Computational modelling of the receptor-tyrosine-kinase-activated MAPK pathway

[Mek1 and Mek2 functions in the formation of the blood placental barrier]

The ERK/MAPK signaling pathway is involved in several cellular functions. Inactivation in mice of genes encoding members of this pathway is often associated with embryonic death resulting from abnormal placental development. The placenta is essential for nutritional and gaseous exchanges between maternal and embryonic circulations, as well as for the removal of metabolic wastes. These exchanges take place without direct contact between the two circulations. In mice, the hematoplacental barrier consists in a triple layer of trophoblast cells and endothelial cells of the embryo. MEK1 and MEK2 are double specificity serine-threonine/tyrosine kinases responsible for the activation of ERK1 and ERK2. Mek1 inactivation results in placental anomalies due to trophoblast cell proliferation and differentiation defects leading to severe delays in the development of placenta and causing the death of the embryo. Although Mek2(-/-) mutant mice survived without any apparent phenotype, double heterozygous Mek1(+/-)Mek2(+/-) mutants die during gestation from placental malformations. Together, these data emphasize the crucial role of the ERK/MAPK cascade in the formation of extraembryonic structures.

A new validated mathematical model of the Wnt signalling pathway predicts effective combinational therapy by sFRP and Dkk

The Wnt signalling pathway controls cell proliferation and differentiation, and its deregulation is implicated in different diseases including cancer. Learning how to manipulate this pathway could substantially contribute to the development of therapies. We developed a mathematical model describing the initial sequence of events in the Wnt pathway, from ligand binding to β-catenin accumulation, and the effects of inhibitors, such as sFRPs (secreted Frizzled-related proteins) and Dkk (Dickkopf). Model parameters were retrieved from experimental data reported previously. The model was retrospectively validated by accurately predicting the effects of Wnt3a and sFRP1 on β-catenin levels in two independent published experiments (R2 between 0.63 and 0.91). Prospective validation was obtained by testing the model's accuracy in predicting the effect of Dkk1 on Wnt-induced β-catenin accumulation (R2≈0.94). Model simulations under different combinations of sFRP1 and Dkk1 predicted a clear synergistic effect of these two inhibitors on β-catenin accumulation, which may point towards a new treatment avenue. Our model allows precise calculation of the effect of inhibitors applied alone or in combination, and provides a flexible framework for identifying potential targets for intervention in the Wnt signalling pathway.

Lactobacillus casei extract induces apoptosis in gastric cancer by inhibiting NF-κB and mTOR-mediated signaling

Lactobacillus casei extract (LBX) has been reported to prevent gastric cancer, but the underlying mechanism remains unclear. The proliferation and cell death of gastric cancer KATO3 cells were examined after treatment with LBX for various times and at various doses. LBX inhibited the growth of gastric cancer cells and induced apoptosis by inactivating NF-κB promoter activity. Apoptosis induced by LBX, however, is not directly associated with the intrinsic mitochondrial pathway. Immunoblot analysis revealed that LBX decreased the expressions of NF-κB and IκB. The reduced NF-κB levels led to the decreased phosphorylation of mTOR signaling components, such as PI3K, Akt, and (p70)S6 kinase. These results showed for the first time that LBX induced apoptosis in gastric cancer cells by inhibiting NF-κB and mTOR-mediated signaling.

BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes

BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.

The role of MAPK in drug-induced kidney injury

This paper focuses on the role that mitogen-activated protein kinases (MAPKs) play in drug-induced kidney injury. The MAPKs, of which there are four major classes (ERK, p38, JNK, and ERK5/BMK), are signalling cascades which have been found to be broadly conserved across a wide variety of organisms. MAPKs allow effective transmission of information from the cell surface to the cytosolic or nuclear compartments. Cross talk between the MAPKs themselves and with other signalling pathways allows the cell to modulate responses to a wide variety of external stimuli. The MAPKs have been shown to play key roles in both mediating and ameliorating cellular responses to stress including xenobiotic-induced toxicity. Therefore, this paper will discuss the specific role of the MAPKs in the kidney in response to injury by a variety of xenobiotics and the potential for therapeutic intervention at the level of MAPK signalling across different types of kidney disease.

Erk2 in ovarian development of green mud crab Scylla paramamosain

We identified extracellular signal-regulated kinase 2 (erk2) from green mud crab, Scylla paramamosain, in this article. It was originally identified from an expressed sequence tag fragment from a normalized gonadal cDNA library. 5' Rapid amplification of cDNA end (RACE) technique was used to obtain the 5' untranslated region (UTR). The full-length cDNA of Sp-erk2 is 1516 bp, including a 5'-terminal UTR of 19 bp, an open-reading frame of 1098 bp, and a 3'-terminal UTR of 399 bp. The translated protein is 365 amino acids in length with a predicted molecular weight of 42 kDa, which is the same as other species. It is the first time that the expression of Sp-erk2 in different stages of ovary development of crustacean was analyzed, and the result showed that the expression of Sp-erk2 increased gradually with ovarian development, with a peak in the mature phase. In situ hybridization histochemistry was used to clarify the detail of expression. Positive signals illustrated that Sp-erk2 mRNA is present in follicular cells when the ovary is in early stages, and in both follicular cells and oocytes when it is in mature phases. All above suggest that Sp-erk2 is important for ovarian development.

