A systems-biology model of the tumor necrosis factor (TNF) interactions with TNF receptor 1 and 2.

MOTIVATION: Clustering enables TNF receptors to stimulate intracellular signaling. The differential soluble ligand-induced clustering behavior of TNF receptor 1 (TNFR1) and TNFR2 was modeled. A structured, rule-based model implemented ligand-independent pre-ligand binding assembly domain (PLAD)-mediated homotypic low affinity interactions of unliganded and liganded TNF receptors. RESULTS: Soluble TNF initiates TNFR1 signaling but not TNFR2 signaling despite receptor binding unless it is secondarily oligomerized. We consider high affinity binding of TNF to signaling-incompetent pre-assembled dimeric TNFR1 and TNFR2 molecules and secondary clustering of liganded dimers to signaling competent ligand-receptor clusters. Published receptor numbers, affinities and measured different activities of clustered receptors validated model simulations for a large range of receptor and ligand concentrations. Different PLAD-PLAD affinities and different activities of receptor clusters explain the observed differences in the TNF receptor stimulating activities of soluble TNF. AVAILABILITY AND IMPLEMENTATION: All scripts and data are in manuscript and supplement at Bioinformatics online. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A modular systems biological modelling framework studies cyclic nucleotide signaling in platelets.

BACKGROUND: The cyclic nucleotides cAMP and cGMP inhibit platelet activation. Different platelet signaling modules work together. We develop here a modelling framework to integrate different signaling modules and apply it to platelets. RESULTS: We introduce a novel standardized bilinear coupling mechanism allowing sub model debugging and standardization of coupling with optimal data driven modelling by methods from optimization. Besides cAMP signaling our model considers specific cGMP effects including external stimuli by drugs. Moreover, the output of the cGMP module serves as input for a modular model of VASP phosphorylation and for the activity of cAMP and cGMP pathways in platelets. Experimental data driven modeling allows us to design models with quantitative output. We use the condensed information about involved regulation and system responses for modeling drug effects and obtaining optimal experimental settings. Stepwise further validation of our model is given by direct experimental data. CONCLUSIONS: We present a general framework for model integration using modules and their stimulus responses. We demonstrate it by a multi-modular model for platelet signaling focusing on cGMP and VASP phosphorylation. Moreover, this allows to estimate drug action on any of the inhibitory cyclic nucleotide pathways (cGMP, cAMP) and is supported by experimental data.

Physiology-based toxicokinetic modelling of aluminium in rat and man.

A sufficient quantitative understanding of aluminium (Al) toxicokinetics (TK) in man is still lacking, although highly desirable for risk assessment of Al exposure. Baseline exposure and the risk of contamination severely limit the feasibility of TK studies administering the naturally occurring isotope 27Al, both in animals and man. These limitations are absent in studies with 26Al as a tracer, but tissue data are limited to animal studies. A TK model capable of inter-species translation to make valid predictions of Al levels in humans-especially in toxicological relevant tissues like bone and brain-is urgently needed. Here, we present: (i) a curated dataset which comprises all eligible studies with single doses of 26Al tracer administered as citrate or chloride salts orally and/or intravenously to rats and humans, including ultra-long-term kinetic profiles for plasma, blood, liver, spleen, muscle, bone, brain, kidney, and urine up to 150 weeks; and (ii) the development of a physiology-based (PB) model for Al TK after intravenous and oral administration of aqueous Al citrate and Al chloride solutions in rats and humans. Based on the comprehensive curated 26Al dataset, we estimated substance-dependent parameters within a non-linear mixed-effect modelling context. The model fitted the heterogeneous 26Al data very well and was successfully validated against datasets in rats and humans. The presented PBTK model for Al, based on the most extensive and diverse dataset of Al exposure to date, constitutes a major advancement in the field, thereby paving the way towards a more quantitative risk assessment in humans.

Aluminium toxicokinetics after intramuscular, subcutaneous, and intravenous injection of Al citrate solution in rats.

