Tuning the activation threshold of a kinase network by nested feedback loops

Biological feedback control-Respect the loops

We, and all organisms, are an evolutionary masterpiece of multiscale feedback control. Feedback loops enable our cells to grow and then stop at the right size, to divide and self-repair, and to respond with agility to their changing environment. Individual cells engage in long range extracellular feedback with other cells, ensuring continued homeostasis of our tissues and organs. Many long ranging feedback loops regulate vital physiological variables. Here, I will argue that focused efforts to understand the properties and constraints of biological feedback control networks should be central to the quest of understanding life. I will also propose many pressing challenges in this field and review conceptual frameworks that might be consequential for addressing them.

Noisy Cell-Size-Correlated Expression of Cyclin B Drives Probabilistic Cell-Size Homeostasis in Fission Yeast

How cells correct deviations from a mean cell size at mitosis remains uncertain. Classical cell-size homeostasis models are the sizer, timer, and adder [1]. Sizers postulate that cells divide at some threshold size; timers, that cells grow for a set time; and adders, that cells add a constant volume before division. Here, we show that a size-based probabilistic model of cell-size control at the G2/M transition (P(Div)) can generate realistic cell-size homeostasis in silico. In fission yeast cells, Cyclin B^Cdc13 scales with size, and we propose that this increases the likelihood of mitotic entry, while molecular noise in its expression adds a probabilistic component to the model. Varying Cdc13 expression levels exogenously using a newly developed tetracycline inducible promoter shows that both the level and variability of its expression influence cell size at division. Our results demonstrate that as cells grow larger, their probability of dividing increases, and this is sufficient to generate cell-size homeostasis. Size-correlated Cdc13 expression forms part of the molecular circuitry of this system.

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A size-correlated division probability can generate cell-size homeostasis

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Cyclin B concentration scales noisily with size in fission yeast

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Cells with stochastically suprathreshold cyclin B are the ones that divide

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A new tetracycline inducible promoter with linear dose response is developed

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

The role of stochastic sequestration dynamics for intrinsic noise filtering in signaling network motifs

The relation between design principles of signaling network motifs and their robustness against intrinsic noise still remains illusive. In this work we investigate the role of cascading for coping with intrinsic noise due to stochasticity in molecular reactions. We use stochastic approaches to quantify fluctuations in the terminal kinase of phosphorylation-dephosphorylation cascade motifs and demonstrate that cascading highly affects these fluctuations. We show that this purely stochastic effect can be explained by time-varying sequestration of upstream kinase molecules. In particular, we discuss conditions on time scales and parameter regimes which lead to a reduction of output fluctuations. Our results are put into biological context by adapting rate parameters of our modeling approach to biologically feasible ranges for general binding-unbinding and phosphorylation-dephosphorylation mechanisms. Overall, this study reveals a novel role of stochastic sequestration for dynamic noise filtering in signaling cascade motifs.

A Precise Cdk Activity Threshold Determines Passage through the Restriction Point

At the restriction point (R), mammalian cells irreversibly commit to divide. R has been viewed as a point in G1 that is passed when growth factor signaling initiates a positive feedback loop of Cdk activity. However, recent studies have cast doubt on this model by claiming R occurs prior to positive feedback activation in G1 or even before completion of the previous cell cycle. Here we reconcile these results and show that whereas many commonly used cell lines do not exhibit a G1 R, primary fibroblasts have a G1 R that is defined by a precise Cdk activity threshold and the activation of cell-cycle-dependent transcription. A simple threshold model, based solely on Cdk activity, predicted with more than 95% accuracy whether individual cells had passed R. That a single measurement accurately predicted cell fate shows that the state of complex regulatory networks can be assessed using a few critical protein activities.

Catch and Release of Cytokines Mediated by Tumor Phosphatidylserine Converts Transient Exposure into Long-Lived Inflammation

Immune cells constantly survey the host for pathogens or tumors and secrete cytokines to alert surrounding cells of these threats. In vivo, activated immune cells secrete cytokines for several hours, yet an acute immune reaction occurs over days. Given these divergent timescales, we addressed how cytokine-responsive cells translate brief cytokine exposure into phenotypic changes that persist over long timescales. We studied melanoma cell responses to transient exposure to the cytokine interferon γ (IFNγ) by combining a systems-scale analysis of gene expression dynamics with computational modeling and experiments. We discovered that IFNγ is captured by phosphatidylserine (PS) on the surface of viable cells both in vitro and in vivo then slowly released to drive long-term transcription of cytokine-response genes. This mechanism introduces an additional function for PS in dynamically regulating inflammation across diverse cancer and primary cell types and has potential to usher in new immunotherapies targeting PS and inflammatory pathways.