Implication of MEK1 and MEK2 in the establishment of the blood-placenta barrier during placentogenesis in mouse

The ERK/MAPK signalling cascade is involved in many cellular functions. In mice, the targeted ablation of genes coding for members of this pathway is often associated with embryonic death due to the abnormal development of the placenta. The placenta is essential for nutritional and gaseous exchanges between maternal and embryonic circulations, as well as for the elimination of metabolic waste. These exchanges occur without direct contact between the two circulations. In mice, the blood-placenta barrier consists of a triple layer of trophoblast cells adjacent to endothelial cells from the embryo. In the ERK/MAPK cascade, MEK1 and MEK2 are dual-specificity kinases responsible for the activation of the ERK1 and ERK2 kinases. Inactivation of Mek1 causes placental malformations resulting from defective proliferation and differentiation of the labyrinthine trophoblast cells and leading to a severe delay in the development and the vascularization of the placenta, which explains the embryonic death. Although Mek2(-/-) mutants survive without any apparent phenotype, a large proportion of Mek1(+/-)Mek2(+/-) double heterozygous mutants die during gestation from placenta anomalies affecting the establishment of the blood-placenta barrier. Together, these data reveal how crucial is the role of the ERK/MAPK pathway during the formation of the placenta.

The Roles of Mitogen-Activated Protein Kinase Pathways in TGF-β-Induced Epithelial-Mesenchymal Transition

The mitogen-activated protein kinase (MAPK) pathway allows cells to interpret external signals and respond appropriately, especially during the epithelial-mesenchymal transition (EMT). EMT is an important process during embryonic development, fibrosis, and tumor progression in which epithelial cells acquire mesenchymal, fibroblast-like properties and show reduced intercellular adhesion and increased motility. TGF-β signaling is the first pathway to be described as an inducer of EMT, and its relationship with the Smad family is already well characterized. Studies of four members of the MAPK family in different biological systems have shown that the MAPK and TGF-β signaling pathways interact with each other and have a synergistic effect on the secretion of additional growth factors and cytokines that in turn promote EMT. In this paper, we present background on the regulation and function of MAPKs and their cascades, highlight the mechanisms of MAPK crosstalk with TGF-β signaling, and discuss the roles of MAPKs in EMT.

Unraveling the design principle for motif organization in signaling networks

Cellular signaling networks display complex architecture. Defining the design principle of this architecture is crucial for our understanding of various biological processes. Using a mathematical model for three-node feed-forward loops, we identify that the organization of motifs in specific manner within the network serves as an important regulator of signal processing. Further, incorporating a systemic stochastic perturbation to the model we could propose a possible design principle, for higher-order organization of motifs into larger networks in order to achieve specific biological output. The design principle was then verified in a large, complex human cancer signaling network. Further analysis permitted us to classify signaling nodes of the network into robust and vulnerable nodes as a result of higher order motif organization. We show that distribution of these nodes within the network at strategic locations then provides for the range of features displayed by the signaling network.

THE IMPORTANCE OF INHIBITORS FOR THE SIMULATION OF METABOLIC PROCESSES: IN SILICOZn2+ INHIBITION OF m-ACONITASE FROM ANALYSIS OF GLYCOLYSIS AND KREBS CYCLE KINETIC MODELS

Metal ions have a major effect on the metabolic processes in cells either as inhibitors or as integral components of enzymes. The inhibition of enzymes can take place either through the inhibition of gene expression or through inhibition of protein function. A particularly interesting example of the effect of a metal ion on metabolism is the observed inhibition of Krebs cycle and alteration of energy metabolism by zinc (II) cations. In this particular case metal ion inhibition of enzyme is linked to one of the major functions of prostate cells of accumulation and excretion of citrate. Experimental results have shown that increase in concentration of zinc (II) in prostate cells effectively blocks progression of a part of the Krebs cycle leading to change in the concentration of several metabolites with largest effect in the accumulation of citrate. Based on previously reported experimental results, several distinct mechanisms for zinc (II) inhibition of Krebs cycle were proposed. In order to determine the precise mechanism of inhibition in this system, a mathematical model of glycolysis and Krebs cycle was constructed. Three different types of inhibition were analyzed, including competitive and uncompetitive inhibition as well as inhibition through the alteration of the expression level of m-aconitase. The effects of different inhibition models on metabolite concentrations were investigated as a time course simulation of the system of reactions. Several kinetic parameters in the model were optimized in order to best resemble experimental measurements. The simulation shows that only competitive inhibition leads to an agreement with experimental data.

