AZD9567 versus prednisolone in patients with active rheumatoid arthritis: A phase IIa, randomized, double-blind, efficacy, and safety study.

Oral corticosteroid use is limited by side effects, some caused by off-target actions on the mineralocorticoid receptor that disrupt electrolyte balance. AZD9567 is a selective, nonsteroidal glucocorticoid receptor modulator. The efficacy, safety, and tolerability of AZD9567 and prednisolone were assessed in a phase IIa study. Anti-inflammatory mechanism of action was also evaluated in vitro in monocytes from healthy donors. In this randomized, double-blind, parallel-group, multicenter study, patients with active rheumatoid arthritis were randomized 1:1 to AZD9567 40 mg or prednisolone 20 mg once daily orally for 14 days. The primary end point was change from baseline in DAS28-CRP at day 15. Secondary end points included components of DAS28-CRP, American College of Rheumatology (ACR) response criteria (ACR20, ACR50, and ACR70), and safety end points, including serum electrolytes. Overall, 21 patients were randomized to AZD9567 (n = 11) or prednisolone (n = 10), and all completed the study. As anticipated, AZD9567 had a similar efficacy profile to prednisolone, with no clinically meaningful (i.e., >1.0) difference in change from baseline to day 15 in DAS28-CRP between AZD9567 and prednisolone (least-squares mean difference: 0.47, 95% confidence interval: -0.49 to 1.43). Similar results were observed for the secondary efficacy end points. In vitro transcriptomic analysis showed that anti-inflammatory responses were similar for AZD9567, prednisolone, and dexamethasone. Unlike prednisolone, AZD9567 had no effect on the serum sodium:potassium ratio. The safety profile was not different from that of prednisolone. Larger studies of longer duration are required to determine whether AZD9567 40 mg may in the future be an alternative to prednisolone in patients with inflammatory disease.

Dysregulation of COVID-19 related gene expression in the COPD lung.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) patients are at increased risk of poor outcome from Coronavirus disease (COVID-19). Early data suggest elevated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) receptor angiotensin converting enzyme 2 (ACE2) expression, but relationships to disease phenotype and downstream regulators of inflammation in the Renin-Angiotensin system (RAS) are unknown. We aimed to determine the relationship between RAS gene expression relevant to SARS-CoV-2 infection in the lung with disease characteristics in COPD, and the regulation of newly identified SARS-CoV-2 receptors and spike-cleaving proteases, important for SARS-CoV-2 infection. METHODS: We quantified gene expression using RNA sequencing of epithelial brushings and bronchial biopsies from 31 COPD and 37 control subjects. RESULTS: ACE2 gene expression (log2-fold change (FC)) was increased in COPD compared to ex-smoking (HV-ES) controls in epithelial brushings (0.25, p = 0.042) and bronchial biopsies (0.23, p = 0.050), and correlated with worse lung function (r = - 0.28, p = 0.0090). ACE2 was further increased in frequent exacerbators compared to infrequent exacerbators (0.51, p = 0.00045) and associated with use of ACE inhibitors (ACEi) (0.50, p = 0.0034), having cardiovascular disease (0.23, p = 0.048) or hypertension (0.34, p = 0.0089), and inhaled corticosteroid use in COPD subjects in bronchial biopsies (0.33, p = 0.049). Angiotensin II receptor type (AGTR)1 and 2 expression was decreased in COPD bronchial biopsies compared to HV-ES controls with log2FC of -0.26 (p = 0.033) and - 0.40, (p = 0.0010), respectively. However, the AGTR1:2 ratio was increased in COPD subjects compared with HV-ES controls, log2FC of 0.57 (p = 0.0051). Basigin, a newly identified potential SARS-CoV-2 receptor was also upregulated in both brushes, log2FC of 0.17 (p = 0.0040), and bronchial biopsies, (log2FC of 0.18 (p = 0.017), in COPD vs HV-ES. Transmembrane protease, serine (TMPRSS)2 was not differentially regulated between control and COPD. However, various other spike-cleaving proteases were, including TMPRSS4 and Cathepsin B, in both epithelial brushes (log2FC of 0.25 (p = 0.0012) and log2FC of 0.56 (p = 5.49E-06), respectively) and bronchial biopsies (log2FC of 0.49 (p = 0.00021) and log2FC of 0.246 (p = 0.028), respectively). CONCLUSION: This study identifies key differences in expression of genes related to susceptibility and aetiology of COVID-19 within the COPD lung. Further studies to understand the impact on clinical course of disease are now required.

Human Lung Conventional Dendritic Cells Orchestrate Lymphoid Neogenesis during Chronic Obstructive Pulmonary Disease.

