Multisite Phosphorylation Modulates the T Cell Receptor ζ-Chain Potency but not the Switchlike Response

An evolutionary divergent thermodynamic brake in ZAP-70 fine-tunes the kinetic proofreading in T cells

T cell signaling starts with assembling several tyrosine kinases and adaptor proteins to the T cell receptor (TCR), following the antigen-binding to the TCR. The stability of the TCR-antigen complex and the delay between the recruitment and activation of each kinase determines the T cell response. Integration of such delays constitutes a kinetic proofreading mechanism to regulate T cell response to the antigen binding. However, the mechanism of these delays is not fully understood. Combining biochemical experiments and kinetic modelling, here we report a thermodynamic brake in the regulatory module of the tyrosine kinase ZAP-70, which determines the ligand selectivity, and may delay the ZAP-70 activation upon antigen binding to TCR. The regulatory module of ZAP-70 comprises of a tandem SH2 (tSH2) domain that binds to its ligand, doubly-phosphorylated ITAM peptide (ITAM-Y2P), in two kinetic steps: a fast step and a slow step. We show the initial encounter complex formation between the ITAM-Y2P and tSH2 domain follows a fast-kinetic step, whereas the conformational transition to the holo-state follows a slow-kinetic step. We further observed a thermodynamic penalty imposed during the second phosphate-binding event reduces the rate of structural transition to the holo-state. Phylogenetic analysis revealed the evolution of the thermodynamic brake coincides with the divergence of the adaptive immune system to the cell-mediated and humoral responses. In addition, the paralogous kinase Syk expressed in B cells does not possess such a functional thermodynamic brake, which may explain the higher basal activation and lack of ligand selectivity in Syk.

A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy

Chimeric antigen receptor (CAR) T-cell therapy is an immunotherapy that has recently become highly instrumental in the fight against life-threatening diseases. A variety of modeling and computational simulation efforts have addressed different aspects of CAR T-cell therapy, including T-cell activation, T- and malignant cell population dynamics, therapeutic cost-effectiveness strategies, and patient survival. In this article, we present a systematic review of those efforts, including mathematical, statistical, and stochastic models employing a wide range of algorithms, from differential equations to machine learning. To the best of our knowledge, this is the first review of all such models studying CAR T-cell therapy. In this review, we provide a detailed summary of the strengths, limitations, methodology, data used, and data gap in currently published models. This information may help in designing and building better models for enhanced prediction and assessment of the benefit-risk balance associated with novel CAR T-cell therapies, as well as with the data need for building such models.

Intrinsic Disorder in the T Cell Receptor Creates Cooperativity and Controls ZAP70 Binding

Many immunoreceptors have cytoplasmic domains that are intrinsically disordered (i.e., have high configurational entropy), have multiple sites of posttranslational modification (e.g., tyrosine phosphorylation), and participate in nonlinear signaling pathways (e.g., exhibiting switch-like behavior). Several hypotheses to explain the origin of these nonlinearities fall under the broad hypothesis that modification at one site changes the immunoreceptor’s entropy, which in turn changes further modification dynamics. Here, we use coarse-grain simulation to study three scenarios, all related to the chains that constitute the T cell receptor (TCR). We find that first, if phosphorylation induces local changes in the flexibility of the TCR ζ-chain, this naturally leads to rate enhancements and cooperativity. Second, we find that TCR CD3ɛ can provide a switch by modulating its residence in the plasma membrane. By constraining our model to be consistent with the previous observation that both basic residues and phosphorylation control membrane residence, we find that there is only a moderate rate enhancement of 10% between first and subsequent phosphorylation events. Third, we find that volume constraints do not limit the number of ZAP70s that can bind the TCR but that entropic penalties lead to a 200-fold decrease in binding rate by the seventh ZAP70, potentially explaining the observation that each TCR has around six ZAP70 molecules bound after receptor triggering. In all three scenarios, our results demonstrate that phenomena that change an immunoreceptor chain’s entropy (stiffening, confinement to a membrane, and multiple simultaneous binding) can lead to nonlinearities (rate enhancement, switching, and negative cooperativity) in how the receptor participates in signaling. These polymer-entropy-driven nonlinearities may augment the nonlinearities that arise from, e.g., kinetic proofreading and cluster formation. They also suggest different design strategies for engineered receptors, e.g., whether or not to put signaling modules on one chain or multiple clustered chains.