CROSSTALK FACILITATES SPATIAL SIGNAL PROPAGATION THROUGH MAPK CASCADES

In intracellular mitogen-activated protein kinase (MAPK) cascades, it has been shown that signals can be propagated across the cell cytosol in the form of phosphoprotein waves arising from the bistable response of MAPK to active MAPK kinase. Without such a bistable response, however, they can not propagate into distant cell compartments, although a long positive feedback endows a mechanistically-distinct bistable response of MAPK to extracellular signal. Here we provide a compensate means that uses crosstalk between parallel identical pathways of MAPK cascades. For a spherical cell, we find that both unidirectional and bidirectional crosstalk with enhancement of phosphorylation can facilitate phosphoprotein signal propagation from the plasma membrane to the periphery of cell nucleus. Moreover, different shallow spatial gradients of biphosphorylated MAPK occur in the cytosol under different strengths of pathway interactions. These results suggest that crosstalk would be utilized by living organisms for spatial information transfer and cellular decision-making processing.

Mechanistic modeling to investigate signaling by oncogenic Ras mutants

Mathematical models based on biochemical reaction mechanisms can be a powerful complement to experimental investigations of cell signaling networks. In principle, such models have the potential to find the behaviors that result from well-understood component interactions and their measurable properties, such as concentrations and rate constants. As cancer results from the acquisition of mutations that alter the expression level and/or the biochemistry of proteins encoded by mutated genes, mathematical models of cell signaling networks would also seem to have the potential to predict how these changes alter cell signaling to produce a cancer phenotype. Ras is commonly found in cancer and has been extensively characterized at the level of detail needed to develop such models. Here, we consider how biochemical mechanism-based models have been used to study mutant Ras signaling. These models demonstrate that it is clearly possible to use observable properties of individual reactions to predict how the entire system behaves to produce the high levels of signal that drive the cancer phenotype. These models also demonstrate differences in how models are developed and studied. Their evaluation suggests which approaches are most promising for future work.

Sensitivity analysis predicts that the ERK-pMEK interaction regulates ERK nuclear translocation

Following phosphorylation, nuclear translocation of the mitogen-activated protein kinases (MAPKs), ERK1 and ERK2, is critical for both gene expression and DNA replication induced by growth factors. ERK nuclear translocation has therefore been studied extensively, but many details remain unresolved, including whether or not ERK dimerisation is required for translocation. Here, we simulate ERK nuclear translocation with a compartmental computational model that includes systematic sensitivity analysis. The governing ordinary differential equations are solved with the backward differentiation formula and decoupled direct methods. To better understand the regulation of ERK nuclear translocation, we use this model in conjunction with a previously published model of the ERK pathway that does not include an ERK dimer species and with experimental measurements of nuclear translocation of wild-type ERK and a mutant form, ERK1-4, which is unable to dimerise. Sensitivity analysis reveals that the delayed nuclear uptake of ERK1-4 compared to that of wild-type ERK1 can be explained by the altered interaction of ERK1-4 with phosphorylated MEK (MAPK/ERK kinase), and so may be independent of dimerisation. Our study also identifies biological experiments that can verify this explanation.

Raf family kinases: old dogs have learned new tricks

First identified in the early 1980s as retroviral oncogenes, the Raf proteins have been the objects of intense research. The discoveries 10 years later that the Raf family members (Raf-1, B-Raf, and A-Raf) are bona fide Ras effectors and upstream activators of the ubiquitous ERK pathway increased the interest in these proteins primarily because of the central role that this cascade plays in cancer development. The important role of Raf in cancer was corroborated in 2002 with the discovery of B-Raf genetic mutations in a large number of tumors. This led to intensified drug development efforts to target Raf signaling in cancer. This work yielded not only recent clinical successes but also surprising insights into the regulation of Raf proteins by homodimerization and heterodimerization. Surprising insights also came from the hunt for new Raf targets. Although MEK remains the only widely accepted Raf substrate, new kinase-independent roles for Raf proteins have emerged. These include the regulation of apoptosis by suppressing the activity of the proapoptotic kinases, ASK1 and MST2, and the regulation of cell motility and differentiation by controlling the activity of Rok-α. In this review, we discuss the regulation of Raf proteins and their role in cancer, with special focus on the interacting proteins that modulate Raf signaling. We also describe the new pathways controlled by Raf proteins and summarize the successes and failures in the development of efficient anticancer therapies targeting Raf. Finally, we also argue for the necessity of more systemic approaches to obtain a better understanding of how the Ras-Raf signaling network generates biological specificity.

Integrative systems biology for data-driven knowledge discovery

Integrative systems biology is an approach that brings together diverse high-throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost-effective manner. By using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of as yet unknown components of a system of interest and how its malfunction leads to disease.