Genetic Redundancies Enhance Information Transfer in Noisy Regulatory Circuits

Cellular decision making is based on regulatory circuits that associate signal thresholds to specific physiological actions. This transmission of information is subjected to molecular noise what can decrease its fidelity. Here, we show instead how such intrinsic noise enhances information transfer in the presence of multiple circuit copies. The result is due to the contribution of noise to the generation of autonomous responses by each copy, which are altogether associated with a common decision. Moreover, factors that correlate the responses of the redundant units (extrinsic noise or regulatory cross-talk) contribute to reduce fidelity, while those that further uncouple them (heterogeneity within the copies) can lead to stronger information gain. Overall, our study emphasizes how the interplay of signal thresholding, redundancy, and noise influences the accuracy of cellular decision making. Understanding this interplay provides a basis to explain collective cell signaling mechanisms, and to engineer robust decisions with noisy genetic circuits.

There is increasing evidence that the presence of molecular noise greatly influences function in biological systems. This could imply, for instance, that genetic circuits adopt particular architectures in order to reduce noise. On the other hand, noise can be beneficial. Here, we show that this could be the case for the functioning of analog to digital genetic devices, which are commonly found in cellular decision making situations. We use the framework of information theory to illustrate first how noise can enhance information transfer in these devices. In those regimes in which noise is detrimental, we discuss how genetic redundancies allow information to be maximized, and how this effect depends on the specifics of the devices, and the interdependence among them. These results provide overall an additional rationale for genetic redundancies in genomic systems.

Synthetic mixed-signal computation in living cells

Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.

Digital and analogue gene circuits each have distinct advantages in natural and engineered cells. Here, Rubens et al. engineer synthetic gene circuits that implement mixed-signal digital and analogue computations in living cells.

Cell-Size Control

Cells of a given type maintain a characteristic cell size to function efficiently in their ecological or organismal context. They achieve this through the regulation of growth rates or by actively sensing size and coupling this signal to cell division. We focus this review on potential size-sensing mechanisms, including geometric, external cue, and titration mechanisms. Mechanisms that titrate proteins against DNA are of particular interest because they are consistent with the robust correlation of DNA content and cell size. We review the literature, which suggests that titration mechanisms may underlie cell-size sensing in Xenopus embryos, budding yeast, and Escherichia coli, whereas alternative mechanisms may function in fission yeast.

MAPK feedback encodes a switch and timer for tunable stress adaptation in yeast

Signaling pathways can behave as switches or rheostats, generating binary or graded responses to a given cell stimulus. We evaluated whether a single signaling pathway can simultaneously encode a switch and a rheostat. We found that the kinase Hog1 mediated a bifurcated cellular response: Activation and commitment to adaptation to osmotic stress are switchlike, whereas protein induction and the resolution of this commitment are graded. Through experimentation, bioinformatics analysis, and computational modeling, we determined that graded recovery is encoded through feedback phosphorylation and a gene induction program that is both temporally staggered and variable across the population. This switch-to-rheostat signaling mechanism represents a versatile stress adaptation system, wherein a broad range of inputs generate an "all-in" response that is later tuned to allow graded recovery of individual cells over time.

Positive feedback of NDT80 expression ensures irreversible meiotic commitment in budding yeast

In budding yeast, meiotic commitment is the irreversible continuation of the developmental path of meiosis. After reaching meiotic commitment, cells finish meiosis and gametogenesis, even in the absence of the meiosis-inducing signal. In contrast, if the meiosis-inducing signal is removed and the mitosis-inducing signal is provided prior to reaching meiotic commitment, cells exit meiosis and return to mitosis. Previous work has shown that cells commit to meiosis after prophase I but before entering the meiotic divisions. Since the Ndt80 transcription factor induces expression of middle meiosis genes necessary for the meiotic divisions, we examined the role of the NDT80 transcriptional network in meiotic commitment. Using a microfluidic approach to analyze single cells, we found that cells commit to meiosis in prometaphase I, after the induction of the Ndt80-dependent genes. Our results showed that high-level expression of NDT80 is important for the timing and irreversibility of meiotic commitment. A modest reduction in NDT80 levels delayed meiotic commitment based on meiotic stages, although the timing of each meiotic stage was similar to that of wildtype cells. A further reduction of NDT80 resulted in the surprising finding of inappropriately uncommitted cells: withdrawal of the meiosis-inducing signal and addition of the mitosis-inducing signal to cells at stages beyond metaphase I caused return to mitosis, leading to multi-nucleate cells. Since Ndt80 enhances its own transcription through positive feedback, we tested whether positive feedback ensured the irreversibility of meiotic commitment. Ablating positive feedback in NDT80 expression resulted in a complete loss of meiotic commitment. These findings suggest that irreversibility of meiotic commitment is a consequence of the NDT80 transcriptional positive feedback loop, which provides the high-level of Ndt80 required for the developmental switch of meiotic commitment. These results also illustrate the importance of irreversible meiotic commitment for maintaining genome integrity by preventing formation of multi-nucleate cells.

