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Sample records for signaling protein networking

  1. Text mining for metabolic pathways, signaling cascades, and protein networks.

    PubMed

    Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso

    2005-05-10

    The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks. PMID:15886388

  2. P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

    PubMed

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

    Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

  3. Autophagy signal transduction by ATG proteins: from hierarchies to networks.

    PubMed

    Wesselborg, Sebastian; Stork, Björn

    2015-12-01

    Autophagy represents an intracellular degradation process which is involved in both cellular homeostasis and disease settings. In the last two decades, the molecular machinery governing this process has been characterized in detail. To date, several key factors regulating this intracellular degradation process have been identified. The so-called autophagy-related (ATG) genes and proteins are central to this process. However, several additional molecules contribute to the outcome of an autophagic response. Several review articles describing the molecular process of autophagy have been published in the recent past. In this review article we would like to add the most recent findings to this knowledge, and to give an overview of the network character of the autophagy signaling machinery. PMID:26390974

  4. Protein and Signaling Networks in Vertebrate Photoreceptor Cells

    PubMed Central

    Koch, Karl-Wilhelm; Dell’Orco, Daniele

    2015-01-01

    Vertebrate photoreceptor cells are exquisite light detectors operating under very dim and bright illumination. The photoexcitation and adaptation machinery in photoreceptor cells consists of protein complexes that can form highly ordered supramolecular structures and control the homeostasis and mutual dependence of the secondary messengers cyclic guanosine monophosphate (cGMP) and Ca2+. The visual pigment in rod photoreceptors, the G protein-coupled receptor rhodopsin is organized in tracks of dimers thereby providing a signaling platform for the dynamic scaffolding of the G protein transducin. Illuminated rhodopsin is turned off by phosphorylation catalyzed by rhodopsin kinase (GRK1) under control of Ca2+-recoverin. The GRK1 protein complex partly assembles in lipid raft structures, where shutting off rhodopsin seems to be more effective. Re-synthesis of cGMP is another crucial step in the recovery of the photoresponse after illumination. It is catalyzed by membrane bound sensory guanylate cyclases (GCs) and is regulated by specific neuronal Ca2+-sensor proteins called guanylate cyclase-activating proteins (GCAPs). At least one GC (ROS-GC1) was shown to be part of a multiprotein complex having strong interactions with the cytoskeleton and being controlled in a multimodal Ca2+-dependent fashion. The final target of the cGMP signaling cascade is a cyclic nucleotide-gated (CNG) channel that is a hetero-oligomeric protein located in the plasma membrane and interacting with accessory proteins in highly organized microdomains. We summarize results and interpretations of findings related to the inhomogeneous organization of signaling units in photoreceptor outer segments. PMID:26635520

  5. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    PubMed

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed.

  6. Protein signaling networks from single cell fluctuations and information theory profiling.

    PubMed

    Shin, Young Shik; Remacle, F; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R D; Heath, James R

    2011-05-18

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  7. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks.

    PubMed

    Teschendorff, Andrew E; Banerji, Christopher R S; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-04-28

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology.

  8. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    PubMed Central

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  9. A simple feature construction method for predicting upstream/downstream signal flow in human protein-protein interaction networks

    PubMed Central

    Mei, Suyu; Zhu, Hao

    2015-01-01

    Signaling pathways play important roles in understanding the underlying mechanism of cell growth, cell apoptosis, organismal development and pathways-aberrant diseases. Protein-protein interaction (PPI) networks are commonly-used infrastructure to infer signaling pathways. However, PPI networks generally carry no information of upstream/downstream relationship between interacting proteins, which retards our inferring the signal flow of signaling pathways. In this work, we propose a simple feature construction method to train a SVM (support vector machine) classifier to predict PPI upstream/downstream relations. The domain based asymmetric feature representation naturally embodies domain-domain upstream/downstream relations, providing an unconventional avenue to predict the directionality between two objects. Moreover, we propose a semantically interpretable decision function and a macro bag-level performance metric to satisfy the need of two-instance depiction of an interacting protein pair. Experimental results show that the proposed method achieves satisfactory cross validation performance and independent test performance. Lastly, we use the trained model to predict the PPIs in HPRD, Reactome and IntAct. Some predictions have been validated against recent literature. PMID:26648121

  10. From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry

    PubMed Central

    Li, Xu; Wang, Wenqi; Chen, Junjie

    2015-01-01

    Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, mass spectrometry has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using mass spectrometry approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by mass spectrometry approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans. PMID:25137225

  11. From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry.

    PubMed

    Li, Xu; Wang, Wenqi; Chen, Junjie

    2015-01-01

    Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, MS has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using MS approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by MS approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans. PMID:25137225

  12. Experimental and Computational Analysis of a Large Protein Network That Controls Fat Storage Reveals the Design Principles of a Signaling Network

    PubMed Central

    Al-Anzi, Bader; Zinn, Kai

    2015-01-01

    An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates “small-world” networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein’s position within a module and to the module’s relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model. PMID:26020510

  13. Calcium-Oxidant Signaling Network Regulates AMP-activated Protein Kinase (AMPK) Activation upon Matrix Deprivation*

    PubMed Central

    Sundararaman, Ananthalakshmy; Amirtham, Usha; Rangarajan, Annapoorni

    2016-01-01

    The AMP-activated protein kinase (AMPK) has recently been implicated in anoikis resistance. However, the molecular mechanisms that activate AMPK upon matrix detachment remain unexplored. In this study, we show that AMPK activation is a rapid and sustained phenomenon upon matrix deprivation, whereas re-attachment to the matrix leads to its dephosphorylation and inactivation. Because matrix detachment leads to loss of integrin signaling, we investigated whether integrin signaling negatively regulates AMPK activation. However, modulation of focal adhesion kinase or Src, the major downstream components of integrin signaling, failed to cause a corresponding change in AMPK signaling. Further investigations revealed that the upstream AMPK kinases liver kinase B1 (LKB1) and Ca2+/calmodulin-dependent protein kinase kinase β (CaMKKβ) contribute to AMPK activation upon detachment. In LKB1-deficient cells, we found AMPK activation to be predominantly dependent on CaMKKβ. We observed no change in ATP levels under detached conditions at early time points suggesting that rapid AMPK activation upon detachment was not triggered by energy stress. We demonstrate that matrix deprivation leads to a spike in intracellular calcium as well as oxidant signaling, and both these intracellular messengers contribute to rapid AMPK activation upon detachment. We further show that endoplasmic reticulum calcium release-induced store-operated calcium entry contributes to intracellular calcium increase, leading to reactive oxygen species production, and AMPK activation. We additionally show that the LKB1/CaMKK-AMPK axis and intracellular calcium levels play a critical role in anchorage-independent cancer sphere formation. Thus, the Ca2+/reactive oxygen species-triggered LKB1/CaMKK-AMPK signaling cascade may provide a quick, adaptable switch to promote survival of metastasizing cancer cells. PMID:27226623

  14. CAMK1 phosphoinositide signal-mediated protein sorting and transport network in human hepatocellular carcinoma (HCC) by biocomputation.

    PubMed

    Wang, Lin; Huang, Juxiang; Jiang, Minghu; Chen, Qingchun; Jiang, Zhenfu; Feng, Haitao

    2014-11-01

    We data-analyzed and constructed the high-expression CAMK1 phosphoinositide signal-mediated protein sorting and transport network in human hepatocellular carcinoma (HCC) compared with low-expression (fold change ≥ 2) no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) in GEO data set, using integration of gene regulatory network inference method with gene ontology (GO). Our result showed that CAMK1 transport subnetwork upstream KCNQ3, LCN2, NKX2_5, NUP62, SORT1, STX1A activated CAMK1, and downstream CAMK1-activated AFP, ENAH, KPNA2, SLC4A3; CAMK1 signal subnetwork upstream BRCA1, DKK1, GPSM2, LEF1, NR5A1, NUP62, SORT1, SSTR5, TBL3 activated CAMK1, and downstream CAMK1-activated MAP2K6, SFRP4, SSTR5, TSHB, UBE2C in HCC. We proposed that CAMK1 activated network enhanced endosome to lysosome transport, endosome transport via multivesicular body sorting pathway, Golgi to endosome transport, intracellular protein transmembrane transport, intracellular protein transport, ion transport, mRNA transport, plasma membrane to endosome transport, potassium ion transport, protein transport, vesicle-mediated transport, anion transport, intracellular transport, androgen receptor signaling pathway, cell surface receptor-linked signal transduction, hormone-mediated signaling, induction of apoptosis by extracellular signals, signal transduction by p53 class mediator resulting in transcription of p21 class mediator, signal transduction resulting in induction of apoptosis, phosphoinositide-mediated signaling, Wnt receptor signaling pathway, as a result of inducing phosphoinositide signal-mediated protein sorting, and transport in HCC. Our hypothesis was verified by CAMK1 functional regulation subnetwork containing positive regulation of calcium ion transport via voltage gated calcium channel, cell proliferation, DNA repair, exocytosis, I-kappaB kinase/NF-kappaB cascade, immunoglobulin-mediated immune response, mast cell activation, natural killer cell-mediated cytotoxicity

  15. G-protein-coupled receptor signaling and the EGF network in endocrine systems.

    PubMed

    Hsieh, Minnie; Conti, Marco

    2005-09-01

    The epidermal growth factor (EGF) network is composed of a complex array of growth factors synthesized as precursors and expressed on the cell surface. These latent growth factors are activated by cleavage and shedding from the cell surface and act by binding to various homo- and hetero-dimers of the EGF receptors (ErbBs). Although the exact molecular steps are poorly understood, ligand binding to G-protein-coupled receptors as diverse as the beta-adrenoceptors or the lysophosphatidic acid receptors leads to shedding of EGF growth factors and activation of EGF receptors. Recent observations from the pituitary and in the ovary are providing new insight into the role of this network in endocrine systems.

  16. The Hedgehog Signal Transduction Network

    PubMed Central

    Robbins, David J.; Fei, Dennis Liang; Riobo, Natalia A.

    2013-01-01

    Hedgehog (Hh) proteins regulate the development of a wide range of metazoan embryonic and adult structures, and disruption of Hh signaling pathways results in various human diseases. Here, we provide a comprehensive review of the signaling pathways regulated by Hh, consolidating data from a diverse array of organisms in a variety of scientific disciplines. Similar to the elucidation of many other signaling pathways, our knowledge of Hh signaling developed in a sequential manner centered on its earliest discoveries. Thus, our knowledge of Hh signaling has for the most part focused on elucidating the mechanism by which Hh regulates the Gli family of transcription factors, the so-called “canonical” Hh signaling pathway. However, in the past few years, numerous studies have shown that Hh proteins can also signal through Gli-independent mechanisms collectively referred to as “noncanonical” signaling pathways. Noncanonical Hh signaling is itself subdivided into two distinct signaling modules: (i) those not requiring Smoothened (Smo) and (ii) those downstream of Smo that do not require Gli transcription factors. Thus, Hh signaling is now proposed to occur through a variety of distinct context-dependent signaling modules that have the ability to crosstalk with one another to form an interacting, dynamic Hh signaling network. PMID:23074268

  17. Simulated evolution of signal transduction networks.

    PubMed

    Mobashir, Mohammad; Schraven, Burkhart; Beyer, Tilo

    2012-01-01

    Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.