Gene expression in the medulla following oral infection of cattle with bovine spongiform encephalopathy

The identification of variations in gene expression in response to bovine spongiform encephalopathy (BSE) may help to elucidate the mechanisms of neuropathology and prion replication and discover biomarkers for disease. In this study, genes that are differentially expressed in the caudal medulla tissues of animals infected with different doses of PrP(BSE) at 12 and 45 mo post infection were compared using array containing 24,000 oligonucleotide probes. Data analysis identified 966 differentially expressed (DE) genes between control and infected animals. Genes identified in at least two of four experiments (control versus 1-g infected animals at 12 and 45-mo; control versus 100-g infected animals at 12 and 45 mo) were considered to be the genes that may be associated with BSE disease. From the 176 DE genes associated with BSE, 84 had functions described in the Gene Ontology (GO) database. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of 14 genes revealed that prion infection may cause dysfunction of several different networks, including extracellular matrix (ECM), cell adhesion, neuroactive ligand-receptor interaction, complement and coagulation cascades, MAPK signaling, neurodegenerative disorder, SNARE interactions in vesicular transport, and the transforming growth factor (TGF) beta signaling pathways. The identification of DE genes will contribute to a better understanding of the molecular mechanisms of neuropathology in bovine species. Additional studies on larger number of animals are in progress in our laboratory to investigate the roles of these DE genes in pathogenesis of BSE.

Computational modelling of kinase signalling cascades

In this chapter, we describe general methods used to create dynamic computational models of kinase signalling cascades, and tools to support this activity. We focus on the ordinary differential equation models, and show how these fit into a general framework of qualitative and quantitative (stochastic and continuous) models. The modelling we describe is part of the activity of BioModel engineering which provides a systematic approach for designing, constructing, and analyzing computational models of biological systems.

Neurotoxic mechanisms of DNA damage: focus on transcriptional inhibition

Although DNA damage-induced neurotoxicity is implicated in various pathologies of the nervous system, its underlying mechanisms are not completely understood. Transcription is a DNA transaction that is highly active in the nervous system. In addition to its direct role in expression of the genetic information, transcription contributes to DNA damage detection and repair as well as chromatin organization including biogenesis of the nucleolus. Transcription is inhibited by DNA single-strand breaks and DNA adducts. Hence, transcription inhibition may be an important contributor to the neurotoxic consequences of such types of DNA damage. This review discusses the existing evidence in support of the latter hypothesis. The presented literature suggests that neuronal DNA damage interferes with the RNA-Polymerase-2-dependent transcription of genes encoding proteins with critical functions in neurotransmission and intracellular signaling. The latter category includes extracellular signal-regulated kinase-1/2 mitogen-activated protein kinase phosphatases whose lowered expression results in chronic activation of extracellular signal-regulated kinase-1/2 and its reduced responsiveness to physiological stimuli. Conversely, DNA damage-induced inhibition of RNA-Polymerase-1 and the subsequent disruption of the nucleolus induce p53-mediated apoptosis of developing neurons. Finally, decreasing nucleolar transcription may link DNA damage to chronic neurodegeneration in adults.

Multiple decisive phosphorylation sites for the negative feedback regulation of SOS1 via ERK

EGF-induced activation of ERK has been extensively studied by both experimental and theoretical approaches. Here, we used a simulation model based mostly on experimentally determined parameters to study the ERK-mediated negative feedback regulation of the Ras guanine nucleotide exchange factor, son of sevenless (SOS). Because SOS1 is phosphorylated at multiple serine residues upon stimulation, we evaluated the role of the multiplicity by building two simulation models, which we termed the decisive and cooperative phosphorylation models. The two models were constrained by the duration of Ras activation and basal phosphorylation level of SOS1. Possible solutions were found only in the decisive model wherein at least three, and probably more than four, phosphorylation sites decisively suppress the SOS activity. Thus, the combination of experimental approaches and the model analysis has suggested an unexpected role of multiple phosphorylations of SOS1 in the negative regulation.

A mathematical model of intercellular signaling during epithelial wound healing

Recent experiments monitoring the healing process of wounded epithelial monolayers have demonstrated the necessity of MAPK activation for coordinated cell movement after damage. This MAPK activity is characterized by two wave-like phenomena. One MAPK "wave" that originates immediately after injury, propagates deep into the cell sheet, away from the edge, and then rebounds back to the wound interface. After this initial MAPK activity has largely disappeared, a second MAPK front propagates slowly from the wound interface and also continues into the cell sheet, maintaining a sustained level of MAPK activity throughout the cell sheet. It has been suggested that the first wave is initiated by Reactive Oxygen Species (ROS) generated at the time of injury. In this work, we develop a minimal mathematical model that reproduces the observed behavior. The main ingredients of our model are a competition between ligand (e.g., Epithelial Growth Factor) and ROS for the activation of Epithelial Growth Factor Receptor, and a feedback loop between receptor occupancy and MAPK activation. We explore the mathematical properties of the model and look for traveling wave solutions consistent with the experimentally observed MAPK activity patterns.

Cellular signaling identifiability analysis: a case study

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology.

