Principles behind the multifarious control of signal transduction. ERK phosphorylation and kinase/phosphatase control

Quantifying redox transcription factor dynamics as a tool to investigate redox signalling

A critical feature of the cellular antioxidant response is the induction of gene expression by redox-sensitive transcription factors. In many cells, activating these transcription factors is a dynamic process involving multiple redox steps, but it is unclear how these dynamics should be measured. Here, we show how the dynamic profile of the Schizosaccharomyces pombe Pap1 transcription factor is quantifiable by three parameters: signal amplitude, signal time and signal duration. In response to increasing hydrogen peroxide concentrations, the Pap1 amplitude decreased while the signal time and duration showed saturable increases. In co-response plots, these parameters showed a complex, non-linear relationship to the mRNA levels of four Pap1-regulated genes. We also demonstrate that hydrogen peroxide and tert-butyl hydroperoxide trigger quantifiably distinct Pap1 activation profiles and transcriptional responses. Based on these findings, we propose that different oxidants and oxidant concentrations modulate the Pap1 dynamic profile, leading to specific transcriptional responses. We further show how the effect of combination and pre-exposure stresses on Pap1 activation dynamics can be quantified using this approach. This method is therefore a valuable addition to the redox signalling toolbox that may illuminate the role of dynamics in determining appropriate responses to oxidative stress.

Index analysis: An approach to understand signal transduction with application to the EGFR signalling pathway

In systems biology and pharmacology, large-scale kinetic models are used to study the dynamic response of a system to a specific input or stimulus. While in many applications, a deeper understanding of the input-response behaviour is highly desirable, it is often hindered by the large number of molecular species and the complexity of the interactions. An approach that identifies key molecular species for a given input-response relationship and characterises dynamic properties of states is therefore highly desirable. We introduce the concept of index analysis; it is based on different time- and state-dependent quantities (indices) to identify important dynamic characteristics of molecular species. All indices are defined for a specific pair of input and response variables as well as for a specific magnitude of the input. In application to a large-scale kinetic model of the EGFR signalling cascade, we identified different phases of signal transduction, the peculiar role of Phosphatase3 during signal activation and Ras recycling during signal onset. In addition, we discuss the challenges and pitfalls of interpreting the relevance of molecular species based on knock-out simulation studies, and provide an alternative view on conflicting results on the importance of parallel EGFR downstream pathways. Beyond the applications in model interpretation, index analysis is envisioned to be a valuable tool in model reduction.

On paradoxes between optimal growth, metabolic control analysis, and flux balance analysis

In Microbiology it is often assumed that growth rate is maximal. This may be taken to suggest that the dependence of the growth rate on every enzyme activity is at the top of an inverse-parabolic function, i.e. that all flux control coefficients should equal zero. This might seem to imply that the sum of these flux control coefficients equals zero. According to the summation law of Metabolic Control Analysis (MCA) the sum of flux control coefficients should equal 1 however. And in Flux Balance Analysis (FBA) catabolism is often limited by a hard bound, causing catabolism to fully control the fluxes, again in apparent contrast with a flux control coefficient of zero. Here we resolve these paradoxes (apparent contradictions) in an analysis that uses the 'Edinburgh pathway', the 'Amsterdam pathway', as well as a generic metabolic network providing the building blocks or Gibbs energy for microbial growth. We review and show that (i) optimization depends on so-called enzyme control coefficients rather than the 'catalytic control coefficients' of MCA's summation law, (ii) when optimization occurs at fixed total protein, the former differ from the latter to the extent that they may all become equal to zero in the optimum state, (iii) in more realistic scenarios of optimization where catalytically inert biomass is compensating or maintenance metabolism is taken into consideration, the optimum enzyme concentrations should not be expected to equal those that maximize the specific growth rate, (iv) optimization may be in terms of yield rather than specific growth rate, which resolves the paradox because the sum of catalytic control coefficients on yield equals 0, (v) FBA effectively maximizes growth yield, and for yield the summation law states 0 rather than 1, thereby removing the paradox, (vi) furthermore, FBA then comes more often to a 'hard optimum' defined by a maximum catabolic flux and a catabolic-enzyme control coefficient of 1. The trade-off between maintenance metabolism and growth is highlighted as worthy of further analysis.

Evaluating the Pharmacokinetics and Pharmacodynamics of Chemotherapeutics within a Spatial SILAC-Labeled Spheroid Model System

Tumors have considerable cellular heterogeneity that is impossible to explore with simple cell cultures. Spheroid cultures contain pathophysiological and chemical gradients similar to in vivo tumors and show complex responses to therapeutics, similar to a tumor. Using pulsed isotopic labels, we demonstrate the pronounced differential response of the proteome to the drug Regorafenib, a multikinase inhibitor, in HCT 116 spheroids. Regorafenib treatment of outer spheroids inhibits proteins involved in critical pathways such as mTOR signaling, extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) signaling, and colorectal cancer metastasis signaling, resulting in decreased proliferation and cellular apoptosis. By contrast, analysis of the treated core cells shows upregulation of MAPK1 and KRAS, possibly implicating drug resistance within these late apoptotic cells. Thus, pulsed isotopic labeling enables evaluation of the distinct proteomic responses for cells residing in the different chemical microenvironments of the spheroid. This platform promises great utility in assisting researchers' predictions of pharmacodynamic therapeutic responses within complex tumors.

