MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network

Plant systems biology: network matters

Systems biology is all about networks. A recent trend has been to associate systems biology exclusively with the study of gene regulatory or protein-interaction networks. However, systems biology approaches can be applied at many other scales, from the subatomic to the ecosystem scales. In this review, we describe studies at the sub-cellular, tissue, whole plant and crop scales and highlight how these studies can be related to systems biology. We discuss the properties of system approaches at each scale as well as their current limits, and pinpoint in each case advances unique to the considered scale but representing potential for the other scales. We conclude by examining plant models bridging different scales and considering the future prospects of plant systems biology.

Systems glycobiology: biochemical reaction networks regulating glycan structure and function

There is a growing use of bioinformatics based methods in the field of Glycobiology. These have been used largely to curate glycan structures, organize array-based experimental data and display existing knowledge of glycosylation-related pathways in silico. Although the cataloging of vast amounts of data is beneficial, it is often a challenge to gain meaningful mechanistic insight from this exercise alone. The development of specific analysis tools to query the database is necessary. If these queries can integrate existing knowledge of glycobiology, new insights may be gained. Such queries that couple biochemical knowledge and mathematics have been developed in the field of Systems Biology. The current review summarizes the current state of the art in the application of computational modeling in the field of Glycobiology. It provides (i) an overview of experimental and online resources that can be used to construct glycosylation reaction networks, (ii) mathematical methods to formulate the problem including a description of ordinary differential equation and logic-based reaction networks, (iii) optimization techniques that can be applied to fit experimental data for the purpose of model reconstruction and for evaluating unknown model parameters, (iv) post-simulation analysis methods that yield experimentally testable hypotheses and (v) a summary of available software tools that can be used by non-specialists to perform many of the above functions.

Stochastic hybrid modeling of intracellular calcium dynamics

Deterministic models of biochemical processes at the subcellular level might become inadequate when a cascade of chemical reactions is induced by a few molecules. Inherent randomness of such phenomena calls for the use of stochastic simulations. However, being computationally intensive, such simulations become infeasible for large and complex reaction networks. To improve their computational efficiency in handling these networks, we present a hybrid approach, in which slow reactions and fluxes are handled through exact stochastic simulation and their fast counterparts are treated partially deterministically through chemical Langevin equation. The classification of reactions as fast or slow is accompanied by the assumption that in the time-scale of fast reactions, slow reactions do not occur and hence do not affect the probability of the state. Our new approach also handles reactions with complex rate expressions such as Michaelis-Menten kinetics. Fluxes which cannot be modeled explicitly through reactions, such as flux of Ca(2+) from endoplasmic reticulum to the cytosol through inositol 1,4,5-trisphosphate receptor channels, are handled deterministically. The proposed hybrid algorithm is used to model the regulation of the dynamics of cytosolic calcium ions in mouse macrophage RAW 264.7 cells. At relatively large number of molecules, the response characteristics obtained with the stochastic and deterministic simulations coincide, which validates our approach in the limit of large numbers. At low doses, the response characteristics of some key chemical species, such as levels of cytosolic calcium, predicted with stochastic simulations, differ quantitatively from their deterministic counterparts. These observations are ubiquitous throughout dose response, sensitivity, and gene-knockdown response analyses. While the relative differences between the peak-heights of the cytosolic [Ca(2+)] time-courses obtained from stochastic (mean of 16 realizations) and deterministic simulations are merely 1%-4% for most perturbations, it is specially sensitive to levels of G(βγ) (relative difference as large as 90% at very low G(βγ)).

Feedback regulation of EGFR signalling: decision making by early and delayed loops

Human-made information relay systems invariably incorporate central regulatory components, which are mirrored in biological systems by dense feedback and feedforward loops. This type of system control is exemplified by positive and negative feedback loops (for example, receptor endocytosis and dephosphorylation) that enable growth factors and receptor Tyr kinases of the epidermal growth factor receptor (EGFR)/ERBB family to regulate cellular function. Recent studies show that the collection of feedback regulatory loops can perform computational tasks - such as decoding ligand specificity, transforming graded input signals into a digital output and regulating response kinetics. Aberrant signal processing and feedback regulation can lead to defects associated with pathologies such as cancer.

The elements of human cyclin D1 promoter and regulation involved

Cyclin D1 is a cell cycle machine, a sensor of extracellular signals and plays an important role in G1-S phase progression. The human cyclin D1 promoter contains multiple transcription factor binding sites such as AP-1, NF-қB, E2F, Oct-1, and so on. The extracellular signals functions through the signal transduction pathways converging at the binding sites to active or inhibit the promoter activity and regulate the cell cycle progression. Different signal transduction pathways regulate the promoter at different time to get the correct cell cycle switch. Disorder regulation or special extracellular stimuli can result in cell cycle out of control through the promoter activity regulation. Epigenetic modifications such as DNA methylation and histone acetylation may involved in cyclin D1 transcriptional regulation.

Tunable signal processing in synthetic MAP kinase cascades

The flexibility of MAPK cascade responses enables regulation of a vast array of cell fate decisions, but elucidating the mechanisms underlying this plasticity is difficult in endogenous signaling networks. We constructed insulated mammalian MAPK cascades in yeast to explore how intrinsic and extrinsic perturbations affect the flexibility of these synthetic signaling modules. Contrary to biphasic dependence on scaffold concentration, we observe monotonic decreases in signal strength as scaffold concentration increases. We find that augmenting the concentration of sequential kinases can enhance ultrasensitivity and lower the activation threshold. Further, integrating negative regulation and concentration variation can decouple ultrasensitivity and threshold from the strength of the response. Computational analyses show that cascading can generate ultrasensitivity and that natural cascades with different kinase concentrations are innately biased toward their distinct activation profiles. This work demonstrates that tunable signal processing is inherent to minimal MAPK modules and elucidates principles for rational design of synthetic signaling systems.