Rationale: Emerging evidence supports a crucial role for tertiary lymphoid organs (TLOs) in chronic obstructive pulmonary disease (COPD) progression. However, mechanisms of immune cell activation leading to TLOs in COPD remain to be defined.Objectives: To examine the role of lung dendritic cells (DCs) in T follicular helper (Tfh)-cell induction, a T-cell subset critically implicated in lymphoid organ formation, in COPD.Methods: Myeloid cell heterogeneity and phenotype were studied in an unbiased manner via single-cell RNA sequencing on HLA-DR+ cells sorted from human lungs. We measured the in vitro capability of control and COPD lung DC subsets, sorted using a fluorescence-activated cell sorter, to polarize IL-21+CXCL13+ (IL-21-positive and C-X-C chemokine ligand type 13-positive) Tfh-like cells. In situ imaging analysis was performed on Global Initiative for Chronic Obstructive Lung Disease stage IV COPD lungs with TLOs.Measurements and Main Results: Single-cell RNA-sequencing analysis revealed a high degree of heterogeneity among human lung myeloid cells. Among these, conventional dendritic type 2 cells (cDC2s) showed increased induction of IL-21+CXCL13+ Tfh-like cells. Importantly, the capacity to induce IL-21+ Tfh-like cells was higher in cDC2s from patients with COPD than in those from control patients. Increased Tfh-cell induction by COPD cDC2s correlated with increased presence of Tfh-like cells in COPD lungs as compared with those in control lungs, and cDC2s colocalized with Tfh-like cells in TLOs of COPD lungs. Mechanistically, cDC2s exhibited a unique migratory signature and (transcriptional) expression of several pathways and genes related to DC-induced Tfh-cell priming. Importantly, blocking the costimulatory OX40L (OX40 ligand)-OX40 axis reduced Tfh-cell induction by control lung cDC2s.Conclusions: In COPD lungs, we found lung EBI2+ (Epstein-Barr virus-induced gene 2-positive) OX-40L-expressing cDC2s that induced IL-21+ Tfh-like cells, suggesting an involvement of these cells in TLO formation.

Mechanistic Models of Cellular Signaling, Cytokine Crosstalk, and Cell-Cell Communication in Immunology.

The cells of the immune system respond to a great variety of different signals that frequently reach them simultaneously. Computational models of signaling pathways and cellular behavior can help us explore the biochemical mechanisms at play during such responses, in particular when those models aim at incorporating molecular details of intracellular reaction networks. Such detailed models can encompass hypotheses about the interactions among molecular binding domains and how these interactions are modulated by, for instance, post-translational modifications, or steric constraints in multi-molecular complexes. In this way, the models become formal representations of mechanistic immunological hypotheses that can be tested through quantitative simulations. Due to the large number of parameters (molecular abundances, association-, dissociation-, and enzymatic transformation rates) the goal of simulating the models can, however, in many cases no longer be the fitting of particular parameter values. Rather, the simulations perform sweeps through parameter space to test whether a model can account for certain experimentally observed features when allowing the parameter values to vary within experimentally determined or physiologically reasonable ranges. We illustrate how this approach can be used to explore possible mechanisms of immunological pathway crosstalk. Probing the input-output behavior of mechanistic pathway models through systematic simulated variations of receptor stimuli will soon allow us to derive cell population behavior from single-cell models, thereby bridging a scale gap that currently still is frequently addressed through heuristic phenomenological multi-scale models.

Using Python for Spatially Resolved Modeling with Simmune.

Mechanistic models are an important tool to gain insights about the quantitative behavior of cell-biological signal transduction networks. Here we show how Simmune can be used in conjunction with IPython to create repeatable, self-contained analyses of signal transduction processes in spatially inhomogeneous environments.

Differential gene expression in human tissue resident regulatory T cells from lung, colon, and blood.

As we learn more about how immune responses occur in situ, it is becoming clear that each organ/tissue is characterized with its own anatomy and microenvironment which may affect and even determine the outcome of the immune responses. With emerging data from animal studies showing that regulatory T cells infiltrating non-lymphoid tissues exhibit unique phenotypes and transcriptional signatures and display functions beyond their well-established suppressive roles, there is an urgent need to explore the function of tissue Treg cells in humans. Here we characterized the transcriptome of Treg residing at the human mucosal tissue obtained from the normal area of cancer resections and their peripheral blood counterparts, identifying human lung and colon tissue Treg signature genes and their upstream regulators. Pathway analysis highlighted potential differences in the cross-talk between tissue Treg cells and other non-immune tissue-specific cell types. For example, genes associated with wnt pathway were differentially regulated in lung Treg cells compared to blood or colon indicating a potential role for lung Treg cells in epithelium repair and regeneration. Moreover, we identified several non-coding RNAs specifically expressed by tissue-resident Tregs. These results provide a comprehensive view of lung and colon tissue Treg transcriptional landscape.