Progress in the development of kinase inhibitors for treating asthma and COPD

Current therapies to mitigate inflammatory responses involved in airway remodeling and associated pathological features of asthma and chronic obstructive pulmonary disease (COPD) are limited and largely ineffective. Inflammation and the release of cytokines and growth factors activate kinase signaling pathways that mediate changes in airway mesenchymal cells such as airway smooth muscle cells and lung fibroblasts. Proliferative and secretory changes in mesenchymal cells exacerbate the inflammatory response and promote airway remodeling, which is often characterized by increased airway smooth muscle mass, airway hyperreactivity, increased mucus secretion, and lung fibrosis. Thus, inhibition of relevant kinases has been viewed as a potential therapeutic approach to mitigate the debilitating and, thus far, irreversible airway remodeling that occurs in asthma and COPD. Despite FDA approval of several kinase inhibitors for the treatment of proliferative disorders, such as cancer and inflammation associated with rheumatoid arthritis and ulcerative colitis, none of these drugs have been approved to treat asthma or COPD. This review will provide a brief overview of the role kinases play in the pathology of asthma and COPD and an update on the status of kinase inhibitors currently in clinical trials for the treatment of obstructive pulmonary disease. In addition, potential issues associated with the current kinase inhibitors, which have limited their success as therapeutic agents in treating asthma or COPD, and alternative approaches to target kinase functions will be discussed.

Induction of the hepatic aryl hydrocarbon receptor by alcohol dysregulates autophagy and phospholipid metabolism via PPP2R2D

Disturbed lipid metabolism precedes alcoholic liver injury. Whether and how AhR alters degradation of lipids, particularly phospho-/sphingo-lipids during alcohol exposure, was not explored. Here, we show that alcohol consumption in mice results in induction and activation of aryl hydrocarbon receptor (AhR) in the liver, and changes the hepatic phospho-/sphingo-lipids content. The levels of kynurenine, an endogenous AhR ligand, are elevated with increased hepatic tryptophan metabolic enzymes in alcohol-fed mice. Either alcohol or kynurenine treatment promotes AhR activation with autophagy dysregulation via AMPK. Protein Phosphatase 2 Regulatory Subunit-Bdelta (Ppp2r2d) is identified as a transcriptional target of AhR. Consequently, PPP2R2D-dependent AMPKα dephosphorylation causes autophagy inhibition and mitochondrial dysfunction. Hepatocyte-specific AhR ablation attenuates steatosis, which is associated with recovery of phospho-/sphingo-lipids content. Changes of AhR targets are corroborated using patient specimens. Overall, AhR induction by alcohol inhibits autophagy in hepatocytes through AMPKα, which is mediated by Ppp2r2d gene transactivation, revealing an AhR-dependent metabolism of phospho-/sphingo-lipids.

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

Friend or foe? Unraveling the complex roles of protein tyrosine phosphatases in cardiac disease and development

Regulation of protein tyrosine phosphorylation is critical for most, if not all, fundamental cellular processes. However, we still do not fully understand the complex and tissue-specific roles of protein tyrosine phosphatases in the normal heart or in cardiac pathology. This review compares and contrasts the various roles of protein tyrosine phosphatases known to date in the context of cardiac disease and development. In particular, it will be considered how specific protein tyrosine phosphatases control cardiac hypertrophy and cardiomyocyte contractility, how protein tyrosine phosphatases contribute to or ameliorate injury induced by ischaemia / reperfusion or hypoxia / reoxygenation, and how protein tyrosine phosphatases are involved in normal heart development and congenital heart disease. This review delves into the newest developments and current challenges in the field, and highlights knowledge gaps and emerging opportunities for future research.

System-Level Scenarios for the Elucidation of T Cell-Mediated Germinal Center B Cell Differentiation

Germinal center (GC) reactions are vital to the correct functioning of the adaptive immune system, through formation of high affinity, class switched antibodies. GCs are transient anatomical structures in secondary lymphoid organs where specific B cells, after recognition of antigen and with T cell help, undergo class switching. Subsequently, B cells cycle between zones of proliferation and somatic hypermutation and zones where renewed antigen acquisition and T cell help allows for selection of high affinity B cells (affinity maturation). Eventually GC B cells first differentiate into long-lived memory B cells (MBC) and finally into plasma cells (PC) that partially migrate to the bone marrow to encapsulate into long-lived survival niches. The regulation of GC reactions is a highly dynamically coordinated process that occurs between various cells and molecules that change in their signals. Here, we present a system-level perspective of T cell-mediated GC B cell differentiation, presenting and discussing the experimental and computational efforts on the regulation of the GCs. We aim to integrate Systems Biology with B cell biology, to advance elucidation of the regulation of high-affinity, class switched antibody formation, thus to shed light on the delicate functioning of the adaptive immune system. Specifically, we: i) review experimental findings of internal and external factors driving various GC dynamics, such as GC initiation, maturation and GCBC fate determination; ii) draw comparisons between experimental observations and mathematical modeling investigations; and iii) discuss and reflect on current strategies of modeling efforts, to elucidate B cell behavior during the GC tract. Finally, perspectives are specifically given on to the areas where a Systems Biology approach may be useful to predict novel GCBC-T cell interaction dynamics.

Neural plasticity and adult neurogenesis: the deep biology perspective

The recognition that neurogenesis does not stop with adolescence has spun off research towards the reduction of brain disorders by enhancing brain regeneration. Adult neurogenesis is one of the tougher problems of developmental biology as it requires the generation of complex intracellular and pericellular anatomies, amidst the danger of neuroinflammation. We here review how a multitude of regulatory pathways optimized for early neurogenesis has to be revamped into a new choreography of time dependencies. Distinct pathways need to be regulated, ranging from neural growth factor induced differentiation to mitochondrial bioenergetics, reactive oxygen metabolism, and apoptosis. Requiring much Gibbs energy consumption, brain depends on aerobic energy metabolism, hence on mitochondrial activity. Mitochondrial fission and fusion, movement and perhaps even mitoptosis, thereby come into play. All these network processes are interlinked and involve a plethora of molecules. We recommend a deep thinking approach to adult neurobiology.

