Stefan Legewie

Systems-level interactions between insulin-EGF networks amplify mitogenic signaling.

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal‐regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin‐induced increase in the phosphatidylinositol‐3,4,5‐triphosphate (PIP3) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin‐induced amplification of mitogenic signaling is abolished by disrupting PIP3‐mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non‐linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.

Effects of sequestration on signal transduction cascades

The building blocks of most signal transduction pathways are pairs of enzymes, such as kinases and phosphatases, that control the activity of protein targets by covalent modification. It has previously been shown [Goldbeter A & Koshland DE (1981) Proc Natl Acad Sci USA78, 6840–6844] that these systems can be highly sensitive to changes in stimuli if their catalysing enzymes are saturated with their target protein substrates. This mechanism, termed zero‐order ultrasensitivity, may set thresholds that filter out subthreshold stimuli. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations. Under these conditions a large fraction of the target protein may be sequestrated by the enzymes. This causes a reduction in ultrasensitivity so that the proposed mechanism is unlikely to account for ultrasensitivity under the conditions present in most in vivo signalling cascades. Furthermore, we show that sequestration changes the dynamics of a covalent modification cycle and may account for signal termination and a sign‐sensitive delay. Finally, we analyse the effect of sequestration on the dynamics of a complex signal transduction cascade: the mitogen‐activated protein kinase (MAPK) cascade with negative feedback. We show that sequestration limits ultrasensitivity in this cascade and may thereby abolish the potential for oscillations induced by negative feedback.

Recurrent design patterns in the feedback regulation of the mammalian signalling network.

Biochemical networks are characterized by recurrent patterns and motifs, but the design principles underlying the dynamics of the mammalian intracellular signalling network remain unclear. We systematically analysed decay rates of 134 signalling proteins and investigated their gene expression profiles in response to stimulation to get insights into transcriptional feedback regulation. We found a clear separation of the signalling pathways into flexible and static parts: for each pathway a subgroup of unstable signal inhibitors is transcriptionally induced upon stimulation, while the other constitutively expressed signalling proteins are long‐lived. Kinetic modelling suggests that this design principle allows for swift feedback regulation and establishes latency phases after signalling, and that it might be an optimal design due to a trade‐off between energy efficiency and flexibility.

Small RNAs Establish Delays and Temporal Thresholds in Gene Expression

Noncoding RNAs are crucial regulators of gene expression in prokaryotes and eukaryotes, but how they affect the dynamics of transcriptional networks remains poorly understood. We analyzed the temporal characteristics of the cyanobacterial iron stress response by mathematical modeling and quantitative experimental analyses and focused on the role of a recently discovered small noncoding RNA, IsrR. We found that IsrR is responsible for a pronounced delay in the accumulation of isiA mRNA encoding the late-phase stress protein, IsiA, and that it ensures a rapid decline in isiA levels once external stress triggers are removed. These kinetic properties allow the system to selectively respond to sustained (as opposed to transient) stimuli and thus establish a temporal threshold, which prevents energetically costly IsiA accumulation under short-term stress conditions. Biological information is frequently encoded in the quantitative aspects of intracellular signals (e.g., amplitude and duration). Our simulations reveal that competitive inhibition and regulated degradation allow intracellular regulatory networks to efficiently discriminate between transient and sustained inputs.

Negative feedback in the bone morphogenetic protein 4 (BMP4) synexpression group governs its dynamic signaling range and canalizes development

What makes embryogenesis a robust and canalized process is an important question in developmental biology. A bone morphogenetic protein (BMP) morphogen gradient plays a key role in embryonic development, and we are beginning to understand how the self-regulating properties of its signaling circuitry ensure robust embryonic patterning. An unexplored question is why the BMP signaling circuit is organized as a modular synexpression group, with a prevalence of feedback inhibitors. Here, we provide evidence from direct experimentation and mathematical modeling that the synexpressed feedback inhibitors BAMBI, SMAD6, and SMAD7 (i) expand the dynamic BMP signaling range essential for proper embryonic patterning and (ii) reduce interindividual phenotypic and molecular variability in Xenopus embryos. Thereby, negative feedback linearizes signaling responses and confers robust patterning, thus promoting canalized development. The presence of negative feedback inhibitors in other growth factor synexpression groups suggests that these properties may constitute a general principle.