Knowledge of dose linearity, plasma clearance, rate and extent of subcutaneous (SC) and intramuscular (IM) absorption of soluble aluminium (Al) citrate is considered a prerequisite for evaluation of toxicokinetic data obtained from SC or IM administration of Al adjuvants in medicinal products. Therefore, total Al plasma kinetics was investigated after SC, IM, and IV administration of single Al doses (36 and 360 µg/kg IM or SC; 30 and 300 µg/kg IV) given as citrate solution in rats. Control groups receiving vehicle (saline) were run in parallel to monitor background plasma Al levels over time resulting from dietary intake. Evaluation of Al plasma profiles was done by both non-compartmental analysis of baseline-corrected data and simultaneous model fitting to the raw data using a population kinetics approach. High and dose-independent total plasma clearance (6.6 mL/min/kg) was observed after IV administration corresponding to 60-82% of normal rat GFR. This supports the previous assumptions that parenterally administered Al citrate is more rapidly cleared from plasma than other Al species (e.g., chloride or lactate). Furthermore, plasma exposure of Al (Cmax and AUC0-inf) increased dose-proportionally at all administration routes. Fast and complete absorption of Al was observed at each dose level after both SC and IM administration (bioavailability estimates: 88 and 110%). Estimates for the first-order absorption rate constant ka correspond to absorption half-lives of 36 min (SC) and ≤ 13 min (IM). There was no increase in tissue Al content (whole bone and brain) after 36 µg/kg IM compared to control rats.

Aluminium in plasma and tissues after intramuscular injection of adjuvanted human vaccines in rats.

Aluminium (Al) toxicokinetics after intramuscular (IM) injection of Al-adjuvanted vaccines is unknown. Since animal data are required for modeling and extrapolation, a rat study was conducted measuring Al in plasma and tissues after IM injection of either plain Al-hydroxide (pAH) or Al-phosphate (pAP) adjuvant (Al dose 1.25 mg), single human doses of three Al-adjuvanted vaccines (V1, V2, and V3; Al doses 0.5-0.82 mg), or vehicle (saline). A significant increase in Al plasma levels compared to controls was observed after pAP (AUC(0-80 d), mean ± SD: 2424 ± 496 vs. 1744 ± 508 µg/L*d). Percentage of Al dose released from injected muscle until day 80 was higher after pAP (66.9%) and AP-adjuvanted V3 (85.5%) than after pAH and AH-adjuvanted V1 (0 and 22.3%, resp.). Estimated absolute Al release was highest for pAP (836.8 µg per rat). Al concentration in humerus bone was increased in all groups, again strongest in the pAP group [3.35 ± 0.39 vs. 0.05 ± 0.06 µg/g wet weight (ww)]. Extrapolated amounts in whole skeleton corresponded to 5-12% of the released Al dose. Very low brain Al concentrations were observed in all groups (adjuvant group means 0.14-0.29 µg/g ww; control 0.13 ± 0.04 µg/g ww). The results demonstrate systemically available Al from marketed vaccines in rats being mainly detectable in bone. Al release appears to be faster from AP- than AH-adjuvants. Dose scaling to human adults suggests that increase of Al in plasma and tissues after single vaccinations will be indistinguishable from baseline levels.

Integrated systems view on networking by hormones in Arabidopsis immunity reveals multiple crosstalk for cytokinin.

Phytohormones signal and combine to maintain the physiological equilibrium in the plant. Pathogens enhance host susceptibility by modulating the hormonal balance of the plant cell. Unlike other plant hormones, the detailed role of cytokinin in plant immunity remains to be fully elucidated. Here, extensive data mining, including of pathogenicity factors, host regulatory proteins, enzymes of hormone biosynthesis, and signaling components, established an integrated signaling network of 105 nodes and 163 edges. Dynamic modeling and system analysis identified multiple cytokinin-mediated regulatory interactions in plant disease networks. This includes specific synergism between cytokinin and salicylic acid pathways and previously undiscovered aspects of antagonism between cytokinin and auxin in plant immunity. Predicted interactions and hormonal effects on plant immunity are confirmed in subsequent experiments with Pseudomonas syringae pv tomato DC3000 and Arabidopsis thaliana. Our dynamic simulation is instrumental in predicting system effects of individual components in complex hormone disease networks and synergism or antagonism between pathways.

Integration of Boolean models exemplified on hepatocyte signal transduction.

The number of mathematical models for biological pathways is rapidly growing. In particular, Boolean modelling proved to be suited to describe large cellular signalling networks. Systems biology is at the threshold to holistic understanding of comprehensive networks. In order to reach this goal, connection and integration of existing models of parts of cellular networks into more comprehensive network models is necessary. We discuss model combination approaches for Boolean models. Boolean modelling is qualitative rather than quantitative and does not require detailed kinetic information. We show that these models are useful precursors for large-scale quantitative models and that they are comparatively easy to combine. We propose modelling standards for Boolean models as a prerequisite for smooth model integration. Using these standards, we demonstrate the coupling of two logical models on two different examples concerning cellular interactions in the liver. In the first example, we show the integration of two Boolean models of two cell types in order to describe their interaction. In the second example, we demonstrate the combination of two models describing different parts of the network of a single cell type. Combination of partial models into comprehensive network models will take systems biology to the next level of understanding. The combination of logical models facilitated by modelling standards is a valuable example for the next step towards this goal.