Proteinaceous Regulators and Inhibitors of Protein Tyrosine Phosphatases

Proper control of the phosphotyrosine content in signal transduction proteins is essential for normal cell behavior and is lost in many pathologies. Attempts to normalize aberrant tyrosine phosphorylation levels in disease states currently involve either the application of small compounds that inhibit tyrosine kinases (TKs) or the addition of growth factors or their mimetics to boost receptor-type TK activity. Therapies that target the TK enzymatic counterparts, the multi-enzyme family of protein tyrosine phosphatases (PTPs), are still lacking despite their undisputed involvement in human diseases. Efforts to pharmacologically modulate PTP activity have been frustrated by the conserved structure of the PTP catalytic core, providing a daunting problem with respect to target specificity. Over the years, however, many different protein interaction-based regulatory mechanisms that control PTP activity have been uncovered, providing alternative possibilities to control PTPs individually. Here, we review these regulatory principles, discuss existing biologics and proteinaceous compounds that affect PTP activity, and mention future opportunities to drug PTPs via these regulatory concepts.

MK-STYX Alters the Morphology of Primary Neurons, and Outgrowths in MK-STYX Overexpressing PC-12 Cells Develop a Neuronal Phenotype

We previously reported that the pseudophosphatase MK-STYX (mitogen activated kinase phosphoserine/threonine/tyrosine binding protein) dramatically increases the number of what appeared to be primary neurites in rat pheochromocytoma (PC-12) cells; however, the question remained whether these MK-STYX-induced outgrowths were bona fide neurites, and formed synapses. Here, we report that microtubules and microfilaments, components of the cytoskeleton that are involved in the formation of neurites, are present in MK-STYX-induced outgrowths. In addition, in response to nerve growth factor (NGF), MK-STYX-expressing cells produced more growth cones than non-MK-STYX-expressing cells, further supporting a model in which MK-STYX has a role in actin signaling. Furthermore, immunoblot analysis demonstrates that MK-STYX modulates actin expression. Transmission electron microscopy confirmed that MK-STYX-induced neurites form synapses. To determine whether these MK-STYX-induced neurites have pre-synaptic or post-synaptic properties, we used classical markers for axons and dendrites, Tau-1 and MAP2 (microtubule associated protein 2), respectively. MK-STYX induced neurites were dopaminergic and expression of both Tau-1 and MAP2 suggests that they have both axonal and dendritic properties. Further studies in rat hippocampal primary neurons demonstrated that MK-STYX altered their morphology. A significant number of primary neurons in the presence of MK-STYX had more than the normal number of primary neurites. Our data illustrate the novel findings that MK-STYX induces outgrowths in PC-12 cells that fit the criteria for neurites, have a greater number of growth cones, form synapses, and have pre-synaptic and post-synaptic properties. It also highlights that the pseudophosphatase MK-STYX significantly alters the morphology of primary neurons.

Modeling and simulation of biological systems using SPICE language

The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology).

Learning to read and write in evolution: from static pseudoenzymes and pseudosignalers to dynamic gear shifters

We present a systems biology view on pseudoenzymes that acknowledges that genes are not selfish: the genome is. With network function as the selectable unit, there has been an evolutionary bonus for recombination of functions of and within proteins. Many proteins house a functionality by which they 'read' the cell's state, and one by which they 'write' and thereby change that state. Should the writer domain lose its cognate function, a 'pseudoenzyme' or 'pseudosignaler' arises. GlnK involved in Escherichia coli ammonia assimilation may well be a pseudosignaler, associating 'reading' the nitrogen state of the cell to 'writing' the ammonium uptake activity. We identify functional pseudosignalers in the cyclin-dependent kinase complexes regulating cell-cycle progression. For the mitogen-activated protein kinase pathway, we illustrate how a 'dead' pseudosignaler could produce potentially selectable functionalities. Four billion years ago, bioenergetics may have shuffled 'electron-writers', producing various networks that all served the same function of anaerobic ATP synthesis and carbon assimilation from hydrogen and carbon dioxide, but at different ATP/acetate ratios. This would have enabled organisms to deal with variable challenges of energy need and substrate supply. The same principle might enable 'gear-shifting' in real time, by dynamically generating different pseudo-redox enzymes, reshuffling their coenzymes, and rerouting network fluxes. Non-stationary pH gradients in thermal vents together with similar such shuffling mechanisms may have produced a first selectable proton-motivated pyrophosphate synthase and subsequent ATP synthase. A combination of functionalities into enzymes, signalers, and the pseudo-versions thereof may offer fitness in terms of plasticity, both in real time and in evolution.

The crucial role of protein phosphorylation in cell signaling and its use as targeted therapy (Review)

Protein phosphorylation is an important cellular regulatory mechanism as many enzymes and receptors are activated/deactivated by phosphorylation and dephosphorylation events, by means of kinases and phosphatases. In particular, the protein kinases are responsible for cellular transduction signaling and their hyperactivity, malfunction or overexpression can be found in several diseases, mostly tumors. Therefore, it is evident that the use of kinase inhibitors can be valuable for the treatment of cancer. In this review, we discuss the mechanism of action of phosphorylation, with particular attention to the importance of phosphorylation under physiological and pathological conditions. We also discuss the possibility of using kinase inhibitors in the treatment of tumors.

Dynamics robustness of cascading systems

A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade’s kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.

