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)P(3) 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

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

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

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

Comparison of the Simulated Activities of PI3K, Membrane-Bound PTEN, and the Resulting Behavior of PIP₃ (Composite Screenshot)

<p>Stimulation of a cell in a 2:1 cAMP gradient (mean concentration 500 nmol) leads to a rapid 3-fold increase in the membrane proximal activity of PI3K (green) and to a loss of membrane-bound PTEN (blue; tracked as GFP-PTEN in real cells). This results in a rapid accumulation of PIP₃ (red; reported by the location of PH-GFP in real cells). Subsequently, the PI3K activity is strongly quenched by the recruitment of regulatory components to the membrane and falls below its prestimulus level in less than 20 s. PTEN returns more slowly to the membrane. During the phase of downregulation of PI3K activity and reattachment of PTEN to the membrane, the concentration of PIP₃ decays. In the front of the cell (which experiences a high cAMP concentration), membrane-associated PTEN only returns to a fraction of its prestimulus level and then enters a second phase of decline. After approximately 50 s, the low level of membrane-bound PTEN that is reached in the front of the cell allows PIP₃ to increase again, even though the amount of active PI3K in this region is modest. In the back of the cell (low cAMP concentration), membrane-bound PTEN increases beyond its prestimulus level, resulting in a decrease of PIP₃ below its resting state concentration. The circular inset shows a two-dimensional representation of the dynamics of membrane-bound PTEN and PIP₃ in different regions of the three-dimensional simulation of a cell.</p

Correspondence in Time and Space between the Predicted and Measured Changes in PIP₃ at the Front and Back of Cells Exposed cAMP Gradients

<p>Experimental data from exposure of <i>Dictyostelium</i> to a 2:1 gradient with a mean cAMP concentration of 100 nmol were used to adjust model parameters. The other two responses are predictions of the model. (A), (B), and (C) are simulated responses. (D), (E), and (F) are experimental measurements, using PH-GFP to monitor PIP₃ levels in single cells exposed to gradients with a mean cAMP concentration of 1 μmol, 100 nmol, and 10 nmol. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0020082#pcbi-0020082-sg006" target="_blank">Figure S6</a> for details on the full dataset of experimental replicates.</p

Standard Model of the Extracellular and Intracellular Distribution of Key Components of <i>Dictyostelium</i> Chemotactic Signaling

<div><p>(A) In an unstimulated cell PTEN is homogeneously distributed at the membrane. The cell membrane contains very little PIP₃.</p><p>(B) Stimulation of the cell leads to the membrane recruitment and activation of PI3K, as indicated by the arrows (1) leading from inactive, mainly cytosolic PI3K (yellow) to membrane-proximal, active PI3K (orange). Activated PI3K transforms PIP₂ into PIP₃. PTEN is deactivated following cAMP stimulation and leaves the membrane. This process is indicated by arrows (2) connecting active PTEN (dark green) and the mainly cytosolic inactive PTEN (light green). Regulatory processes lead to reactivation of PTEN (3). Differences in the speed and degree of cAMP receptor ligation between front and back of the cell lead to preferential accumulation of PTEN at the back of the cell. As a result, the front experiences a higher concentration of PI3K and a lower concentration of PTEN than the back and accumulates PIP₃. Note: To emphasize the changes in PIP₃ content, the amount of PIP₃ relative to that of PIP₂ has been overstated. Even after cAMP stimulation, the actual amount of PIP₂ will be much higher than that of PIP₃.</p></div