Quantitative single-molecule localization microscopy combined with rule-based modeling reveals ligand-induced TNF-R1 reorganization toward higher-order oligomers.

We report on the assembly of tumor necrosis factor receptor 1 (TNF-R1) prior to ligand activation and its ligand-induced reorganization at the cell membrane. We apply single-molecule localization microscopy to obtain quantitative information on receptor cluster sizes and copy numbers. Our data suggest a dimeric pre-assembly of TNF-R1, as well as receptor reorganization toward higher oligomeric states with stable populations comprising three to six TNF-R1. Our experimental results directly serve as input parameters for computational modeling of the ligand-receptor interaction. Simulations corroborate the experimental finding of higher-order oligomeric states. This work is a first demonstration how quantitative, super-resolution and advanced microscopy can be used for systems biology approaches at the single-molecule and single-cell level.

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility.

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk-based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick-start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.

Commentary on the MID3 Good Practices Paper.

During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011 EMA - European Federation of Pharmaceutical Industries and Associations (EFPIA) Workshop on Modelling and Simulation, European regulators agreed to the necessity to build expertise to be able to review M&S data provided by companies in their dossier. This led to the establishment of the EMA Modelling and Simulation Working Group (MSWG). Also, there was agreement reached on the need for harmonization on good M&S practices and for continuing dialog across all parties. The MSWG acknowledges the initiative of the EFPIA Model-Informed Drug Discovery and Development (MID3) group in promoting greater consistency in practice, application, and documentation of M&S and considers the paper is an important contribution towards achieving this objective.

Analyzing ERK 1/2 signalling and targets.

The ERK cascade (e.g. Raf-1) protects the heart from cell death and ischemic injury but can also turn maladaptive. Furthermore, an additional autophosphorylation of ERK2 at Thr188 (Erk1 at Thr208) allows ERK to phosphorylate nuclear targets involved in hypertrophy, stressing this additional phosphorylation as a promising pharmacological target. An in silico model was assembled and setup to reproduce different phosphorylation states of ERK 1/2 and various types of stimuli (hypertrophic versus non-hypertrophic). Synergistic and antagonistic receptor stimuli can be predicted in a semi-quantitative model, simulated time courses were experimentally validated. Furthermore, we detected new targets of ERK 1/2, which possibly contribute to the development of pathological hypertrophy. In addition we modeled further interaction partners involved in the protective and maladaptive cascade. Experimental validation included different gene expression data sets supporting key components and novel interaction partners as well as time courses in chronic heart failure.

Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model.

For the development of new treatment strategies against cancer, understanding signaling networks and their changes upon drug response is a promising approach to identify new drug targets and biomarker profiles. Pre-requisites are tumor models with multiple read-out options that accurately reflect the clinical situation. Tissue engineering technologies offer the integration of components of the tumor microenvironment which are known to impair drug response of cancer cells. We established three-dimensional (3D) lung carcinoma models on a decellularized tissue matrix, providing a complex microenvironment for cell growth. For model generation, we used two cell lines with (HCC827) or without (A549) an activating mutation of the epidermal growth factor receptor (EGFR), exhibiting different sensitivities to the EGFR inhibitor gefitinib. EGFR activation in HCC827 was inhibited by gefitinib, resulting in a significant reduction of proliferation (Ki-67 proliferation index) and in the induction of apoptosis (TUNEL staining, M30-ELISA). No significant effect was observed in conventional cell culture. Results from the 3D model correlated with the results of an in silico model that integrates the EGFR signaling network according to clinical data. The application of TGFß1 induced tumor cell invasion, accompanied by epithelial-mesenchymal transition (EMT) both in vitro and in silico. This was confirmed in the 3D model by acquisition of mesenchymal cell morphology and modified expression of fibronectin, E-cadherin, ß-catenin and mucin-1. Quantitative read-outs for proliferation, apoptosis and invasion were established in the complex 3D tumor model. The combined in vitro and in silico model represents a powerful tool for systems analysis.

A Boolean view separates platelet activatory and inhibitory signalling as verified by phosphorylation monitoring including threshold behaviour and integrin modulation.