Cells use signaling pathways to transmit information received on its membrane to DNA, and many important cellular processes are tied to signaling networks. Past experiments have shown that cells’ internal signaling networks are sophisticated enough to process and encode temporal information such as the length of time a ligand is bound to a receptor. However, little research has been done to verify whether information encoded onto temporal profiles can be made robust. We examined mathematical models of linear signaling networks and found that the relaxation of the response to a transient stimuli can be made robust to certain parameter fluctuations. Robustness is a key concept in biological systems—it would be disastrous if a cell could not operate if there was a slight change in its environment or physiology. Our research shows that such dynamics robustness is a property of linear signaling cascades, and we outline the design principles needed to generate such robustness. We discovered that two conditions regarding the speed of the internal chemical reactions and concentration levels are needed to generate dynamics robustness.

IL-1β-induced and p38MAPK-dependent activation of the mitogen-activated protein kinase-activated protein kinase 2 (MK2) in hepatocytes: Signal transduction with robust and concentration-independent signal amplification

The IL-1β induced activation of the p38^MAPK/MAPK-activated protein kinase 2 (MK2) pathway in hepatocytes is important for control of the acute phase response and regulation of liver regeneration. Many aspects of the regulatory relevance of this pathway have been investigated in immune cells in the context of inflammation. However, very little is known about concentration-dependent activation kinetics and signal propagation in hepatocytes and the role of MK2. We established a mathematical model for IL-1β-induced activation of the p38^MAPK/MK2 pathway in hepatocytes that was calibrated to quantitative data on time- and IL-1β concentration-dependent phosphorylation of p38^MAPK and MK2 in primary mouse hepatocytes. This analysis showed that, in hepatocytes, signal transduction from IL-1β via p38^MAPK to MK2 is characterized by strong signal amplification. Quantification of p38^MAPK and MK2 revealed that, in hepatocytes, at maximum, 11.3% of p38^MAPK molecules and 36.5% of MK2 molecules are activated in response to IL-1β. The mathematical model was experimentally validated by employing phosphatase inhibitors and the p38^MAPK inhibitor SB203580. Model simulations predicted an IC₅₀ of 1-1.2 μm for SB203580 in hepatocytes. In silico analyses and experimental validation demonstrated that the kinase activity of p38^MAPK determines signal amplitude, whereas phosphatase activity affects both signal amplitude and duration. p38^MAPK and MK2 concentrations and responsiveness toward IL-1β were quantitatively compared between hepatocytes and macrophages. In macrophages, the absolute p38^MAPK and MK2 concentration was significantly higher. Finally, in line with experimental observations, the mathematical model predicted a significantly higher half-maximal effective concentration for IL-1β-induced pathway activation in macrophages compared with hepatocytes, underscoring the importance of cell type-specific differences in pathway regulation.

Quantitative measures for redox signaling

Redox signaling is now recognized as an important regulatory mechanism for a number of cellular processes including the antioxidant response, phosphokinase signal transduction and redox metabolism. While there has been considerable progress in identifying the cellular machinery involved in redox signaling, quantitative measures of redox signals have been lacking, limiting efforts aimed at understanding and comparing redox signaling under normoxic and pathogenic conditions. Here we have outlined some of the accepted principles for redox signaling, including the description of hydrogen peroxide as a signaling molecule and the role of kinetics in conferring specificity to these signaling events. Based on these principles, we then develop a working definition for redox signaling and review a number of quantitative methods that have been employed to describe signaling in other systems. Using computational modeling and published data, we show how time- and concentration- dependent analyses, in particular, could be used to quantitatively describe redox signaling and therefore provide important insights into the functional organization of redox networks. Finally, we consider some of the key challenges with implementing these methods.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.

Dynamics of elongation factor 2 kinase regulation in cortical neurons in response to synaptic activity

The rapid regulation of cell signaling in response to calcium in neurons is essential for real-time processing of large amounts of information in the brain. A vital regulatory component, and one of the most energy-intensive biochemical processes in cells, is the elongation phase of mRNA translation, which is controlled by the Ca(2+)/CaM-dependent elongation factor 2 kinase (eEF2K). However, little is known about the dynamics of eEF2K regulation in neurons despite its established role in learning and synaptic plasticity. To explore eEF2K dynamics in depth, we stimulated synaptic activity in mouse primary cortical neurons. We find that synaptic activity results in a rapid, but transient, increase in eEF2K activity that is regulated by a combination of AMPA and NMDA-type glutamate receptors and the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) and mammalian target of rapamycin complex 1 (mTORC1) pathways. We then used computational modeling to test the hypothesis that considering Ca(2+)-coordinated MEK/ERK, mTORC1, and eEF2k activation is sufficient to describe the observed eEF2K dynamics. Although such a model could partially fit the empirical findings, it also suggested that a crucial positive regulator of eEF2K was also necessary. Through additional modeling and empirical evidence, we demonstrate that AMP kinase (AMPK) is also an important regulator of synaptic activity-driven eEF2K dynamics in neurons. Our combined modeling and experimental findings provide the first evidence that it is necessary to consider the combined interactions of Ca(2+) with MEK/ERK, mTORC1, and AMPK to adequately explain eEF2K regulation in neurons.

Integrating phosphoproteomics in systems biology

Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS)-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.

"RAF" neighborhood: protein-protein interaction in the Raf/Mek/Erk pathway

The Raf/Mek/Erk signaling pathway, activated downstream of Ras primarily to promote proliferation, represents the best studied of the evolutionary conserved MAPK cascades. The investigation of the pathway has continued unabated since its discovery roughly 30 years ago. In the last decade, however, the identification of unexpected in vivo functions of pathway components, as well as the discovery of Raf mutations in human cancer, the ensuing quest for inhibitors, and the efforts to understand their mechanism of action, have boosted interest tremendously. From this large body of work, protein-protein interaction has emerged as a recurrent, crucial theme. This review focuses on the role of protein complexes in the regulation of the Raf/Mek/Erk pathway and in its cross-talk with other signaling cascades. Mapping these interactions and finding a way of exploiting them for therapeutic purposes is one of the challenges of future molecule-targeted therapy.

