Bastian R. Angermann

Neutrophil swarms require LTB4 and integrins at sites of cell death in vivo

Neutrophil recruitment from blood to extravascular sites of sterile or infectious tissue damage is a hallmark of early innate immune responses, and the molecular events leading to cell exit from the bloodstream have been well defined. Once outside the vessel, individual neutrophils often show extremely coordinated chemotaxis and cluster formation reminiscent of the swarming behaviour of insects. The molecular players that direct this response at the single-cell and population levels within the complexity of an inflamed tissue are unknown. Using two-photon intravital microscopy in mouse models of sterile injury and infection, we show a critical role for intercellular signal relay among neutrophils mediated by the lipid leukotriene B4, which acutely amplifies local cell death signals to enhance the radius of highly directed interstitial neutrophil recruitment. Integrin receptors are dispensable for long-distance migration, but have a previously unappreciated role in maintaining dense cellular clusters when congregating neutrophils rearrange the collagenous fibre network of the dermis to form a collagen-free zone at the wound centre. In this newly formed environment, integrins, in concert with neutrophil-derived leukotriene B4 and other chemoattractants, promote local neutrophil interaction while forming a tight wound seal. This wound seal has borders that cease to grow in kinetic concert with late recruitment of monocytes and macrophages at the edge of the displaced collagen fibres. Together, these data provide an initial molecular map of the factors that contribute to neutrophil swarming in the extravascular space of a damaged tissue. They reveal how local events are propagated over large-range distances, and how auto-signalling produces coordinated, self-organized neutrophil-swarming behaviour that isolates the wound or infectious site from surrounding viable tissue.

Inflammation-induced effector CD4+ T cell interstitial migration is alpha-v integrin dependent

Leukocytes must traverse inflamed tissues to effectively control local infection. Although motility in dense tissues appears to be integrin-independent actin-myosin based, during inflammation changes to the extracellular matrix (ECM) may necessitate distinct motility requirements. Indeed, we found that T cell interstitial motility was critically dependent on RGD-binding integrins in the inflamed dermis. Inflammation-induced deposition of fibronectin was functionally linked to increased αv integrin expression on effector CD4+ T cells. Using intravital multi-photon imaging, we found that CD4+ T cell motility was dependent on αv expression. Selective αv blockade or knockdown arrested TH1 motility in the inflamed tissue and attenuated local effector function. These data show a context-dependent specificity of lymphocyte movement in inflamed tissues that is essential for protective immunity.Leukocytes must traverse inflamed tissues to effectively control local infection. Although motility in dense tissues seems to be integrin independent and based on actomyosin-mediated protrusion and contraction, during inflammation, changes to the extracellular matrix (ECM) may necessitate distinct motility requirements. Indeed, we found that the interstitial motility of T cells was critically dependent on Arg-Gly-Asp (RGD)-binding integrins in the inflamed dermis. Inflammation-induced deposition of fibronectin was functionally linked to higher expression of integrin αV on effector CD4+ T cells. By intravital multiphoton imaging, we found that the motility of CD4+ T cells was dependent on αV expression. Selective blockade or knockdown of αV arrested T helper type 1 (TH1) cells in the inflamed tissue and attenuated local effector function. Our data demonstrate context-dependent specificity of lymphocyte movement in inflamed tissues that is essential for protective immunity.

Computational modeling of cellular signaling processes embedded into dynamic spatial contexts

Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.

Distinct NF-κB and MAPK Activation Thresholds Uncouple Steady-State Microbe Sensing from Anti-pathogen Inflammatory Responses

The innate immune system distinguishes low-level homeostatic microbial stimuli from those of invasive pathogens, yet we lack understanding of how qualitatively similar microbial products yield context-specific macrophage functional responses. Using quantitative approaches, we found that NF-κB and MAPK signaling was activated at different concentrations of a stimulatory TLR4 ligand in both mouse and human macrophages. Above a threshold of ligand, MAPK were activated in a switch-like manner, facilitating production of inflammatory mediators. At ligand concentrations below this threshold, NF-κB signaling occurred, promoting expression of a restricted set of genes and macrophage priming. Among TLR-induced genes, we observed an inverse correlation between MAPK dependence and ligand sensitivity, highlighting the role of this signaling dichotomy in partitioning innate responses downstream of a single receptor. Our study reveals an evolutionarily conserved innate immune response system in which danger discrimination is enforced by distinct thresholds for NF-κB and MAPK activation, which provide sequential barriers to inflammatory mediator production.

