Following genotoxic stress, cells activate a complex kinase-based signaling network to arrest the cell cycle and initiate DNA repair. p53-defective tumor cells rewire their checkpoint response and become dependent on the p38/MK2 pathway for survival after DNA damage, despite a functional ATR-Chk1 pathway. We used functional genetics to dissect the contributions of Chk1 and MK2 to checkpoint control. We show that nuclear Chk1 activity is essential to establish a G(2)/M checkpoint, while cytoplasmic MK2 activity is critical for prolonged checkpoint maintenance through a process of posttranscriptional mRNA stabilization. Following DNA damage, the p38/MK2 complex relocalizes from nucleus to cytoplasm where MK2 phosphorylates hnRNPA0, to stabilize Gadd45α mRNA, while p38 phosphorylates and releases the translational inhibitor TIAR. In addition, MK2 phosphorylates PARN, blocking Gadd45α mRNA degradation. Gadd45α functions within a positive feedback loop, sustaining the MK2-dependent cytoplasmic sequestration of Cdc25B/C to block mitotic entry in the presence of unrepaired DNA damage. Our findings demonstrate a critical role for the MK2 pathway in the posttranscriptional regulation of gene expression as part of the DNA damage response in cancer cells.

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Signaling systems are exciting to study precisely because they are some of the most complex and dynamical systems that we know. The cell needs operational freedom and, thus, many motif-domain interactions might not be "hard-wired" through evolution, but instead may be like the Linux operating system, where symbolic links can point to files without duplication.

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 Protein phosphorylation dynamically regulates cellular activities in response to environmental cues. Sequence conservation analysis of recent proteome-wide phosphorylation data revealed that many previously unidentified phosphorylation sites are not well-conserved leading to the proposal that many are non-functional. However, this is based on the assumption that protein phosphorylation modulates protein function through specific position on protein sequence. Based on emerging understanding on phosphoregulation of cellular activities, we argue, with examples, that non-positionally conserved phosphorylation sites can very well be functional. We previously identified phosphorylation events that need not be conserved at same positions across orthologous proteins but are likely maintained by evolutionary conserved signaling networks through orthologous kinases. We found that proteins with such conserved phosphorylation patterns are statistically over-represented with protein- and DNA-binding annotation. Here, we further correlated these proteins with protein-protein interaction data from an independent systematic study and observed they indeed interact frequently with other proteins. Hence, we speculate that non-positionally conserved phosphorylation site could be modulating biomolecular association of phosphorylated proteins possibly through fine-tuning protein's bulk electrostatic charge and through creating binding sites for phospho-binding interaction domains. We, therefore, advocate the development of complementary evolutionary approaches to interpret physiological important sites.

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Signaling events are frequently described in textbooks as linear cascades. However, in reality, input cues are processed by dynamic and context-specific networks, which are assembled from numerous signaling molecules. Diseases, such as cancer, are typically associated with multiple genomic alterations that likely change the structure and dynamics of cellular signaling networks. To assess the impact of such genomic alterations on the structure of signaling networks and on the ability of cells to accurately translate environmental cues into phenotypic changes, we argue studies must be conducted on a network level. Advances in technologies and computational approaches for data integration have permitted network studies of signaling events in both cancer and normal cells. Here we will review recent advances and how they have impacted our view on signaling networks with a specific angle on signal processing in cancer.

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Cells have self-organizing properties that control their behavior in complex tissues. Contact between cells expressing either B-type Eph receptors or their transmembrane ephrin ligands initiates bidirectional signals that regulate cell positioning. However, simultaneously investigating how information is processed in two interacting cell types remains a challenge. We implemented a proteomic strategy to systematically determine cell-specific signaling networks underlying EphB2- and ephrin-B1–controlled cell sorting. Quantitative mass spectrometric analysis of mixed populations of EphB2- and ephrin-B1–expressing cells that were labeled with different isotopes revealed cell-specific tyrosine phosphorylation events. Functional associations between these phosphotyrosine signaling networks and cell sorting were established with small interfering RNA screening. Data-driven network modeling revealed that signaling between mixed EphB2- and ephrin-B1–expressing cells is asymmetric and that the distinct cell types use different tyrosine kinases and targets to process signals induced by cell-cell contact. We provide systems- and cell-specific network models of contact-initiated signaling between two distinct cell types.