Simulation of a Petri net-based model of the terpenoid biosynthesis pathway

Background

The development and simulation of dynamic models of terpenoid biosynthesis has yielded a systems perspective that provides new insights into how the structure of this biochemical pathway affects compound synthesis. These insights may eventually help identify reactions that could be experimentally manipulated to amplify terpenoid production. In this study, a dynamic model of the terpenoid biosynthesis pathway was constructed based on the Hybrid Functional Petri Net (HFPN) technique. This technique is a fusion of three other extended Petri net techniques, namely Hybrid Petri Net (HPN), Dynamic Petri Net (HDN) and Functional Petri Net (FPN).

Results

The biological data needed to construct the terpenoid metabolic model were gathered from the literature and from biological databases. These data were used as building blocks to create an HFPNe model and to generate parameters that govern the global behaviour of the model. The dynamic model was simulated and validated against known experimental data obtained from extensive literature searches. The model successfully simulated metabolite concentration changes over time (pt) and the observations correlated with known data. Interactions between the intermediates that affect the production of terpenes could be observed through the introduction of inhibitors that established feedback loops within and crosstalk between the pathways.

Conclusions

Although this metabolic model is only preliminary, it will provide a platform for analysing various high-throughput data, and it should lead to a more holistic understanding of terpenoid biosynthesis.

Pem renders tumor cells resistant to apoptotic cell death induced by a CD8+ T cell-mediated immune response or anticancer drug treatment

Pem, a member of homeobox genes, is an oncofetal gene which is preferentially expressed in reproductive tissues and in multiple tumor cell lines. However, the function of Pem in tumor cell lines has not been elucidated. Herein we report that the ectopic expression of Pem in TC-1, a human papillomavirus type 16 (HPV-16) E7-expressing surrogate cervical tumor cell line, demonstrated a significant increase in extracellular signal-regulated kinase (ERK) activity and multiple resistance to various apoptotic pressures from an E7-specific CD8(+) T cell-mediated immune response and anticancer drug treatment. The observed resistance to apoptotic death of the Pem-over-expressing TC-1 tumor cells (TC-1/Pem) was associated with the down-regulation of a pro-apoptotic molecule, such as BIM, and up-regulation of an anti-apoptotic molecule, such as Bcl-2 protein, which mediated ERK activation. We also observed that the intratumoral injection of an ERK inhibitor enhanced the therapeutic efficacy of E7-specific CD8(+) T cell adoptive transfer or anticancer drug treatment against the resistant TC-1/Pem tumor. This is the first evidence demonstrating an association between Pem and a signaling pathway, namely the ERK-mediated survival signal transduction pathway. Thus, our data indicate that activation of the ERK pathway represents a new mechanism of Pem-mediated multiple resistances and the present research will contribute to the development of a novel strategy in cancer therapy against Pem-over-expressing tumor cells.

Toxicity testing in the 21st century: a vision and a strategy

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology.

Toxicity testing in the 21st century: a vision and a strategy

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology.

Employing a Mechanistic Model for the MAPK Pathway to Examine the Impact of Cellular all or None Behavior on Overall Tissue Response

The mitogen activated protein kinase (MAPK) cascade is a three-tiered phosphorylation cascade that is ubiquitously expressed among eukaryotic cells. Its primary function is to propagate signals from cell surface receptors to various cytosolic and nuclear targets. Recent studies have demonstrated that the MAPK cascade exhibits an all-or-none response to graded stimuli. This study quantitatively investigates MAPK activation in Xenopus oocytes using both empirical and biologically-based mechanistic models. Empirical models can represent overall tissue MAPK activation in the oocytes. However, these models lack description of key biological processes and therefore give no insight into whether the cellular response occurs in a graded or all-or-none fashion. To examine the propagation of cellular MAPK all-or-none activation to overall tissue response, mechanistic models in conjunction with Monte Carlo simulations are employed. An adequate description of the dose response relationship of MAPK activation in Xenopus oocytes is achieved. Furthermore, application of these mechanistic models revealed that the initial receptor-ligand binding rate contributes to the cells' ability to exhibit an all-or-none MAPK activation response, while downstream activation parameters contribute more to the magnitude of activation. These mechanistic models enable us to identify key biological events which quantitatively impact the shape of the dose response curve, especially at low environmentally relevant doses.

Integration of a phosphatase cascade with the mitogen-activated protein kinase pathway provides for a novel signal processing function

We mathematically modeled the receptor-dependent mitogen-activated protein kinase (MAPK) signaling by incorporating the regulation through cellular phosphatases. Activation induced the alignment of a phosphatase cascade in parallel with the MAPK pathway. A novel regulatory motif was, thus, generated, providing for the combinatorial control of each MAPK intermediate. This ensured a non-linear mode of signal transmission with the output being shaped by the balance between the strength of input signal and the activity gradient along the phosphatase axis. Shifts in this balance yielded modulations in topology of the motif, thereby expanding the repertoire of output responses. Thus, we identify an added dimension to signal processing wherein the output response to an external stimulus is additionally filtered through indicators that define the phenotypic status of the cell.

