Marc R. Birtwistle

Ligand‐dependent responses of the ErbB signaling network: experimental and modeling analyses

Deregulation of ErbB signaling plays a key role in the progression of multiple human cancers. To help understand ErbB signaling quantitatively, in this work we combine traditional experiments with computational modeling, building a model that describes how stimulation of all four ErbB receptors with epidermal growth factor (EGF) and heregulin (HRG) leads to activation of two critical downstream proteins, extracellular‐signal‐regulated kinase (ERK) and Akt. Model analysis and experimental validation show that (i) ErbB2 overexpression, which occurs in approximately 25% of all breast cancers, transforms transient EGF‐induced signaling into sustained signaling, (ii) HRG‐induced ERK activity is much more robust to the ERK cascade inhibitor U0126 than EGF‐induced ERK activity, and (iii) phosphoinositol‐3 kinase is a major regulator of post‐peak but not pre‐peak EGF‐induced ERK activity. Sensitivity analysis leads to the hypothesis that ERK activation is robust to parameter perturbation at high ligand doses, while Akt activation is not.

Cell fate decisions are specified by the dynamic ERK interactome.

Extracellular signal-regulated kinase (ERK) controls fundamental cellular functions, including cell fate decisions. In PC12, cells shifting ERK activation from transient to sustained induces neuronal differentiation. As ERK associates with both regulators and effectors, we hypothesized that the mechanisms underlying the switch could be revealed by assessing the dynamic changes in ERK-interacting proteins that specifically occur under differentiation conditions. Using quantitative proteomics, we identified 284 ERK-interacting proteins. Upon induction of differentiation, 60 proteins changed their binding to ERK, including many proteins that were not known to participate in differentiation. We functionally characterized a subset, showing that they regulate the pathway at several levels and by different mechanisms, including signal duration, ERK localization, feedback, crosstalk with the Akt pathway and differential interaction and phosphorylation of transcription factors. Integrating these data with a mathematical model confirmed that ERK dynamics and differentiation are regulated by distributed control mechanisms rather than by a single master switch.

Raf Family Kinases: Old Dogs Have Learned New Tricks

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

The Mammalian MAPK/ERK Pathway Exhibits Properties of a Negative Feedback Amplifier

Analysis of ERK pathway circuitry suggests appropriate targets for inhibition, providing a guide for drug development. Biological Circuits Inform Drug Development The mitogen-activated protein kinase (MAPK) pathway involves a three-tiered kinase module, which amplifies the signal. Many cells also have negative feedback loops from the last kinase in the module to various points upstream in the pathway. Sturm et al. showed that, with negative feedback loops, the MAPK module results in a system like that of a negative feedback amplifier (NFA), which is an engineering design that smoothens the output to changes in input and makes a system robust to change. These NFA-like properties may explain why some cells are sensitive to inhibition of the second kinase in the cascade (they lack feedback loops), whereas other cells are resistant to inhibition at this point (their feedback loops are intact). These results also have implications for drug development, because inhibitors that target components that are outside the NFA are more effective at inhibiting the pathway. Three-tiered kinase modules, such as the Raf–MEK (mitogen-activated or extracellular signal–regulated protein kinase kinase)–ERK (extracellular signal–regulated kinase) mitogen-activated protein kinase pathway, are widespread in biology, suggesting that this structure conveys evolutionarily advantageous properties. We show that the three-tiered kinase amplifier module combined with negative feedback recapitulates the design principles of a negative feedback amplifier (NFA), which is used in electronic circuits to confer robustness, output stabilization, and linearization of nonlinear signal amplification. We used mathematical modeling and experimental validation to demonstrate that the ERK pathway has properties of an NFA that (i) converts intrinsic switch-like activation kinetics into graded linear responses, (ii) conveys robustness to changes in rates of reactions within the NFA module, and (iii) stabilizes outputs in response to drug-induced perturbations of the amplifier. These properties determine biological behavior, including activation kinetics and the response to drugs.

Ligand-Specific c-Fos Expression Emerges from the Spatiotemporal Control of ErbB Network Dynamics

Activation of ErbB receptors by epidermal growth factor (EGF) or heregulin (HRG) determines distinct cell-fate decisions, although signals propagate through shared pathways. Using mathematical modeling and experimental approaches, we unravel how HRG and EGF generate distinct, all-or-none responses of the phosphorylated transcription factor c-Fos. In the cytosol, EGF induces transient and HRG induces sustained ERK activation. In the nucleus, however, ERK activity and c-fos mRNA expression are transient for both ligands. Knockdown of dual-specificity phosphatases extends HRG-stimulated nuclear ERK activation, but not c-fos mRNA expression, implying the existence of a HRG-induced repressor of c-fos transcription. Further experiments confirmed that this repressor is mainly induced by HRG, but not EGF, and requires new protein synthesis. We show how a spatially distributed, signaling-transcription cascade robustly discriminates between transient and sustained ERK activities at the c-Fos system level. The proposed control mechanisms are general and operate in different cell types, stimulated by various ligands.

