Mapping the SLP76 interactome in T cells lacking each of the GRB2-family adaptors reveals molecular plasticity of the TCR signaling pathway.

The propagation and diversification of signals downstream of the T cell receptor (TCR) involve several adaptor proteins that control the assembly of multimolecular signaling complexes (signalosomes). The global characterization of changes in protein-protein interactions (PPI) following genetic perturbations is critical to understand the resulting phenotypes. Here, by combining genome editing techniques in T cells and interactomics studies based on affinity purification coupled to mass spectrometry (AP-MS) analysis, we determined and quantified the molecular reorganization of the SLP76 interactome resulting from the ablation of each of the three GRB2-family adaptors. Our data showed that the absence of GADS or GRB2 induces a major remodeling of the PPI network associated with SLP76 following TCR engagement. Unexpectedly, this PPI network rewiring minimally affects proximal molecular events of the TCR signaling pathway. Nevertheless, during prolonged TCR stimulation, GRB2- and GADS-deficient cells displayed a reduced level of activation and cytokine secretion capacity. Using the canonical SLP76 signalosome, this analysis highlights the plasticity of PPI networks and their reorganization following specific genetic perturbations.

Kinetic proofreading through the multi-step activation of the ZAP70 kinase underlies early T cell ligand discrimination.

T cells recognize a few high-affinity antigens among a vast array of lower affinity antigens. According to the kinetic proofreading model, antigen discrimination properties could be explained by the gradual amplification of small differences in binding affinities as the signal is transduced downstream of the T cell receptor. Which early molecular events are affected by ligand affinity, and how, has not been fully resolved. Here, we used time-resolved high-throughput proteomic analyses to identify and quantify the phosphorylation events and protein-protein interactions encoding T cell ligand discrimination in antigen-experienced T cells. Although low-affinity ligands induced phosphorylation of the Cd3 chains of the T cell receptor and the interaction of Cd3 with the Zap70 kinase as strongly as high-affinity ligands, they failed to activate Zap70 to the same extent. As a result, formation of the signalosome of the Lat adaptor was severely impaired with low- compared with high-affinity ligands, whereas formation of the signalosome of the Cd6 receptor was affected only partially. Overall, this study provides a comprehensive map of molecular events associated with T cell ligand discrimination.

Systems-level conservation of the proximal TCR signaling network of mice and humans.

We exploited traceable gene tagging in primary human T cells to establish the composition and dynamics of seven canonical TCR-induced protein signaling complexes (signalosomes) using affinity purification coupled with mass spectrometry (AP-MS). It unveiled how the LAT adaptor assembles higher-order molecular condensates and revealed that the proximal TCR-signaling network has a high degree of qualitative and quantitative conservation between human CD4+ and CD8+ T cells. Such systems-level conservation also extended across human and mouse T cells and unexpectedly encompassed protein-protein interaction stoichiometry. Independently of evolutionary considerations, our study suggests that a drug targeting the proximal TCR signaling network should behave similarly when applied to human and mouse T cells. However, considering that signaling differences likely exist between the distal TCR-signaling pathway of human and mouse, our fast-track AP-MS approach should be favored to determine the mechanism of action of drugs targeting human T cell activation. An opportunity is illustrated here using an inhibitor of the LCK protein tyrosine kinase as a proof-of-concept.

The T cell CD6 receptor operates a multitask signalosome with opposite functions in T cell activation.

To determine the respective contribution of the LAT transmembrane adaptor and CD5 and CD6 transmembrane receptors to early TCR signal propagation, diversification, and termination, we describe a CRISPR/Cas9-based platform that uses primary mouse T cells and permits establishment of the composition of their LAT, CD5, and CD6 signalosomes in only 4 mo using quantitative mass spectrometry. We confirmed that positive and negative functions can be solely assigned to the LAT and CD5 signalosomes, respectively. In contrast, the TCR-inducible CD6 signalosome comprised both positive (SLP-76, ZAP70, VAV1) and negative (UBASH3A/STS-2) regulators of T cell activation. Moreover, CD6 associated independently of TCR engagement to proteins that support its implication in inflammatory pathologies necessitating T cell transendothelial migration. The multifaceted role of CD6 unveiled here accounts for past difficulties in classifying it as a coinhibitor or costimulator. Congruent with our identification of UBASH3A within the CD6 signalosome and the view that CD6 constitutes a promising target for autoimmune disease treatment, single-nucleotide polymorphisms associated with human autoimmune diseases have been found in the Cd6 and Ubash3a genes.