Theoretical and experimental analysis links isoform-specific ERK signalling to cell fate decisions

Cell fate decisions are regulated by the coordinated activation of signalling pathways such as the extracellular signal-regulated kinase (ERK) cascade, but contributions of individual kinase isoforms are mostly unknown. By combining quantitative data from erythropoietin-induced pathway activation in primary erythroid progenitor (colony-forming unit erythroid stage, CFU-E) cells with mathematical modelling, we predicted and experimentally confirmed a distributive ERK phosphorylation mechanism in CFU-E cells. Model analysis showed bow-tie-shaped signal processing and inherently transient signalling for cytokine-induced ERK signalling. Sensitivity analysis predicted that, through a feedback-mediated process, increasing one ERK isoform reduces activation of the other isoform, which was verified by protein over-expression. We calculated ERK activation for biochemically not addressable but physiologically relevant ligand concentrations showing that double-phosphorylated ERK1 attenuates proliferation beyond a certain activation level, whereas activated ERK2 enhances proliferation with saturation kinetics. Thus, we provide a quantitative link between earlier unobservable signalling dynamics and cell fate decisions.

Rapid and sustained nuclear-cytoplasmic ERK oscillations induced by epidermal growth factor

Although the ERK pathway has a central role in the response of cells to growth factors, its regulatory structure and dynamics are incompletely understood. To investigate ERK activation in real time, we expressed an ERK–GFP fusion protein in human mammary epithelial cells. On EGF stimulation, we observed sustained oscillations of the ERK–GFP fusion protein between the nucleus and cytoplasm with a periodicity of ∼15 min. The oscillations were persistent (>45 cycles), independent of cell cycle phase, and were highly dependent on cell density, essentially disappearing at confluency. Oscillations occurred even at ligand doses that elicited very low levels of ERK phosphorylation, and could be detected biochemically in both transfected and nontransfected cells. Mathematical modeling revealed that negative feedback from phosphorylated ERK to the cascade input was necessary to match the robustness of the oscillation characteristics observed over a broad range of ligand concentrations. Our characterization of single-cell ERK dynamics provides a quantitative foundation for understanding the regulatory structure of this signaling cascade.

Triptolide Inhibits the Proliferation of Immortalized HT22 Hippocampal Cells Via Persistent Activation of Extracellular Signal-Regulated Kinase-1/2 by Down-Regulating Mitogen-Activated Protein Kinase Phosphatase-1 Expression

OBJECTIVE

Triptolide (TP) has been reported to suppress the expression of mitogen-activated protein kinase (MAPK) phosphatase-1 (MKP-1), of which main function is to inactivate the extracellular signal-regulated kinase-1/2 (ERK-1/2), the p38 MAPK and the c-Jun N-terminal kinase-1/2 (JNK-1/2), and to exert antiproliferative and pro-apoptotic activities. However, the mechanisms underlying antiproliferative and pro-apoptotic activities of TP are not fully understood. The purpose of this study was to examine whether the down-regulation of MKP-1 expression by TP would account for antiproliferative activity of TP in immortalized HT22 hippocampal cells.

METHODS

MKP-1 expression and MAPK phosphorylation were analyzed by Western blot. Cell proliferation was assessed by (3)H-thymidine incorporation. Small interfering RNA (siRNA) against MKP-1, vanadate (a phosphatase inhibitor), U0126 (a specific inhibitor for ERK-1/2), SB203580 (a specific inhibitor for p38 MAPK), and SP600125 (a specific inhibitor for JNK-1/2) were employed to evaluate a possible mechanism of antiproliferative action of TP.

RESULTS

At its non-cytotoxic dose, TP suppressed MKP-1 expression, reduced cell growth, and induced persistent ERK-1/2 activation. Similar growth inhibition and ERK-1/2 activation were observed when MKP-1 expression was blocked by MKP-1 siRNA and its activity was inhibited by vanadate. The antiproliferative effects of TP, MKP-1 siRNA, and vanadate were significantly abolished by U0126, but not by SB203580 or SP600125.

CONCLUSION

Our findings suggest that TP inhibits the growth of immortalized HT22 hippocampal cells via persistent ERK-1/2 activation by suppressing MKP-1 expression. Additionally, this study provides evidence supporting that MKP-1 may play an important role in regulation of neuronal cell growth.

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

BACKGROUND

The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway.

RESULTS

We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors.

CONCLUSION

Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.

