoV-2 spike protein alone are unlikely to do so. Our model also predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to seasonal coronaviruses circulating in the population and such cross-reactive CD8+ T cells can indeed be detected in prepandemic blood donors, suggesting that some level of CTL immunity against COVID-19 may be present in some individuals before SARS-CoV-2 infection.

Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2

We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given a Human Leukocyte Antigen (HLA) genotype. The model was trained and tested on experimental data on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. The method is more accurate than publicly available models. Our model predicts that only a fraction of SARS-CoV-2 epitopes that have been predicted to bind to HLA molecules is immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but the immunogenic epitopes in the SARS-CoV-2 spike protein alone are unlikely to do so. Our model predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to those contained in low-pathogenicity coronaviruses circulating in the population. Thus, we suggest that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.

Modes of Communication between T Cells and Relevance for Immune Responses

T cells are essential mediators of the adaptive immune system, which constantly patrol the body in search for invading pathogens. During an infection, T cells that recognise the pathogen are recruited, expand and differentiate into subtypes tailored to the infection. In addition, they differentiate into subsets required for short and long-term control of the pathogen, i.e., effector or memory. T cells have a remarkable degree of plasticity and heterogeneity in their response, however, their overall response to a given infection is consistent and robust. Much research has focused on how individual T cells are activated and programmed. However, in order to achieve a critical level of population-wide reproducibility and robustness, neighbouring cells and surrounding tissues have to provide or amplify relevant signals to tune the overall response accordingly. The characteristics of the immune response-stochastic on the individual cell level, robust on the global level-necessitate coordinated responses on a system-wide level, which facilitates the control of pathogens, while maintaining self-tolerance. This global coordination can only be achieved by constant cellular communication between responding cells, and faults in this intercellular crosstalk can potentially lead to immunopathology or autoimmunity. In this review, we will discuss how T cells mount a global, collective response, by describing the modes of T cell-T cell (T-T) communication they use and highlighting their physiological relevance in programming and controlling the T cell response.

Is T Cell Negative Selection a Learning Algorithm?

Our immune system can destroy most cells in our body, an ability that needs to be tightly controlled. To prevent autoimmunity, the thymic medulla exposes developing T cells to normal “self” peptides and prevents any responders from entering the bloodstream. However, a substantial number of self-reactive T cells nevertheless reaches the periphery, implying that T cells do not encounter all self peptides during this negative selection process. It is unclear if T cells can still discriminate foreign peptides from self peptides they haven’t encountered during negative selection. We use an “artificial immune system”—a machine learning model of the T cell repertoire—to investigate how negative selection could alter the recognition of self peptides that are absent from the thymus. Our model reveals a surprising new role for T cell cross-reactivity in this context: moderate T cell cross-reactivity should skew the post-selection repertoire towards peptides that differ systematically from self. Moreover, even some self-like foreign peptides can be distinguished provided that the peptides presented in the thymus are not too similar to each other. Thus, our model predicts that negative selection on a well-chosen subset of self peptides would generate a repertoire that tolerates even “unseen” self peptides better than foreign peptides. This effect would resemble a “generalization” process as it is found in learning systems. We discuss potential experimental approaches to test our theory.

Modeling cell-cell communication for immune systems across space and time

Communicating is crucial for cells to coordinate their behaviors. Immunological processes, involving diverse cytokines and cell types, are ideal for developing frameworks for modeling coordinated behaviors of cells. Here, we review recent studies that combine modeling and experiments to reveal how immune systems use autocrine, paracrine, and juxtacrine signals to achieve behaviors such as controlling population densities and hair regenerations. We explain that models are useful because one can computationally vary numerous parameters, in experimentally infeasible ways, to evaluate alternate immunological responses. For each model, we focus on the length-scales and time-scales involved and explain why integrating multiple length-scales and time-scales in a model remain challenging. We suggest promising modeling strategies for meeting this challenge and their practical consequences.