Understanding the Dynamics of T-Cell Activation in Health and Disease Through the Lens of Computational Modeling

T cells in the immune system are activated by binding to foreign peptides (from an external pathogen) or mutant peptide (derived from endogenous proteins) displayed on the surface of a diseased cell. This triggers a series of intracellular signaling pathways, which ultimately dictate the response of the T cell. The insights from computational models have greatly improved our understanding of the mechanisms that control T-cell activation. In this review, we focus on the use of ordinary differential equation–based mechanistic models to study T-cell activation. We highlight several examples that demonstrate the models’ utility in answering specific questions related to T-cell activation signaling, from antigen discrimination to the feedback mechanisms that initiate transcription factor activation. In addition, we describe other modeling approaches that can be combined with mechanistic models to bridge time scales and better understand how intracellular signaling events, which occur on the order of seconds to minutes, influence phenotypic responses of T-cell activation, which occur on the order of hours to days. Overall, through concrete examples, we emphasize how computational modeling can be used to enable the rational design and optimization of immunotherapies.

Stimulation strength controls the rate of initiation but not the molecular organisation of TCR-induced signalling

Millions of naïve T cells with different TCRs may interact with a peptide-MHC ligand, but very few will activate. Remarkably, this fine control is orchestrated using a limited set of intracellular machinery. It remains unclear whether changes in stimulation strength alter the programme of signalling events leading to T cell activation. Using mass cytometry to simultaneously measure multiple signalling pathways during activation of murine CD8+ T cells, we found a programme of distal signalling events that is shared, regardless of the strength of TCR stimulation. Moreover, the relationship between transcription of early response genes Nr4a1 and Irf8 and activation of the ribosomal protein S6 is also conserved across stimuli. Instead, we found that stimulation strength dictates the rate with which cells initiate signalling through this network. These data suggest that TCR-induced signalling results in a coordinated activation program, modulated in rate but not organization by stimulation strength.

The Influence of Molecular Reach and Diffusivity on the Efficacy of Membrane-Confined Reactions

Signaling by surface receptors often relies on tethered reactions whereby an enzyme bound to the cytoplasmic tail of a receptor catalyzes reactions on substrates within reach. The overall length and stiffness of the receptor tail, the enzyme, and the substrate determine a biophysical parameter termed the molecular reach of the reaction. This parameter determines the probability that the receptor-tethered enzyme will contact the substrate in the volume proximal to the membrane when separated by different distances within the membrane plane. In this work, we develop particle-based stochastic reaction-diffusion models to study the interplay between molecular reach and diffusion. We find that increasing the molecular reach can increase reaction efficacy for slowly diffusing receptors, whereas for rapidly diffusing receptors, increasing molecular reach reduces reaction efficacy. In contrast, if reactions are forced to take place within the two-dimensional plasma membrane instead of the three-dimensional volume proximal to it or if molecules diffuse in three dimensions, increasing molecular reach increases reaction efficacy for all diffusivities. We show results in the context of immune checkpoint receptors (PD-1 dephosphorylating CD28), a standard opposing kinase-phosphatase reaction, and a minimal two-particle model. The work highlights the importance of the three-dimensional nature of many two-dimensional membrane-confined interactions, illustrating a role for molecular reach in controlling biochemical reactions.

Molecular mechanisms of T cell sensitivity to antigen

T cells initiate and regulate adaptive immune responses that can clear infections. To do this, they use their T cell receptors (TCRs) to continually scan the surfaces of other cells for cognate peptide antigens presented on major histocompatibility complexes (pMHCs). Experimental work has established that as few 1-10 pMHCs are sufficient to activate T cells. This sensitivity is remarkable in light of a number of factors, including the observation that the TCR and pMHC are short molecules relative to highly abundant long surface molecules, such as CD45, that can hinder initial binding, and moreover, the TCR/pMHC interaction is of weak affinity with solution lifetimes of approximately 1 second. Here, we review experimental and mathematical work that has contributed to uncovering molecular mechanisms of T cell sensitivity. We organize the mechanisms by where they act in the pathway to activate T cells, namely mechanisms that (a) promote TCR/pMHC binding, (b) induce rapid TCR signaling, and (c) amplify TCR signaling. We discuss work showing that high sensitivity reduces antigen specificity unless molecular feedbacks are invoked. We conclude by summarizing a number of open questions.