Translating biomaterial properties to intracellular signaling

Bioactive materials present important micro-environmental cues that induce specific intracellular signaling responses which ultimately determine cell behavior. For example, vascular endothelial cells on a normal vessel wall resist inflammation and thrombosis, but the same cells seeded on an artificial vascular graft or stent do not. What makes these cells behave so differently when they are adhered to different materials? Intracellular signaling from integrins and other cell-surface receptors is an important part of the answer, but these signaling responses constitute a highly-branched, interconnected network of molecules. In order to perform rational design of biomaterials, one must understand how altering the properties of the material (micro-environment) causes changes in cell behavior, and this in turn requires understanding the complex signaling response. Systems biology and mathematical modeling aid analysis of the connectivity of this network. This review summarizes applicable systems biology and mathematical modeling techniques including ordinary differential equations-based models, principal component analysis, and Bayesian networks. Next covered is biomaterials research which studies the intracellular signaling responses generated by variation of biomaterial properties. Finally, the review details ways in which modeling has been or could be applied to better understand the link between biomaterial properties and intracellular signaling.

Coupled stochastic spatial and non-spatial simulations of ErbB1 signaling pathways demonstrate the importance of spatial organization in signal transduction

Background

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation.

Methodology/Principal Findings

Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners.

Conclusions/Significance

Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.

Specificity and robustness of the mammalian MAPK-IEG network

The mitogen-activated protein kinase cascade is a conserved signal transduction pathway found in organisms of complexity spanning from yeast to humans. In many mammalian tissue types, this pathway can correctly transduce signals from different extracellular messengers, leading to specific and often mutually exclusive cellular responses. The transduced signal is tuned by a complicated set of positive and negative feedback control mechanisms and fed into a downstream gene expression network. This network, based on the immediate early gene system, has two possible, mutually exclusive outcomes. Using a mathematical model, we study how different stimuli lead to different temporal signal structure. Further, we investigate how each of the feedback controls contributes to the overall specificity of the gene expression output, and hypothesize that the complicated nature of the mammalian mitogen-activated protein kinase pathway results in a system able to robustly identify and transduce the proper signal without investing in two completely separate signal cascades. Finally, we quantify the role of the RKIP protein in shaping the signal, and propose a novel mechanism of its involvement in cancer metastasis.

Positive- and negative-feedback regulations coordinate the dynamic behavior of the Ras-Raf-MEK-ERK signal transduction pathway

The Ras-Raf-MEK-ERK pathway (or ERK pathway) is an important signal transduction system involved in the control of cell proliferation, survival and differentiation. However, the dynamic regulation of the pathway by positive- and negative-feedback mechanisms, in particular the functional role of Raf kinase inhibitor protein (RKIP) are still incompletely understood. RKIP is a physiological endogenous inhibitor of MEK phosphorylation by Raf kinases, but also participates in a positive-feedback loop in which ERK can inactivate RKIP. The aim of this study was to elucidate the hidden dynamics of these feedback mechanisms and to identify the functional role of RKIP through combined efforts of biochemical experiments and in silico simulations based on an experimentally validated mathematical model. We show that the negative-feedback loop from ERK to SOS plays a crucial role in generating an oscillatory behavior of ERK activity. The positive-feedback loop in which ERK functionally inactivates RKIP also enhances the oscillatory activation pattern of ERK. However, RKIP itself has an important role in inducing a switch-like behavior of MEK activity. When overexpressed, RKIP also causes delayed and reduced responses of ERK. Thus, positive- and negative-feedback loops and RKIP work together to shape the response pattern and dynamical characteristics of the ERK pathway.

Current concepts in research related to oncogenes implicated in salivary gland tumourigenesis: a review of the literature

BACKGROUND

Salivary gland tumours are relatively uncommon and there exists considerable difficulty in decisions regarding prognosis and management, as well as diagnostic uncertainty that has implications for treatment.

METHOD

Literature pertaining to individual oncogenes has been reviewed and commented upon, specifically looking at the role of these as diagnostic and prognostic markers and as potential targets for treatments.

RESULTS

kit, PLAG1, Mect1-Maml2, HMGIC, HER2/neu, ras, c-fos and Sox-4 all have seminal small-scale studies in the literature with potential for further research and eventual clinical applications.

CONCLUSION

A wide variety of oncogenes are implicated in salivary gland tumourigenesis, with evidence being confined to small murine or in vitro studies more often than not. There are possible roles for different oncogenes in therapeutics, prognosis and management of specific salivary gland tumours.

Version control of pathway models using XML patches

Background

Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution.

Results

We present a model version control method, along with a prototype implementation, based on XML patches. We show its application to the EGF/RAS/RAF pathway.

Conclusion

Our method allows quick and convenient storage of a wide range of model variations and enables a thorough explanation of these variations. Trying to produce these results without such methods results in slow and cumbersome development that is prone to frustration and human error.