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

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.

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.

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.

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

BACKGROUND: Network 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. RESULTS: We 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. CONCLUSIONS: The 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.

Inflammation-induced interstitial migration of effector CD4⁺ T cells is dependent on integrin αV.

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.

High production rates sustain in vivo levels of PD-1high simian immunodeficiency virus-specific CD8 T cells in the face of rapid clearance.

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-1(high) virus-specific CD8 T cell responses during chronic infection are unknown. Here, we show that the PD-1(high) 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-1(high) compared to PD-1(low) 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-1(high) cells, but virtually all PD-1(low) cells, returned to rest after activation. Similar kinetics operated in both chronic and acute SIV infection. Our data suggest that the persistence of PD-1(high) SIV-specific CD8 T cells in chronic infection is maintained in vivo by a mechanism involving high production coupled with a high disappearance rate.

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.

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!).

Recent progress using systems biology approaches to better understand molecular mechanisms of immunity.

The immune system is composed of multiple dynamic molecular and cellular networks, the complexity of which has been revealed by decades of exacting reductionist research. However, understanding of the immune system sufficient to anticipate its response to novel perturbations requires a more integrative or systems approach to immunology. While methods for unbiased high-throughput data acquisition and computational integration of the resulting datasets are still relatively new, they have begun to substantially enhance our understanding of immunological phenomena. Such approaches have expanded our view of interconnected signaling and transcriptional networks and have highlighted the function of non-linear processes such as spatial regulation and feedback loops. In addition, advances in single cell measurement technology have demonstrated potential sources and functions of response heterogeneity in system behavior. The success of the studies reviewed here often depended upon integration of one or more systems biology approaches with more traditional methods. We hope these examples will inspire a broader range of immunologists to probe questions in a quantitative and integrated manner, advancing collective efforts to understand the immune "system".

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.

Computational modeling of signaling networks for eukaryotic chemosensing.

The task of developing and simulating computational models of signaling networks for eukaryotic chemosensing confronts the modeler with several challenges: (1) The stimuli that initiate the cellular responses one wishes to study are provided by extracellular concentration gradients. This means that the computational model must have a spatially resolved representation of extracellular molecular concentrations. (2) The intracellular responses consist of the generation of intracellular accumulations and/or translocations of signaling molecules, requiring spatially resolved computational representations of the simulated cells. (3) The signaling networks responsible for eukaryotic chemosensing comprise a multitude of components acting as receptors, adaptors, (lipid- and protein-) kinases (including GTPases), (lipid- and protein-) phosphatases, and molecule types used by others for membrane attachment. Models of such signaling networks may become quite complicated, unless one wishes to rely on abstract functional modules with certain input-output characteristics as modeling "shortcuts" replacing subnetworks of biological signaling molecules. In this chapter, we describe how modelers can use a modeling tool ("simmune") developed to facilitate the design and simulation of detailed computational models of signaling pathways (for eukaryotic chemosensing here), thereby avoiding the technical difficulties typically associated with building and simulating such quantitative models.

Yellow fever vaccine induces integrated multilineage and polyfunctional immune responses.

Correlates of immune-mediated protection to most viral and cancer vaccines are still unknown. This impedes the development of novel vaccines to incurable diseases such as HIV and cancer. In this study, we have used functional genomics and polychromatic flow cytometry to define the signature of the immune response to the yellow fever (YF) vaccine 17D (YF17D) in a cohort of 40 volunteers followed for up to 1 yr after vaccination. We show that immunization with YF17D leads to an integrated immune response that includes several effector arms of innate immunity, including complement, the inflammasome, and interferons, as well as adaptive immunity as shown by an early T cell response followed by a brisk and variable B cell response. Development of these responses is preceded, as demonstrated in three independent vaccination trials and in a novel in vitro system of primary immune responses (modular immune in vitro construct [MIMIC] system), by the coordinated up-regulation of transcripts for specific transcription factors, including STAT1, IRF7, and ETS2, which are upstream of the different effector arms of the immune response. These results clearly show that the immune response to a strong vaccine is preceded by coordinated induction of master transcription factors that lead to the development of a broad, polyfunctional, and persistent immune response that integrates all effector cells of the immune system.

Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method.

The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP), made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5)P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networks based on the definition of specific molecular binding site interactions and the subcellular localization of molecules. It automatically translates such inputs into spatially resolved simulations and dynamic graphical representations of the resulting signaling network that can be explored in a manner that closely parallels wet lab experimental procedures. These features of Simmune were critical to the model development and analysis presented here and are likely to be useful in the computational investigation of many aspects of cell biology.