  18. Retrograde signaling: Organelles go networking.

    PubMed

    Kleine, Tatjana; Leister, Dario

    2016-08-01

    The term retrograde signaling refers to the fact that chloroplasts and mitochondria utilize specific signaling molecules to convey information on their developmental and physiological states to the nucleus and modulate the expression of nuclear genes accordingly. Signals emanating from plastids have been associated with two main networks: 'Biogenic control' is active during early stages of chloroplast development, while 'operational' control functions in response to environmental fluctuations. Early work focused on the former and its major players, the GUN proteins. However, our view of retrograde signaling has since been extended and revised. Elements of several 'operational' signaling circuits have come to light, including metabolites, signaling cascades in the cytosol and transcription factors. Here, we review recent advances in the identification and characterization of retrograde signaling components. We place particular emphasis on the strategies employed to define signaling components, spanning the entire spectrum of genetic screens, metabolite profiling and bioinformatics. This article is part of a Special Issue entitled 'EBEC 2016: 19th European Bioenergetics Conference, Riva del Garda, Italy, July 2-6, 2016', edited by Prof. Paolo Bernardi. PMID:26997501

  19. An Arabidopsis WDR protein coordinates cellular networks involved in light, stress response and hormone signals.

    PubMed

    Chuang, Huey-Wen; Feng, Ji-Huan; Feng, Yung-Lin; Wei, Miam-Ju

    2015-12-01

    The WD-40 repeat (WDR) protein acts as a scaffold for protein interactions in various cellular events. An Arabidopsis WDR protein exhibited sequence similarity with human WDR26, a scaffolding protein implicated in H2O2-induced cell death in neural cells. The AtWDR26 transcript was induced by auxin, abscisic acid (ABA), ethylene (ET), osmostic stress and salinity. The expression of AtWDR26 was regulated by light, and seed germination of the AtWDR26 overexpression (OE) and seedling growth of the T-DNA knock-out (KO) exhibited altered sensitivity to light. Root growth of the OE seedlings increased tolerance to ZnSO4 and NaCl stresses and were hypersensitive to inhibition of osmotic stress. Seedlings of OE and KO altered sensitivities to multiple hormones. Transcriptome analysis of the transgenic plants overexpressing AtWDR26 showed that genes involved in the chloroplast-related metabolism constituted the largest group of the up-regulated genes. AtWDR26 overexpression up-regulated a large number of genes related to defense cellular events including biotic and abiotic stress response. Furthermore, several members of genes functioning in the regulation of Zn homeostasis, and hormone synthesis and perception of auxin and JA were strongly up-regulated in the transgenic plants. Our data provide physiological and transcriptional evidence for AtWDR26 role in hormone, light and abiotic stress cellular events.

  20. Proteomic Analysis of Proteins Surrounding Occludin and Claudin-4 Reveals Their Proximity to Signaling and Trafficking Networks

    PubMed Central

    Fredriksson, Karin; Van Itallie, Christina M.; Aponte, Angel; Gucek, Marjan; Tietgens, Amber J.; Anderson, James M.

    2015-01-01

    Tight junctions are complex membrane structures that regulate paracellular movement of material across epithelia and play a role in cell polarity, signaling and cytoskeletal organization. In order to expand knowledge of the tight junction proteome, we used biotin ligase (BioID) fused to occludin and claudin-4 to biotinylate their proximal proteins in cultured MDCK II epithelial cells. We then purified the biotinylated proteins on streptavidin resin and identified them by mass spectrometry. Proteins were ranked by relative abundance of recovery by mass spectrometry, placed in functional categories, and compared not only among the N- and C- termini of occludin and the N-terminus of claudin-4, but also with our published inventory of proteins proximal to the adherens junction protein E-cadherin and the tight junction protein ZO-1. When proteomic results were analyzed, the relative distribution among functional categories was similar between occludin and claudin-4 proximal proteins. Apart from already known tight junction- proteins, occludin and claudin-4 proximal proteins were enriched in signaling and trafficking proteins, especially endocytic trafficking proteins. However there were significant differences in the specific proteins comprising the functional categories near each of the tagging proteins, revealing spatial compartmentalization within the junction complex. Taken together, these results expand the inventory of known and unknown proteins at the tight junction to inform future studies of the organization and physiology of this complex structure. PMID:25789658

  1. Aroclor 1254, a developmental neurotoxicant, alters energy metabolism- and intracellular signaling-associated protein networks in rat cerebellum and hippocampus

    SciTech Connect

    Kodavanti, Prasada Rao S.; Osorio, Cristina; Royland, Joyce E.; Ramabhadran, Ram; Alzate, Oscar

    2011-11-15

    The vast literature on the mode of action of polychlorinated biphenyls (PCBs) indicates that PCBs are a unique model for understanding the mechanisms of toxicity of environmental mixtures of persistent chemicals. PCBs have been shown to adversely affect psychomotor function and learning and memory in humans. Although the molecular mechanisms for PCB effects are unclear, several studies indicate that the disruption of Ca{sup 2+}-mediated signal transduction plays significant roles in PCB-induced developmental neurotoxicity. Culminating events in signal transduction pathways include the regulation of gene and protein expression, which affects the growth and function of the nervous system. Our previous studies showed changes in gene expression related to signal transduction and neuronal growth. In this study, protein expression following developmental exposure to PCB is examined. Pregnant rats (Long Evans) were dosed with 0.0 or 6.0 mg/kg/day of Aroclor-1254 from gestation day 6 through postnatal day (PND) 21, and the cerebellum and hippocampus from PND14 animals were analyzed to determine Aroclor 1254-induced differential protein expression. Two proteins were found to be differentially expressed in the cerebellum following PCB exposure while 18 proteins were differentially expressed in the hippocampus. These proteins are related to energy metabolism in mitochondria (ATP synthase, sub unit {beta} (ATP5B), creatine kinase, and malate dehydrogenase), calcium signaling (voltage-dependent anion-selective channel protein 1 (VDAC1) and ryanodine receptor type II (RyR2)), and growth of the nervous system (dihydropyrimidinase-related protein 4 (DPYSL4), valosin-containing protein (VCP)). Results suggest that Aroclor 1254-like persistent chemicals may alter energy metabolism and intracellular signaling, which might result in developmental neurotoxicity. -- Highlights: Black-Right-Pointing-Pointer We performed brain proteomic analysis of rats exposed to the neurotoxicant

  2. Modelling protein functional domains in signal transduction using Maude

    NASA Technical Reports Server (NTRS)

    Sriram, M. G.

    2003-01-01

    Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

  3. Multi-Tasking Role of the Mechanosensing Protein Ankrd2 in the Signaling Network of Striated Muscle

    PubMed Central

    Mittempergher, Lorenza; Campanaro, Stefano; Martinelli, Valentina C.; Mouly, Vincent; Valle, Giorgio; Kojic, Snezana; Faulkner, Georgine

    2011-01-01

    Background Ankrd2 (also known as Arpp) together with Ankrd1/CARP and DARP are members of the MARP mechanosensing proteins that form a complex with titin (N2A)/calpain 3 protease/myopalladin. In muscle, Ankrd2 is located in the I-band of the sarcomere and moves to the nucleus of adjacent myofibers on muscle injury. In myoblasts it is predominantly in the nucleus and on differentiation shifts from the nucleus to the cytoplasm. In agreement with its role as a sensor it interacts both with sarcomeric proteins and transcription factors. Methodology/Principal Findings Expression profiling of endogenous Ankrd2 silenced in human myotubes was undertaken to elucidate its role as an intermediary in cell signaling pathways. Silencing Ankrd2 expression altered the expression of genes involved in both intercellular communication (cytokine-cytokine receptor interaction, endocytosis, focal adhesion, tight junction, gap junction and regulation of the actin cytoskeleton) and intracellular communication (calcium, insulin, MAPK, p53, TGF-β and Wnt signaling). The significance of Ankrd2 in cell signaling was strengthened by the fact that we were able to show for the first time that Nkx2.5 and p53 are upstream effectors of the Ankrd2 gene and that Ankrd1/CARP, another MARP member, can modulate the transcriptional ability of MyoD on the Ankrd2 promoter. Another novel finding was the interaction between Ankrd2 and proteins with PDZ and SH3 domains, further supporting its role in signaling. It is noteworthy that we demonstrated that transcription factors PAX6, LHX2, NFIL3 and MECP2, were able to bind both the Ankrd2 protein and its promoter indicating the presence of a regulatory feedback loop mechanism. Conclusions/Significance In conclusion we demonstrate that Ankrd2 is a potent regulator in muscle cells affecting a multitude of pathways and processes. PMID:22016770

  4. Signalling networks associated with urokinase-type plasminogen activator (uPA) and its inhibitor PAI-1 in breast cancer tissues: new insights from protein microarray analysis.

    PubMed

    Wolff, Claudia; Malinowsky, Katharina; Berg, Daniela; Schragner, Kerstin; Schuster, Tibor; Walch, Axel; Bronger, Holger; Höfler, Heinz; Becker, Karl-Friedrich

    2011-01-01

    The urokinase-type plasminogen activator (uPA) and the main uPA inhibitor PAI-1 play important roles in cell migration and invasion in both physiological and pathological contexts. Both factors are clinically applicable predictive markers in node-negative breast cancer patients that are used to stratify patients for adjuvant chemotherapy. In addition to their classical functions in plasmin regulation, both factors are key components in cancer-related cell signalling. Such signalling cascades are well described in cell culture systems, but a better understanding of uPA- and PAI-1-associated signalling networks in clinical tissues is needed. We examined the expression of uPA, PAI-1, and 21 signalling molecules in 201 primary breast cancer tissues using protein microarrays. Expression of uPA was significantly correlated with the expression of ERK and Stat3, while expression of PAI-1 was correlated with the uPA receptor and Akt activation, presumably via integrin and HER-receptor signalling. Analysis of uPA expression did not reveal any significant correlation with staging, grading or age of the patients. The PAI-1 expression was correlated with nodal stage. Network monitoring for uPA and PAI-1 in breast cancer reveals interactions with main signalling cascades and extends the findings from cell culture experiments. Our results reveal possible mechanisms underlying cancer development.

  5. SIGNALING NETWORKS IN PALATE DEVELOPMENT

    PubMed Central

    Lane, Jamie; Kaartinen, Vesa

    2014-01-01

    Palatogenesis, the formation of the palate, is a dynamic process that is regulated by a complex series of context-dependent morphogenetic signaling events. Many genes involved in palatogenesis have been discovered through the use of genetically-manipulated mouse models as well as from human genetic studies, but the roles of these genes and their products in signaling networks regulating palatogenesis are still poorly known. In this review, we give a brief overview on palatogenesis and introduce key signaling cascades leading to formation of the intact palate. Moreover, we review conceptual differences between pathway biology and network biology and discuss how some of the recent technological advances in conjunction with mouse genetic models have contributed to our understanding of signaling networks regulating palate growth and fusion. PMID:24644145

  6. A Parkinson's disease gene regulatory network identifies the signaling protein RGS2 as a modulator of LRRK2 activity and neuronal toxicity

    PubMed Central

    Dusonchet, Julien; Li, Hu; Guillily, Maria; Liu, Min; Stafa, Klodjan; Derada Troletti, Claudio; Boon, Joon Y.; Saha, Shamol; Glauser, Liliane; Mamais, Adamantios; Citro, Allison; Youmans, Katherine L.; Liu, LiQun; Schneider, Bernard L.; Aebischer, Patrick; Yue, Zhenyu; Bandopadhyay, Rina; Glicksman, Marcie A.; Moore, Darren J.; Collins, James J.; Wolozin, Benjamin

    2014-01-01

    Mutations in LRRK2 are one of the primary genetic causes of Parkinson's disease (PD). LRRK2 contains a kinase and a GTPase domain, and familial PD mutations affect both enzymatic activities. However, the signaling mechanisms regulating LRRK2 and the pathogenic effects of familial mutations remain unknown. Identifying the signaling proteins that regulate LRRK2 function and toxicity remains a critical goal for the development of effective therapeutic strategies. In this study, we apply systems biology tools to human PD brain and blood transcriptomes to reverse-engineer a LRRK2-centered gene regulatory network. This network identifies several putative master regulators of LRRK2 function. In particular, the signaling gene RGS2, which encodes for a GTPase-activating protein (GAP), is a key regulatory hub connecting the familial PD-associated genes DJ-1 and PINK1 with LRRK2 in the network. RGS2 expression levels are reduced in the striata of LRRK2 and sporadic PD patients. We identify RGS2 as a novel interacting partner of LRRK2 in vivo. RGS2 regulates both the GTPase and kinase activities of LRRK2. We show in mammalian neurons that RGS2 regulates LRRK2 function in the control of neuronal process length. RGS2 is also protective against neuronal toxicity of the most prevalent mutation in LRRK2, G2019S. We find that RGS2 regulates LRRK2 function and neuronal toxicity through its effects on kinase activity and independently of GTPase activity, which reveals a novel mode of action for GAP proteins. This work identifies RGS2 as a promising target for interfering with neurodegeneration due to LRRK2 mutations in PD patients. PMID:24794857

  7. Hypothesis generation in signaling networks.

    PubMed

    Ruths, Derek A; Nakhleh, Luay; Iyengar, M Sriram; Reddy, Shrikanth A G; Ram, Prahlad T

    2006-11-01

    Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.