The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions

MOTIVATION Biochemical modeling efforts now frequently take advantage of the possibility to automatically create reaction networks based on the specification of pairwise molecular interactions. Even though a variety of tools exist to visualize the resulting networks, defining the rules for the molecular interactions typically requires writing scripts, which impacts the non-specialist accessibility of those approaches. We introduce the Simmune Modeler that allows users to specify molecular complexes and their interactions as well as the reaction-induced modifications of the molecules through a flexible visual interface. It can take into account the positions of the components of trans-membrane complexes relative to the embedding membranes as well as symmetry aspects affecting the reactions of multimeric molecular structures. Models created with this tool can be simulated using the Simmune Simulator or be exported as SBML code or as files describing the reaction networks as systems of ODEs for import into Matlab. AVAILABILITY The Simmune Modeler and the associated simulators as well as extensive additional documentation and tutorials are freely available for Linux, Mac and Windows: http://go.usa.gov/QeH (Note shortened case-sensitive URL!).

NetworkViewer: visualizing biochemical reaction networks with embedded rendering of molecular interaction rules.

BackgroundNetwork representations of cell-biological signaling processes frequently contain large numbers of interacting molecular and multi-molecular components that can exist in, and switch between, multiple biochemical and/or structural states. In addition, the interaction categories (associations, dissociations and transformations) in such networks cannot satisfactorily be mapped onto simple arrows connecting pairs of components since their specifications involve information such as reaction rates and conditions with regard to the states of the interacting components. This leads to the challenge of having to reconcile competing objectives: providing a high-level overview without omitting relevant information, and showing interaction specifics while not overwhelming users with too much detail displayed simultaneously. This problem is typically addressed by splitting the information required to understand a reaction network model into several categories that are rendered separately through combinations of visualizations and/or textual and tabular elements, requiring modelers to consult several sources to obtain comprehensive insights into the underlying assumptions of the model.ResultsWe report the development of an application, the Simmune NetworkViewer, that visualizes biochemical reaction networks using iconographic representations of protein interactions and the conditions under which the interactions take place using the same symbols that were used to specify the underlying model with the Simmune Modeler. This approach not only provides a coherent model representation but, moreover, following the principle of “overview first, zoom and filter, then details-on-demand,” can generate an overview visualization of the global network and, upon user request, presents more detailed views of local sub-networks and the underlying reaction rules for selected interactions. This visual integration of information would be difficult to achieve with static network representations or approaches that use scripted model specifications without offering simple but detailed symbolic representations of molecular interactions, their conditions and consequences in terms of biochemical modifications.ConclusionsThe Simmune NetworkViewer provides concise, yet comprehensive visualizations of reaction networks created in the Simmune framework. In the near future, by adopting the upcoming SBML standard for encoding multi-component, multi-state molecular complexes and their interactions as input, the NetworkViewer will, moreover, be able to offer such visualization for any rule-based model that can be exported to that standard.

High Production Rates Sustain In Vivo Levels of PD-1high Simian Immunodeficiency Virus-Specific CD8 T Cells in the Face of Rapid Clearance

ABSTRACT Programmed Death 1 (PD-1) expression by human/simian immunodeficiency virus (HIV/SIV)-specific CD8 T cells has been associated with defective cytokine production and reduced in vitro proliferation capacity. However, the cellular mechanisms that sustain PD-1high virus-specific CD8 T cell responses during chronic infection are unknown. Here, we show that the PD-1high phenotype is associated with accelerated in vivo CD8 T cell turnover in SIV-infected rhesus macaques, especially within the SIV-specific CD8 T cell pool. Mathematical modeling of 5-bromo-2′ deoxyuridine (BrdU) labeling dynamics demonstrated a significantly increased generation rate of PD-1high compared to PD-1low CD8 T cells in all memory compartments. Simultaneous analysis of Ki67 and BrdU kinetics revealed a complex in vivo turnover profile whereby only a small fraction of PD-1high cells, but virtually all PD-1low cells, returned to rest after activation. Similar kinetics operated in both chronic and acute SIV infection. Our data suggest that the persistence of PD-1high SIV-specific CD8 T cells in chronic infection is maintained in vivo by a mechanism involving high production coupled with a high disappearance rate.

Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing.

Osteoclasts are monocyte-derived multinuclear cells that directly attach to and resorb bone. Sphingosine-1-phosphate (S1P)1 regulates bone resorption by functioning as both a chemoattractant and chemorepellent of osteoclast precursors through two G-protein coupled receptors that antagonize each other in an S1P-concentration-dependent manner. To quantitatively explore the behavior of this chemosensing pathway, we applied targeted proteomics, transcriptomics, and rule-based pathway modeling using the Simmune toolset. RAW264.7 cells (a mouse monocyte/macrophage cell line) were used as model osteoclast precursors, RNA-seq was used to identify expressed target proteins, and selected reaction monitoring (SRM) mass spectrometry using internal peptide standards was used to perform absolute abundance measurements of pathway proteins. The resulting transcript and protein abundance values were strongly correlated. Measured protein abundance values, used as simulation input parameters, led to in silico pathway behavior matching in vitro measurements. Moreover, once model parameters were established, even simulated responses toward stimuli that were not used for parameterization were consistent with experimental findings. These findings demonstrate the feasibility and value of combining targeted mass spectrometry with pathway modeling for advancing biological insight.

A hierarchy of affinities between cytokine receptors and the common gamma chain leads to pathway cross-talk

Limiting amounts of the common receptor subunit γc result in asymmetric cross-talk among cytokines. Hierarchical sharing of the γc subunit Cytokines that belong to the common gamma chain (γc) family, including interleukin-4 (IL-4), IL-7, and IL-21, not only bind to distinct receptor subunits but also rely on a shared γc subunit for signaling. Given the roles of these cytokines in immune cell survival, proliferation, and function, it is important to understand how their shared use of the γc receptor affects the responses of cells to multiple family members. Through computational modeling and experimental analysis of cytokine receptor signaling on naïve T cells, Gonnord et al. showed that whereas treatment with IL-7 reduced the responses of cells to subsequent treatment with IL-4 or IL-21, the reverse was not true. The amount of available γc subunit was limiting and bound more readily to the IL-7 receptor α subunit (IL-7Rα) than to IL-4Rα or IL-21Rα, thus sequestering the γc subunit. The γc subunit preassociated with the IL-7Rα in the absence of cytokine. These data suggest that there exists a hierarchy of responses of naïve T cells to cytokines, which has relevance for cells in inflammatory environments exposed to multiple cytokines. Cytokines belonging to the common gamma chain (γc) family depend on the shared γc receptor subunit for signaling. We report the existence of a fast, cytokine-induced pathway cross-talk acting at the receptor level, resulting from a limiting amount of γc on the surface of T cells. We found that this limited abundance of γc reduced interleukin-4 (IL-4) and IL-21 responses after IL-7 preexposure but not vice versa. Computational modeling combined with quantitative experimental assays indicated that the asymmetric cross-talk resulted from the ability of the “private” IL-7 receptor subunits (IL-7Rα) to bind to many of the γc molecules even before stimulation with cytokine. Upon exposure of T cells to IL-7, the high affinity of the IL-7Rα:IL-7 complex for γc further reduced the amount of free γc in a manner dependent on the concentration of IL-7. Measurements of bioluminescence resonance energy transfer (BRET) between IL-4Rα and γc were reduced when IL-7Rα was overexpressed. Furthermore, in a system expressing IL-7Rα, IL-4Rα, and γc, BRET between IL-4Rα and γc increased after IL-4 binding and decreased when cells were preexposed to IL-7, supporting the assumption that IL-7Rα and the IL-7Rα:IL-7 complex limit the accessibility of γc for other cytokine receptor complexes. We propose that in complex inflammatory environments, such asymmetric cross-talk establishes a hierarchy of cytokine responsiveness.