Start and the restriction point

Commitment to division requires that cells sense, interpret, and respond appropriately to multiple signals. In most eukaryotes, cells commit to division in G1 before DNA replication. Beyond a point, known as Start in yeast and the restriction point in mammals, cells will proceed through the cell cycle despite changes in upstream signals. In metazoans, misregulated G1 control can lead to developmental problems or disease, so it is important to understand how cells decipher the myriad external and internal signals that contribute to the fundamental all-or-none decision to divide. Extensive study of G1 control in the budding yeast Saccharomyces cerevisiae and mammalian culture systems has revealed highly similar networks regulating commitment. However, protein sequences of functional orthologs often indicate a total lack of conservation suggesting significant evolution of G1 control. Here, we review recent studies defining the conserved and diverged features of G1 control and highlight systems-level aspects that may be common to other biological regulatory networks.

Progesterone receptor A stability is mediated by glycogen synthase kinase-3β in the Brca1-deficient mammary gland

Germ line mutations of the BRCA1 gene increase the risk of breast and ovarian cancer, but the basis of this tissue-specific tumor predisposition is not fully understood. Previously, we reported that the progesterone receptors are stabilized in Brca1-deficient mammary epithelial cells, and treating with anti-progesterone delays mammary tumorigenesis in Brca1/p53 conditional knock-out mice, suggesting that the progesterone has a critical role in breast carcinogenesis. To further explore how the stability of progesterone receptor is modulated, here, we have found that glycogen synthase kinase (GSK)-3β phosphorylation of progesterone receptor-A (PR-A) facilitates its ubiquitination. GSK-3β-mediated phosphorylation of serine 390 in PR-A regulates its subsequent ubiquitination and protein stability. Expression of PR-A(S390A) mutant in the human breast epithelial cells, MCF-10A, results in enhanced proliferation and formation of aberrant acini structure in the three-dimensional culture. Consistently, reduction of phosphorylation of serine 390 of PR-A and GSK-3β activity is observed in the Brca1-deficient mammary gland. Taken together, these results provide important aspects of tissue specificity of BRCA1-mediated suppression of breast carcinogenesis.

Bistability, bifurcations, and Waddington's epigenetic landscape

Waddington's epigenetic landscape is probably the most famous and most powerful metaphor in developmental biology. Cells, represented by balls, roll downhill through a landscape of bifurcating valleys. Each new valley represents a possible cell fate and the ridges between the valleys maintain the cell fate once it has been chosen. Here I examine models of two important developmental processes - cell-fate induction and lateral inhibition - and ask whether the landscapes for these models at least qualitatively resemble Waddington's picture. For cell-fate induction, the answer is no. The commitment of a cell to a new fate corresponds to the disappearance of a valley from the landscape, not the splitting of one valley into two, and it occurs through a type of bifurcation - a saddle-node bifurcation - that possesses an intrinsic irreversibility that is missing from Waddington's picture. Lateral inhibition, a symmetrical cell-cell competition process, corresponds better to Waddington's picture, with one valley reversibly splitting into two through a pitchfork bifurcation. I propose an alternative epigenetic landscape that has numerous valleys and ridges right from the start, with the process of cell-fate commitment corresponding to the irreversible disappearance of some of these valleys and ridges, via cell-fate induction, complemented by the creation of new valleys and ridges through processes like cell-cell competition.

Modeling of hysteresis in gene regulatory networks

Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E.coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function.

Cell size control in yeast

Cell size is an important adaptive trait that influences nearly all aspects of cellular physiology. Despite extensive characterization of the cell-cycle regulatory network, the molecular mechanisms coupling cell growth to division, and thereby controlling cell size, have remained elusive. Recent work in yeast has reinvigorated the size control field and suggested provocative mechanisms for the distinct functions of setting and sensing cell size. Further examination of size-sensing models based on spatial gradients and molecular titration, coupled with elucidation of the pathways responsible for nutrient-modulated target size, may reveal the fundamental principles of eukaryotic cell size control.