LymphoAtlas: a dynamic and integrated phosphoproteomic resource of TCR signaling in primary T cells reveals ITSN2 as a regulator of effector functions.

T-cell receptor (TCR) ligation-mediated protein phosphorylation regulates the activation, cellular responses, and fates of T cells. Here, we used time-resolved high-resolution phosphoproteomics to identify, quantify, and characterize the phosphorylation dynamics of thousands of phosphorylation sites in primary T cells during the first 10 min after TCR stimulation. Bioinformatic analysis of the data revealed a coherent orchestration of biological processes underlying T-cell activation. In particular, functional modules associated with cytoskeletal remodeling, transcription, translation, and metabolic processes were mobilized within seconds after TCR engagement. Among proteins whose phosphorylation was regulated by TCR stimulation, we demonstrated, using a fast-track gene inactivation approach in primary lymphocytes, that the ITSN2 adaptor protein regulated T-cell effector functions. This resource, called LymphoAtlas, represents an integrated pipeline to further decipher the organization of the signaling network encoding T-cell activation. LymphoAtlas is accessible to the community at: https://bmm-lab.github.io/LymphoAtlas.

Quantitative interactomics in primary T cells unveils TCR signal diversification extent and dynamics.

The activation of T cells by the T cell antigen receptor (TCR) results in the formation of signaling protein complexes (signalosomes), the composition of which has not been analyzed at a systems level. Here, we isolated primary CD4+ T cells from 15 gene-targeted mice, each expressing one tagged form of a canonical protein of the TCR-signaling pathway. Using affinity purification coupled with mass spectrometry, we analyzed the composition and dynamics of the signalosomes assembling around each of the tagged proteins over 600 s of TCR engagement. We showed that the TCR signal-transduction network comprises at least 277 unique proteins involved in 366 high-confidence interactions, and that TCR signals diversify extensively at the level of the plasma membrane. Integrating the cellular abundance of the interacting proteins and their interaction stoichiometry provided a quantitative and contextual view of each documented interaction, permitting anticipation of whether ablation of a single interacting protein can impinge on the whole TCR signal-transduction network.

CD5, an Undercover Regulator of TCR Signaling.

T cells are critical components of adaptive immunity. As such, their activation is regulated by the T cell receptor (TCR) that constantly scan peptides associated with major histocompatibility complexes (MHC). TCR engagement initiates a series of molecular events leading to cytokine secretion, proliferation, and differentiation of T cells. As a second coincident event, activation of co-stimulatory molecules, such as CD28, synergize with the TCR in order to prolong and/or amplify intracellular signals. With the recent advances in immunotherapies targeting T cells, co-inhibitory receptors are of growing interest for immunologists due to their potential modulatory properties on T cell functions. However, special attention should be dedicated to avoid unwanted clinical outcomes (1). In particular, Manichean categorization of receptors based on incomplete functional knowledge can lead to an over-simplistic view of complex cellular regulations. Thus, analysis of the functions that characterize these receptors in diverse physiological contexts remains essential for their rational use in therapeutic protocols. Here we focus on CD5, a transmembrane receptor that regulates T cell functions and development but remains poorly characterized at the molecular level. We will review its roles in physiological conditions and suggest potential molecular effectors that could account for CD5-dependent regulation of TCR signaling.

Co-recruitment analysis of the CBL and CBLB signalosomes in primary T cells identifies CD5 as a key regulator of TCR-induced ubiquitylation.

T-cell receptor (TCR) signaling is essential for the function of T cells and negatively regulated by the E3 ubiquitin-protein ligases CBL and CBLB Here, we combined mouse genetics and affinity purification coupled to quantitative mass spectrometry to monitor the dynamics of the CBL and CBLB signaling complexes that assemble in normal T cells over 600 seconds of TCR stimulation. We identify most previously known CBL and CBLB interacting partners, as well as a majority of proteins that have not yet been implicated in those signaling complexes. We exploit correlations in protein association with CBL and CBLB as a function of time of TCR stimulation for predicting the occurrence of direct physical association between them. By combining co-recruitment analysis with biochemical analysis, we demonstrated that the CD5 transmembrane receptor constitutes a key scaffold for CBL- and CBLB-mediated ubiquitylation following TCR engagement. Our results offer an integrated view of the CBL and CBLB signaling complexes induced by TCR stimulation and provide a molecular basis for their negative regulatory function in normal T cells.