Theoretical modeling reveals that regulatory T cells increase T-cell interaction with antigen-presenting cells for stable immune tolerance

The immune system in tolerance maintains cell diversity without responding to self-antigens. Foxp3-expressing CD25+CD4+ regulatory T cells (Tregs) inhibit T-cell activation through various molecular mechanisms. However, several key questions are still not resolved, including how Tregs control the immune response on the basis of their self-skewed T-cell receptor repertoire and how Tregs avoid impeding relevant immunity against pathogens. Here, we show that Tregs promote the proliferation of conventional T cells in the presence of excessive co-stimulation when murine T cells are stimulated in vitro with allogeneic antigen-presenting cells (APCs). Antigen-specific Tregs increase the number of cells interacting with dendritic cells (DCs) by increasing the number of viable DCs and the expression of adhesion molecules on DCs. Theoretical simulations and mathematical models representing the dynamics of T-APC interaction and T-cell numbers in a lymph node indicate that Tregs reduce the dissociation probability of T cells from APCs and increase the new association. These functions contribute to tolerance by enhancing the interaction of low-affinity T cells with APCs. Supporting the theoretical analyses, we found that reducing the T-cell numbers in mice increases the ratio of specific T cells among CD4+ T cells after immunization and effectively induces autoimmune diabetes in non obese diabetes mice. Thus, as a critical function, antigen-specific Tregs stabilize the immune state, irrespective of it being tolerant or responsive, by augmenting T-APC interaction. We propose a novel regulation model in which stable tolerance with large heterogeneous populations proceeds to a specific immune response through a transient state with few populations.

The Potential Role of Quorum Sensing in Clonal Growth and Subsequent Expansion of Bone Marrow Stromal Cell Strains in Culture

Clonal development (clonogenicity) is an inherent property of a subset of postnatal bone marrow (BM) adherent stromal mesenchymal stem cells (MSCs) from which a multipotent progeny develops in culture. Our data suggest that clonogenicity and BM-MSC expansion are two distinct biological events. This hypothesis is based on the following observations: (1) the beginning of clonal growth is a property strictly dependent on serum and independent of the social context, (2) the expansion of individual clone is influenced by events deriving from a social context during initial growth, (3) clonogenic cells grown in a social context in presence of serum can emancipate themselves to generate a secondary different progeny, and (4) the ability of socially generated clones to develop an inherent potential for further growth suggests that quorum sensing may operate in BM-MSC cultures and determine the potential growth of clonal strains.

Towards multiscale modeling of the CD8+ T cell response to viral infections

The CD8⁺ T cell response is critical to the control of viral infections. Yet, defining the CD8⁺ T cell response to viral infections quantitatively has been a challenge. Following antigen recognition, which triggers an intracellular signaling cascade, CD8⁺ T cells can differentiate into effector cells, which proliferate rapidly and destroy infected cells. When the infection is cleared, they leave behind memory cells for quick recall following a second challenge. If the infection persists, the cells may become exhausted, retaining minimal control of the infection while preventing severe immunopathology. These activation, proliferation and differentiation processes as well as the mounting of the effector response are intrinsically multiscale and collective phenomena. Remarkable experimental advances in the recent years, especially at the single cell level, have enabled a quantitative characterization of several underlying processes. Simultaneously, sophisticated mathematical models have begun to be constructed that describe these multiscale phenomena, bringing us closer to a comprehensive description of the CD8⁺ T cell response to viral infections. Here, we review the advances made and summarize the challenges and opportunities ahead. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Cell Fates Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models.

Towards the development of human immune-system-on-a-chip platforms

Organ-on-a-chip (OoCs) platforms could revolutionize drug discovery and might ultimately become essential tools for precision therapy. Although many single-organ and interconnected systems have been described, the immune system has been comparatively neglected, despite its pervasive role in the body and the trend towards newer therapeutic products (i.e., complex biologics, nanoparticles, immune checkpoint inhibitors, and engineered T cells) that often cause, or are based on, immune reactions. In this review, we recapitulate some distinctive features of the immune system before reviewing microfluidic devices that mimic lymphoid organs or other organs and/or tissues with an integrated immune system component.