Negative feedback confers mutational robustness in yeast transcription factor regulation

Organismal fitness depends on the ability of gene networks to function robustly in the face of environmental and genetic perturbations. Understanding the mechanisms of this stability is one of the key aims of modern systems biology. Dissecting the basis of robustness to mutation has proven a particular challenge, with most experimental models relying on artificial DNA sequence variants engineered in the laboratory. In this work, we hypothesized that negative regulatory feedback could stabilize gene expression against the disruptions that arise from natural genetic variation. We screened yeast transcription factors for feedback and used the results to establish ROX1 (Repressor of hypOXia) as a model system for the study of feedback in circuit behaviors and its impact across genetically heterogeneous populations. Mutagenesis experiments revealed the mechanism of Rox1 as a direct transcriptional repressor at its own gene, enabling a regulatory program of rapid induction during environmental change that reached a plateau of moderate steady-state expression. Additionally, in a given environmental condition, Rox1 levels varied widely across genetically distinct strains; the ROX1 feedback loop regulated this variation, in that the range of expression levels across genetic backgrounds showed greater spread in ROX1 feedback mutants than among strains with the ROX1 feedback loop intact. Our findings indicate that the ROX1 feedback circuit is tuned to respond to perturbations arising from natural genetic variation in addition to its role in induction behavior. We suggest that regulatory feedback may be an important element of the network architectures that confer mutational robustness across biology.

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

A dynamical model of oocyte maturation unveils precisely orchestrated meiotic decisions

Maturation of vertebrate oocytes into haploid gametes relies on two consecutive meioses without intervening DNA replication. The temporal sequence of cellular transitions driving eggs from G2 arrest to meiosis I (MI) and then to meiosis II (MII) is controlled by the interplay between cyclin-dependent and mitogen-activated protein kinases. In this paper, we propose a dynamical model of the molecular network that orchestrates maturation of Xenopus laevis oocytes. Our model reproduces the core features of maturation progression, including the characteristic non-monotonous time course of cyclin-Cdks, and unveils the network design principles underlying a precise sequence of meiotic decisions, as captured by bifurcation and sensitivity analyses. Firstly, a coherent and sharp meiotic resumption is triggered by the concerted action of positive feedback loops post-translationally activating cyclin-Cdks. Secondly, meiotic transition is driven by the dynamic antagonism between positive and negative feedback loops controlling cyclin turnover. Our findings reveal a highly modular network in which the coordination of distinct regulatory schemes ensures both reliable and flexible cell-cycle decisions.

In the life cycle of sexual organisms, a specialized cell division -meiosis- reduces the number of chromosomes in gametes or spores while fertilization or mating restores the original number. The essential feature that distinguishes meiosis from mitosis (the usual division) is the succession of two rounds of division following a single DNA replication, as well as the arrest at the second division in the case of oocyte maturation. The fact that meiosis and mitosis are similar but different raises several interesting questions: What is the meiosis-specific dynamics of cell-cycle regulators? Are there mechanisms which guarantee the occurence of two and only two rounds of division despite the presence of intrinsic and extrinsic noises ? The study of a model of the molecular network that underlies the meiotic maturation process in Xenopus oocytes provides unexpected answers to these questions. On the one hand, the modular organization of this network ensures separate controls of the first and second divisions. On the other hand, regulatory synergies ensure that these two stages are precisely and reliably sequenced during meiosis. We conclude that cells have evolved a sophisticated regulatory network to achieve a robust, albeit flexible, meiotic dynamics.

Unraveling the design principle for motif organization in signaling networks

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

Commitment to a cellular transition precedes genome-wide transcriptional change

In budding yeast, commitment to cell division corresponds to activating the positive feedback loop of G1 cyclins controlled by the transcription factors SBF and MBF. This pair of transcription factors has over 200 targets, implying that cell-cycle commitment coincides with genome-wide changes in transcription. Here, we find that genes within this regulon have a well-defined distribution of transcriptional activation times. Combinatorial use of SBF and MBF results in a logical OR function for gene expression and partially explains activation timing. Activation of G1 cyclin expression precedes the activation of the bulk of the G1/S regulon, ensuring that commitment to cell division occurs before large-scale changes in transcription. Furthermore, we find similar positive feedback-first regulation in the yeasts S. bayanus and S. cerevisiae, as well as human cells. The widespread use of the feedback-first motif in eukaryotic cell-cycle control, implemented by nonorthologous proteins, suggests its frequent deployment at cellular transitions.