Tunable signal processing through a kinase control cycle: the IKK signaling node

The transcription factor NFκB, a key component of the immune system, shows intricate stimulus-specific temporal dynamics. Those dynamics are thought to play a role in controlling the physiological response to cytokines and pathogens. Biochemical evidence suggests that the NFκB inducing kinase, IKK, a signaling hub onto which many signaling pathways converge, is regulated via a regulatory cycle comprising a poised, an active, and an inactive state. We hypothesize that it operates as a modulator of signal dynamics, actively reshaping the signals generated at the receptor proximal level. Here we show that a regulatory cycle can function in at least three dynamical regimes, tunable by regulating a single kinetic parameter. In particular, the simplest three-state regulatory cycle can generate signals with two well-defined phases, each with distinct coding capabilities in terms of the information they can carry about the stimulus. We also demonstrate that such a kinase cycle can function as a signal categorizer classifying diverse incoming signals into outputs with a limited set of temporal activity profiles. Finally, we discuss the extension of the results to other regulatory motifs that could be understood in terms of the regimes of the three-state cycle.

Small G proteins Rac1 and Ras regulate serine/threonine protein phosphatase 5 (PP5)·extracellular signal-regulated kinase (ERK) complexes involved in the feedback regulation of Raf1

Serine/threonine protein phosphatase 5 (PP5, PPP5C) is known to interact with the chaperonin heat shock protein 90 (HSP90) and is involved in the regulation of multiple cellular signaling cascades that control diverse cellular processes, such as cell growth, differentiation, proliferation, motility, and apoptosis. Here, we identify PP5 in stable complexes with extracellular signal-regulated kinases (ERKs). Studies using mutant proteins reveal that the formation of PP5·ERK1 and PP5·ERK2 complexes partially depends on HSP90 binding to PP5 but does not require PP5 or ERK1/2 activity. However, PP5 and ERK activity regulates the phosphorylation state of Raf1 kinase, an upstream activator of ERK signaling. Whereas expression of constitutively active Rac1 promotes the assembly of PP5·ERK1/2 complexes, acute activation of ERK1/2 fails to influence the phosphatase-kinase interaction. Introduction of oncogenic HRas (HRas(V12)) has no effect on PP5-ERK1 binding but selectively decreases the interaction of PP5 with ERK2, in a manner that is independent of PP5 and MAPK/ERK kinase (MEK) activity, yet paradoxically requires ERK2 activity. Additional studies conducted with oncogenic variants of KRas4B reveal that KRas(L61), but not KRas(V12), also decreases the PP5-ERK2 interaction. The expression of wild type HRas or KRas proteins fails to reduce PP5-ERK2 binding, indicating that the effect is specific to HRas(V12) and KRas(L61) gain-of-function mutations. These findings reveal a novel, differential responsiveness of PP5-ERK1 and PP5-ERK2 interactions to select oncogenic Ras variants and also support a role for PP5·ERK complexes in regulating the feedback phosphorylation of PP5-associated Raf1.

Systems biology-embedded target validation: improving efficacy in drug discovery

The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment.

Mathematical modelling of miRNA mediated BCR.ABL protein regulation in chronic myeloid leukaemia vis-a-vis therapeutic strategies

Chronic myeloid leukaemia (CML) is a clonal myeloproliferative disease resulting from an aberrant BCR.ABL gene and protein. To predict BCR.ABL protein abundance and phosphorylation in individual cells in a population of CML cells, we modelled BCR.ABL protein regulation through associated miRNAs using a systems approach. The model rationalizes the level of BCR.ABL protein heterogeneity in CML cells in correlation with the heterogeneous BCR.ABL mRNA levels. We also measured BCR.ABL mRNA and BCR.ABLp phosphorylation in individual cells. The experimental data were consistent with the modelling results, thereby partly validating the model. Provided it is tested further, the model may be used to support effective therapeutic strategies including the combined application of a tyrosine kinase inhibitor and miRNAs targeting BCR.ABL. It appears able to predict different effects of the two types of drug on cells with different expression levels and consequently different effects on the generation of resistance.

Analysing the impact of nucleo-cytoplasmic shuttling of β-catenin and its antagonists APC, Axin and GSK3 on Wnt/β-catenin signalling

The canonical Wnt signalling pathway plays a critical role in development and disease. The key player of the pathway is β-catenin. Its activity is mainly regulated by the destruction complex consisting of APC, Axin and GSK3. In the nucleus, the complex formation of β-catenin and TCF initiates target gene expression. Our study provides a comprehensive analysis of the role of nucleo-cytoplasmic shuttling of APC, Axin, and GSK3 and the inactivation of β-catenin by the destruction complex in Wnt/β-catenin signalling. We address the following questions: Can nucleo-cytoplasmic shuttling of APC, Axin and GSK3 increase the [β-catenin/TCF] concentration? And, how is the [β-catenin/TCF] concentration influenced by phosphorylation and subsequent degradation of nuclear β-catenin? Based on experimental findings, we develop a compartmental model and conduct several simulation experiments. Our analysis reveals the following key findings: 1) nucleo-cytoplasmic shuttling of β-catenin and its antagonists can yield a spatial separation between the said proteins, which results in a breakdown of β-catenin degradation, followed by an accumulation of β-catenin and hence leads to an increase of the [β-catenin/TCF] concentration. Our results strongly suggest that Wnt signalling can benefit from nucleo-cytoplasmic shuttling of APC, Axin and GSK3, although they are in general β-catenin antagonising proteins. 2) The total robustness of the [β-catenin/TCF] output is closely linked to its absolute concentration levels. We demonstrate that the compartmental separation of β-catenin and the destruction complex does not only lead to a maximization, but additionally to an increased robustness of [β-catenin/TCF] signalling against perturbations in the cellular environment. 3) A nuclear accumulation of the destruction complex renders the pathway robust against fluctuations in Wnt signalling and against changes in the compartmental distribution of β-catenin. 4) Elucidating the impact of destruction complex inhibition, we show that the [β-catenin/TCF] concentration is more effectively enhanced by inhibition of the kinase GSK3 rather than the binding of β-catenin to the destruction complex.