The expanding role of systems immunology in decoding the T cell receptor repertoire

T cells play a crucial role in the immune system's defense against many infectious diseases, including persistent infections for which no effective vaccines currently exist. The T cell component of the adaptive immune system is highly complex involving a constantly evolving landscape of various inter-related T cell populations. These T cell populations are characterized by their phenotypic and functional properties as well as the collection, or repertoire, of T cell receptors (TCR) that mediate T cell recognition of antigenic peptides derived from pathogens. Understanding the various processes and factors that impact the development and evolution of the broader T cell repertoire available to recognize and respond to pathogens and the characteristics of antigen-experienced T cell repertoires associated with effective immune control of pathogens is critical to the rational design of T cell-based vaccines and therapies. In this article we discuss, using examples of recent research, the promise that systems immunology approaches, involving quantitative analysis and mathematical and computational modeling of immunological data, hold for decoding the complex TCR repertoire system in the current era of advancing technologies.

The regulation of lymphocyte activation and proliferation

Activation induced proliferation and clonal expansion of antigen specific lymphocytes is a hallmark of the adaptive immune response to pathogens. Recent studies identify two distinct control phases. In the first T and B lymphocytes integrate antigen and additional costimuli to motivate a programmed proliferative burst that ceases with a return to cell quiescence and eventual death. This proliferative burst is autonomously timed, ensuring an appropriate response magnitude whilst preventing uncontrolled expansion. This initial response is subject to further modification and extension by a range of signals that modify, expand and direct the emergence of a rich array of new cell types. Thus, both robust clonal expansion of a small number of antigen specific T cells, and the concurrent emergence of extensive cellular diversity, confers immunity to a vast array of different pathogens. The in vivo response to a given pathogen is made up by the sum of all responding clones and is reproducible and pathogen specific. Thus, a precise description of the regulatory principles governing lymphocyte proliferation, differentiation and survival is essential to a unified understanding of the immune system.

IL-2 Modulates the TCR Signaling Threshold for CD8 but Not CD4 T Cell Proliferation on a Single-Cell Level

Lymphocytes integrate Ag and cytokine receptor signals to make cell fate decisions. Using a specific reporter of TCR signaling that is insensitive to cytokine signaling, Nur77-eGFP, we identify a sharp, minimal threshold of cumulative TCR signaling required for proliferation in CD4 and CD8 T cells that is independent of both Ag concentration and affinity. Unexpectedly, IL-2 reduces this threshold in CD8 but not CD4 T cells, suggesting that integration of multiple mitogenic inputs may alter the minimal requirement for TCR signaling in CD8 T cells. Neither naive CD4 nor naive CD8 T cells are responsive to low doses of IL-2. We show that activated CD8 T cells become responsive to low doses of IL-2 more quickly than CD4 T cells, and propose that this relative delay in turn accounts for the differential effects of IL-2 on the minimal TCR signaling threshold for proliferation in these populations. In contrast to Nur77-eGFP, c-Myc protein expression integrates mitogenic signals downstream of both IL-2 and the TCR, yet marks an invariant minimal threshold of cumulative mitogenic stimulation required for cell division. Our work provides a conceptual framework for understanding the regulation of clonal expansion of CD8 T cells by subthreshold TCR signaling in the context of mitogenic IL-2 signals, thereby rendering CD8 T cells exquisitely dependent upon environmental cues. Conversely, CD4 T cell proliferation requires an invariant minimal intensity of TCR signaling that is not modulated by IL-2, thereby restricting responses to low-affinity or low-abundance self-antigens even in the context of an inflammatory milieu.

MHC class I-associated peptides derive from selective regions of the human genome

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology.

Complete integrability of information processing by biochemical reactions

Statistical mechanics provides an effective framework to investigate information processing in biochemical reactions. Within such framework far-reaching analogies are established among (anti-) cooperative collective behaviors in chemical kinetics, (anti-)ferromagnetic spin models in statistical mechanics and operational amplifiers/flip-flops in cybernetics. The underlying modeling - based on spin systems - has been proved to be accurate for a wide class of systems matching classical (e.g. Michaelis-Menten, Hill, Adair) scenarios in the infinite-size approximation. However, the current research in biochemical information processing has been focusing on systems involving a relatively small number of units, where this approximation is no longer valid. Here we show that the whole statistical mechanical description of reaction kinetics can be re-formulated via a mechanical analogy - based on completely integrable hydrodynamic-type systems of PDEs - which provides explicit finite-size solutions, matching recently investigated phenomena (e.g. noise-induced cooperativity, stochastic bi-stability, quorum sensing). The resulting picture, successfully tested against a broad spectrum of data, constitutes a neat rationale for a numerically effective and theoretically consistent description of collective behaviors in biochemical reactions.