More from less - bottom-up reconstitution of cell biology

The ultimate goal of bottom-up synthetic biology is recreating life in its simplest form. However, in its quest to find the minimal functional units of life, this field contributes more than its main aim by also offering a range of tools for asking, and experimentally approaching, biological questions. This Review focusses on how bottom-up reconstitution has furthered our understanding of cell biology. Studying cell biological processes in vitro has a long tradition, but only recent technological advances have enabled researchers to reconstitute increasingly complex biomolecular systems by controlling their multi-component composition and their spatiotemporal arrangements. We illustrate this progress using the example of cytoskeletal processes. Our understanding of these has been greatly enhanced by reconstitution experiments, from the first in vitro experiments 70 years ago to recent work on minimal cytoskeleton systems (including this Special Issue of Journal of Cell Science). Importantly, reconstitution approaches are not limited to the cytoskeleton field. Thus, we also discuss progress in other areas, such as the shaping of biomembranes and cellular signalling, and prompt the reader to add their subfield of cell biology to this list in the future.

A Thermodynamic Model for Multivalency in 14-3-3 Protein-Protein Interactions

Protein-protein interactions (PPIs) are at the core of molecular control over cellular function. Multivalency in PPI formation, such as via proteins with multiple binding sites and different valencies, requires fundamental understanding to address correlated challenges in pathologies and drug development. Thermodynamic binding models are needed to provide frameworks for describing multivalent PPIs. We established a model based on ditopic host-guest systems featuring the effective molarity, a hallmark property of multivalency, as a prime parameter governing the intramolecular binding in divalent interactions. By way of illustration, we study the interaction of the bivalent 14-3-3 protein scaffold with both the nonavalent CFTR and the hexavalent LRRK2 proteins, determining the underlying thermodynamics and providing insights into the role of individual sites in the context of the multivalent platform. Fitting of binding data reveals enthalpy-entropy correlation in both systems. Simulations of speciations for the entire phosphorylated protein domains reveal that the CFTR protein preferably binds to 14-3-3 by combinations including the strongest binding site pS768, but that other binding sites take over when this site is eliminated, leading to only a minor decrease in total affinity for 14-3-3. For LRRK2, two binding sites dominate the complex formation with 14-3-3, but the distantly located pS1444 site also plays a role in complex formation. Thermodynamic modeling of these multivalent PPIs allowed analyzing and predicting the effects of individual sites regarding their modulation via, for example, (de)phosphorylation or small-molecule targeting. The results specifically bring forward the potential of PPI stabilization, as an entry for drug discovery for multivalent PPIs.

Computational Model of Chimeric Antigen Receptors Explains Site-Specific Phosphorylation Kinetics

Chimeric antigen receptors (CARs) have recently been approved for the treatment of hematological malignancies, but our lack of understanding of the basic mechanisms that activate these proteins has made it difficult to optimize and control CAR-based therapies. In this study, we use phosphoproteomic mass spectrometry and mechanistic computational modeling to quantify the in vitro kinetics of individual tyrosine phosphorylation on a variety of CARs. We show that each of the 10 tyrosine sites on the CD28-CD3ζ CAR is phosphorylated by lymphocyte-specific protein-tyrosine kinase (LCK) with distinct kinetics. The addition of CD28 at the N-terminal of CD3ζ increases the overall rate of CD3ζ phosphorylation. Our computational model identifies that LCK phosphorylates CD3ζ through a mechanism of competitive inhibition. This model agrees with previously published data in the literature and predicts that phosphatases in this system interact with CD3ζ through a similar mechanism of competitive inhibition. This quantitative modeling framework can be used to better understand CAR signaling and T cell activation.