T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens.

T lymphocytes' ability to discriminate between structurally related antigens has been attributed to the unique signaling properties of the T cell receptor. However, recent studies have suggested that the output of this discrimination process is conditioned by environmental cues. Here, we demonstrate how the IL-2 cytokine, collectively generated by strongly activated T cell clones, can induce weaker T cell clones to proliferate. We identify the PI3K pathway as being critical for integrating the antigen and cytokine responses and for controlling cell-cycle entry. We build a hybrid stochastic/deterministic computational model that accounts for such signal synergism and demonstrates quantitatively how T cells tune their cell-cycle entry according to environmental cytokine cues. Our findings indicate that antigen discrimination by T cells is not solely an intrinsic cellular property but rather a product of integration of multiple cues, including local cues such as antigen quality and quantity, to global ones like the extracellular concentration of inflammatory cytokines.

T cells translate individual, quantal activation into collective, analog cytokine responses via time-integrated feedbacks.

Variability within isogenic T cell populations yields heterogeneous 'local' signaling responses to shared antigenic stimuli, but responding clones may communicate 'global' antigen load through paracrine messengers, such as cytokines. Such coordination of individual cell responses within multicellular populations is critical for accurate collective reactions to shared environmental cues. However, cytokine production may saturate as a function of antigen input, or be dominated by the precursor frequency of antigen-specific T cells. Surprisingly, we found that T cells scale their collective output of IL-2 to total antigen input over a large dynamic range, independently of population size. Through experimental quantitation and computational modeling, we demonstrate that this scaling is enforced by an inhibitory cross-talk between antigen and IL-2 signaling, and a nonlinear acceleration of IL-2 secretion per cell. Our study reveals how time-integration of these regulatory loops within individual cell signaling generates scaled collective responses and can be leveraged for immune monitoring. DOI: http://dx.doi.org/10.7554/eLife.01944.001.

Annular PIP3 accumulation controls actin architecture and modulates cytotoxicity at the immunological synapse.

The immunological synapse formed by a T lymphocyte on the surface of a target cell contains a peripheral ring of filamentous actin (F-actin) that promotes adhesion and facilitates the directional secretion of cytokines and cytolytic factors. We show that growth and maintenance of this F-actin ring is dictated by the annular accumulation of phosphatidylinositol trisphosphate (PIP3) in the synaptic membrane. PIP3 functions in this context by recruiting the exchange factor Dock2 to the periphery of the synapse, where it drives actin polymerization through the Rho-family GTPase Rac. We also show that synaptic PIP3 is generated by class IA phosphoinositide 3-kinases that associate with T cell receptor microclusters and are activated by the GTPase Ras. Perturbations that inhibit or promote PIP3-dependent F-actin remodeling dramatically affect T cell cytotoxicity, demonstrating the functional importance of this pathway. These results reveal how T cells use lipid-based signaling to control synaptic architecture and modulate effector responses.

Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death.

Populations of 'identical' cells are rarely truly identical. Even when in the same state of differentiation, isogenic cells may vary in expression of key signaling regulators, activate signal transduction at different thresholds, and consequently respond heterogeneously to a given stimulus. Here, we review how new experimental and analytical techniques are suited to connect these different levels of variability, quantitatively mapping the effects of cell-to-cell variability on cellular decision-making. In particular, we summarize how this helps classify signaling regulators according to the impact of their variability on biological functions. We further discuss how variability can also be leveraged to shed light on the molecular mechanisms regulating cellular signaling, from the individual cell to the population of cells as a whole.

Cell-to-cell variability analysis dissects the plasticity of signaling of common γ chain cytokines in T cells.