Affinity and dose of TCR engagement yield proportional enhancer and gene activity in CD4+ T cells

Affinity and dose of T cell receptor (TCR) interaction with antigens govern the magnitude of CD4+ T cell responses, but questions remain regarding the quantitative translation of TCR engagement into downstream signals. We find that while the response of mouse CD4+ T cells to antigenic stimulation is bimodal, activated cells exhibit analog responses proportional to signal strength. Gene expression output reflects TCR signal strength, providing a signature of T cell activation. Expression changes rely on a pre-established enhancer landscape and quantitative acetylation at AP-1 binding sites. Finally, we show that graded expression of activation genes depends on ERK pathway activation, suggesting that an ERK-AP-1 axis plays an important role in translating TCR signal strength into proportional activation of enhancers and genes essential for T cell function.

DOI:http://dx.doi.org/10.7554/eLife.10134.001

T helper cells recognize and respond to bacteria, viruses and other invading microbes and thus play a central role in the adaptive immune system. These cells have a receptor on their surface that binds to fragments of proteins – known as oligopeptides – from the microbes that have been digested and presented on the surfaces of other immune cells. Once active, T helper cells multiply, grow and release signals that regulate genes in other cells to promote immune responses. Previous studies suggest that a T helper cell’s response is binary – that is, either on or off. However, this does not explain how the strength of the T cell response to infection can vary.

Allison et al. used a technique called high-throughput sequencing to examine the activity of genes in T helper cells from mice that had been genetically engineered to only produce one type of T cell receptor. For the experiments, the T cells were exposed to various concentrations of different peptides known to bind either well or poorly to the receptor. Allison et al. found that, once activated, the response of an individual T cell was not binary, but instead was related to the strength of the signal it received through its receptor.

Further experiments showed that although a subset of the genes activated in T helper cells do respond in a binary fashion, the activities of many other genes involved in immune responses and cell metabolism were related to the strength of the signal from the receptor. This “analog” gene activation depends on the level of activity of the MAP kinase signaling pathway. Together, Allison et al.’s findings help us to understand how T cells are able to fine-tune immune responses to invading microbes. The next challenge will be to investigate the mechanisms underlying binary and analog gene activity in T cells.

DOI:http://dx.doi.org/10.7554/eLife.10134.002

Memory T cell-driven differentiation of naive cells impairs adoptive immunotherapy

Adoptive cell transfer (ACT) of purified naive, stem cell memory, and central memory T cell subsets results in superior persistence and antitumor immunity compared with ACT of populations containing more-differentiated effector memory and effector T cells. Despite a clear advantage of the less-differentiated populations, the majority of ACT trials utilize unfractionated T cell subsets. Here, we have challenged the notion that the mere presence of less-differentiated T cells in starting populations used to generate therapeutic T cells is sufficient to convey their desirable attributes. Using both mouse and human cells, we identified a T cell-T cell interaction whereby antigen-experienced subsets directly promote the phenotypic, functional, and metabolic differentiation of naive T cells. This process led to the loss of less-differentiated T cell subsets and resulted in impaired cellular persistence and tumor regression in mouse models following ACT. The T memory-induced conversion of naive T cells was mediated by a nonapoptotic Fas signal, resulting in Akt-driven cellular differentiation. Thus, induction of Fas signaling enhanced T cell differentiation and impaired antitumor immunity, while Fas signaling blockade preserved the antitumor efficacy of naive cells within mixed populations. These findings reveal that T cell subsets can synchronize their differentiation state in a process similar to quorum sensing in unicellular organisms and suggest that disruption of this quorum-like behavior among T cells has potential to enhance T cell-based immunotherapies.