  8. How do oncoprotein mutations rewire protein-protein interaction networks?

    PubMed

    Bowler, Emily H; Wang, Zhenghe; Ewing, Rob M

    2015-01-01

    The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein-protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein-protein interaction networks and drive the cancer phenotype. PMID:26325016

  9. Master Regulators in Plant Glucose Signaling Networks

    PubMed Central

    Sheen, Jen

    2014-01-01

    The daily life of photosynthetic plants revolves around sugar production, transport, storage and utilization, and the complex sugar metabolic and signaling networks integrate internal regulators and environmental cues to govern and sustain plant growth and survival. Although diverse sugar signals have emerged as pivotal regulators from embryogenesis to senescence, glucose is the most ancient and conserved regulatory signal that controls gene and protein expression, cell-cycle progression, central and secondary metabolism, as well as growth and developmental programs. Glucose signals are perceived and transduced by two principal mechanisms: direct sensing through glucose sensors and indirect sensing via a variety of energy and metabolite sensors. This review focuses on the comparative and functional analyses of three glucose-modulated master regulators in Arabidopsis thaliana, the hexokinase1 (HXK1) glucose sensor, the energy sensor kinases KIN10/KIN11 inactivated by glucose, and the glucose-activated target of rapamycin (TOR) kinase. These regulators are evolutionarily conserved, but have evolved universal and unique regulatory wiring and functions in plants and animals. They form protein complexes with multiple partners as regulators or effectors to serve distinct functions in different subcellular locales and organs, and play integrative and complementary roles from cellular signaling and metabolism to development in the plant glucose signaling networks. PMID:25530701

  10. Calcium/calmodulin-dependent protein kinase II regulates Caenorhabditis elegans locomotion in concert with a G(o)/G(q) signaling network.

    PubMed Central

    Robatzek, M; Thomas, J H

    2000-01-01

    Caenorhabditis elegans locomotion is a complex behavior generated by a defined set of motor neurons and interneurons. Genetic analysis shows that UNC-43, the C. elegans Ca(2+)/calmodulin protein kinase II (CaMKII), controls locomotion rate. Elevated UNC-43 activity, from a gain-of-function mutation, causes severely lethargic locomotion, presumably by inappropriate phosphorylation of targets. In a genetic screen for suppressors of this phenotype, we identified multiple alleles of four genes in a G(o)/G(q) G-protein signaling network, which has been shown to regulate synaptic activity via diacylglycerol. Mutations in goa-1, dgk-1, eat-16, or eat-11 strongly or completely suppressed unc-43(gf) lethargy, but affected other mutants with reduced locomotion only weakly. We conclude that CaMKII and G(o)/G(q) pathways act in concert to regulate synaptic activity, perhaps through a direct interaction between CaMKII and G(o). PMID:11063685

  11. Protein interaction networks from literature mining

    NASA Astrophysics Data System (ADS)

    Ihara, Sigeo

    2005-03-01

    The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

  12. Evolution of SH2 domains and phosphotyrosine signalling networks

    PubMed Central

    Liu, Bernard A.; Nash, Piers D.

    2012-01-01

    Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

  13. Regulators of G-protein-signaling proteins: negative modulators of G-protein-coupled receptor signaling.

    PubMed

    Woodard, Geoffrey E; Jardín, Isaac; Berna-Erro, A; Salido, Gines M; Rosado, Juan A

    2015-01-01

    Regulators of G-protein-signaling (RGS) proteins are a category of intracellular proteins that have an inhibitory effect on the intracellular signaling produced by G-protein-coupled receptors (GPCRs). RGS along with RGS-like proteins switch on through direct contact G-alpha subunits providing a variety of intracellular functions through intracellular signaling. RGS proteins have a common RGS domain that binds to G alpha. RGS proteins accelerate GTPase and thus enhance guanosine triphosphate hydrolysis through the alpha subunit of heterotrimeric G proteins. As a result, they inactivate the G protein and quickly turn off GPCR signaling thus terminating the resulting downstream signals. Activity and subcellular localization of RGS proteins can be changed through covalent molecular changes to the enzyme, differential gene splicing, and processing of the protein. Other roles of RGS proteins have shown them to not be solely committed to being inhibitors but behave more as modulators and integrators of signaling. RGS proteins modulate the duration and kinetics of slow calcium oscillations and rapid phototransduction and ion signaling events. In other cases, RGS proteins integrate G proteins with signaling pathways linked to such diverse cellular responses as cell growth and differentiation, cell motility, and intracellular trafficking. Human and animal studies have revealed that RGS proteins play a vital role in physiology and can be ideal targets for diseases such as those related to addiction where receptor signaling seems continuously switched on.

  14. DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

    SciTech Connect

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Complex networks appear in biology on many different levels: (1) All biochemical reactions taking place in a single cell constitute its metabolic network, where nodes are individual metabolites, and edges are metabolic reactions converting them to each other. (2) Virtually every one of these reactions is catalyzed by an enzyme and the specificity of this catalytic function is ensured by the key and lock principle of its physical interaction with the substrate. Often the functional enzyme is formed by several mutually interacting proteins. Thus the structure of the metabolic network is shaped by the network of physical interactions of cell's proteins with their substrates and each other. (3) The abundance and the level of activity of each of the proteins in the physical interaction network in turn is controlled by the regulatory network of the cell. Such regulatory network includes all of the multiple mechanisms in which proteins in the cell control each other including transcriptional and translational regulation, regulation of mRNA editing and its transport out of the nucleus, specific targeting of individual proteins for degradation, modification of their activity e.g. by phosphorylation/dephosphorylation or allosteric regulation, etc. To get some idea about the complexity and interconnectedness of protein-protein regulations in baker's yeast Saccharomyces Cerevisiae in Fig. 1 we show a part of the regulatory network corresponding to positive or negative regulations that regulatory proteins exert on each other. (4) On yet higher level individual cells of a multicellular organism exchange signals with each other. This gives rise to several new networks such as e.g. nervous, hormonal, and immune systems of animals. The intercellular signaling network stages the development of a multicellular organism from the fertilized egg. (5) Finally, on the grandest scale, the interactions between individual species in ecosystems determine their food webs. An interesting

  15. Optimal Prediction by Cellular Signaling Networks

    NASA Astrophysics Data System (ADS)

    Becker, Nils B.; Mugler, Andrew; ten Wolde, Pieter Rein

    2015-12-01

    Living cells can enhance their fitness by anticipating environmental change. We study how accurately linear signaling networks in cells can predict future signals. We find that maximal predictive power results from a combination of input-noise suppression, linear extrapolation, and selective readout of correlated past signal values. Single-layer networks generate exponential response kernels, which suffice to predict Markovian signals optimally. Multilayer networks allow oscillatory kernels that can optimally predict non-Markovian signals. At low noise, these kernels exploit the signal derivative for extrapolation, while at high noise, they capitalize on signal values in the past that are strongly correlated with the future signal. We show how the common motifs of negative feedback and incoherent feed-forward can implement these optimal response functions. Simulations reveal that E. coli can reliably predict concentration changes for chemotaxis, and that the integration time of its response kernel arises from a trade-off between rapid response and noise suppression.

  16. SIMULATING BIOCHEMICAL SIGNALING NETWORKS IN COMPLEX MOVING GEOMETRIES.

    PubMed

    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C

    2010-01-01

    Signaling networks regulate cellular responses to environmental stimuli through cascades of protein interactions. External signals can trigger cells to polarize and move in a specific direction. During migration, spatially localized activity of proteins is maintained. To investigate the effects of morphological changes on intracellular signaling, we developed a numerical scheme consisting of a cut cell finite volume spatial discretization coupled with level set methods to simulate the resulting advection-reaction-diffusion system. We then apply the method to several biochemical reaction networks in changing geometries. We found that a Turing instability can develop exclusively by cell deformations that maintain constant area. For a Turing system with a geometry-dependent single or double peak solution, simulations in a dynamically changing geometry suggest that a single peak solution is the only stable one, independent of the oscillation frequency. The method is also applied to a model of a signaling network in a migrating fibroblast. PMID:24086102

  17. mTOR signaling in protein homeostasis

    PubMed Central

    Conn, Crystal S

    2011-01-01

    A proper balance between synthesis, maturation and degradation of cellular proteins is crucial for cells to maintain physiological functions. The costly process of protein synthesis is tightly coupled to energy status and nutrient levels by the mammalian target of rapamycin (mTOR), whereas the quality of newly synthesized polypeptides is largely maintained by molecular chaperones and the ubiquitin-proteasome system. There is a wealth of evidence indicating close ties between the nutrient signaling pathway and the intracellular stress response. Dysregulation of both systems has been implicated in aging and age-associated pathologies. In this review, we describe molecular mechanisms underlying the connection between mTOR and the chaperone network and discuss the importance of their functional interaction in growth and aging. PMID:21555915

  18. Community detection by signaling on complex networks

    NASA Astrophysics Data System (ADS)

    Hu, Yanqing; Li, Menghui; Zhang, Peng; Fan, Ying; di, Zengru

    2008-07-01

    Based on a signaling process of complex networks, a method for identification of community structure is proposed. For a network with n nodes, every node is assumed to be a system which can send, receive, and record signals. Each node is taken as the initial signal source to excite the whole network one time. Then the source node is associated with an n -dimensional vector which records the effects of the signaling process. By this process, the topological relationship of nodes on the network could be transferred into a geometrical structure of vectors in n -dimensional Euclidean space. Then the best partition of groups is determined by F statistics and the final community structure is given by the K -means clustering method. This method can detect community structure both in unweighted and weighted networks. It has been applied to ad hoc networks and some real networks such as the Zachary karate club network and football team network. The results indicate that the algorithm based on the signaling process works well.

  19. Protein contact network topology: a natural language for allostery.

    PubMed

    Di Paola, Luisa; Giuliani, Alessandro

    2015-04-01

    Protein molecules work as a whole, so that any local perturbation may resonate on the entire structure: allostery deals with this general property of protein molecules. It is worth noting a perturbation does not necessarily involve a conformational change but, more generally, it travels across the structure as an 'energy signal'. The atomic interactions within the network provide the structural support for this 'signaling highway'. Network descriptors, capturing network signaling efficiency, explain allostery in terms of signal transmission. In this review we will survey the key applications of graph theory to protein allostery. The complex network approach introduces a new perspective in biochemistry; as for applications, the development of new drugs relying on allosteric effects (allo-network drugs) represents a promising avenue of contact network formalism.

  20. A Network of Mitogen-Activated Protein Kinases Links G Protein-Coupled Receptors to the c-jun Promoter: a Role for c-Jun NH2-Terminal Kinase, p38s, and Extracellular Signal-Regulated Kinase 5

    PubMed Central

    Marinissen, Maria Julia; Chiariello, Mario; Pallante, Michael; Gutkind, J. Silvio

    1999-01-01

    The expression of the c-jun proto-oncogene is rapidly induced in response to mitogens acting on a large variety of cell surface receptors. The resulting functional activity of c-Jun proteins appears to be critical for cell proliferation. Recently, we have shown that a large family of G protein-coupled receptors (GPCRs), represented by the m1 muscarinic receptor, can initiate intracellular signaling cascades that result in the activation of mitogen-activated protein kinases (MAPK) and c-Jun NH2-terminal kinases (JNK) and that the activation of JNK but not of MAPK correlated with a remarkable increase in the expression of c-jun mRNA. Subsequently, however, we obtained evidence that GPCRs can potently stimulate the activity of the c-jun promoter through MEF2 transcription factors, which do not act downstream from JNK. In view of these observations, we set out to investigate further the nature of the signaling pathway linking GPCRs to the c-jun promoter. Utilizing NIH 3T3 cells, we found that GPCRs can activate the c-jun promoter in a JNK-independent manner. Additionally, we demonstrated that these GPCRs can elevate the activity of novel members of the MAPK family, including ERK5, p38α, p38γ, and p38δ, and that the activation of certain kinases acting downstream from MEK5 (ERK5) and MKK6 (p38α and p38γ) is necessary to fully activate the c-jun promoter. Moreover, in addition to JNK, ERK5, p38α, and p38γ were found to stimulate the c-jun promoter by acting on distinct responsive elements. Taken together, these results suggest that the pathway linking GPCRs to the c-jun promoter involves the integration of numerous signals transduced by a highly complex network of MAPK, rather than resulting from the stimulation of a single linear protein kinase cascade. Furthermore, our findings suggest that each signaling pathway affects one or more regulatory elements on the c-jun promoter and that the transcriptional response most likely results from the temporal integration

  1. The protein folding network

    NASA Astrophysics Data System (ADS)

    Rao, Francesco; Caflisch, Amedeo

    2004-03-01

    Networks are everywhere. The conformation space of a 20-residue antiparallel beta-sheet peptide [1], sampled by molecular dynamics simulations, is mapped to a network. Conformations are nodes of the network, and the transitions between them are links. As previously found for the World-Wide Web as well as for social and biological networks , the conformation space contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the network shows a hierarchical modularity [2] which is consistent with the funnel mechanism of folding [3] and is not observed for a random heteropolymer lacking a native state. Here we show that the conformation space network describes the free energy landscape without requiring projections into arbitrarily chosen reaction coordinates. The network analysis provides a basis for understanding the heterogeneity of the folding transition state and the existence of multiple pathways. [1] P. Ferrara and A. Caflisch, Folding simulations of a three-stranded antiparallel beta-sheet peptide, PNAS 97, 10780-10785 (2000). [2] Ravasz, E. and Barabási, A. L. Hierarchical organization in complex networks. Phys. Rev. E 67, 026112 (2003). [3] Dill, K. and Chan, H From Levinthal to pathways to funnels. Nature Struct. Biol. 4, 10-19 (1997)

  2. Calcium/calmodulin-mediated signal network in plants

    NASA Technical Reports Server (NTRS)

    Yang, Tianbao; Poovaiah, B. W.

    2003-01-01

    Various extracellular stimuli elicit specific calcium signatures that can be recognized by different calcium sensors. Calmodulin, the predominant calcium receptor, is one of the best-characterized calcium sensors in eukaryotes. In recent years, completion of the Arabidopsis genome project and advances in functional genomics have helped to identify and characterize numerous calmodulin-binding proteins in plants. There are some similarities in Ca(2+)/calmodulin-mediated signaling in plants and animals. However, plants possess multiple calmodulin genes and many calmodulin target proteins, including unique protein kinases and transcription factors. Some of these proteins are likely to act as "hubs" during calcium signal transduction. Hence, a better understanding of the function of these calmodulin target proteins should help in deciphering the Ca(2+)/calmodulin-mediated signal network and its role in plant growth, development and response to environmental stimuli.

  3. Synthetic biology with surgical precision: targeted reengineering of signaling proteins.

    PubMed

    Gurevich, Vsevolod V; Gurevich, Eugenia V

    2012-10-01

    The complexity of living systems exceeds everything else studied by natural sciences. Sophisticated networks of intimately intertwined signaling pathways coordinate cellular functions. Clear understanding how the integration of multiple inputs produces coherent behavior is one of the major challenges of cell biology. Integration via perfectly timed highly regulated protein-protein interactions and precise targeting of the "output" proteins to particular substrates is emerging as a common theme of signaling regulation. This often involves specialized scaffolding proteins, whose key function is to ensure that correct partners come together in an appropriate place at the right time. Defective or faulty signaling underlies many congenital and acquired human disorders. Several pioneering studies showed that ectopic expression of existing proteins or their elements can restore functions destroyed by mutations or normalize the signaling pushed out of balance by disease and/or current small molecule-based therapy. Several recent studies show that proteins with new functional modalities can be generated by mixing and matching existing domains, or via functional recalibration and fine-tuning of existing proteins by precisely targeted mutations. Using arrestins as an example, we describe how manipulation of individual functions yields signaling-biased proteins. Creative protein redesign generates novel tools valuable for unraveling the intricacies of cell biology. Engineered proteins with specific functional changes also have huge therapeutic potential in disorders associated with inherited or acquired signaling errors. PMID:22664341

  4. Controlling allosteric networks in proteins

    NASA Astrophysics Data System (ADS)

    Dokholyan, Nikolay

    2013-03-01

    We present a novel methodology based on graph theory and discrete molecular dynamics simulations for delineating allosteric pathways in proteins. We use this methodology to uncover the structural mechanisms responsible for coupling of distal sites on proteins and utilize it for allosteric modulation of proteins. We will present examples where inference of allosteric networks and its rewiring allows us to ``rescue'' cystic fibrosis transmembrane conductance regulator (CFTR), a protein associated with fatal genetic disease cystic fibrosis. We also use our methodology to control protein function allosterically. We design a novel protein domain that can be inserted into identified allosteric site of target protein. Using a drug that binds to our domain, we alter the function of the target protein. We successfully tested this methodology in vitro, in living cells and in zebrafish. We further demonstrate transferability of our allosteric modulation methodology to other systems and extend it to become ligh-activatable.

  5. The nuclear retention signal of HPV16 L2 protein is essential for incoming viral genome to transverse the trans-Golgi network

    SciTech Connect

    DiGiuseppe, Stephen; Bienkowska-Haba, Malgorzata; Hilbig, Lydia; Sapp, Martin

    2014-06-15

    The Human papillomavirus (HPV) capsid is composed of the major and minor capsid proteins, L1 and L2, respectively. Infectious entry requires a complex series of conformational changes in both proteins that lead to uptake and allow uncoating to occur. During entry, the capsid is disassembled and host cyclophilins dissociate L1 protein from the L2/DNA complex. Herein, we describe a mutant HPV16 L2 protein (HPV16 L2-R302/5A) that traffics pseudogenome to the trans-Golgi network (TGN) but fails to egress. Our data provide further evidence that HPV16 traffics through the TGN and demonstrates that L2 is essential for TGN egress. Furthermore, we show that cyclophilin activity is required for the L2/DNA complex to be transported to the TGN which is accompanied by a reduced L1 protein levels. - Highlights: • mNLS mutant HPV16 L2 protein traffics pseudogenome to the TGN but fails to egress. • Cyclophilin activity is required for trafficking of the L2/DNA complex to the TGN. • Majority of L1 protein is shed from the L2/DNA complex prior to reaching the TGN.

  6. Multifractal characterization of protein contact networks

    NASA Astrophysics Data System (ADS)

    Maiorino, Enrico; Livi, Lorenzo; Giuliani, Alessandro; Sadeghian, Alireza; Rizzi, Antonello

    2015-06-01

    The multifractal detrended fluctuation analysis of time series is able to reveal the presence of long-range correlations and, at the same time, to characterize the self-similarity of the series. The rich information derivable from the characteristic exponents and the multifractal spectrum can be further analyzed to discover important insights into the underlying dynamical process. In this paper, we employ multifractal analysis techniques in the study of protein contact networks. To this end, initially a network is mapped to three different time series, each of which is generated by a stationary unbiased random walk. To capture the peculiarities of the networks at different levels, we accordingly consider three observables at each vertex: the degree, the clustering coefficient, and the closeness centrality. To compare the results with suitable references, we consider also instances of three well-known network models and two typical time series with pure monofractal and multifractal properties. The first result of notable interest is that time series associated to protein contact networks exhibit long-range correlations (strong persistence), which are consistent with signals in-between the typical monofractal and multifractal behavior. Successively, a suitable embedding of the multifractal spectra allows to focus on ensemble properties, which in turn gives us the possibility to make further observations regarding the considered networks. In particular, we highlight the different role that small and large fluctuations of the considered observables play in the characterization of the network topology.

  7. Biased Gs versus Gq proteins and β-arrestin signaling in the NK1 receptor determined by interactions in the water hydrogen bond network.

    PubMed

    Valentin-Hansen, Louise; Frimurer, Thomas M; Mokrosinski, Jacek; Holliday, Nicholas D; Schwartz, Thue W

    2015-10-01

    X-ray structures, molecular dynamics simulations, and mutational analysis have previously indicated that an extended water hydrogen bond network between trans-membranes I-III, VI, and VII constitutes an allosteric interface essential for stabilizing different active and inactive helical constellations during the seven-trans-membrane receptor activation. The neurokinin-1 receptor signals efficiently through Gq, Gs, and β-arrestin when stimulated by substance P, but it lacks any sign of constitutive activity. In the water hydrogen bond network the neurokinin-1 has a unique Glu residue instead of the highly conserved AspII:10 (2.50). Here, we find that this GluII:10 occupies the space of a putative allosteric modulating Na(+) ion and makes direct inter-helical interactions in particular with SerIII:15 (3.39) and AsnVII:16 (7.49) of the NPXXY motif. Mutational changes in the interface between GluII:10 and AsnVII:16 created receptors that selectively signaled through the following: 1) Gq only; 2) β-arrestin only; and 3) Gq and β-arrestin but not through Gs. Interestingly, increased constitutive Gs but not Gq signaling was observed by Ala substitution of four out of the six core polar residues of the network, in particular SerIII:15. Three residues were essential for all three signaling pathways, i.e. the water-gating micro-switch residues TrpVI:13 (6.48) of the CWXP motif and TyrVII:20 (7.53) of the NPXXY motif plus the totally conserved AsnI:18 (1.50) stabilizing the kink in trans-membrane VII. It is concluded that the interface between position II:10 (2.50), III:15 (3.39), and VII:16 (7.49) in the center of the water hydrogen bond network constitutes a focal point for fine-tuning seven trans-membrane receptor conformations activating different signal transduction pathways.

  8. Sensory properties of the PII signalling protein family.

    PubMed

    Forchhammer, Karl; Lüddecke, Jan

    2016-02-01

    PII signalling proteins constitute one of the largest families of signalling proteins in nature. An even larger superfamily of trimeric sensory proteins with the same architectural principle as PII proteins appears in protein structure databases. Large surface-exposed flexible loops protrude from the intersubunit faces, where effector molecules are bound that tune the conformation of the loops. Via this mechanism, PII proteins control target proteins in response to cellular ATP/ADP levels and the 2-oxoglutarate status, thereby coordinating the cellular carbon/nitrogen balance. The antagonistic (ATP versus ADP) and synergistic (2-oxoglutarate and ATP) mode of effector molecule binding is further affected by PII -receptor interaction, leading to a highly sophisticated signalling network organized by PII . Altogether, it appears that PII is a multitasking information processor that, depending on its interaction environment, differentially transmits information on the energy status and the cellular 2-oxoglutarate level. In addition to the basic mode of PII function, several bacterial PII proteins may transmit a signal of the cellular glutamine status via covalent modification. Remarkably, during the evolution of plant chloroplasts, glutamine signalling by PII proteins was re-established by acquisition of a short sequence extension at the C-terminus. This plant-specific C-terminus makes the interaction of plant PII proteins with one of its targets, the arginine biosynthetic enzyme N-acetyl-glutamate kinase, glutamine-dependent.

  9. Role of regulator of G protein signaling proteins in bone

    PubMed Central

    Keinan, David; Yang, Shuying; Cohen, Robert E.; Yuan, Xue; Liu, Tongjun; Li, Yi-Ping

    2014-01-01

    Regulators of G protein signaling (RGS) proteins are a family with more than 30 proteins that all contain an RGS domain. In the past decade, increasing evidence has indicated that RGS proteins play crucial roles in the regulation of G protein coupling receptors (GPCR), G proteins, and calcium signaling during cell proliferation, migration, and differentiation in a variety of tissues. In bone, those proteins modulate bone development and remodeling by influencing various signaling pathways such as GPCR-G protein signaling, Wnt, calcium oscillations and PTH. This review summarizes the recent advances in the understanding of the regulation of RGS genes expression, as well as the functions and mechanisms of RGS proteins, especially in regulating GPCR-G protein signaling, Wnt signaling, calcium oscillations signaling and PTH signaling during bone development and remodeling. This review also highlights the regulation of different RGS proteins in osteoblasts, chondrocytes and osteoclasts. The knowledge from the recent advances of RGS study summarized in the review would provide the insights into new therapies for bone diseases. PMID:24389209

  10. Signaling pathway networks mined from human pituitary adenoma proteomics data

    PubMed Central

    2010-01-01

    Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to

  11. Sentra, a database of signal transduction proteins.

    SciTech Connect

    Maltsev, N.; Marland, E.; Yu, G. X.; Bhatnagar, S.; Lusk, R.; Mathematics and Computer Science

    2002-01-01

    Sentra (http://www-wit.mcs.anl.gov/sentra) is a database of signal transduction proteins with the emphasis on microbial signal transduction. The database was updated to include classes of signal transduction systems modulated by either phosphorylation or methylation reactions such as PAS proteins and serine/threonine kinases, as well as the classical two-component histidine kinases and methyl-accepting chemotaxis proteins. Currently, Sentra contains signal transduction proteins from 43 completely sequenced prokaryotic genomes as well as sequences from SWISS-PROT and TrEMBL. Signal transduction proteins are annotated with information describing conserved domains, paralogous and orthologous sequences, and conserved chromosomal gene clusters. The newly developed user interface supports flexible search capabilities and extensive visualization of the data.

  12. SENTRA, a database of signal transduction proteins.

    SciTech Connect

    D'Souza, M.; Romine, M. F.; Maltsev, N.; Mathematics and Computer Science; PNNL

    2000-01-01

    SENTRA, available via URL http://wit.mcs.anl.gov/WIT2/Sentra/, is a database of proteins associated with microbial signal transduction. The database currently includes the classical two-component signal transduction pathway proteins and methyl-accepting chemotaxis proteins, but will be expanded to also include other classes of signal transduction systems that are modulated by phosphorylation or methylation reactions. Although the majority of database entries are from prokaryotic systems, eukaroytic proteins with bacterial-like signal transduction domains are also included. Currently SENTRA contains signal transduction proteins in 34 complete and almost completely sequenced prokaryotic genomes, as well as sequences from 243 organisms available in public databases (SWISS-PROT and EMBL). The analysis was carried out within the framework of the WIT2 system, which is designed and implemented to support genetic sequence analysis and comparative analysis of sequenced genomes.

  13. Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.

    PubMed

    Rhee, Alex; Cheong, Raymond; Levchenko, Andre

    2014-12-01

    Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic-intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.

  14. Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters

    PubMed Central

    Rhee, Alex; Cheong, Raymond; Levchenko, Andre

    2014-01-01

    Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic–intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise. PMID:25404303

  15. Artificial neural networks for classifying olfactory signals.

    PubMed

    Linder, R; Pöppl, S J

    2000-01-01

    For practical applications, artificial neural networks have to meet several requirements: Mainly they should learn quick, classify accurate and behave robust. Programs should be user-friendly and should not need the presence of an expert for fine tuning diverse learning parameters. The present paper demonstrates an approach using an oversized network topology, adaptive propagation (APROP), a modified error function, and averaging outputs of four networks described for the first time. As an example, signals from different semiconductor gas sensors of an electronic nose were classified. The electronic nose smelt different types of edible oil with extremely different a-priori-probabilities. The fully-specified neural network classifier fulfilled the above mentioned demands. The new approach will be helpful not only for classifying olfactory signals automatically but also in many other fields in medicine, e.g. in data mining from medical databases.

  16. The beta-arrestin pathway-selective type 1A angiotensin receptor (AT1A) agonist [Sar1,Ile4,Ile8]angiotensin II regulates a robust G protein-independent signaling network.

    PubMed

    Kendall, Ryan T; Strungs, Erik G; Rachidi, Saleh M; Lee, Mi-Hye; El-Shewy, Hesham M; Luttrell, Deirdre K; Janech, Michael G; Luttrell, Louis M

    2011-06-01

    The angiotensin II peptide analog [Sar(1),Ile(4),Ile(8)]AngII (SII) is a biased AT(1A) receptor agonist that stimulates receptor phosphorylation, β-arrestin recruitment, receptor internalization, and β-arrestin-dependent ERK1/2 activation without activating heterotrimeric G-proteins. To determine the scope of G-protein-independent AT(1A) receptor signaling, we performed a gel-based phosphoproteomic analysis of AngII and SII-induced signaling in HEK cells stably expressing AT(1A) receptors. A total of 34 differentially phosphorylated proteins were detected, of which 16 were unique to SII and eight to AngII stimulation. MALDI-TOF/TOF mass fingerprinting was employed to identify 24 SII-sensitive phosphoprotein spots, of which three (two peptide inhibitors of protein phosphatase 2A (I1PP2A and I2PP2A) and prostaglandin E synthase 3 (PGES3)) were selected for validation and further study. We found that phosphorylation of I2PP2A was associated with rapid and transient inhibition of a β-arrestin 2-associated pool of protein phosphatase 2A, leading to activation of Akt and increased phosphorylation of glycogen synthase kinase 3β in an arrestin signalsome complex. SII-stimulated PGES3 phosphorylation coincided with an increase in β-arrestin 1-associated PGES3 and an arrestin-dependent increase in cyclooxygenase 1-dependent prostaglandin E(2) synthesis. These findings suggest that AT(1A) receptors regulate a robust G protein-independent signaling network that affects protein phosphorylation and autocrine/paracrine prostaglandin production and that these pathways can be selectively modulated by biased ligands that antagonize G protein activation.

  17. Modeling Protein Expression and Protein Signaling Pathways

    PubMed Central

    Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

    2015-01-01

    High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

  18. The low energy signaling network

    PubMed Central

    Tomé, Filipa; Nägele, Thomas; Adamo, Mattia; Garg, Abhroop; Marco-llorca, Carles; Nukarinen, Ella; Pedrotti, Lorenzo; Peviani, Alessia; Simeunovic, Andrea; Tatkiewicz, Anna; Tomar, Monika; Gamm, Magdalena

    2014-01-01

    Stress impacts negatively on plant growth and crop productivity, caicultural production worldwide. Throughout their life, plants are often confronted with multiple types of stress that affect overall cellular energy status and activate energy-saving responses. The resulting low energy syndrome (LES) includes transcriptional, translational, and metabolic reprogramming and is essential for stress adaptation. The conserved kinases sucrose-non-fermenting-1-related protein kinase-1 (SnRK1) and target of rapamycin (TOR) play central roles in the regulation of LES in response to stress conditions, affecting cellular processes and leading to growth arrest and metabolic reprogramming. We review the current understanding of how TOR and SnRK1 are involved in regulating the response of plants to low energy conditions. The central role in the regulation of cellular processes, the reprogramming of metabolism, and the phenotypic consequences of these two kinases will be discussed in light of current knowledge and potential future developments. PMID:25101105

  19. The low energy signaling network.

    PubMed

    Tomé, Filipa; Nägele, Thomas; Adamo, Mattia; Garg, Abhroop; Marco-Llorca, Carles; Nukarinen, Ella; Pedrotti, Lorenzo; Peviani, Alessia; Simeunovic, Andrea; Tatkiewicz, Anna; Tomar, Monika; Gamm, Magdalena

    2014-01-01

    Stress impacts negatively on plant growth and crop productivity, caicultural production worldwide. Throughout their life, plants are often confronted with multiple types of stress that affect overall cellular energy status and activate energy-saving responses. The resulting low energy syndrome (LES) includes transcriptional, translational, and metabolic reprogramming and is essential for stress adaptation. The conserved kinases sucrose-non-fermenting-1-related protein kinase-1 (SnRK1) and target of rapamycin (TOR) play central roles in the regulation of LES in response to stress conditions, affecting cellular processes and leading to growth arrest and metabolic reprogramming. We review the current understanding of how TOR and SnRK1 are involved in regulating the response of plants to low energy conditions. The central role in the regulation of cellular processes, the reprogramming of metabolism, and the phenotypic consequences of these two kinases will be discussed in light of current knowledge and potential future developments.

  20. Roles for Regulator of G Protein Signaling Proteins in Synaptic Signaling and Plasticity.

    PubMed

    Gerber, Kyle J; Squires, Katherine E; Hepler, John R

    2016-02-01

    The regulator of G protein signaling (RGS) family of proteins serves critical roles in G protein-coupled receptor (GPCR) and heterotrimeric G protein signal transduction. RGS proteins are best understood as negative regulators of GPCR/G protein signaling. They achieve this by acting as GTPase activating proteins (GAPs) for Gα subunits and accelerating the turnoff of G protein signaling. Many RGS proteins also bind additional signaling partners that either regulate their functions or enable them to regulate other important signaling events. At neuronal synapses, GPCRs, G proteins, and RGS proteins work in coordination to regulate key aspects of neurotransmitter release, synaptic transmission, and synaptic plasticity, which are necessary for central nervous system physiology and behavior. Accumulating evidence has revealed key roles for specific RGS proteins in multiple signaling pathways at neuronal synapses, regulating both pre- and postsynaptic signaling events and synaptic plasticity. Here, we review and highlight the current knowledge of specific RGS proteins (RGS2, RGS4, RGS7, RGS9-2, and RGS14) that have been clearly demonstrated to serve critical roles in modulating synaptic signaling and plasticity throughout the brain, and we consider their potential as future therapeutic targets.

  1. Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

    PubMed Central

    Hu, Jianfei; Neiswinger, Johnathan; Zhang, Jin; Zhu, Heng; Qian, Jiang

    2015-01-01

    Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process. PMID:26393507

  2. Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction.

    PubMed

    Hu, Jianfei; Neiswinger, Johnathan; Zhang, Jin; Zhu, Heng; Qian, Jiang

    2015-01-01

    Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.

  3. Signaling through G protein coupled receptors

    PubMed Central

    2009-01-01

    Heterotrimeric G proteins (Gα, Gβ/Gγ subunits) constitute one of the most important components of cell signaling cascade. G Protein Coupled Receptors (GPCRs) perceive many extracellular signals and transduce them to heterotrimeric G proteins, which further transduce these signals intracellular to appropriate downstream effectors and thereby play an important role in various signaling pathways. GPCRs exist as a superfamily of integral membrane protein receptors that contain seven transmembrane α-helical regions, which bind to a wide range of ligands. Upon activation by a ligand, the GPCR undergoes a conformational change and then activate the G proteins by promoting the exchange of GDP/GTP associated with the Gα subunit. This leads to the dissociation of Gβ/Gγ dimer from Gα. Both these moieties then become free to act upon their downstream effectors and thereby initiate unique intracellular signaling responses. After the signal propagation, the GTP of Gα-GTP is hydrolyzed to GDP and Gα becomes inactive (Gα-GDP), which leads to its re-association with the Gβ/Gγ dimer to form the inactive heterotrimeric complex. The GPCR can also transduce the signal through G protein independent pathway. GPCRs also regulate cell cycle progression. Till to date thousands of GPCRs are known from animal kingdom with little homology among them, but only single GPCR has been identified in plant system. The Arabidopsis GPCR was reported to be cell cycle regulated and also involved in ABA and in stress signaling. Here I have described a general mechanism of signal transduction through GPCR/G proteins, structure of GPCRs, family of GPCRs and plant GPCR and its role. PMID:19826234

  4. Signal-BNF: a Bayesian network fusing approach to predict signal peptides.

    PubMed

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells.

  5. Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

    PubMed Central

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells. PMID:23118510

  6. Novel links in the plant TOR kinase signaling network.

    PubMed

    Xiong, Yan; Sheen, Jen

    2015-12-01

    Nutrient and energy sensing and signaling mechanisms constitute the most ancient and fundamental regulatory networks to control growth and development in all life forms. The target of rapamycin (TOR) protein kinase is modulated by diverse nutrient, energy, hormone and stress inputs and plays a central role in regulating cell proliferation, growth, metabolism and stress responses from yeasts to plants and animals. Recent chemical, genetic, genomic and metabolomic analyses have enabled significant progress toward molecular understanding of the TOR signaling network in multicellular plants. This review discusses the applications of new chemical tools to probe plant TOR functions and highlights recent findings and predictions on TOR-mediate biological processes. Special focus is placed on novel and evolutionarily conserved TOR kinase effectors as positive and negative signaling regulators that control transcription, translation and metabolism to support cell proliferation, growth and maintenance from embryogenesis to senescence in the plant system.

  7. Protons as second messenger regulators of G protein signaling

    PubMed Central

    Isom, Daniel G.; Sridharan, Vishwajith; Baker, Rachael; Clement, Sarah T.; Smalley, David M.; Dohlman, Henrik G.

    2013-01-01

    Summary In response to environmental stress cells often generate pH signals that serve to protect vital cellular components and reprogram gene expression for survival. A major barrier to our understanding of this process has been the identification of signaling proteins that detect changes in intracellular pH. To identify candidate pH sensors we developed a computer algorithm that searches proteins for networks of proton-binding sidechains. This analysis indicates that Gα subunits, the principal transducers of G protein-coupled receptor signals, are pH sensors. Our structure-based calculations and biophysical investigations reveal that Gα subunits contain networks of pH-sensing sidechains buried between their Ras and helical domains. We show further that proton binding induces changes in conformation that promote Gα phosphorylation and suppress receptor-initiated signaling. Together, our computational, biophysical and cellular analyses reveal a new and unexpected function for G proteins as mediators of stress-response signaling. PMID:23954348

  8. Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data.

    PubMed

    von der Heyde, Silvia; Sonntag, Johanna; Kramer, Frank; Bender, Christian; Korf, Ulrike; Beißbarth, Tim

    2016-01-01

    In this chapter, we describe an approach to reconstruct cellular signaling networks based on measurements of protein activation after different stimulation experiments. As experimental platform reverse-phase protein arrays (RPPA) are used. RPPA allow the measurement of proteins and phosphoproteins across many samples in parallel with minimal sample consumption using a panel of highly target protein-specific antibodies. Functional interactions of proteins are modeled using a Boolean network. We describe the Boolean network reconstruction approach ddepn (dynamic deterministic effects propagation networks), which uses time course data to derive protein interactions based on perturbation experiments. We explain how the method works, give a practical application example, and describe how the results can be interpreted. Furthermore prior knowledge on signaling pathways is essential for network reconstruction. Here we describe the use of our software rBiopaxParser to integrate prior knowledge on protein signaling available in public databases. All applied methods are freely available as open-source R software packages. We describe the preparation of RPPA data as well as all relevant programming steps to format the RPPA data, to infer the prior knowledge, and to reconstruct and analyze the protein signaling networks. PMID:26519181

  9. The statistical mechanics of complex signaling networks: nerve growth factor signaling

    NASA Astrophysics Data System (ADS)

    Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.

    2004-10-01

    The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

  10. MicroRNAs in the Imprinted DLK1-DIO3 Region Repress the Epithelial-to-Mesenchymal Transition by Targeting the TWIST1 Protein Signaling Network*

    PubMed Central

    Haga, Christopher L.; Phinney, Donald G.

    2012-01-01

    Development of metastatic disease accounts for the vast majority of cancer-related deaths. Nevertheless, few treatments exist that are designed to specifically inhibit processes that drive tumor metastasis. The imprinted DLK1-DIO3 region contains tumor-suppressing miRNAs, but their identity and function remain indeterminate. In this study we identify seven miRNAs in the imprinted DLK1-DIO3 region that function cooperatively to repress the epithelial-to-mesenchymal transition, a critical step that drives tumor metastasis, as well as proliferation of carcinoma cells. These seven miRNAs (miRs 300, 382, 494, 495, 539, 543, and 544) repress a signaling network comprising TWIST1, BMI1, ZEB1/2, and miR-200 family miRNAs and silencing of the cluster, which occurs via hypermethylation of upstream CpG islands in human ductal carcinomas, confers morphological, molecular, and function changes consistent with an epithelial-to-mesenchymal transition. Moreover, ectopic expression of miR-544 independently inhibited proliferation of numerous tumor cell lines by inducing the ATM cell cycle checkpoint pathway. These results establish the DLKI-DIO3 miRNA cluster as a critical checkpoint regulating tumor growth and metastasis and implicate epigenetic modification of the cluster in driving tumor progression. These results also suggest that promoter methylation status and miRNA expression levels represent new diagnostic tools and therapeutic targets to predict and inhibit, respectively, tumor metastasis in carcinoma patients. PMID:23105110

  11. MicroRNAs in the imprinted DLK1-DIO3 region repress the epithelial-to-mesenchymal transition by targeting the TWIST1 protein signaling network.

    PubMed

    Haga, Christopher L; Phinney, Donald G

    2012-12-14

    Development of metastatic disease accounts for the vast majority of cancer-related deaths. Nevertheless, few treatments exist that are designed to specifically inhibit processes that drive tumor metastasis. The imprinted DLK1-DIO3 region contains tumor-suppressing miRNAs, but their identity and function remain indeterminate. In this study we identify seven miRNAs in the imprinted DLK1-DIO3 region that function cooperatively to repress the epithelial-to-mesenchymal transition, a critical step that drives tumor metastasis, as well as proliferation of carcinoma cells. These seven miRNAs (miRs 300, 382, 494, 495, 539, 543, and 544) repress a signaling network comprising TWIST1, BMI1, ZEB1/2, and miR-200 family miRNAs and silencing of the cluster, which occurs via hypermethylation of upstream CpG islands in human ductal carcinomas, confers morphological, molecular, and function changes consistent with an epithelial-to-mesenchymal transition. Moreover, ectopic expression of miR-544 independently inhibited proliferation of numerous tumor cell lines by inducing the ATM cell cycle checkpoint pathway. These results establish the DLKI-DIO3 miRNA cluster as a critical checkpoint regulating tumor growth and metastasis and implicate epigenetic modification of the cluster in driving tumor progression. These results also suggest that promoter methylation status and miRNA expression levels represent new diagnostic tools and therapeutic targets to predict and inhibit, respectively, tumor metastasis in carcinoma patients.

  12. Numeric simulation of plant signaling networks.

    PubMed

    Genoud, T; Trevino Santa Cruz, M B; Métraux, J P

    2001-08-01

    Plants have evolved an intricate signaling apparatus that integrates relevant information and allows an optimal response to environmental conditions. For instance, the coordination of defense responses against pathogens involves sophisticated molecular detection and communication systems. Multiple protection strategies may be deployed differentially by the plant according to the nature of the invading organism. These responses are also influenced by the environment, metabolism, and developmental stage of the plant. Though the cellular signaling processes traditionally have been described as linear sequences of events, it is now evident that they may be represented more accurately as network-like structures. The emerging paradigm can be represented readily with the use of Boolean language. This digital (numeric) formalism allows an accurate qualitative description of the signal transduction processes, and a dynamic representation through computer simulation. Moreover, it provides the required power to process the increasing amount of information emerging from the fields of genomics and proteomics, and from the use of new technologies such as microarray analysis. In this review, we have used the Boolean language to represent and analyze part of the signaling network of disease resistance in Arabidopsis. PMID:11500542

  13. Signal integration by chloroplast phosphorylation networks: an update

    PubMed Central

    Schönberg, Anna; Baginsky, Sacha

    2012-01-01

    Forty years after the initial discovery of light-dependent protein phosphorylation at the thylakoid membrane system, we are now beginning to understand the roles of chloroplast phosphorylation networks in their function to decode and mediate information on the metabolic status of the organelle to long-term adaptations in plastid and nuclear gene expression. With the help of genetics and functional genomics tools, chloroplast kinases and several hundred phosphoproteins were identified that now await detailed functional characterization. The regulation and the target protein spectrum of some kinases are understood, but this information is fragmentary with respect to kinase and target protein crosstalk in a changing environment. In this review, we will highlight the most recent advances in the field and discuss approaches that might lead to a comprehensive understanding of plastid signal integration by protein phosphorylation. PMID:23181067

  14. Defining the Protein-Protein Interaction Network of the Human Protein Tyrosine Phosphatase Family.

    PubMed

    Li, Xu; Tran, Kim My; Aziz, Kathryn E; Sorokin, Alexey V; Chen, Junjie; Wang, Wenqi

    2016-09-01

    Protein tyrosine phosphorylation, which plays a vital role in a variety of human cellular processes, is coordinated by protein tyrosine kinases and protein tyrosine phosphatases (PTPs). Genomic studies provide compelling evidence that PTPs are frequently mutated in various human cancers, suggesting that they have important roles in tumor suppression. However, the cellular functions and regulatory machineries of most PTPs are still largely unknown. To gain a comprehensive understanding of the protein-protein interaction network of the human PTP family, we performed a global proteomic study. Using a Minkowski distance-based unified scoring environment (MUSE) for the data analysis, we identified 940 high confidence candidate-interacting proteins that comprise the interaction landscape of the human PTP family. Through a gene ontology analysis and functional validations, we connected the PTP family with several key signaling pathways or cellular functions whose associations were previously unclear, such as the RAS-RAF-MEK pathway, the Hippo-YAP pathway, and cytokinesis. Our study provides the first glimpse of a protein interaction network for the human PTP family, linking it to a number of crucial signaling events, and generating a useful resource for future studies of PTPs.

  15. Investigation of a protein complex network

    NASA Astrophysics Data System (ADS)

    Mashaghi, A. R.; Ramezanpour, A.; Karimipour, V.

    2004-09-01

    The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal non-random features of the network we also compare it with a null model in which the complexes randomly select their proteins. Finally we propose a simple evolutionary model based on duplication and divergence of proteins.

  16. Transferring network topological knowledge for predicting protein-protein interactions.

    PubMed

    Xu, Qian; Xiang, Evan Wei; Yang, Qiang

    2011-10-01

    Protein-protein interactions (PPIs) play an important role in cellular processes within a cell. An important task is to determine the existence of interactions among proteins. Unfortunately, the existing biological experimental techniques are expensive, time-consuming and labor-intensive. The network structures of many such networks are sparse, incomplete and noisy. Thus, state-of-the-art methods for link prediction in these networks often cannot give satisfactory prediction results, especially when some networks are extremely sparse. Noticing that we typically have more than one PPI network available, we naturally wonder whether it is possible to 'transfer' the linkage knowledge from some existing, relatively dense networks to a sparse network, to improve the prediction performance. Noticing that a network structure can be modeled using a matrix model, we introduce the well-known collective matrix factorization technique to 'transfer' usable linkage knowledge from relatively dense interaction network to a sparse target network. Our approach is to establish a correspondence between a source network and a target network via network-wide similarities. We test this method on two real PPI networks, Helicobacter pylori (as a target network) and human (as a source network). Our experimental results show that our method can achieve higher performance as compared with some baseline methods. PMID:21770035

  17. Integrating multiple networks for protein function prediction

    PubMed Central

    2015-01-01

    Background High throughput techniques produce multiple functional association networks. Integrating these networks can enhance the accuracy of protein function prediction. Many algorithms have been introduced to generate a composite network, which is obtained as a weighted sum of individual networks. The weight assigned to an individual network reflects its benefit towards the protein functional annotation inference. A classifier is then trained on the composite network for predicting protein functions. However, since these techniques model the optimization of the composite network and the prediction tasks as separate objectives, the resulting composite network is not necessarily optimal for the follow-up protein function prediction. Results We address this issue by modeling the optimization of the composite network and the prediction problems within a unified objective function. In particular, we use a kernel target alignment technique and the loss function of a network based classifier to jointly adjust the weights assigned to the individual networks. We show that the proposed method, called MNet, can achieve a performance that is superior (with respect to different evaluation criteria) to related techniques using the multiple networks of four example species (yeast, human, mouse, and fly) annotated with thousands (or hundreds) of GO terms. Conclusion MNet can effectively integrate multiple networks for protein function prediction and is robust to the input parameters. Supplementary data is available at https://sites.google.com/site/guoxian85/home/mnet. The Matlab code of MNet is available upon request. PMID:25707434

  18. Glycosphingolipid–Protein Interaction in Signal Transduction

    PubMed Central

    Russo, Domenico; Parashuraman, Seetharaman; D’Angelo, Giovanni

    2016-01-01

    Glycosphingolipids (GSLs) are a class of ceramide-based glycolipids essential for embryo development in mammals. The synthesis of specific GSLs depends on the expression of distinctive sets of GSL synthesizing enzymes that is tightly regulated during development. Several reports have described how cell surface receptors can be kept in a resting state or activate alternative signalling events as a consequence of their interaction with GSLs. Specific GSLs, indeed, interface with specific protein domains that are found in signalling molecules and which act as GSL sensors to modify signalling responses. The regulation exerted by GSLs on signal transduction is orthogonal to the ligand–receptor axis, as it usually does not directly interfere with the ligand binding to receptors. Due to their properties of adjustable production and orthogonal action on receptors, GSLs add a new dimension to the control of the signalling in development. GSLs can, indeed, dynamically influence progenitor cell response to morphogenetic stimuli, resulting in alternative differentiation fates. Here, we review the available literature on GSL–protein interactions and their effects on cell signalling and development. PMID:27754465

  19. Pathway connectivity and signaling coordination in the yeast stress-activated signaling network

    PubMed Central

    Chasman, Deborah; Ho, Yi-Hsuan; Berry, David B; Nemec, Corey M; MacGilvray, Matthew E; Hose, James; Merrill, Anna E; Lee, M Violet; Will, Jessica L; Coon, Joshua J; Ansari, Aseem Z; Craven, Mark; Gasch, Audrey P

    2014-01-01

    Stressed cells coordinate a multi-faceted response spanning many levels of physiology. Yet knowledge of the complete stress-activated regulatory network as well as design principles for signal integration remains incomplete. We developed an experimental and computational approach to integrate available protein interaction data with gene fitness contributions, mutant transcriptome profiles, and phospho-proteome changes in cells responding to salt stress, to infer the salt-responsive signaling network in yeast. The inferred subnetwork presented many novel predictions by implicating new regulators, uncovering unrecognized crosstalk between known pathways, and pointing to previously unknown ‘hubs’ of signal integration. We exploited these predictions to show that Cdc14 phosphatase is a central hub in the network and that modification of RNA polymerase II coordinates induction of stress-defense genes with reduction of growth-related transcripts. We find that the orthologous human network is enriched for cancer-causing genes, underscoring the importance of the subnetwork's predictions in understanding stress biology. PMID:25411400

  20. Protein-protein interaction networks (PPI) and complex diseases

    PubMed Central

    Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

    2014-01-01

    The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094

  1. Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

    PubMed Central

    CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

    2016-01-01

    Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

  2. Phosphatase specificity and pathway insulation in signaling networks.

    PubMed

    Rowland, Michael A; Harrison, Brian; Deeds, Eric J

    2015-02-17

    Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase's substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A's adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for

  3. Phosphatase Specificity and Pathway Insulation in Signaling Networks

    PubMed Central

    Rowland, Michael A.; Harrison, Brian; Deeds, Eric J.

    2015-01-01

    Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase’s substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A’s adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for

  4. Collective Calcium Signaling of Defective Multicellular Networks

    NASA Astrophysics Data System (ADS)

    Potter, Garrett; Sun, Bo

    2015-03-01

    A communicating multicellular network processes environmental cues into collective cellular dynamics. We have previously demonstrated that, when excited by extracellular ATP, fibroblast monolayers generate correlated calcium dynamics modulated by both the stimuli and gap junction communication between the cells. However, just as a well-connected neural network may be compromised by abnormal neurons, a tissue monolayer can also be defective with cancer cells, which typically have down regulated gap junctions. To understand the collective cellular dynamics in a defective multicellular network we have studied the calcium signaling of co-cultured breast cancer cells and fibroblast cells in various concentrations of ATP delivered through microfluidic devices. Our results demonstrate that cancer cells respond faster, generate singular spikes, and are more synchronous across all stimuli concentrations. Additionally, fibroblast cells exhibit persistent calcium oscillations that increase in regularity with greater stimuli. To interpret these results we quantitatively analyzed the immunostaining of purigenic receptors and gap junction channels. The results confirm our hypothesis that collective dynamics are mainly determined by the availability of gap junction communications.

  5. MSAT signalling and network management architectures

    NASA Technical Reports Server (NTRS)

    Garland, Peter; Keelty, J. Malcolm

    1989-01-01

    Spar Aerospace has been active in the design and definition of Mobile Satellite Systems since the mid 1970's. In work sponsored by the Canadian Department of Communications, various payload configurations have evolved. In addressing the payload configuration, the requirements of the mobile user, the service provider and the satellite operator have always been the most important consideration. The current Spar 11 beam satellite design is reviewed, and its capabilities to provide flexibility and potential for network growth within the WARC87 allocations are explored. To enable the full capabilities of the payload to be realized, a large amount of ground based Switching and Network Management infrastructure will be required, when space segment becomes available. Early indications were that a single custom designed Demand Assignment Multiple Access (DAMA) switch should be implemented to provide efficient use of the space segment. As MSAT has evolved into a multiple service concept, supporting many service providers, this architecture should be reviewed. Some possible signalling and Network Management solutions are explored.

  6. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  7. A Network Synthesis Model for Generating Protein Interaction Network Families

    PubMed Central

    Sahraeian, Sayed Mohammad Ebrahim; Yoon, Byung-Jun

    2012-01-01

    In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein–protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model can effectively create synthetic networks whose internal and cross-network properties closely resemble those of real PPI networks. The proposed model can serve as an effective framework for generating comprehensive benchmark datasets that can be used for reliable performance assessment of comparative network analysis algorithms. Using this model, we constructed a large-scale network alignment benchmark, called NAPAbench, and evaluated the performance of several representative network alignment algorithms. Our analysis clearly shows the relative performance of the leading network algorithms, with their respective advantages and disadvantages. The algorithm and source code of the network synthesis model and the network alignment benchmark NAPAbench are publicly available at http://www.ece.tamu.edu/bjyoon/NAPAbench/. PMID:22912671

  8. The Roles of NDR Protein Kinases in Hippo Signalling

    PubMed Central

    Hergovich, Alexander

    2016-01-01

    The Hippo tumour suppressor pathway has emerged as a critical regulator of tissue growth through controlling cellular processes such as cell proliferation, death, differentiation and stemness. Traditionally, the core cassette of the Hippo pathway includes the MST1/2 protein kinases, the LATS1/2 protein kinases, and the MOB1 scaffold signal transducer, which together regulate the transcriptional co-activator functions of the proto-oncoproteins YAP and TAZ through LATS1/2-mediated phosphorylation of YAP/TAZ. Recent research has identified additional kinases, such as NDR1/2 (also known as STK38/STK38L) and MAP4Ks, which should be considered as novel members of the Hippo core cassette. While these efforts helped to expand our understanding of Hippo core signalling, they also began to provide insights into the complexity and redundancy of the Hippo signalling network. Here, we focus on summarising our current knowledge of the regulation and functions of mammalian NDR kinases, discussing parallels between the NDR pathways in Drosophila and mammals. Initially, we provide a general overview of the cellular functions of NDR kinases in cell cycle progression, centrosome biology, apoptosis, autophagy, DNA damage signalling, immunology and neurobiology. Finally, we put particular emphasis on discussing NDR1/2 as YAP kinases downstream of MST1/2 and MOB1 signalling in Hippo signalling. PMID:27213455

  9. A modular analysis of the auxin signalling network.

    PubMed

    Farcot, Etienne; Lavedrine, Cyril; Vernoux, Teva

    2015-01-01

    Auxin is essential for plant development from embryogenesis onwards. Auxin acts in large part through regulation of transcription. The proteins acting in the signalling pathway regulating transcription downstream of auxin have been identified as well as the interactions between these proteins, thus identifying the topology of this network implicating 54 Auxin Response Factor (ARF) and Aux/IAA (IAA) transcriptional regulators. Here, we study the auxin signalling pathway by means of mathematical modeling at the single cell level. We proceed analytically, by considering the role played by five functional modules into which the auxin pathway can be decomposed: the sequestration of ARF by IAA, the transcriptional repression by IAA, the dimer formation amongst ARFs and IAAs, the feedback loop on IAA and the auxin induced degradation of IAA proteins. Focusing on these modules allows assessing their function within the dynamics of auxin signalling. One key outcome of this analysis is that there are both specific and overlapping functions between all the major modules of the signaling pathway. This suggests a combinatorial function of the modules in optimizing the speed and amplitude of auxin-induced transcription. Our work allows identifying potential functions for homo- and hetero-dimerization of transcriptional regulators, with ARF:IAA, IAA:IAA and ARF:ARF dimerization respectively controlling the amplitude, speed and sensitivity of the response and a synergistic effect of the interaction of IAA with transcriptional repressors on these characteristics of the signaling pathway. Finally, we also suggest experiments which might allow disentangling the structure of the auxin signaling pathway and analysing further its function in plants.