Exploration of trade-offs between steady-state and dynamic properties in signaling cycles

In the intracellular signaling networks that regulate important cell processes, the base pattern comprises the cycle of reversible phosphorylation of a protein, catalyzed by kinases and opposing phosphatases. Mathematical modeling and analysis have been used for gaining a better understanding of their functions and to capture the rules governing system behavior. Since biochemical parameters in signaling pathways are not easily accessible experimentally, it is necessary to explore possibilities for both steady-state and dynamic responses in these systems. While a number of studies have focused on analyzing these properties separately, it is necessary to take into account both of these responses simultaneously in order to be able to interpret a broader range of phenotypes. This paper investigates the trade-offs between optimal characteristics of both steady-state and dynamic responses. Following an inverse sensitivity analysis approach, we use systematic optimization methods to find the biochemical and biophysical parameters that simultaneously achieve optimal steady-state and dynamic performance. Remarkably, we find that even a single covalent modification cycle can simultaneously and robustly achieve high ultrasensitivity, high amplification and rapid signal transduction. We also find that the response rise and decay times can be modulated independently by varying the activating- and deactivating-enzyme-to-interconvertible-protein ratios.

Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade

Background

The three layer mitogen activated protein kinase (MAPK) signaling cascade exhibits different designs of interactions between its kinases and phosphatases. While the sequential interactions between the three kinases of the cascade are tightly preserved, the phosphatases of the cascade, such as MKP3 and PP2A, exhibit relatively diverse interactions with their substrate kinases. Additionally, the kinases of the MAPK cascade can also sequester their phosphatases. Thus, each topologically distinct interaction design of kinases and phosphatases could exhibit unique signal processing characteristics, and the presence of phosphatase sequestration may lead to further fine tuning of the propagated signal.

Results

We have built four architecturally distinct types of models of the MAPK cascade, each model with identical kinase-kinase interactions but unique kinases-phosphatases interactions. Our simulations unravelled that MAPK cascade’s robustness to external perturbations is a function of nature of interaction between its kinases and phosphatases. The cascade’s output robustness was enhanced when phosphatases were sequestrated by their target kinases. We uncovered a novel implicit/hidden negative feedback loop from the phosphatase MKP3 to its upstream kinase Raf-1, in a cascade resembling the B cell MAPK cascade. Notably, strength of the feedback loop was reciprocal to the strength of phosphatases’ sequestration and stronger sequestration abolished the feedback loop completely. An experimental method to verify the presence of the feedback loop is also proposed. We further showed, when the models were activated by transient signal, memory (total time taken by the cascade output to reach its unstimulated level after removal of signal) of a cascade was determined by the specific designs of interaction among its kinases and phosphatases.

Conclusions

Differences in interaction designs among the kinases and phosphatases can differentially shape the robustness and signal response behaviour of the MAPK cascade and phosphatase sequestration dramatically enhances the robustness to perturbations in each of the cascade. An implicit negative feedback loop was uncovered from our analysis and we found that strength of the negative feedback loop is reciprocally related to the strength of phosphatase sequestration. Duration of output phosphorylation in response to a transient signal was also found to be determined by the individual cascade’s kinase-phosphatase interaction design.

A specialized ODE integrator for the efficient computation of parameter sensitivities

Background

Dynamic mathematical models in the form of systems of ordinary differential equations (ODEs) play an important role in systems biology. For any sufficiently complex model, the speed and accuracy of solving the ODEs by numerical integration is critical. This applies especially to systems identification problems where the parameter sensitivities must be integrated alongside the system variables. Although several very good general purpose ODE solvers exist, few of them compute the parameter sensitivities automatically.

Results

We present a novel integration algorithm that is based on second derivatives and contains other unique features such as improved error estimates. These features allow the integrator to take larger time steps than other methods. In practical applications, i.e. systems biology models of different sizes and behaviors, the method competes well with established integrators in solving the system equations, and it outperforms them significantly when local parameter sensitivities are evaluated. For ease-of-use, the solver is embedded in a framework that automatically generates the integrator input from an SBML description of the system of interest.

Conclusions

For future applications, comparatively ‘cheap’ parameter sensitivities will enable advances in solving large, otherwise computationally expensive parameter estimation and optimization problems. More generally, we argue that substantially better computational performance can be achieved by exploiting characteristics specific to the problem domain; elements of our methods such as the error estimation could find broader use in other, more general numerical algorithms.

Plasma from patients with liver failure inhibits the proliferation of HepG2 cells

AIM: To explore the mechanisms by which plasma from patients with liver failure inhibits the proliferation of HepG2 cells and to evaluate whether epidermal growth factor (EGF) can reverse this inhibitory effect.

METHODS: Plasma samples were collected from three patients with acute-on-chronic liver failure during plasma exchange therapy and treated with heparin. After HepG2 cells were cultured in medium containing 50% plasma from patients with liver failure with or without EGF stimulation, cell proliferation and apoptosis were detected by methyl thiazolyl tetrazolium (MTT) assay and Hoechst staining, respectively. The expression of intracellular cyclin D1 and cyclin-dependent kinase 4 (CDK4) in HepG2 cells was examined by Western blotting.