A systems biological approach suggests that transcriptional feedback regulation by dual-specificity phosphatase 6 shapes extracellular signal-related kinase activity in RAS-transformed fibroblasts

Mitogen-activated protein kinase (MAPK) signaling determines crucial cell fate decisions in most cell types, and mediates cellular transformation in many types of cancer. The activity of MAPK is controlled by reversible phosphorylation, and the quantitative characteristics of MAPK activation determine the cellular response. Many systems biological studies have analyzed the activation kinetics and the dose-response behavior of the MAPK signaling pathway. Here we investigate how the pathway activity is controlled by transcriptional feedback loops. Initially, we predict that MAPK signaling regulates phosphatases, by integrating promoter sequence data and ontology-based classification of gene function. From this, we deduce that MAPK signaling might be controlled by transcriptional negative feedback regulation via dual-specificity phosphatases (DUSPs), and implement a mathematical model to further test this hypothesis. Using time-resolved measurements of pathway activity and gene expression, we employ a model selection approach, and select DUSP6 as a highly likely candidate for shaping the activity of the MAPK pathway during cellular transformation caused by oncogenic RAS. Two predictions from the model were confirmed: first, feedback regulation requires that DUSP6 mRNA and protein are unstable; and second, the activation kinetics of MAPK are ultrasensitive. Taken together, an integrated systems biological approach reveals that transcriptional negative feedback controls the kinetics and the extent of MAPK activation under both physiological and pathological conditions.

Modelling cellular signalling systems

Cell signalling pathways and networks are complex and often non-linear. Signalling pathways can be represented as systems of biochemical reactions that can be modelled using differential equations. Computational modelling of cell signalling pathways is emerging as a tool that facilitates mechanistic understanding of complex biological systems. Mathematical models are also used to generate predictions that may be tested experimentally. In the present chapter, the various steps involved in building models of cell signalling pathways are discussed. Depending on the nature of the process being modelled and the scale of the model, different mathematical formulations, ranging from stochastic representations to ordinary and partial differential equations are discussed. This is followed by a brief summary of some recent modelling successes and the state of future models.

Ontologies of cellular networks

As part of a series of workshops on different aspects of biomedical ontology sponsored by the National Center for Biomedical Ontology (NCBO), a workshop titled "Ontologies of Cellular Networks" took place in Newark, New Jersey, on 27 to 28 March 2008. This workshop included more than 30 participants from various backgrounds in biomedicine and bioinformatics. The goal of the workshop was to provide an introduction to the basic tools and methods of ontology, as well as to enhance coordination between groups already working on ontologies of cellular networks. The meeting focused on three questions: What is an ontology? What is a pathway? What is a cellular network?

A comparison of gene expression profiles between primary human AML cells and AML cell line

In acute myeloid leukemia (AML), hematologic malignancies are characterized by recurring chromosomal abnormalities. Chromosome translocation t(9;11)(p22;q23) is one of the most common genetic aberrations and results in the formation of the MLL-AF9 fusion gene that functions as a facilitator of cell growth directly. In order to study this type of AML, the cell lines with cytogenetically diagnosed t(9;11)(p22;q23), such as Mono Mac 6 (MM6), have been widely used. To examine whether there is any difference in gene expression between the primary human t(9;11) AML cells and MM6 cell line, genome-wide transcriptome analysis was performed on MM6 cell line using SAGE and the results were compared to the profile of primary human t(9;11) AML cells. 884 transcripts which were alternatively expressed between MM6 cells and primary human t(9;11) cells were identified through statistical analysis (P < 0.05) and 4-fold expression change. Of these transcripts, 830 (94%) matched to known genes or EST were classified by functional categories (http://david.abcc.ncifcrf.gov/). The majority of alternatively expressed genes in MM6 were involved in biosynthetic and metabolic processes, but HRAS, a protein that is known to be associated with leukemogenesis, was expressed only in MM6 cells and several other genes involved in Erk1/Erk2 MAPK pathway were also over-expressed in MM6. Therefore, since MM6 cell line has a similar expression profile to primary human t(9;11) AML in general and expresses uniquely a strong Erk1/Erk2 MAPK pathway including HRAS, it can be used as a model for HRAS-positive t(9;11) AML.

Nanovehicular intracellular delivery systems

This article provides an overview of principles and barriers relevant to intracellular drug and gene transport, accumulation and retention (collectively called as drug delivery) by means of nanovehicles (NV). The aim is to deliver a cargo to a particular intracellular site, if possible, to exert a local action. Some of the principles discussed in this article apply to noncolloidal drugs that are not permeable to the plasma membrane or to the blood-brain barrier. NV are defined as a wide range of nanosized particles leading to colloidal objects which are capable of entering cells and tissues and delivering a cargo intracelullarly. Different localization and targeting means are discussed. Limited discussion on pharmacokinetics and pharmacodynamics is also presented. NVs are contrasted to micro-delivery and current nanotechnologies which are already in commercial use. Newer developments in NV technologies are outlined and future applications are stressed. We also briefly review the existing modeling tools and approaches to quantitatively describe the behavior of targeted NV within the vascular and tumor compartments, an area of particular importance. While we list "elementary" phenomena related to different level of complexity of delivery to cancer, we also stress importance of multi-scale modeling and bottom-up systems biology approach.