Evaluating Strategies to Normalise Biological Replicates of Western Blot Data

Western blot data are widely used in quantitative applications such as statistical testing and mathematical modelling. To ensure accurate quantitation and comparability between experiments, Western blot replicates must be normalised, but it is unclear how the available methods affect statistical properties of the data. Here we evaluate three commonly used normalisation strategies: (i) by fixed normalisation point or control; (ii) by sum of all data points in a replicate; and (iii) by optimal alignment of the replicates. We consider how these different strategies affect the coefficient of variation (CV) and the results of hypothesis testing with the normalised data. Normalisation by fixed point tends to increase the mean CV of normalised data in a manner that naturally depends on the choice of the normalisation point. Thus, in the context of hypothesis testing, normalisation by fixed point reduces false positives and increases false negatives. Analysis of published experimental data shows that choosing normalisation points with low quantified intensities results in a high normalised data CV and should thus be avoided. Normalisation by sum or by optimal alignment redistributes the raw data uncertainty in a mean-dependent manner, reducing the CV of high intensity points and increasing the CV of low intensity points. This causes the effect of normalisations by sum or optimal alignment on hypothesis testing to depend on the mean of the data tested; for high intensity points, false positives are increased and false negatives are decreased, while for low intensity points, false positives are decreased and false negatives are increased. These results will aid users of Western blotting to choose a suitable normalisation strategy and also understand the implications of this normalisation for subsequent hypothesis testing.

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 spatiotemporal guidance for multiple target proteins, dictating receptor‐specific cellular outcomes. Computational modeling 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. Copyright

Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise

BackgroundCell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses.ResultsWe observe bimodal distributions of extracellular signal-regulated kinase (ERK) responses to epidermal growth factor (EGF) stimulation, which are generally thought to indicate bistable or ultrasensitive signaling behavior in single cells. Surprisingly, we find that a simple MAPK/ERK-cascade model with negative feedback that displays graded, analog ERK responses at a single cell level can explain the experimentally observed bimodality at the cell population level. Model analysis suggests that a conversion of graded input–output responses in single cells to digital responses at the population level is caused by a broad distribution of ERK pathway activation thresholds brought about by cell-to-cell variability in protein expression.ConclusionsOur results show that bimodal signaling response distributions do not necessarily imply digital (ultrasensitive or bistable) single cell signaling, and the interplay between protein expression noise and network topologies can bring about digital population responses from analog single cell dose responses. Thus, cells can retain the benefits of robustness arising from negative feedback, while simultaneously generating population-level on/off responses that are thought to be critical for regulating cell fate decisions.

NFκB and HIF display synergistic behaviour during hypoxic inflammation

The oxygen-sensitive transcription factor hypoxia inducible factor (HIF) is a key regulator of gene expression during adaptation to hypoxia. Crucially, inflamed tissue often displays regions of prominent hypoxia. Recent studies have shown HIF signalling is intricately linked to that of the pro-inflammatory transcription factor nuclear factor kappa B (NFκB) during hypoxic inflammation. We describe the relative temporal contributions of each to hypoxia-induced inflammatory gene expression and investigate the level of crosstalk between the two pathways using a novel Gaussia princeps luciferase (Gluc) reporter system. Under the control of an active promoter, Gluc is expressed and secreted into the cell culture media, where it can be sampled and measured over time. Thus, Gluc constructs under the control of either HIF or NFκB were used to resolve their temporal transcriptional dynamics in response to hypoxia and to cytokine stimuli, respectively. We also investigated the interactions between HIF and NFκB activities using a construct containing the sequence from the promoter of the inflammatory gene cyclooxygenase 2 (COX-2), which includes functionally active binding sites for both HIF and NFκB. Finally, based on our experimental data, we constructed a mathematical model of the binding affinities of HIF and NFκB to their respective response elements to analyse transcriptional crosstalk. Taken together, these data reveal distinct temporal HIF and NFκB transcriptional activities in response to hypoxic inflammation. Furthermore, we demonstrate synergistic activity between these two transcription factors on the regulation of the COX-2 promoter, implicating a co-ordinated role for both HIF and NFκB in the expression of COX-2 in hypoxic inflammation.

Bistability in the Rac1, PAK, and RhoA signaling network drives actin cytoskeleton dynamics and cell motility switches

Summary Dynamic interactions between RhoA and Rac1, members of the Rho small GTPase family, play a vital role in the control of cell migration. Using predictive mathematical modeling, mass spectrometry-based quantitation of network components, and experimental validation in MDA-MB-231 mesenchymal breast cancer cells, we show that a network containing Rac1, RhoA, and PAK family kinases can produce bistable, switch-like responses to a graded PAK inhibition. Using a small chemical inhibitor of PAK, we demonstrate that cellular RhoA and Rac1 activation levels respond in a history-dependent, bistable manner to PAK inhibition. Consequently, we show that downstream signaling, actin dynamics, and cell migration also behave in a bistable fashion, displaying switches and hysteresis in response to PAK inhibition. Our results demonstrate that PAK is a critical component in the Rac1-RhoA inhibitory crosstalk that governs bistable GTPase activity, cell morphology, and cell migration switches.