RESULTS: Treatment with 50% plasma from patients with liver failure for 12 to 72 hours significantly inhibited the proliferation of HepG2 cells in a time-dependent manner when compared to cells cultured with 50% normal control plasma (NCP). EGF at a concentration of 5, 10 or 20 μg/L significantly induced the proliferation of HepG2 cells cultured with NCP, while only high-dose EGF (20 μg/L) showed a transient promotion to the proliferation of HepG2 cells cultured with plasma from patients with liver failure. After stimulation with 20 μg/L EGF, the proliferation was still significantly inhibited in cells cultured with patient plasma compared to those cultured with NCP. The presence of 50% patient plasma did not significantly alter apoptosis index of HepG2 cells (P > 0.05). The expression of intracellular cyclin D1 and CDK4 in HepG2 cells was obviously inhibited after treatment with patient plasma for 12 to 72 hours.

CONCLUSION: Plasma from patients with liver failure inhibits the proliferation of HepG2 cells possibly by down-regulating the expression of intracellular cyclin D1 and CDK4. EGF can not reverse this inhibitory effect.

Signalling by protein phosphatases and drug development: a systems-centred view

Protein modification cycles catalysed by opposing enzymes, such as kinases and phosphatases, form the backbone of signalling networks. Although, historically, kinases have been at the research forefront, a systems-centred approach reveals predominant roles for phosphatases in controlling the network response times and spatio-temporal profiles of signalling activities. Emerging evidence suggests that phosphatase kinetics are critical for network function and cell-fate decisions. Protein phosphatases operate as both immediate and delayed regulators of signal transduction, capable of attenuating or amplifying signalling. This versatility of phosphatase action emphasizes the need for systems biology approaches to understand cellular signalling networks and predict the cellular outcomes of combinatorial drug interventions.

Systemic redox regulation of cellular information processing

Receptor-mediated signaling leads to transient changes in redox state, resulting in reversible oxidation of protein cysteine thiols. Numerous signaling proteins have been identified as being redox sensitive; however, to date, most investigations have focused on the ramifications of isolated protein modifications on cellular phenotypes. We propose that reversible thiol oxidation of proteins in a signaling network and their systemic interactions introduce features in the dynamics and control of cellular responses that are unique compared with isolated oxidative protein modifications. Simulations of dynamic redox regulation in different cellular contexts reveal feasible regulatory features for future experimental investigation. We suggest that location within a network, compartmentalization, and the degree of connectivity between redox proteins can dramatically modulate cellular information processing.

Protein arginine methyltransferase 5 regulates ERK1/2 signal transduction amplitude and cell fate through CRAF

The RAS to extracellular signal-regulated kinase (ERK) signal transduction cascade is crucial to cell proliferation, differentiation, and survival. Although numerous growth factors activate the RAS-ERK pathway, they can have different effects on the amplitude and duration of the ERK signal and, therefore, on the biological consequences. For instance, nerve growth factor, which elicits a larger and more sustained increase in ERK phosphorylation in PC12 cells than does epidermal growth factor (EGF), stimulates PC12 cell differentiation, whereas EGF stimulates PC12 cell proliferation. Here, we show that protein arginine methylation limits the ERK1/2 signal elicited by particular growth factors in different cell types from various species. We found that this restriction in ERK1/2 phosphorylation depended on methylation of RAF proteins by protein arginine methyltransferase 5 (PRMT5). PRMT5-dependent methylation enhanced the degradation of activated CRAF and BRAF, thereby reducing their catalytic activity. Inhibition of PRMT5 activity or expression of RAF mutants that could not be methylated not only affected the amplitude and duration of ERK phosphorylation in response to growth factors but also redirected the response of PC12 cells to EGF from proliferation to differentiation. This additional level of regulation within the RAS pathway may lead to the identification of new targets for therapeutic intervention.

Protein-tyrosine phosphatase 1B modulates early endosome fusion and trafficking of Met and epidermal growth factor receptors

The endoplasmic reticulum-localized non-receptor protein-tyrosine phosphatase 1B (PTP1B) is associated with oncogenic, metabolic, and cytokine-related signaling and functionally targets multiple receptor tyrosine kinases (RTKs) for dephosphorylation. Loss of PTP1B activity leads to enhanced ligand-dependent biological activity of the Met RTK among others. Here, we demonstrate that knockdown of PTP1B or expression of a PTP1B trapping aspartic acid-to-alanine substitution (D/A) mutant delayed ligand-induced degradation of the Met and EGF RTKs. Loss of PTP1B function abrogated trafficking of Met and EGF receptor to Rab5- and phosphatidylinositol 3-phosphate (Pl3P)-positive early endosomes and subsequent trafficking through the degradative pathway. Under these conditions, internalization of the Met and EGF receptors was unaltered, suggesting a block at the level of early endosome formation. We show that the N-ethylmaleimide-sensitive factor (NSF), an essential component of the vesicle fusion machinery, was hyperphosphorylated in PTP1B knockdown or PTP1B D/A-expressing cells and was a target for PTP1B. NSF knockdown phenocopied PTP1B knockdown, demonstrating a mechanism through which PTP1B regulates endocytic trafficking. Finally, we show that PTP1B dephosphorylated NSF and that this interaction was required for physiological RTK trafficking and appropriate attenuation of downstream signaling.

Retrieval, alignment, and clustering of computational models based on semantic annotations

As the number of computational systems biology models increases, new methods are needed to explore their content and build connections with experimental data. In this Perspective article, the authors propose a flexible semantic framework that can help achieve these aims.