Tuning ITAM multiplicity on T cell receptors can control potency and selectivity to ligand density

The T cell antigen receptor (TCR) recognizes peptides from pathogenic proteins bound in the major histocompatibility complex (MHC). To convert this binding event into downstream signaling, the TCR complex contains immunoreceptor tyrosine-based activation motifs (ITAMs) that act as docking sites for the cytoplasmic tyrosine kinase ZAP-70. Unique among antigen receptors, the TCR complex uses 10 ITAMs to transduce peptide-MHC binding to the cell interior. Using synthetic, drug-inducible receptor-ligand pairs, it was found that greater ITAM multiplicity primarily enhanced the efficiency with which ligand binding was converted into an intracellular signal. This manifested as an increase in the fraction of cells that became activated in response to antigen, and a more synchronous initiation of TCR-proximal signaling, rather than direct amplification of the intracellular signals. Exploiting these findings, the potency and selectivity of chimeric antigen receptors targeted against cancer were substantially enhanced by modulating the number of encoded ITAMs.

Structural Regulation of a Neurofilament-Inspired Intrinsically Disordered Protein Brush by Multisite Phosphorylation

Intrinsically disordered proteins (IDPs) play central roles in numerous cellular processes. While IDP structure and function are often regulated by multisite phosphorylation, the biophysical mechanisms linking these post-translational modifications to IDP structure remain elusive. For example, the intrinsically disordered C-terminal sidearm domain of the neurofilament heavy subunit (NFH-SA) forms a dense brush along axonal NF backbones and is subject to extensive serine phosphorylation. Yet, biophysical insight into the relationship between phosphorylation and structure has been limited by the lack of paradigms in which NF brush conformational responses can be measured in the setting of controlled phosphorylation. Here, we approach this question by immobilizing a recombinant NFH-SA (rNFH-SA) as IDP brushes onto glass, and controllably phosphorylating the sequence in situ with mitogen-activated protein kinase 1 (ERK2) preactivated by mitogen-activated protein kinase kinase (MKK). We then monitor brush height changes using atomic force microscopy, which shows that phosphorylation induces significant brush swelling to an extent that strongly depends upon pH and ionic strength, consistent with a mechanism in which phosphorylation regulates brush structure through local electrostatic interactions. Further consistent with this mechanism, the phosphorylated rNFH-SA brush may be dramatically condensed with micromolar concentrations of divalent cations. Phosphorylation-induced height changes are qualitatively reversible via alkaline phosphatase-mediated dephosphorylation. Our study demonstrates that multisite phosphorylation controls NFH-SA structure through modulation of chain electrostatics and points to a general strategy for engineering IDP-based interfaces that can be reversibly and dynamically modulated by enzymes.

Computational simulation of formin-mediated actin polymerization predicts homologue-dependent mechanosensitivity

Many actin structures are nucleated and assembled by the barbed-end tracking polymerase formin family, including filopodia, focal adhesions, the cytokinetic ring and cell cortex. These structures respond to forces in distinct ways. Formins typically have profilin-actin binding sites embedded in highly flexible disordered FH1 domains, hypothesized to diffusively explore space to rapidly capture actin monomers for delivery to the barbed end. Recent experiments demonstrate that formin-mediated polymerization accelerates when under tension. The acceleration has been attributed to modifying the state of the FH2 domain of formin. Intriguingly, the same acceleration is reported when tension is applied to the FH1 domains, ostensibly pulling monomers away from the barbed end. Here we develop a mesoscale coarse-grain model of formin-mediated actin polymerization, including monomer capture and delivery by FH1, which sterically interacts with actin along its entire length. The binding of actin monomers to their specific sites on FH1 is entropically disfavored by the high disorder. We find that this penalty is attenuated when force is applied to the FH1 domain by revealing the binding site, increasing monomer capture efficiency. Overall polymerization rates can decrease or increase with increasing force, depending on the length of FH1 domain and location of binding site. Our results suggest that the widely varying FH1 lengths and binding site locations found in known formins could be used to differentially respond to force, depending on the actin structure being assembled. © 2016 Wiley Periodicals, Inc.

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways.