How and why does the immunological synapse form? Physical chemistry meets cell biology

T cell antigen receptor signaling and immunological synapse stability require myosin IIA

Immunological synapses are initiated by signaling in discrete T cell antigen receptor microclusters and are important for the differentiation and effector functions of T cells. Synapse formation involves the orchestrated movement of microclusters toward the center of the contact area with the antigen-presenting cell. Microcluster movement is associated with centripetal actin flow, but the function of motor proteins is unknown. Here we show that myosin IIA was necessary for complete assembly and movement of T cell antigen receptor microclusters. In the absence of myosin IIA or its ATPase activity, T cell signaling was interrupted 'downstream' of the kinase Lck and the synapse was destabilized. Thus, T cell antigen receptor signaling and the subsequent formation of immunological synapses are active processes dependent on myosin IIA.

The evolution of mathematical immunology

The types of mathematical models used in immunology and their scope have changed drastically in the past 10 years. Classical models were based on ordinary differential equations (ODEs), difference equations, and cellular automata. These models focused on the 'simple' dynamics obtained between a small number of reagent types (e.g. one type of receptor and one type of antigen or two T-cell populations). With the advent of high-throughput methods, genomic data, and unlimited computing power, immunological modeling shifted toward the informatics side. Many current applications of mathematical models in immunology are now focused around the concepts of high-throughput measurements and system immunology (immunomics), as well as the bioinformatics analysis of molecular immunology. The types of models have shifted from mainly ODEs of simple systems to the extensive use of Monte Carlo simulations. The transition to a more molecular and more computer-based attitude is similar to the one occurring over all the fields of complex systems analysis. An interesting additional aspect in theoretical immunology is the transition from an extreme focus on the adaptive immune system (that was considered more interesting from a theoretical point of view) to a more balanced focus taking into account the innate immune system also. We here review the origin and evolution of mathematical modeling in immunology and the contribution of such models to many important immunological concepts.

Mathematical models of cytotoxic T-lymphocyte killing

By killing infected host cells, cytotoxic T lymphocytes (CTL) mediate an important defense mechanism against viruses and other intracellular pathogens. Quantitative aspects of this killing process have been studied for several decades in vitro. More recently, methods have been developed to measure the timescales of CTL killing in vivo. Here, we review the estimates of kinetic rates involved in CTL killing which were obtained in these studies, and elaborate on the differences between them.

Synapses: sites of cell recognition, adhesion, and functional specification

Synapses are specialized adhesive contacts characteristic of many types of cell-cell interactions involving neurons, immune cells, epithelial cells, and even pathogens and host cells. Cell-cell adhesion is mediated by structurally diverse classes of cell-surface glycoproteins, which form homophilic or heterophilic interactions across the intercellular space. Adhesion proteins bind to a cytoplasmic network of scaffolding proteins, regulators of the actin cytoskeleton, and signal transduction pathways that control the structural and functional organization of synapses. The themes of this review are to compare the organization of synapses in different cell types and to understand how different classes of cell adhesion proteins and cytoplasmic protein networks specify the assembly of functionally distinct synapses in different cell contexts.

Emergent dynamics of thymocyte development and lineage determination

Experiments have generated a plethora of data about the genes, molecules, and cells involved in thymocyte development. Here, we use a computer-driven simulation that uses data about thymocyte development to generate an integrated dynamic representation-a novel technology we have termed reactive animation (RA). RA reveals emergent properties in complex dynamic biological systems. We apply RA to thymocyte development by reproducing and extending the effects of known gene knockouts: CXCR4 and CCR9. RA simulation revealed a previously unidentified role of thymocyte competition for major histocompatability complex presentation. We now report that such competition is required for normal anatomical compartmentalization, can influence the rate of thymocyte velocities within chemokine gradients, and can account for the disproportion between single-positive CD4 and CD8 lineages developing from double-positive precursors.

'KMC-TDGL'-a coarse-grained methodology for simulating interfacial dynamics in complex fluids: application to protein-mediated membrane processes

In this article, we describe a new multiscale simulation algorithm (which we term the 'KMC-TDGL' method) applicable for the description of equilibrium and dynamic processes associated with a particular class of complex fluids with nanoscale inclusions, namely, biological membranes mediated by membrane-associating and membrane-bound proteins. We adopt a novel strategy of integrating two different phenomenological approaches, namely, a field theoretic (continuum) description for the membrane dynamics given by the time-dependent Ginzburg-Landau equation and a random walk on a discretized lattice description for protein diffusion dynamics. We illustrate that this integrated approach results in a unified description of protein-mediated membrane dynamics.

Low T cell receptor expression and thermal fluctuations contribute to formation of dynamic multifocal synapses in thymocytes

Mature T cell activation and selection of immature T cells (thymocytes) are both initiated by binding of T cell receptor (TCR) molecules on the surface of T cells to MHC peptide (MHCp) molecules on the surface of antigen-presenting cells. Recent experiments have shown that the spatial pattern of receptors and ligands in the intercellular junction (synapse) is different during thymocyte selection compared with mature T cell activation. Using a statistical mechanical model, we show that lower TCR expression in thymocytes contributes to effecting these differences. An analogy with the phase behavior of simple fluids helps clarify how, for low TCR expression, thermal fluctuations lead to the dynamic synapse patterns observed for thymocytes. We suggest that a different synapse pattern resulting from lower TCR expression, which could mediate differential signaling, may be the reason why TCR expression level is low in thymocytes.

The size of the synaptic cleft and distinct distributions of filamentous actin, ezrin, CD43, and CD45 at activating and inhibitory human NK cell immune synapses

In this study, we report the organization of cytoskeletal and large transmembrane proteins at the inhibitory and activating NK cell immunological or immune synapse (IS). Filamentous actin accumulates at the activating, but not the inhibitory, NK cell IS. However, surprisingly, ezrin and the associated protein CD43 are excluded from the inhibitory, but not the activating, NK cell IS. This distribution of ezrin and CD43 at the inhibitory NK cell IS is similar to that previously seen at the activating T cell IS. CD45 is also excluded from the inhibitory, but not activating, NK cell IS. In addition, electron microscopy reveals wide and narrow domains across the synaptic cleft. Target cell HLA-C, located by immunogold labeling, clusters where the synaptic cleft spans the size of HLA-C bound to the inhibitory killer Ig-like receptor. These data are consistent with assembly of the NK cell IS involving a combination of cytoskeletal-driven mechanisms and thermodynamics favoring the organization of receptor/ligand pairs according to the size of their extracellular domains.