Novel computational approaches to polypharmacology as a means to define responses to individual drugs

Polypharmacology, which focuses on designing therapeutics to target multiple receptors, has emerged as a new paradigm in drug discovery. Polypharmacological effects are an attribute of most, if not all, drug molecules. The efficacy and toxicity of drugs, whether designed as single- or multitarget therapeutics, result from complex interactions between pharmacodynamic, pharmacokinetic, genetic, epigenetic, and environmental factors. Ultimately, to predict a drug response phenotype, it is necessary to understand the change in information flow through cellular networks resulting from dynamic drug-target interactions and the impact that this has on the complete biological system. Although such is a future objective, we review recent progress and challenges in computational techniques that enable the prediction and analysis of in vitro and in vivo drug-response phenotypes.

Light-activated kinases enable temporal dissection of signaling networks in living cells

We report a general strategy for creating protein kinases in mammalian cells that are poised for very rapid activation by light. By photoactivating a caged version of MEK1, we demonstrate the specific, rapid, and receptor independent activation of an artificial subnetwork within the Raf/MEK/ERK pathway. Time-lapse microscopy allowed us to precisely characterize the kinetics of elementary steps in the signaling cascade and provided insight into adaptive feedback and rate-determining processes in the pathway.

Microfluidic Western blot

We develop a novel method for Western blot based on microfluidics, incorporating the internal molecular weight marker, loading control, and antibody titration in the same protocol. Compared with the conventional method which could detect only one protein, the microfluidic Western blot could analyze at least 10 proteins simultaneously from a single sample, and it requires only about 1% of the amount of antibody used in conventional Western blot.

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.

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.

Lose and gain: impacts of ERK5 and JNK cascades on each other

Kinase cascades in ERK5 (Extracellular signal-regulated kinases) and JNK (c-Jun N-terminal kinases) signaling pathways mediate the sensing and processing of stimuli. Cross-talks between signaling cascades is a likely phenomenon that can cause apparently different biological responses from a single pathway, on its activation. Feedback loops have the potential to greatly alter the properties of a pathway and its response to stimuli. Based on enzyme kinetic reactions, mathematical models have been developed to predict and analyze the impacts of cross-talks and feedback loops in ERK5 and JNK cascades. It has been observed that, there is no significant impact on neither ERK5 activation nor JNKs' activation due to cross-talks between them. But it is due to cross-talks and feedback loops in ERK5 and JNK cascade, ERK5 gets activated in a transient manner in the absence of input signals. Planning to obtain the parameter values from the experimentalist and the result should be validated by experimental verification.

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A global protein kinase and phosphatase interaction network in yeast

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses.

Genetic dissection of differential signaling threshold requirements for the Wnt/beta-catenin pathway in vivo

Contributions of null and hypomorphic alleles of Apc in mice produce both developmental and pathophysiological phenotypes. To ascribe the resulting genotype-to-phenotype relationship unambiguously to the Wnt/β-catenin pathway, we challenged the allele combinations by genetically restricting intracellular β-catenin expression in the corresponding compound mutant mice. Subsequent evaluation of the extent of resulting Tcf4-reporter activity in mouse embryo fibroblasts enabled genetic measurement of Wnt/β-catenin signaling in the form of an allelic series of mouse mutants. Different permissive Wnt signaling thresholds appear to be required for the embryonic development of head structures, adult intestinal polyposis, hepatocellular carcinomas, liver zonation, and the development of natural killer cells. Furthermore, we identify a homozygous Apc allele combination with Wnt/β-catenin signaling capacity similar to that in the germline of the Apc^min mice, where somatic Apc loss-of-heterozygosity triggers intestinal polyposis, to distinguish whether co-morbidities in Apc^min mice arise independently of intestinal tumorigenesis. Together, the present genotype–phenotype analysis suggests tissue-specific response levels for the Wnt/β-catenin pathway that regulate both physiological and pathophysiological conditions.