Platelets are critical for haemostasis and blood clotting. However, since under normal circumstances blood should flow without clotting, its function is regulated via a complex interplay of activating and inhibiting signal transduction pathways. Understanding this network is crucial for treatment of cardiovascular and bleeding diseases. Detailed protein interaction and phosphorylation data are explored to establish a simplified Boolean model of the central platelet cascades. We implemented the model by means of CellNetAnalyzer and showed how different signalling events coalesce into a fully activated system state. Furthermore, we examined the networks' inherent threshold behaviour using the semi-quantitative modelling software SQUAD. Finally, predictions are verified monitoring phosphorylations which mark different activation phases as modelled. The model can also be applied to simulate different pharmacological conditions as they modify node activity (aspirin, clopidogrel, milrinon, iloprost, combination) and is available for further studies. It agrees well with observations. Activatory pathways are diversified to cope with complex environmental conditions. Platelet activation needs several activation steps to integrate over different network subsets, as they are formed by the interplay of activating kinases, calcium mobilization, and the inhibiting cAMP-PKA system. System stability analysis shows two phases: a sub-threshold behaviour, characterized by integration over different activatory and inhibitory conditions, and a beyond threshold phase, represented by competition and shutting down of counter-regulatory pathways. The integrin network and Akt-protein are critical for stable effector response. Dynamic threshold-analysis reveals a dependency of the relative activating input strength necessary to irreversibly engage the system from the absolute inhibitory signal strength.

Exogenous administration of a recombinant variant of TWEAK impairs healing after myocardial infarction by aggravation of inflammation.

BACKGROUND: Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) and its receptor fibroblast growth factor-inducible 14 (Fn14) are upregulated after myocardial infarction (MI) in both humans and mice. They modulate inflammation and the extracellular matrix, and could therefore be important for healing and remodeling after MI. However, the function of TWEAK after MI remains poorly defined. METHODS AND RESULTS: Following ligation of the left coronary artery, mice were injected twice per week with a recombinant human serum albumin conjugated variant of TWEAK (HSA-Flag-TWEAK), mimicking the activity of soluble TWEAK. Treatment with HSA-Flag-TWEAK resulted in significantly increased mortality in comparison to the placebo group due to myocardial rupture. Infarct size, extracellular matrix remodeling, and apoptosis rates were not different after MI. However, HSA-Flag-TWEAK treatment increased infiltration of proinflammatory cells into the myocardium. Accordingly, depletion of neutrophils prevented cardiac ruptures without modulating all-cause mortality. CONCLUSION: Treatment of mice with HSA-Flag-TWEAK induces myocardial healing defects after experimental MI. This is mediated by an exaggerated neutrophil infiltration into the myocardium.

Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation.

BACKGROUND: Hemostasis is a critical and active function of the blood mediated by platelets. Therefore, the prevention of pathological platelet aggregation is of great importance as well as of pharmaceutical and medical interest. Endogenous platelet inhibition is predominantly based on cyclic nucleotides (cAMP, cGMP) elevation and subsequent cyclic nucleotide-dependent protein kinase (PKA, PKG) activation. In turn, platelet phosphodiesterases (PDEs) and protein phosphatases counterbalance their activity. This main inhibitory pathway in human platelets is crucial for countervailing unwanted platelet activation. Consequently, the regulators of cyclic nucleotide signaling are of particular interest to pharmacology and therapeutics of atherothrombosis. Modeling of pharmacodynamics allows understanding this intricate signaling and supports the precise description of these pivotal targets for pharmacological modulation. RESULTS: We modeled dynamically concentration-dependent responses of pathway effectors (inhibitors, activators, drug combinations) to cyclic nucleotide signaling as well as to downstream signaling events and verified resulting model predictions by experimental data. Experiments with various cAMP affecting compounds including anti-platelet drugs and their combinations revealed a high fidelity, fine-tuned cAMP signaling in platelets without cross-talk to the cGMP pathway. The model and the data provide evidence for two independent feedback loops: PKA, which is activated by elevated cAMP levels in the platelet, subsequently inhibits adenylyl cyclase (AC) but as well activates PDE3. By multi-experiment fitting, we established a comprehensive dynamic model with one predictive, optimized and validated set of parameters. Different pharmacological conditions (inhibition, activation, drug combinations, permanent and transient perturbations) are successfully tested and simulated, including statistical validation and sensitivity analysis. Downstream cyclic nucleotide signaling events target different phosphorylation sites for cAMP- and cGMP-dependent protein kinases (PKA, PKG) in the vasodilator-stimulated phosphoprotein (VASP). VASP phosphorylation as well as cAMP levels resulting from different drug strengths and combined stimulants were quantitatively modeled. These predictions were again experimentally validated. High sensitivity of the signaling pathway at low concentrations is involved in a fine-tuned balance as well as stable activation of this inhibitory cyclic nucleotide pathway. CONCLUSIONS: On the basis of experimental data, literature mining and database screening we established a dynamic in silico model of cyclic nucleotide signaling and probed its signaling sensitivity. Thoroughly validated, it successfully predicts drug combination effects on platelet function, including synergism, antagonism and regulatory loops.