Immune Tolerance Maintained by Cooperative Interactions between T Cells and Antigen Presenting Cells Shapes a Diverse TCR Repertoire

The T cell population in an individual needs to avoid harmful activation by self peptides while maintaining the ability to respond to an unknown set of foreign peptides. This property is acquired by a combination of thymic and extra-thymic mechanisms. We extend current models for the development of self/non-self discrimination to consider the acquisition of self-tolerance as an emergent system level property of the overall T cell receptor repertoire. We propose that tolerance is established at the level of the antigen presenting cell/T cell cluster, which facilitates and integrates cooperative interactions between T cells of different specificities. The threshold for self-reactivity is therefore imposed at a population level, and not at the level of the individual T cell/antigen encounter. Mathematically, the model can be formulated as a linear programing optimization problem that can be implemented as a multiplicative update algorithm, which shows a rapid convergence to a stable state. The model constrains self-reactivity within a predefined threshold, but maintains repertoire diversity and cross reactivity which are key characteristics of human T cell immunity. We show further that the size of individual clones in the model repertoire becomes heterogeneous, and that new clones can establish themselves even when the repertoire has stabilized. Our study combines the salient features of the “danger” model of self/non-self discrimination with the concepts of quorum sensing, and extends repertoire generation models to encompass the establishment of tolerance. Furthermore, the dynamic and continuous repertoire reshaping, which underlies tolerance in this model, suggests opportunities for therapeutic intervention to achieve long-term tolerance following transplantation.

The role of T cell receptor signaling thresholds in guiding T cell fate decisions

Canonical T cell receptor signal transduction has been extensively studied and dissected in cell lines and primary lymphocytes. However, a static depiction of this signaling cascade fails to capture the complex and dynamic process by which individual T cells discriminate TCR:peptide-MHC affinity, then integrate signals over time to drive discrete cellular behaviors such as thymic selection, proliferation, and cytokine production. Recent technological advances have made it possible to study complex lymphocyte behavior on a single cell level and are revealing how T cells interpret information about affinity and abundance of antigen in order to make life-and-death cell fate decisions individually and collectively.

Optimal T-cell receptor affinity for inducing autoimmunity

T-cell receptor affinity for self-antigen has an important role in establishing self-tolerance. Three transgenic mouse strains expressing antigens of variable affinity for the OVA transgenic-I T-cell receptor were generated to address how TCR affinity affects the efficiency of negative selection, the ability to prime an autoimmune response, and the elimination of the relevant target cell. Mice expressing antigens with an affinity just above the negative selection threshold exhibited the highest risk of developing experimental autoimmune diabetes. The data demonstrate that close to the affinity threshold for negative selection, sufficient numbers of self-reactive T cells escape deletion and create an increased risk for the development of autoimmunity.

Modeling the T cell immune response: a fascinating challenge

The immune system is designed to protect the organism from infection and to repair damaged tissue. An effective response requires recognition of the threat, the appropriate effector mechanism to clear the pathogen and a return to homeostasis with minimal damage to self-tissues. T cells play a central role in orchestrating the immune response at all stages of the response and have been the subject of intense study by both experimental immunologists and modelers. This review examines some of the more critical questions in T cell biology and describes the latest attempts to address those questions using approaches that combine mathematical modeling and experiments.

A sharp T-cell antigen receptor signaling threshold for T-cell proliferation

T-cell antigen receptor (TCR) signaling is essential for activation, proliferation, and effector function of T cells. Modulation of both intensity and duration of TCR signaling can regulate these events. However, it remains unclear how individual T cells integrate such signals over time to make critical cell-fate decisions. We have previously developed an engineered mutant allele of the critical T-cell kinase zeta-chain-associated protein kinase 70 kDa (Zap70) that is catalytically inhibited by a small molecule inhibitor, thereby blocking TCR signaling specifically and efficiently. We have also characterized a fluorescent reporter Nur77-eGFP transgenic mouse line in which T cells up-regulate GFP uniquely in response to TCR stimulation. The combination of these technologies unmasked a sharp TCR signaling threshold for commitment to cell division both in vitro and in vivo. Further, we demonstrate that this threshold is independent of both the magnitude of the TCR stimulus and Interleukin 2. Similarly, we identify a temporal threshold of TCR signaling that is required for commitment to proliferation, after which T cells are able to proliferate in a Zap70 kinase-independent manner. Taken together, our studies reveal a sharp threshold for the magnitude and duration of TCR signaling required for commitment of T cells to proliferation. These results have important implications for understanding T-cell responses to infection and optimizing strategies for immunomodulatory drug delivery.

Theories and quantification of thymic selection

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