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

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

Systems analysis of MAPK signal transduction

For more than a decade, the MAPK (mitogen-activated protein kinase) cascade has been studied using mathematical modelling and quantitative experimentation [1]. The MAPK cascade relays the presence of extracellular stimuli such as growth hormones to the nucleus and controls the expression of hundreds of genes. MAPKs control major cell fate decisions such as proliferation, differentiation and apoptosis, mainly by inducing alterations in gene expression. In this chapter, we discuss how systems biology analysis provides insights into the functioning of this cascade. We show how this pathway assists the cell in responding properly to extracellular cues by filtering out sub-threshold stimuli, while efficiently transmitting physiologically relevant inputs. Several different receptors signal through the MAPK pathway even though they elicit opposite biological responses, thus raising the question of how specificity is achieved in MAPK signalling. Experimental studies revealed that specific biological responses are encoded by quantitative aspects of the MAPK signal such as amplitude or duration. We discuss mechanisms that enable the pathway to generate quantitatively different signals, and also explain how different signals are interpreted by the downstream gene expression machinery.

Quantitative analysis of ultrasensitive responses.

Ultrasensitive responses are common in cellular information transfer because they allow cells to decode extracellular stimuli in an all‐or‐none manner. Biochemical responses are usually analyzed by fitting the Hill equation, and the estimated Hill coefficient is taken as a measure of sensitivity. However, this approach is not appropriate if the response under consideration significantly deviates from the best‐fit Hill equation. In addition, Hill coefficients greater than unity do not necessarily imply ultrasensitive behaviour if basal activation is significant. In order to circumvent these problems we propose a general method for the quantitative analysis of sensitivity, the relative amplification plot, which is based on the response coefficient defined in metabolic control analysis. To quantify sensitivity globally (i.e. over the whole stimulus range) we introduce the integral‐based relative amplification coefficient. Our relative amplification approach can easily be extended to monotonically decreasing, bell‐shaped or nonsaturated responses.

Caspase-8 activity has an essential role in CD95/Fas-mediated MAPK activation

Stimulation of CD95/Fas/APO-1 results in the induction of both apoptotic and non-apoptotic signaling pathways. The processes regulating these two opposing pathways have not been thoroughly elucidated to date. In this study, using quantitative immunoblots, imaging, and mathematical modeling, we addressed the dynamics of the DED proteins of the death-inducing signaling complex (DISC), procaspase-8, and cellular FLICE inhibitory proteins (c-FLIPs) to the onset of CD95-mediated ERK1/2 and p38 mitogen-activated protein kinase (MAPK) activation. We found that CD95 DISC-induced caspase-8 activity is important for the initiation of ERK1/2 and p38 MAPK activation. The long c-FLIP isoform, c-FLIPL, and the short c-FLIP isoform, c-FLIPR, inhibited MAPK induction by blocking caspase-8 processing at the DISC. Furthermore, we built a mathematical model describing CD95 DISC-mediated MAPK activation and apoptosis. The model quantitatively defined the dynamics of DED proteins, procaspase-8, and c-FLIP, which lead to caspase-8 activation and induction of apoptotic and non-apoptotic signaling pathways. In conclusion, the combination of biochemical analysis with mathematical modeling provides evidence for an important role of caspase-8 in CD95-mediated activation of MAPKs, while c-FLIP exerts a regulatory function in this process.

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here, we used a reverse‐engineering approach in an ovarian cancer model to reconstruct KRAS oncogene‐dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT–PCR and western blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions, we analysed growth parameters and transcriptional deregulation in the KRAS‐transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.