Germline or somatic mutations in genes are the underlying cause of many human diseases, most notably cancer. Interestingly though, even in situations where every cell of every tissue of an organism carries the same mutation (as is the case for germline mutations), some tissues are more susceptible to the development of disease over time than others. For example, in familial adenomatous polyposis (FAP), affected persons carry different germline mutations in the APC gene and are prone to developing cancers of the colon and the rectum—and, less frequently, cancers in other tissues such as stomach, liver, and bones. Here we utilize a panel of mutant mice with truncating or hypomorphic mutations in the Apc gene, resulting in different levels of activation of the Wnt/β-catenin pathway. Our results reveal that different pathophysiological outcomes depend on different permissive signaling thresholds in embryonic, intestinal, and liver tissues. Importantly, we demonstrate that reducing Wnt pathway activation by 50% is enough to prevent the manifestation of embryonic abnormalities and disease in the adult mouse. This raises the possibility of developing therapeutic strategies that modulate the activation levels of this pathway rather than trying to “repair” the mutation in the gene itself.

Kicked by Mos and tuned by MPF-the initiation of the MAPK cascade in Xenopus oocytes

The mitogen-activated protein kinase (MAPK) cascade is a paradigmatic signaling cascade, which plays a crucial role in many aspects of cellular events. The main initiator of the cascade in Xenopus oocytes is the oncoprotein Mos. After activation of the cascade, Mos activity is stabilized by MAPK via a feedback loop. Mos concentration levels are, however, not controlled by MAPK alone. In this paper we show, by imposing either a sustained or a peaked activity of M-phase promoting factor (MPF) (Cdc2-cyclin B), how the latter regulates the dynamics of Mos. Our experiments are supported by a detailed kinetic model for the Mos-MPF-MAPK network, which takes into account the three different phosphorylation states of Mos and, as a consequence, allows us to determine the time evolution of Mos under control of MPF. Our work opens a path toward a more complete and biologically realistic quantitative understanding of the dynamic interdependence of Mos and MPF in Xenopus oocytes.

Positive-feedback loops in cell cycle progression

A positive-feedback loop is a simple motif that is ubiquitous to the modules and networks that comprise cellular signaling systems. Signaling behaviors that are synonymous with positive feedback include amplification and rapid switching, maintenance, and the coherence of outputs. Recent advances have been made towards understanding how positive-feedback loops function, as well as their mechanistic basis in controlling eukaryotic cell cycle progression. Some of these advances will be reviewed here, including: how cyclin controls passage through Start and maintains coherence of G1/S regulon expression in yeast; how Polo-like kinase 1 activation is driven by Bora and Aurora A, and its expression is stimulated by Forkhead Box M1 in mammalian cells; and how some of the various dynamic behaviors of spindle assembly and anaphase onset can be produced.

Growth control and ribosome biogenesis

Ribosomes provide the basis for protein production and this drives cell growth. Recent studies, both in yeast and in higher eukaryotes, are beginning to reveal new mechanisms underlying the elaborate control of ribosome biogenesis, which requires coordinate regulation of all three RNA polymerases. Transcription of ribosomal RNA is finely tuned to cellular energy status and linked to the production of ribosomal proteins. Several autoregulatory mechanisms controlling various aspects of ribosome biogenesis have been uncovered and reveal new connections to cell-cycle and cell-size control. Ribosome biogenesis has now been clearly linked to disease, particularly to cancer and anemia, and also to aging. A challenge for future studies will be to elucidate further the molecular mechanisms underlying these connections.

Adaptive regulation at the cell surface by N-glycosylation

The association of receptors and solute transporters with components of the endocytic machinery regulates their surface levels, and thereby cellular sensitivity to cytokines, ligands and nutrients in the extracellular environment. Most transmembrane receptors and solute transporters are glycoproteins, and the Asn (N)-linked oligosaccharides (N-glycans) can bind animal lectins, forming multivalent lattices or microdomains that regulate glycoprotein mobility in the plane of membrane. The N-glycan number (sequence-encoded NXS/T) and context-dependent Golgi N-glycan branching cooperate to regulate glycoprotein affinities for the galectin family of lectins. Galectin-3 binding reduces EGF receptor trafficking into clathrin-coated pits and caveolae lipid rafts, decreases ligand-independent receptor activation and promotes alpha5beta1 integrin remodelling in focal adhesions. N-glycan branching in the medial Golgi increases glycan affinity for galectins, and the Golgi pathway is sensitive to uridine diphosphate-N-acetylglucosamine (UDP-GlcNAc) supply, in turn hexosamine pathway metabolites (fructose-6-P, glutamine and acetyl-CoA). Thus, lattice avidity and cellular responsiveness to extracellular cues are regulated in an adaptive manner by metabolism and Golgi modification to glycoproteins. Computational modelling of the hexosamine/Golgi/lattice has provided new insight on cell surface adaptation in cancer and autoimmune disease.