The exploding number of computational models produced by Systems Biologists over the last years is an invitation to structure and exploit this new wealth of information. Researchers would like to trace models relevant to specific scientific questions, to explore their biological content, to align and combine them, and to match them with experimental data. To automate these processes, it is essential to consider semantic annotations, which describe their biological meaning. As a prerequisite for a wide range of computational methods, we propose general and flexible similarity measures for Systems Biology models computed from semantic annotations. By using these measures and a large extensible ontology, we implement a platform that can retrieve, cluster, and align Systems Biology models and experimental data sets. At present, its major application is the search for relevant models in the BioModels Database, starting from initial models, data sets, or lists of biological concepts. Beyond similarity searches, the representation of models by semantic feature vectors may pave the way for visualisation, exploration, and statistical analysis of large collections of models and corresponding data.

Receptor-type protein tyrosine phosphatase beta (RPTP-beta) directly dephosphorylates and regulates hepatocyte growth factor receptor (HGFR/Met) function

Protein tyrosine phosphorylation is a ubiquitous, fundamental biochemical mechanism that regulates essential eukaryotic cellular functions. The level of tyrosine phosphorylation of specific proteins is finely tuned by the dynamic balance between protein tyrosine kinase and protein tyrosine phosphatase activities. Hepatocyte growth factor receptor (also known as Met), a receptor protein tyrosine kinase, is a major regulator of proliferation, migration, and survival for many epithelial cell types. We report here that receptor-type protein tyrosine phosphatase β (RPTP-β) specifically dephosphorylates Met and thereby regulates its function. Expression of RPTP-β, but not other RPTP family members or catalytically inactive forms of RPTP-β, reduces hepatocyte growth factor (HGF)-stimulated Met tyrosine phosphorylation in HEK293 cells. Expression of RPTP-β in primary human keratinocytes reduces both basal and HGF-induced Met phosphorylation at tyrosine 1356 and inhibits downstream MEK1/2 and Erk activation. Furthermore, shRNA-mediated knockdown of endogenous RPTP-β increases basal and HGF-stimulated Met phosphorylation at tyrosine 1356 in primary human keratinocytes. Purified RPTP-β intracellular domain preferentially dephosphorylates purified Met at tyrosine 1356 in vitro. In addition, the substrate-trapping mutant of RPTP-β specifically interacts with Met in intact cells. Expression of RPTP-β in human primary keratinocytes reduces HGF induction of VEGF expression, proliferation, and motility. Taken together, the above data indicate that RPTP-β is a key regulator of Met function.

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.

From Physics to Pharmacology?

Over the last fifty years there has been an explosion of biological data, leading to the realization that to fully explain biological mechanisms it is necessary to interpret them as complex dynamical systems. The first stage of this interpretation is to determine which components (proteins, genes or metabolites) of the system interact. This is usually represented by a graph, or network. The behavior of this network can then be investigated using mathematical modeling. In vivo these biological networks show several remarkable (and seemingly paradoxical) properties including robustness, plasticity and sensitivity. Erroneous behavior of these networks is often associated with disease. Hence understanding the system-level properties can have important implications for the treatment of disease. Systems biology is an organized approach to quantitatively describe and elucidate the behavior of these complex networks. This review focuses on the progress and future challenges of a systems approach to biology.

Four-dimensional dynamics of MAPK information processing systems

Mitogen activated protein kinase (MAPK) cascades process a myriad of stimuli received by cell-surface receptors and generate precise spatio-temporal guidance for multiple target proteins, dictating receptor-specific cellular outcomes. Computational modelling reveals that the intrinsic topology of MAPK cascades enables them to amplify signal sensitivity and amplitude, reduce noise and display intricate dynamic properties, which include toggle switches, excitation pulses and oscillations. Specificity of signaling responses can be brought about by signal-induced feedback and feedforward wiring imposed on the MAPK cascade backbone. Intracellular gradients of protein activities arise from the spatial separation of opposing reactions in kinase-phosphatase cycles. The membrane confinement of the initiating kinase in MAPK cascades and cytosolic localization of phosphatases can result in precipitous gradients of phosphorylated signal-transducers if they spread solely by diffusion. Endocytotic trafficking of active kinases driven by molecular motors and traveling waves of protein phosphorylation can propagate phosphorylation signals from the plasma membrane to the nucleus, especially in large cells, such as Xenopus eggs.

ATM-dependent and -independent dynamics of the nuclear phosphoproteome after DNA damage

The double-strand break (DSB) is a cytotoxic DNA lesion caused by oxygen radicals, ionizing radiation, and radiomimetic chemicals. Cells cope with DNA damage by activating the DNA damage response (DDR), which leads either to damage repair and cellular survival or to programmed cell death. The main transducer of the DSB response is the nuclear protein kinase ataxia telangiectasia mutated (ATM). We applied label-free quantitative mass spectrometry to follow the dynamics of DSB-induced phosphoproteome in nuclear fractions of the human melanoma G361 cells after radiomimetic treatment. We found that these dynamics are complex, including both phosphorylation and dephosphorylation events. In addition to identifying previously unknown ATM-dependent phosphorylation and dephosphorylation events, we found that about 40% of DSB-induced phosphorylations were ATM-independent and that several other kinases are potentially involved. Sustained activity of ATM was required to maintain many ATM-dependent phosphorylations. We identified an ATM-dependent phosphorylation site on ATM itself that played a role in its retention on damaged chromatin. By connecting many of the phosphorylated and dephosphorylated proteins into functional networks, we highlight putative cross talks between proteins pertaining to several cellular biological processes. Our study expands the DDR phosphorylation landscape and identifies previously unknown ATM-dependent and -independent branches. It reveals insights into the breadth and complexity of the cellular responses involved in the coordination of many DDR pathways, which is in line with the critical importance of genomic stability in maintenance of cellular homeostasis.

Confidence from uncertainty--a multi-target drug screening method from robust control theory

Background

Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty.

Results

We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty.

Conclusions

The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.