Natural variability in the abundance of signaling regulators can lead to divergence in cell fate, even within genetically identical cells that share a common differentiation state. We introduce cell-to-cell variability analysis (CCVA), an experimental and computational methodology that quantifies the correlation between variability in signaling regulator abundance and variation in the sensitivity of cells to stimuli. With CCVA, we investigated the unexpected effects of the interleukin 2 (IL-2) receptor α chain (IL-2Rα) on the sensitivity of primary mouse T lymphocytes to cytokines that signal through receptors that have the common γ chain (γ(c)). Our work showed that increased IL-2Rα abundance decreased the concentration of IL-2 required for a half-maximal activation (EC(50)) of the downstream effector signal transducer and activator of transcription 5 (STAT5), but reduced the responsiveness to IL-7 or IL-15, without affecting the EC(50) values of other γ(c) cytokines. To investigate the mechanism of the effect of IL-2Rα on γ(c) cytokine signaling, we introduced a Bayesian-inference computational framework that models the formation of receptor signaling complexes with data from previous biophysical measurements. With this framework, we found that a model in which IL-2Rα drives γ(c) depletion through the assembly of functional IL-2R complexes was consistent with both the CCVA data and experimental measurements. The combination of CCVA and computational modeling produced quantitative understanding of the crosstalk between γ(c) cytokine receptor signaling in T lymphocytes.

Phenotypic model for early T-cell activation displaying sensitivity, specificity, and antagonism.

Early T-cell activation is selected by evolution to discriminate a few foreign peptides rapidly from a vast excess of self-peptides, and it is unclear in quantitative terms how this is possible. We show that a generic proofreading cascade supplemented by a single negative feedback mediated by the Src homology 2 domain phosphatase-1 (SHP-1) accounts quantitatively for early T-cell activation, including the effects of antagonists. Modulation of the negative feedback with SHP-1 concentration explains counterintuitive experimental observations, such as the nonmonotonic behavior of receptor activity on agonist concentration, the digital vs. continuous behavior on certain parameters, and the loss of response for high SHP-1 concentration. New experiments validate predictions on the nontrivial joint dependence on binding time and concentration for the relative effect of two antagonists: We explain why strong antagonists behave as partial agonists at low concentration and predict that the relative effect of antagonists can invert as their concentrations are varied. By focusing on the phenotype, our model quantitatively fits a body of experimental data with minimal variables and parameters.

Noninvasive inference of the molecular chemotactic response using bacterial trajectories.

The quality of sensing and response to external stimuli constitutes a basic element in the selective performance of living organisms. Here we consider the response of Escherichia coli to chemical stimuli. For moderate amplitudes, the bacterial response to generic profiles of sensed chemicals is reconstructed from its response function to an impulse, which then controls the efficiency of bacterial motility. We introduce a method for measuring the impulse response function based on coupling microfluidic experiments and inference methods: The response function is inferred using Bayesian methods from the observed trajectories of bacteria swimming in microfluidically controlled chemical fields. The notable advantages are that the method is based on the bacterial swimming response, it is noninvasive, without any genetic and/or mechanical preparation, and assays the behavior of the whole flagella bundle. We exploit the inference method to measure responses to aspartate and α-methylaspartate--measured previously by other methods--as well as glucose, leucine, and serine. The response to the attractant glucose is shown to be biphasic and perfectly adapted, as for aspartate. The response to the attractant serine is shown to be biphasic yet imperfectly adapted, that is, the response function has a nonzero (positive) integral. The adaptation of the response to the repellent leucine is also imperfect, with the sign of the two phases inverted with respect to serine. The diversity in the bacterial population of the response function and its dependency upon the background concentration are quantified.

Quantifying biomolecule diffusivity using an optimal Bayesian method.

We propose a Bayesian method to extract the diffusivity of biomolecules evolving freely or inside membrane microdomains. This approach assumes a model of motion for the particle considered, namely free Brownian motion or confined diffusion. In each framework, a systematic Bayesian scheme is provided for estimating the diffusivity. We show that this method reaches the best performances theoretically achievable. Its efficiency overcomes that of widely used methods based on the analysis of the mean-square displacement. The approach presented here also gives direct access to the uncertainty on the estimation of the diffusivity and predicts the number of steps of the trajectory necessary to achieve any desired precision. Its robustness with respect to noise on the position of the biomolecule is also investigated.