Models at the single cell level

Many cellular behaviors cannot be completely captured or appropriately described at the cell population level. Noise induced by stochastic chemical reactions, spatially polarized signaling networks, and heterogeneous cell-cell communication are among the many phenomena that require fine-grained analysis. Accordingly, the mathematical models used to describe such systems must be capable of single cell or subcellular resolution. Here, we review techniques for modeling single cells, including models of stochastic chemical kinetics, spatially heterogeneous intracellular signaling, and spatial stochastic systems. We also briefly discuss applications of each type of model.

Mitogen-activated protein kinase signalling and ERK1/2 bistability in asthma

Mitogen-activated protein kinases (MAPKs) integrate signals from numerous receptors and translate these signals into cell functions. MAPKs are critical for immune cell metabolism, migration, production of pro-inflammatory mediators, survival and differentiation. We provide a concise review of the involvement of MAPK in important cells of the immune system. Certain cell functions, e.g. production of pro-inflammatory mediators resolve quickly and may require a transient MAPK activation, other processes such as cell differentiation and long-term survival may require persistent MAPK signal. The persistent MAPK signal is frequently a consequence of positive feedback loops or double negative feedback loops which perpetuate the signal after removal of an external cell stimulus. This self-perpetuated activation of a signalling circuit is a manifestation of its bistability. Bistable systems can exist in 'on' and 'off' states and both states are stable. We have demonstrated the existence of self-perpetuated activation mechanism for ERK1/2 in bronchial epithelial cells. This sustained activation of ERK1/2 supports long-term survival of these cells and primes them for cytokine transcription. ERK1/2 bistability arises from repetitive stimulation of the cell. The repeated stimulation (e.g. repeated viral infection or repeated allergen exposure) seems to be a common theme in asthma and other chronic illnesses. We thus hypothesize that the self-perpetuated ERK1/2 signal plays an important role in the pathogenesis of asthma.

Architecture-dependent robustness and bistability in a class of genetic circuits

Understanding the relationship between genotype and phenotype is a challenge in systems biology. An interesting yet related issue is why a particular circuit topology is present in a cell when the same function can supposedly be obtained from an alternative architecture. Here we analyzed two topologically equivalent genetic circuits of coupled positive and negative feedback loops, named NAT and ALT circuits, respectively. The computational search for the oscillation volume of the entire biologically reasonable parameter region through large-scale random samplings shows that the NAT circuit exhibits a distinctly larger fraction of the oscillatory region than the ALT circuit. Such a global robustness difference between two circuits is supplemented by analyzing local robustness, including robustness to parameter perturbations and to molecular noise. In addition, detailed dynamical analysis shows that the molecular noise of both circuits can induce transient switching of the different mechanism between a stable steady state and a stable limit cycle. Our investigation on robustness and dynamics through examples provides insights into the relationship between network architecture and its function.

Systematic quantification of negative feedback mechanisms in the extracellular signal-regulated kinase (ERK) signaling network

Cell responses are actuated by tightly controlled signal transduction pathways. Although the concept of an integrated signaling network replete with interpathway cross-talk and feedback regulation is broadly appreciated, kinetic data of the type needed to characterize such interactions in conjunction with mathematical models are lacking. In mammalian cells, the Ras/ERK pathway controls cell proliferation and other responses stimulated by growth factors, and several cross-talk and feedback mechanisms affecting its activation have been identified. In this work, we take a systematic approach to parse the magnitudes of multiple regulatory mechanisms that attenuate ERK activation through canonical (Ras-dependent) and non-canonical (PI3K-dependent) pathways. In addition to regulation of receptor and ligand levels, we consider three layers of ERK-dependent feedback: desensitization of Ras activation, negative regulation of MEK kinase (e.g. Raf) activities, and up-regulation of dual-specificity ERK phosphatases. Our results establish the second of these as the dominant mode of ERK self-regulation in mouse fibroblasts. We further demonstrate that kinetic models of signaling networks, trained on a sufficient diversity of quantitative data, can be reasonably comprehensive, accurate, and predictive in the dynamical sense.

Mathematical modeling of K-Ras nanocluster formation on the plasma membrane

K-Ras functions as a critical node in the mitogen-activated protein kinase (MAPK) pathway that regulates key cellular functions including proliferation, differentiation, and apoptosis. Following growth factor receptor activation K-Ras.GTP forms nanoclusters on the plasma membrane through interaction with the scaffold protein galectin-3. The generation of nanoclusters is essential for high fidelity signal transduction via the MAPK pathway. To explore the mechanisms underlying K-Ras.GTP nanocluster formation, we developed a mathematical model of K-Ras-galectin-3 interactions. We designed a computational method to calculate protein collision rates based on experimentally determined protein diffusion rates and diffusion mechanisms and used a genetic algorithm to search the values of key model parameters. The optimal estimated model parameters were validated using experimental data. The resulting model accurately replicates critical features of K-Ras nanoclustering, including a fixed ratio of clustered K-Ras.GTP to monomeric K-Ras.GTP that is independent of the concentration of K-Ras.GTP. The model reproduces experimental results showing that the cytosolic level of galectin-3 determines the magnitude of the K-Ras.GTP clustered fraction and illustrates that nanoclustering is regulated by key nonequilibrium processes. Our kinetic model identifies a potential biophysical mechanism for K-Ras nanoclustering and suggests general principles that may be relevant for other plasma-membrane-localized proteins.

Modulation of gonadotropin-releasing hormone-induced extracellular signal-regulated kinase activation by dual-specificity protein phosphatase 1 in LbetaT2 gonadotropes

As the regulator of pituitary reproductive hormone synthesis, the hypothalamic neuropeptide GnRH is the central regulator of reproduction. A hallmark of GnRH action is the differential control of gene expression in pituitary gonadotropes through varied pulsatile stimulation. Among other signaling events, GnRH activation of the ERK family of MAPKs plays a significant role in the transcriptional regulation of the luteinizing hormone β-subunit gene and regulation of cap-dependent translation. We evaluated the ERK response to different GnRH pulse amplitudes in the gonadotrope cell line LβT2. We found that low-amplitude stimulation with GnRH invokes a rapid and transient ERK activation, whereas high-amplitude stimulation invokes a prolonged activation specifically in the cytoplasm fraction of LβT2 cells. Nuclear and cytoplasmic targets of ERK, Ets-like gene 1, and eukaryotic initiation factor 4E, respectively, are similarly activated. Feedback control of ERK activation occurs mainly through the dual-specificity protein phosphatases (DUSPs). DUSP1 is localized to the nucleus in LβT2 cells but DUSP4, another member implicated in GnRH feedback, exists in both the nucleus and cytoplasm. Manipulation of nuclear DUSP activity through overexpression or knockdown of Dusp1 modulates the ERK response to low and high GnRH pulse amplitudes and activation of the Lhb promoter. Dusp1 overexpression abolishes sustained ERK activation and inhibits Lhb promoter activity induced by high amplitude pulses. Conversely, Dusp1 knockdown enhances ERK activation by low-amplitude stimulation and increases stimulation of Lhb promoter activity. We conclude that DUSP1 feedback activity modulates ERK activation and the transcriptional response to GnRH.

Identification of optimal drug combinations targeting cellular networks: integrating phospho-proteomics and computational network analysis

Targeted therapeutics hold tremendous promise in inhibiting cancer cell proliferation. However, targeting proteins individually can be compensated for by bypass mechanisms and activation of regulatory loops. Designing optimal therapeutic combinations must therefore take into consideration the complex dynamic networks in the cell. In this study, we analyzed the insulin-like growth factor (IGF-1) signaling network in the MDA-MB231 breast cancer cell line. We used reverse-phase protein array to measure the transient changes in the phosphorylation of proteins after IGF-1 stimulation. We developed a computational procedure that integrated mass action modeling with particle swarm optimization to train the model against the experimental data and infer the unknown model parameters. The trained model was used to predict how targeting individual signaling proteins altered the rest of the network and identify drug combinations that minimally increased phosphorylation of other proteins elsewhere in the network. Experimental testing of the modeling predictions showed that optimal drug combinations inhibited cell signaling and proliferation, whereas nonoptimal combination of inhibitors increased phosphorylation of nontargeted proteins and rescued cells from cell death. The integrative approach described here is useful for generating experimental intervention strategies that could optimize drug combinations and discover novel pharmacologic targets for cancer therapy.

Trade-offs and noise tolerance in signal detection by genetic circuits

Genetic circuits can implement elaborated tasks of amplitude or frequency signal detection. What type of constraints could circuits experience in the performance of these tasks, and how are they affected by molecular noise? Here, we consider a simple detection process–a signal acting on a two-component module–to analyze these issues. We show that the presence of a feedback interaction in the detection module imposes a trade-off on amplitude and frequency detection, whose intensity depends on feedback strength. A direct interaction between the signal and the output species, in a type of feed-forward loop architecture, greatly modifies these trade-offs. Indeed, we observe that coherent feed-forward loops can act simultaneously as good frequency and amplitude noise-tolerant detectors. Alternatively, incoherent feed-forward loop structures can work as high-pass filters improving high frequency detection, and reaching noise tolerance by means of noise filtering. Analysis of experimental data from several specific coherent and incoherent feed-forward loops shows that these properties can be realized in a natural context. Overall, our results emphasize the limits imposed by circuit structure on its characteristic stimulus response, the functional plasticity of coherent feed-forward loops, and the seemingly paradoxical advantage of improving signal detection with noisy circuit components.

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.

Neuregulin 1 sustains the gene regulatory network in both trabecular and nontrabecular myocardium

RATIONALE

The cardiac gene regulatory network (GRN) is controlled by transcription factors and signaling inputs, but network logic in development and it unraveling in disease is poorly understood. In development, the membrane-tethered signaling ligand Neuregulin (Nrg)1, expressed in endocardium, is essential for ventricular morphogenesis. In adults, Nrg1 protects against heart failure and can induce cardiomyocytes to divide.

OBJECTIVE

To understand the role of Nrg1 in heart development through analysis of null and hypomorphic Nrg1 mutant mice.

METHODS AND RESULTS

Chamber domains were correctly specified in Nrg1 mutants, although chamber-restricted genes Hand1 and Cited1 failed to be activated. The chamber GRN subsequently decayed with individual genes exhibiting decay patterns unrelated to known patterning boundaries. Both trabecular and nontrabecular myocardium were affected. Network demise was spatiotemporally dynamic, the most sensitive region being the central part of the left ventricle, in which the GRN underwent complete collapse. Other regions were partially affected with graded sensitivity. In vitro, Nrg1 promoted phospho-Erk1/2-dependent transcription factor expression, cardiomyocyte maturation and cell cycle inhibition. We monitored cardiac pErk1/2 in embryos and found that expression was Nrg1-dependent and levels correlated with cardiac GRN sensitivity in mutants.

CONCLUSIONS

The chamber GRN is fundamentally labile and dependent on signaling from extracardiac sources. Nrg1-ErbB1/4-Erk1/2 signaling critically sustains elements of the GRN in trabecular and nontrabecular myocardium, challenging our understanding of Nrg1 function. Transcriptional decay patterns induced by reduced Nrg1 suggest a novel mechanism for cardiac transcriptional regulation and dysfunction in disease, potentially linking biomechanical feedback to molecular pathways for growth and differentiation.

Bistable behavior of the lac operon in E. coli when induced with a mixture of lactose and TMG

In this work we investigate multistability in the lac operon of Escherichia coli when it is induced by a mixture of lactose and the non-metabolizable thiomethyl galactoside (TMG). In accordance with previously published experimental results and computer simulations, our simulations predict that: (1) when the system is induced by TMG, the system shows a discernible bistable behavior while, (2) when the system is induced by lactose, bistability does not disappear but excessively high concentrations of lactose would be required to observe it. Finally, our simulation results predict that when a mixture of lactose and TMG is used, the bistability region in the extracellular glucose concentration vs. extracellular lactose concentration parameter space changes in such a way that the model predictions regarding bistability could be tested experimentally. These experiments could help to solve a recent controversy regarding the existence of bistability in the lac operon under natural conditions.

shRNA interference for extracellular signal-regulated kinase 2 can inhibit the growth of esophageal cancer cell line Eca109

BACKGROUND

Esophageal squamous cell carcinoma is one of the most common digestive tract cancers with 5-year survival rate less than 10% owing to its poor prognosis. Mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signaling pathway has been mainly involved in the pathogenesis of various cancers. In present study, we investigated the role of ERK2 in human esophageal cancer cell line Eca109.

METHODS

Short-hairpin RNA (shRNA) interference vector targeted ERK2 was constructed using pGeneclip U1 hairpin cloning systems, then transfected into Eca109 cell line. The transfection efficiency was observed by fluorescence microscope and cell growth after transfection with shRNA-ERK2 vector was determined by methylthiazolyl blue tetrazolium (MTT) assay. The ERK2 expression after transfection was detected by western-blotting. The cell apoptosis and cell-cycle was analyzed by flow cytometry. The role of p-ERK2 was confirmed by immunohistochemistry and soft agar colony formation assay.

RESULTS

The growth of Eca109 transfected with shRNA-ERK2 vector was obviously inhibited compared to control group via MTT analysis. The inhibition rate after transfection with shRNA-ERK2 for 96 h was 10.45%, the expression of ERK2 was obviously reduced compared to the control analyzed by western-blot, cell apoptosis was 9.7% (compared to control, P < 0.05), and cell-cycle was arrested at G1 phase.

CONCLUSIONS

In present study we demonstrated for the first time that transfection with shRNA-ERK2 targeted ERK2 into Eca109 cells can inhibit growth of Eca109, inducing cell apoptosis and influencing cell-cycle. Together, these results we obtained suggested that ERK2 plays an important role in cell growth of Eca109.

Large-scale analysis of network bistability for human cancers

Protein-protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers.

Myristoylation of the dual-specificity phosphatase c-JUN N-terminal kinase (JNK) stimulatory phosphatase 1 is necessary for its activation of JNK signaling and apoptosis

Activation of the c-JUN N-terminal kinase (JNK) pathway is implicated in a number of important physiological processes, from embryonic morphogenesis to cell survival and apoptosis. JNK stimulatory phosphatase 1 (JSP1) is a member of the dual-specificity phosphatase subfamily of protein tyrosine phosphatases. In contrast to other dual-specificity phosphatases that catalyze the inactivation of mitogen-activated protein kinases, expression of JSP1 activates JNK-mediated signaling. JSP1 and its relative DUSP15 are unique among members of the protein tyrosine phosphatase family in that they contain a potential myristoylation site at the N-terminus (MGNGMXK). In this study, we investigated whether JSP1 was myristoylated and examined the functional consequences of myristoylation. Using mass spectrometry, we showed that wild-type JSP1, but not a JSP1 mutant in which Gly2 was mutated to Ala (JSP1-G2A), was myristoylated in cells. Although JSP1 maintained intrinsic phosphatase activity in the absence of myristoylation, the subcellular localization of the enzyme was altered. Compared with the wild type, the ability of nonmyristoylated JSP1 to induce JNK activation and phosphorylation of the transcription factor c-JUN was attenuated. Upon expression of wild-type JSP1, a subpopulation of cells, with the highest levels of the phosphatase, was induced to float off the dish and undergo apoptosis. In contrast, cells expressing similar levels of JSP1-G2A remained attached, further highlighting that the myristoylation mutant was functionally compromised.

Extracellular-regulated kinase-mitogen-activated protein kinase cascade: unsolved issues

This review point out several aspects regarding the mitogen-activated protein kinase (MAPK)/extracellular-regulated kinase (Erk) network, which are still pending issues in the understanding how this pathway integrate information to drive cell fates. Focusing on the role of Erk during cell cycle, it has to be underlined that Erk downstream effectors, which are required for mitosis progression and contribute to aneuploidy during tumorigenesis, remain to be determined. In addition to the identity of the terminal enzymes or effectors of Erk, it has to be stressed that the dynamic nature of the Erk signal is itself a key factor in cell phenotype decisions. Development of biophotonics strategies for monitoring the Erk network at the spatiotemporal level in living cells, as well as computational and hypothesis-driven approaches, are called to unravel the principles by which signaling networks create biochemical and biological specificities. Finally, Erk dynamics might also be impacted by other post-translational modification than phosphorylation, such as O-GlcNAcylation.

Mechanisms controlling cell size and shape during isotropic cell spreading

Cell motility is important for many developmental and physiological processes. Motility arises from interactions between physical forces at the cell surface membrane and the biochemical reactions that control the actin cytoskeleton. To computationally analyze how these factors interact, we built a three-dimensional stochastic model of the experimentally observed isotropic spreading phase of mammalian fibroblasts. The multiscale model is composed at the microscopic levels of three actin filament remodeling reactions that occur stochastically in space and time, and these reactions are regulated by the membrane forces due to membrane surface resistance (load) and bending energy. The macroscopic output of the model (isotropic spreading of the whole cell) occurs due to the movement of the leading edge, resulting solely from membrane force-constrained biochemical reactions. Numerical simulations indicate that our model qualitatively captures the experimentally observed isotropic cell-spreading behavior. The model predicts that increasing the capping protein concentration will lead to a proportional decrease in the spread radius of the cell. This prediction was experimentally confirmed with the use of Cytochalasin D, which caps growing actin filaments. Similarly, the predicted effect of actin monomer concentration was experimentally verified by using Latrunculin A. Parameter variation analyses indicate that membrane physical forces control cell shape during spreading, whereas the biochemical reactions underlying actin cytoskeleton dynamics control cell size (i.e., the rate of spreading). Thus, during cell spreading, a balance between the biochemical and biophysical properties determines the cell size and shape. These mechanistic insights can provide a format for understanding how force and chemical signals together modulate cellular regulatory networks to control cell motility.

Mitogen-activated protein kinase phosphatase 2 regulates the inflammatory response in sepsis

Sepsis results from a dysregulation of the regulatory mechanisms of the pro- and anti-inflammatory response to invading pathogens. The mitogen-activated protein (MAP) kinase cascades are key signal transduction pathways involved in the cellular production of cytokines. The dual-specific phosphatase 1 (DUSP 1), mitogen-activated protein kinase phosphatase-1 (MKP-1), has been shown to be an important negative regulator of the inflammatory response by regulating the p38 and Jun N-terminal protein kinase (JNK) MAP kinase pathways to influence pro- and anti-inflammatory cytokine production. MKP-2, also a dual-specific phosphatase (DUSP 4), is a phosphatase highly homologous with MKP-1 and is known to regulate MAP kinase signaling; however, its role in regulating the inflammatory response is not known. We hypothesized a regulatory role for MKP-2 in the setting of sepsis. Mice lacking the MKP-2 gene had a survival advantage over wild-type mice when challenged with intraperitoneal lipopolysaccharide (LPS) or a polymicrobial infection via cecal ligation and puncture. The MKP-2(-/-) mice also exhibited decreased serum levels of both pro-inflammatory cytokines (tumor necrosis factor alpha [TNF-alpha], interleukin-1beta [IL-1beta], IL-6) and anti-inflammatory cytokines (IL-10) following endotoxin challenge. Isolated bone marrow-derived macrophages (BMDMs) from MKP-2(-/-) mice showed increased phosphorylation of the extracellular signal-regulated kinase (ERK), decreased phosphorylation of JNK and p38, and increased induction of MKP-1 following LPS stimulation. The capacity for cytokine production increased in MKP-2(-/-) BMDMs following MKP-1 knockdown. These data support a mechanism by which MKP-2 targets ERK deactivation, thereby decreasing MKP-1 and thus removing the negative inhibition of MKP-1 on cytokine production.

Next-generation synthetic gene networks

Synthetic biology is focused on the rational construction of biological systems based on engineering principles. During the field's first decade of development, significant progress has been made in designing biological parts and assembling them into genetic circuits to achieve basic functionalities. These circuits have been used to construct proof-of-principle systems with promising results in industrial and medical applications. However, advances in synthetic biology have been limited by a lack of interoperable parts, techniques for dynamically probing biological systems and frameworks for the reliable construction and operation of complex, higher-order networks. As these challenges are addressed, synthetic biologists will be able to construct useful next-generation synthetic gene networks with real-world applications in medicine, biotechnology, bioremediation and bioenergy.

Thresholds in transient dynamics of signal transduction pathways

Transient dynamics of signal transduction pathways play an important role in many biological processes, including cell differentiation, apoptosis, metabolism and DNA damage response. Recent examples of quantitative methods to characterize transient signals include transient metabolic control coefficients and finite time Lyapunov exponents. In our work we compare these quantitative methods to characterize transient phenomena and specifically discuss their predictive power for three examples. We focus on the identification of thresholds that separate different transient dynamic behaviors. Our investigation leads to the following results: The spectrum of the finite-time Lyapunov exponents unambiguously and reliably identifies putative thresholds in transient dynamics. Metabolic control coefficients do not reliably detect all thresholds and suffer from false positives.

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.

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

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.

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.

ERK-regulated differential expression of the Mitf 6a/b splicing isoforms in melanoma

The master regulator of the melanocyte lineage Mitf is intimately involved in development as well as melanoma, controlling cell survival, differentiation, proliferation and metastasis/migration. Consistent with its central role, Mitf expression and Mitf post-translational modifications are tightly regulated. An additional potential level of regulation is afforded by differential splicing of Mitf exon-6 leading to the generation of two isoforms that differ by the presence of six amino-acids in the Mitf (+) isoform and which have differential effects on cell cycle progression. However, whether the ratio of the two isoforms is regulated and whether their expression correlates with melanoma progression is not known. Here, we show that the differential expression of the Mitf 6a/b isoforms is dependent on the MAPKinase signalling, being linked to the activation of MEK1-ERK2, but not to N-RAS/B-RAF mutation status. In addition, quantification of Mitf 6a/b splicing forms in 86 melanoma samples revealed substantially increased levels of the Mitf (-) form in a subset of metastatic melanomas. The results suggest that differential expression of the Mitf 6a/b isoforms may represent an additional mechanism for regulating Mitf function and melanoma biology.

The smallest chemical reaction system with bistability

Background

Bistability underlies basic biological phenomena, such as cell division, differentiation, cancer onset, and apoptosis. So far biologists identified two necessary conditions for bistability: positive feedback and ultrasensitivity.

Results

Biological systems are based upon elementary mono- and bimolecular chemical reactions. In order to definitely clarify all necessary conditions for bistability we here present the corresponding minimal system. According to our definition, it contains the minimal number of (i) reactants, (ii) reactions, and (iii) terms in the corresponding ordinary differential equations (decreasing importance from i-iii). The minimal bistable system contains two reactants and four irreversible reactions (three bimolecular, one monomolecular).

We discuss the roles of the reactions with respect to the necessary conditions for bistability: two reactions comprise the positive feedback loop, a third reaction filters out small stimuli thus enabling a stable 'off' state, and the fourth reaction prevents explosions. We argue that prevention of explosion is a third general necessary condition for bistability, which is so far lacking discussion in the literature.

Moreover, in addition to proving that in two-component systems three steady states are necessary for bistability (five for tristability, etc.), we also present a simple general method to design such systems: one just needs one production and three different degradation mechanisms (one production, five degradations for tristability, etc.). This helps modelling multistable systems and it is important for corresponding synthetic biology projects.

Conclusion

The presented minimal bistable system finally clarifies the often discussed question for the necessary conditions for bistability. The three necessary conditions are: positive feedback, a mechanism to filter out small stimuli and a mechanism to prevent explosions. This is important for modelling bistability with simple systems and for synthetically designing new bistable systems. Our simple model system is also well suited for corresponding teaching purposes.

A systems biology perspective on Nrf2-mediated antioxidant response

Cells in vivo are constantly exposed to reactive oxygen species (ROS) generated endogenously and exogenously. To defend against the deleterious consequences of ROS, cells contain multiple antioxidant enzymes expressed in various cellular compartments to scavenge these toxic species. Under oxidative stresses, these antioxidant enzymes are upregulated to restore redox homeostasis. Such an adaptive response results from the activation of a redox-sensitive gene regulatory network mediated by nuclear factor E2-related factor 2. To more completely understand how the redox control system is designed by nature to meet homeostatic goals, we have examined the network from a systems perspective using engineering approaches. As with man-made control devices, the redox control system can be decomposed into distinct functional modules, including transducer, controller, actuator, and plant. Cells achieve specific performance objectives by utilizing nested feedback loops, feedforward control, and ultrasensitive signaling motifs, etc. Given that endogenously generated ROS are also used as signaling molecules, our analysis suggests a novel mode of action to explain oxidative stress-induced pathological conditions and diseases. Specifically, by adaptively upregulating antioxidant enzymes, oxidative stress may inadvertently attenuate ROS signals that mediate physiological processes, resulting in aberrations of cellular functions and adverse consequences. Lastly, by simultaneously considering the two competing cellular tasks-adaptive antioxidant defense and ROS signaling-we re-examine the premise that dietary antioxidant supplements is generally beneficial to human health. Our analysis highlights some possible adverse effects of these widely consumed antioxidants.

A non-redundant role for MKP5 in limiting ROS production and preventing LPS-induced vascular injury

There are at least 11 mitogen-activated protein kinase (MAPK) phosphatases (MKPs) and only 3 major groups of MAPKs, raising the question of whether these phosphatases have non-redundant functions in vivo. Using a modified mouse model of local Shwartzman reaction, we found that deletion of the MKP5 gene, but not the MKP1 gene, led to robust and accelerated vascular inflammatory responses to a single dose of LPS injection. Depletion of neutrophils significantly reduced the vascular injury in Mkp5(-/-) mice, whereas adoptive transfer of Mkp5(-/-) neutrophils replicated the LPS-induced skin lesions in wild-type recipients. Neutrophils isolated from Mkp5(-/-) mice exhibited augmented p38 MAPK activation and increased superoxide generation on activation. The p38 MAPK inhibitor, SB203580, significantly reduced p47(phox) phosphorylation and diminished superoxide production in neutrophils. p38 MAPK phosphorylated mouse p47(phox), and deletion of the p47(phox) gene ablated the LPS-induced vascular injury in Mkp5(-/-) mice. Collectively, these results show an earlier unrecognized and non-redundant function of MKP5 in restraining p38 MAPK-mediated neutrophil oxidant production, thereby preventing LPS-induced vascular injury.

Interlinking positive and negative feedback loops creates a tunable motif in gene regulatory networks

Positive and negative feedback loops are often coupled to perform various functions in gene regulatory networks, acting as bistable switches, oscillators, and excitable devices. It is implied that such a system with interlinked positive and negative feedback loops is a flexible motif that can modulate itself among various functions. Here, we developed a minimal model for the system and systematically explored its dynamics and performance advantage in response to stimuli in a unifying framework. The system indeed displays diverse behaviors when the strength of feedback loops is changed. First, the system can be tunable from monostability to bistability by increasing the strength of positive feedback, and the bistability regime is modulated by the strength of negative feedback. Second, the system undergoes transitions from bistability to excitability and to oscillation with increasing the strength of negative feedback, and the reverse conversion occurs by enhancing the strength of positive feedback. Third, the system is more flexible than a single feedback loop; it can produce robust larger-amplitude oscillations over a wider stimulus regime compared with a single time-delayed negative feedback loop. Furthermore, the tunability of the system depends mainly on the topology of coupled feedback loops but less on the exact parameter values or the mode of interactions between model components. Thus, our results interpret why such a system represents a tunable motif and can accomplish various functions. These also suggest that coupled feedback loops can act as toolboxes for engineering diverse functional circuits in synthetic biology.

Prediction and validation of a mechanism to control the threshold for inhibitory synaptic plasticity

Synaptic plasticity, neuronal activity-dependent sustained alteration of the efficacy of synaptic transmission, underlies learning and memory. Activation of positive-feedback signaling pathways by an increase in intracellular Ca²⁺ concentration ([Ca²⁺]_i) has been implicated in synaptic plasticity. However, the mechanism that determines the [Ca²⁺]_i threshold for inducing synaptic plasticity is elusive. Here, we developed a kinetic simulation model of inhibitory synaptic plasticity in the cerebellum, and systematically analyzed the behavior of intricate molecular networks composed of protein kinases, phosphatases, etc. The simulation showed that Ca²⁺/calmodulin-dependent protein kinase II (CaMKII), which is essential for the induction of synaptic plasticity, was persistently activated or suppressed in response to different combinations of stimuli. The sustained CaMKII activation depended on synergistic actions of two positive-feedback reactions, CaMKII autophosphorylation and CaMKII-mediated inhibition of a CaM-dependent phosphodiesterase, PDE1. The simulation predicted that PDE1-mediated feedforward inhibition of CaMKII predominantly controls the Ca²⁺ threshold, which was confirmed by electrophysiological experiments in primary cerebellar cultures. Thus, combined application of simulation and experiments revealed that the Ca²⁺ threshold for the cerebellar inhibitory synaptic plasticity is primarily determined by PDE1.

Inhibiting JNK dephosphorylation and induction of apoptosis by novel anticancer agent NSC-741909 in cancer cells

NSC-741909 is a recently identified novel anticancer agent that suppresses the growth of several NCI-60 cancer cell lines with a unique anticancer spectrum. However, its molecular mechanisms remain unknown. To determine the molecular mechanisms of NSC-741909-induced antitumor activity, we analyzed the changes of 77 protein biomarkers in a sensitive lung cancer cell line after treatment with this compound by using reverse-phase protein microarray. The results showed that phosphorylation of mitogen-activated protein (MAP) kinases (P38 MAPK, ERK, and JNK) were persistently elevated by the treatment with NSC-741909. However, only the JNK-specific inhibitor SP600125 effectively blocked the apoptosis induced by NSC-741909. Moreover, NSC-741909-mediated apoptosis was also blocked by a dominant-negative JNK construct, suggesting that sustained activation of JNK is critical for the apoptosis induction. Further studies revealed that treatment with NSC-741909 suppressed dephosphorylation of JNK and the expression of MAPK phosphatase-1. Thus, NSC-741909-mediated inhibition of JNK dephosphorylation results in sustained JNK activation, which leads to apoptosis in cancer cells.

Mixed-integer nonlinear optimisation approach to coarse-graining biochemical networks

Quantitative modelling and analysis of biochemical networks is challenging because of the inherent complexities and nonlinearities of the system and the limited availability of parameter values. Even if a mathematical model of the network can be developed, the lack of large-scale good-quality data makes accurate estimation of a large number of parameters impossible. Hence, coarse-grained models (CGMs) consisting of essential biochemical mechanisms are more suitable for computational analysis and for studying important systemic functions. The central question in constructing a CGM is which mechanisms should be deemed 'essential' and which can be ignored. Also, how should parameter values be defined when data are sparse? A mixed-integer nonlinear-programming (MINLP) based optimisation approach to coarse-graining is presented. Starting with a detailed biochemical model with associated computational details (reaction network and mathematical description) and data on the biochemical system, the structure and the parameters of a CGM can be determined simultaneously. In this optimisation problem, the authors use a genetic algorithm to simultaneously identify parameter values and remove unimportant reactions. The methodology is exemplified by developing two CGMs for the GTPase-cycle module of M1 muscarinic acetylcholine receptor, Gq, and regulator of G protein signalling 4 [RGS4, a GTPase-activating protein (GAP)] starting from a detailed model of 48 reactions. Both the CGMs have only 17 reactions, fit experimental data well and predict, as does the detailed model, four limiting signalling regimes (LSRs) corresponding to the extremes of receptor and GAP concentration. The authors demonstrate that coarse-graining, in addition to resulting in a reduced-order model, also provides insights into the mechanisms in the network. The best CGM obtained for the GTPase cycle also contains an unconventional mechanism and its predictions explain an old problem in pharmacology, the biphasic (bell-shaped) response to certain drugs. The MINLP methodology is broadly applicable to larger and complex (dense) biochemical modules.

Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling

When modeling cell signaling networks, a balance must be struck between mechanistic detail and ease of interpretation. In this paper we apply a fuzzy logic framework to the analysis of a large, systematic dataset describing the dynamics of cell signaling downstream of TNF, EGF, and insulin receptors in human colon carcinoma cells. Simulations based on fuzzy logic recapitulate most features of the data and generate several predictions involving pathway crosstalk and regulation. We uncover a relationship between MK2 and ERK pathways that might account for the previously identified pro-survival influence of MK2. We also find unexpected inhibition of IKK following EGF treatment, possibly due to down-regulation of autocrine signaling. More generally, fuzzy logic models are flexible, able to incorporate qualitative and noisy data, and powerful enough to produce quantitative predictions and new biological insights about the operation of signaling networks.

Cells use networks of interacting proteins to interpret intra-cellular state and extra-cellular cues and to execute cell-fate decisions. Even when individual proteins are well understood at a molecular level, the dynamics and behavior of networks as a whole are harder to understand. However, deciphering the operation of such networks is key to understanding disease processes and therapeutic opportunities. As a means to study signaling networks, we have modified and applied a fuzzy logic approach originally developed for industrial control. We use fuzzy logic to model the responses of colon cancer cells in culture to combinations of pro-survival and pro-death cytokines, making it possible to interpret quantitative data in the context of abstract information drawn from the literature. Our work establishes that fuzzy logic can be used to understand complex signaling pathways with respect to multi-factorial activity-based protein data and prior knowledge.

Antitumor efficacy of the novel RAF inhibitor GDC-0879 is predicted by BRAFV600E mutational status and sustained extracellular signal-regulated kinase/mitogen-activated protein kinase pathway suppression

Oncogenic activation of the BRAF serine/threonine kinase has been associated with initiation and maintenance of melanoma tumors. As such, development of pharmacologic agents to target RAF proteins or their effector kinases is an area of intense investigation. Here we report the biological properties of GDC-0879, a highly selective, potent, and orally bioavailable RAF small-molecule inhibitor. We used extracellular signal-regulated kinase (ERK)-1/2 and mitogen-activated protein kinase/ERK kinase (MEK)-1/2 phosphorylation as biomarkers to explore the relationship between tumor outcome and pharmacodynamic inhibition of the RAF-MEK-ERK pathway. In GDC-0879-treated mice, both cell line- and patient-derived BRAF(V600E) tumors exhibited stronger and more sustained pharmacodynamic inhibition (>90% for 8 hours) and improved survival compared with mutant KRAS-expressing tumors. Despite the involvement of activated RAF signaling in RAS-induced tumorigenesis, decreased time to progression was observed for some KRAS-mutant tumors following GDC-0879 administration. Moreover, striking differences were noted for RAF and MEK inhibition across a panel of 130 tumor cell lines. Whereas GDC-0879-mediated efficacy was associated strictly with BRAF(V600E) status, MEK inhibition also attenuated proliferation and tumor growth of cell lines expressing wild-type BRAF (81% KRAS mutant, 38% KRAS wild type). The responsiveness of BRAF(V600E) melanoma cells to GDC-0879 could be dramatically altered by pharmacologic and genetic modulation of phosphatidylinositol 3-kinase pathway activity. These data suggest that GDC-0879-induced signaling changes are dependent on the point of oncogenic activation within the RAS network. Taken together, these studies increase our understanding of the molecular determinants for antitumor efficacy resulting from RAF pathway inhibition and have implications for therapeutic intervention in the clinic.

Mechanistic systems biology of inflammatory gene expression in airway smooth muscle as tool for asthma drug development

There is compelling evidence that airway smooth muscle cells may function as inflammatory cells in the airway system by producing multiple inflammatory cytokines in response to a large array of external stimuli such as acetylcholine, bradykinin, inflammatory cytokines, and toll-like receptor activators. However, how multiple extracellular stimuli interact in the regulation of inflammatory gene expression in an airway smooth muscle cell remains poorly understood. This review addresses the mechanistic systems biology of inflammatory gene expression in airway smooth muscle by discussing: a) redundancy underlying multiple stimulus-product relations in receptor-mediated inflammatory gene expression, and their regulation by convergent activation of Erk1/2 mitogen-activated protein kinase (MAPK), b) Erk1/2 MAPK-dependent induction of phosphatase expression as a negative feedback mechanism in the robust maintenance of inflammatory gene expression, and c) cyclooxygenase 2-dependent regulation of the differential temporal dynamics of early and late inflammatory gene expression. It is becoming recognized that a single-target approach is unlikely to be effective for the treatment of inflammatory airway diseases because airway inflammation is a result of complex interactions among multiple inflammatory mediators and cells types in the airway system. Understanding the mechanistic systems biology of inflammatory gene expression in airway smooth muscle and other cell types in the airway system may lead to the development of multi-target drug regimens for the treatment of inflammatory airway diseases such as asthma.

Positional information generated by spatially distributed signaling cascades

The temporal and stationary behavior of protein modification cascades has been extensively studied, yet little is known about the spatial aspects of signal propagation. We have previously shown that the spatial separation of opposing enzymes, such as a kinase and a phosphatase, creates signaling activity gradients. Here we show under what conditions signals stall in the space or robustly propagate through spatially distributed signaling cascades. Robust signal propagation results in activity gradients with long plateaus, which abruptly decay at successive spatial locations. We derive an approximate analytical solution that relates the maximal amplitude and propagation length of each activation profile with the cascade level, protein diffusivity, and the ratio of the opposing enzyme activities. The control of the spatial signal propagation appears to be very different from the control of transient temporal responses for spatially homogenous cascades. For spatially distributed cascades where activating and deactivating enzymes operate far from saturation, the ratio of the opposing enzyme activities is shown to be a key parameter controlling signal propagation. The signaling gradients characteristic for robust signal propagation exemplify a pattern formation mechanism that generates precise spatial guidance for multiple cellular processes and conveys information about the cell size to the nucleus.

Investigating differential dynamics of the MAPK signaling cascade using a multi-parametric global sensitivity analysis

Cell growth critically depends on signalling pathways whose regulation is the focus of intense research. Without utilizing a priori knowledge of the relative importance of pathway components, we have applied in silico computational methods to the EGF-induced MAPK cascade. Specifically, we systematically perturbed the entire parameter space, including initial conditions, using a Monte Carlo approach, and investigate which protein components or kinetic reaction steps contribute to the differentiation of ERK responses. The model, based on previous work by Brightman and Fell (2000), is composed of 28 reactions, 27 protein molecules, and 48 parameters from both mass action and Michaelis-Menten kinetics. Our multi-parametric systems analysis confirms that Raf inactivation is one of the key steps regulating ERK responses to be either transient or sustained. Furthermore, the results of amplitude-differential ERK phosphorylations within the transient case are mainly attributed to the balance between activation and inactivation of Ras while duration-differential ERK responses for the sustained case are, in addition to Ras, markedly affected by dephospho-/phosphorylation of both MEK and ERK. Our sub-module perturbations showed that MEK and ERK's contribution to this differential ERK activation originates from fluctuations in intermediate pathway module components such as Ras and Raf, implicating a cooperative regulatory mode among the key components. The initial protein concentrations of corresponding reactions such as Ras, GAP, and Raf also influence the distinct signalling outputs of ERK activation. We then compare these results with those obtained from a single-parametric perturbation approach using an overall state sensitivity (OSS) analysis. The OSS findings indicate a more pronounced role of ERK's inhibitory feedback effect on catalysing the dissociation of the SOS complex. Both approaches reveal the presence of multiple specific reactions involved in the distinct dynamics of ERK responses and the cell fate decisions they trigger. This work adds a mechanistic insight of the contribution of key pathway components, thus may support the identification of biomarkers for pharmaceutical drug discovery processes.