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[Editors Choice - Science Signaling]

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The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease progression are crucial for better understanding, detection and intervention. The era of network medicine has begun; however, there are fundamental principles associated with molecular networks that are essential to consider for this field to succeed. Here, we introduce network biology and some of its associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example.

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The explosion of site- and context-specific in vivo phosphorylation events presents a potentially rich source of biological knowledge and calls for novel data analysis and modeling paradigms. Perhaps the most immediate challenge is delineating detected phosphorylation sites to their effector kinases. This is important for (re)constructing transient kinase-substrate interaction networks that are essential for mechanistic understanding of cellular behaviors and therapeutic intervention, but has largely eluded high-throughput protein-interaction studies due to their transient nature and strong dependencies on cellular context. Here, we surveyed some of the computational approaches developed to dissect phosphorylation data detected in systematic proteomic experiments and reviewed some experimental and computational approaches used to map phosphorylation sites to their effector kinases in efforts aimed at reconstructing biological signaling networks.

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Pluripotent stem cells self-renew indefinitely and possess characteristic protein-protein networks that remodel during differentiation. How this occurs is poorly understood. Using quantitative mass spectrometry, we analyzed the (phospho)proteome of human embryonic stem cells (hESCs) during differentiation induced by bone morphogenetic protein (BMP) and removal of hESC growth factors. Of 5222 proteins identified, 1399 were phosphorylated on 3067 residues. Approximately 50% of these phosphosites were regulated within 1 hr of differentiation induction, revealing a complex interplay of phosphorylation networks spanning different signaling pathways and kinase activities. Among the phosphorylated proteins was the pluripotency-associated protein SOX2, which was SUMOylated as a result of phosphorylation. Using the data to predict kinase-substrate relationships, we reconstructed the hESC kinome; CDK1/2 emerged as central in controlling self-renewal and lineage specification. The findings provide new insights into how hESCs exit the pluripotent state and present the hESC (phospho)proteome resource as a complement to existing pluripotency network databases.

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Protein kinases enable cellular information processing. Although numerous human phosphorylation sites and their dynamics have been characterized, the evolutionary history and physiological importance of many signaling events remain unknown. Using target phosphoproteomes determined with a similar experimental and computational pipeline, we investigated the conservation of human phosphorylation events in distantly related model organisms (fly, worm, and yeast). With a sequence-alignment approach, we identified 479 phosphorylation events in 344 human proteins that appear to be positionally conserved over approximately 600 million years of evolution and hence are likely to be involved in fundamental cellular processes. This sequence-alignment analysis suggested that many phosphorylation sites evolve rapidly and therefore do not display strong evolutionary conservation in terms of sequence position in distantly related organisms. Thus, we devised a network-alignment approach to reconstruct conserved kinase-substrate networks, which identified 778 phosphorylation events in 698 human proteins. Both methods identified proteins tightly regulated by phosphorylation as well as signal integration hubs, and both types of phosphoproteins were enriched in proteins encoded by disease-associated genes. We analyzed the cellular functions and structural relationships for these conserved signaling events, noting the incomplete nature of current phosphoproteomes. Assessing phosphorylation conservation at both site and network levels proved useful for exploring both fast-evolving and ancient signaling events. We reveal that multiple complex diseases seem to converge within the conserved networks, suggesting that disease development might rely on common molecular networks.

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[2009: Signaling Breakthroughs of the Year]

[Editorial - Science Signaling]

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John Nash showed that within a complex system, individuals are best off if they make the best decision that they can, taking into account the decisions of the other individuals. Here, we investigate whether similar principles influence the evolution of signaling networks in multicellular animals. Specifically, by analyzing a set of metazoan species we observed a striking negative correlation of genomically encoded tyrosine content with biological complexity (as measured by the number of cell types in each organism). We discuss how this observed tyrosine loss correlates with the expansion of tyrosine kinases in the evolution of the metazoan lineage and how it may relate to the optimization of signaling systems in multicellular animals. We propose that this phenomenon illustrates genome-wide adaptive evolution to accommodate beneficial genetic perturbation.

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[2009: Signaling Breakthroughs of the Year]

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[Editors Choice - Science Signaling]

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[Research Highlight - Nature Reviews Genetics]

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A key role of signal transduction pathways is to control transcriptional programs in the nucleus as a function of signals received by the cell via complex post-translational modification cascades. This determines cell-context specific responses to environmental stimuli. Given the difficulty of quantitating protein concentration and post-translational modifications, signaling pathway studies are still for the most part conducted one interaction at the time. Thus, genome-wide, cell-context specific dissection of signaling pathways is still an open challenge in molecular systems biology. In this manuscript we extend the MINDy algorithm for the identification of posttranslational modulators of transcription factor activity, to produce a first genome-wide map of the interface between signaling and transcriptional regulatory programs in human B cells. We show that the serine-threonine kinase STK38 emerges as the most pleiotropic signaling protein in this cellular context and we biochemically validate this finding by shRNA-mediated silencing of this kinase, followed by gene expression profile analysis. We also extensively validate the inferred interactions using protein-protein interaction databases and the kinase-substrate interaction prediction algorithm NetworKIN.

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Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

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DNA damage checkpoints arrest cell cycle progression to facilitate DNA repair. The ability to survive genotoxic insults depends not only on the initiation of cell cycle checkpoints but also on checkpoint maintenance. While activation of DNA damage checkpoints has been studied extensively, molecular mechanisms involved in sustaining and ultimately inactivating cell cycle checkpoints are largely unknown. Here, we explored feedback mechanisms that control the maintenance and termination of checkpoint function by computationally identifying an evolutionary conserved mitotic phosphorylation network within the DNA damage response. We demonstrate that the non-enzymatic checkpoint adaptor protein 53BP1 is an in vivo target of the cell cycle kinases Cyclin-dependent kinase-1 and Polo-like kinase-1 (Plk1). We show that Plk1 binds 53BP1 during mitosis and that this interaction is required for proper inactivation of the DNA damage checkpoint. 53BP1 mutants that are unable to bind Plk1 fail to restart the cell cycle after ionizing radiation-mediated cell cycle arrest. Importantly, we show that Plk1 also phosphorylates the 53BP1-binding checkpoint kinase Chk2 to inactivate its FHA domain and inhibit its kinase activity in mammalian cells. Thus, a mitotic kinase-mediated negative feedback loop regulates the ATM-Chk2 branch of the DNA damage signaling network by phosphorylating conserved sites in 53BP1 and Chk2 to inactivate checkpoint signaling and control checkpoint duration.

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Cellular signaling networks have evolved to enable swift and accurate responses, even in the face of genetic or environmental perturbation. Thus, genetic screens may not identify all the genes that regulate different biological processes. Moreover, although classical screening approaches have succeeded in providing parts lists of the essential components of signaling networks, they typically do not provide much insight into the hierarchical and functional relations that exist among these components. We describe a high-throughput screen in which we used RNA interference to systematically inhibit two genes simultaneously in 17,724 combinations to identify regulators of Drosophila JUN NH(2)-terminal kinase (JNK). Using both genetic and phosphoproteomics data, we then implemented an integrative network algorithm to construct a JNK phosphorylation network, which provides structural and mechanistic insights into the systems architecture of JNK signaling.

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[News and Views - Nature Biotechnology]

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