  10. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    PubMed Central

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  11. Near-Perfect Adaptation in the E. coli Chemotaxis Signal Transduction Network

    NASA Astrophysics Data System (ADS)

    Yang, Yang; Setayeshgar, Sima

    2007-03-01

    Biochemical reaction networks constitute the computing language of the cell, from converting external stimuli into appropriate intracellular signals to regulating gene expression. Precise adaptation is an important property of many signaling networks, allowing compensation for continued stimulation without saturation. Furthermore, a common feature of intracellular reaction networks is the ability to operate in a noisy environment where concentrations of key components, such as signaling molecules and enzymes controlling reaction rates are typically small and therefore fluctuations in their numbers are significant. In the context of the well- characterized E. coli chemotaxis signal transduction network, we present a new computational scheme that explores surfaces in the space of total protein concentrations and reaction rates on which (near-)perfect adaptation holds. The resulting dependencies between parameters provide conditions for (near-)perfect adaptation as well as ranges of numerical values for parameters not reliably known from experiments. We generalize the applicability of this scheme to other signaling networks.

  12. Ontology integration to identify protein complex in protein interaction networks

    PubMed Central

    2011-01-01

    Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity method, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. Following the approach of that of the previously proposed clustering algorithm IPCA which expands clusters starting from seeded vertices, we present a clustering algorithm OIIP based on the new weighted Protein-Protein interaction networks for identifying protein complexes. Results The algorithm OIIP is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm OIIP has higher F-measure and accuracy compared to other competing approaches. PMID:22165991

  13. Unraveling Protein Networks with Power Graph Analysis

    PubMed Central

    Royer, Loïc; Reimann, Matthias; Andreopoulos, Bill; Schroeder, Michael

    2008-01-01

    Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we demonstrate the generality of Power Graph Analysis by applying it to two other types of networks. We show how power graphs induce a clustering of both transcription factors and target genes in bipartite transcription networks, and how the erosion of a phosphatase domain in type 22 non-receptor tyrosine phosphatases is detected. We apply Power Graph Analysis to high-throughput protein interaction networks and show that up to 85% (56% on average) of the information is redundant. Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques. Power Graphs are a novel representation of networks, which reduces network complexity by explicitly representing re-occurring network motifs. Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks. PMID:18617988

  14. Logic integer programming models for signaling networks.

    PubMed

    Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

    2009-05-01

    We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

  15. Alignment-free protein interaction network comparison

    PubMed Central

    Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

    2014-01-01

    Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

  16. Molecular signaling involving intrinsically disordered proteins in prostate cancer

    PubMed Central

    Russo, Anna; Manna, Sara La; Novellino, Ettore; Malfitano, Anna Maria; Marasco, Daniela

    2016-01-01

    Investigations on cellular protein interaction networks (PINs) reveal that proteins that constitute hubs in a PIN are notably enriched in Intrinsically Disordered Proteins (IDPs) compared to proteins that constitute edges, highlighting the role of IDPs in signaling pathways. Most IDPs rapidly undergo disorder-to-order transitions upon binding to their biological targets to perform their function. Conformational dynamics enables IDPs to be versatile and to interact with a broad range of interactors under normal physiological conditions where their expression is tightly modulated. IDPs are involved in many cellular processes such as cellular signaling, transcriptional regulation, and splicing; thus, their high-specificity/low-affinity interactions play crucial roles in many human diseases including cancer. Prostate cancer (PCa) is one of the leading causes of cancer-related mortality in men worldwide. Therefore, identifying molecular mechanisms of the oncogenic signaling pathways that are involved in prostate carcinogenesis is crucial. In this review, we focus on the aspects of cellular pathways leading to PCa in which IDPs exert a primary role. PMID:27212129

  17. Spatial Modeling of Cell Signaling Networks

    PubMed Central

    Cowan, Ann E.; Moraru, Ion I.; Schaff, James C.; Slepchenko, Boris M.; Loew, Leslie M.

    2012-01-01

    The shape of a cell, the sizes of subcellular compartments and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic vs, stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling. PMID:22482950

  18. Mitogen-activated protein kinase signal transduction and DNA repair network are involved in aluminum-induced DNA damage and adaptive response in root cells of Allium cepa L.

    PubMed Central

    Panda, Brahma B.; Achary, V. Mohan M.

    2014-01-01

    In the current study, we studied the role of signal transduction in aluminum (Al3+)-induced DNA damage and adaptive response in root cells of Allium cepa L. The root cells in planta were treated with Al3+ (800 μM) for 3 h without or with 2 h pre-treatment of inhibitors of mitogen-activated protein kinase (MAPK), and protein phosphatase. Also, root cells in planta were conditioned with Al3+ (10 μM) for 2 h and then subjected to genotoxic challenge of ethyl methane sulfonate (EMS; 5 mM) for 3 h without or with the pre-treatment of the aforementioned inhibitors as well as the inhibitors of translation, transcription, DNA replication and repair. At the end of treatments, roots cells were assayed for cell death and/or DNA damage. The results revealed that Al3+ (800 μM)-induced significant DNA damage and cell death. On the other hand, conditioning with low dose of Al3+ induced adaptive response conferring protection of root cells from genotoxic stress caused by EMS-challenge. Pre-treatment of roots cells with the chosen inhibitors prior to Al3+-conditioning prevented or reduced the adaptive response to EMS genotoxicity. The results of this study suggested the involvement of MAPK and DNA repair network underlying Al-induced DNA damage and adaptive response to genotoxic stress in root cells of A. cepa. PMID:24926302

  19. Hepatitis C virus infection protein network

    PubMed Central

    de Chassey, B; Navratil, V; Tafforeau, L; Hiet, M S; Aublin-Gex, A; Agaugué, S; Meiffren, G; Pradezynski, F; Faria, B F; Chantier, T; Le Breton, M; Pellet, J; Davoust, N; Mangeot, P E; Chaboud, A; Penin, F; Jacob, Y; Vidalain, P O; Vidal, M; André, P; Rabourdin-Combe, C; Lotteau, V

    2008-01-01

    A proteome-wide mapping of interactions between hepatitis C virus (HCV) and human proteins was performed to provide a comprehensive view of the cellular infection. A total of 314 protein–protein interactions between HCV and human proteins was identified by yeast two-hybrid and 170 by literature mining. Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HCV are enriched in highly central and interconnected proteins. A global analysis on the basis of functional annotation highlighted the enrichment of cellular pathways targeted by HCV. A network of proteins associated with frequent clinical disorders of chronically infected patients was constructed by connecting the insulin, Jak/STAT and TGFβ pathways with cellular proteins targeted by HCV. CORE protein appeared as a major perturbator of this network. Focal adhesion was identified as a new function affected by HCV, mainly by NS3 and NS5A proteins. PMID:18985028

  20. From networks of protein interactions to networks of functional dependencies

    PubMed Central

    2012-01-01

    Background As protein-protein interactions connect proteins that participate in either the same or different functions, networks of interacting and functionally annotated proteins can be converted into process graphs of inter-dependent function nodes (each node corresponding to interacting proteins with the same functional annotation). However, as proteins have multiple annotations, the process graph is non-redundant, if only proteins participating directly in a given function are included in the related function node. Results Reasoning that topological features (e.g., clusters of highly inter-connected proteins) might help approaching structured and non-redundant understanding of molecular function, an algorithm was developed that prioritizes inclusion of proteins into the function nodes that best overlap protein clusters. Specifically, the algorithm identifies function nodes (and their mutual relations), based on the topological analysis of a protein interaction network, which can be related to various biological domains, such as cellular components (e.g., peroxisome and cellular bud) or biological processes (e.g., cell budding) of the model organism S. cerevisiae. Conclusions The method we have described allows converting a protein interaction network into a non-redundant process graph of inter-dependent function nodes. The examples we have described show that the resulting graph allows researchers to formulate testable hypotheses about dependencies among functions and the underlying mechanisms. PMID:22607727

  1. Understanding the neurospecificity of Prion protein signaling.

    PubMed

    Schneider, Benoit; Pietri, Mathea; Pradines, Elodie; Loubet, Damien; Launay, Jean-Marie; Kellermann, Odile; Mouillet-Richard, Sophie

    2011-01-01

    The cellular prion protein PrP(C) is the normal counterpart of the scrapie prion protein PrP(Sc), the main component of the infectious agent of transmissible spongiform encephalopathies (TSEs). It is a ubiquitous cell-surface glycoprotein, abundantly expressed in neurons, which constitute the targets of TSE pathogenesis. The presence of PrP(C) at the surface of neurons is an absolute requirement for the development of prion diseases and corruption of PrP(C) function(s) within an infectious context emerges as a proximal cause for PrP(Sc)-induced neurodegeneration. Experimental evidence gained over the past decade indicates that PrP(C) has the capacity to mobilize promiscuous signal transduction cascades that, notably, contribute to cell homeostasis. Beyond ubiquitous effectors, much data converge onto a neurospecificity of PrP(C) signaling, which may be the clue to neuronal cell demise in prion disorders. In this article, we highlight the requirement of PrP(C) for TSEs-associated neurodegeneration and review the current knowledge of PrP(C)-dependent signal transduction in neuronal cells and its implications for PrP(Sc)-mediated neurotoxicity.

  2. MANET: tracing evolution of protein architecture in metabolic networks

    PubMed Central

    Kim, Hee Shin; Mittenthal, Jay E; Caetano-Anollés, Gustavo

    2006-01-01

    Background Cellular metabolism can be characterized by networks of enzymatic reactions and transport processes capable of supporting cellular life. Our aim is to find evolutionary patterns and processes embedded in the architecture and function of modern metabolism, using information derived from structural genomics. Description The Molecular Ancestry Network (MANET) project traces evolution of protein architecture in biomolecular networks. We describe metabolic MANET, a database that links information in the Structural Classification of Proteins (SCOP), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and phylogenetic reconstructions depicting the evolution of protein fold architecture. Metabolic MANET literally 'paints' the ancestries of enzymes derived from rooted phylogenomic trees directly onto over one hundred metabolic subnetworks, enabling the study of evolutionary patterns at global and local levels. An initial analysis of painted subnetworks reveals widespread enzymatic recruitment and an early origin of amino acid metabolism. Conclusion MANET maps evolutionary relationships directly and globally onto biological networks, and can generate and test hypotheses related to evolution of metabolism. We anticipate its use in the study of other networks, such as signaling and other protein-protein interaction networks. PMID:16854231

  3. Prion protein induced signaling cascades in monocytes

    SciTech Connect

    Krebs, Bjarne; Dorner-Ciossek, Cornelia; Vassallo, Neville; Herms, Jochen; Kretzschmar, Hans A. . E-mail: Hans.Kretzschmar@med.uni-muenchen.de

    2006-02-03

    Prion proteins play a central role in transmission and pathogenesis of transmissible spongiform encephalopathies. The cellular prion protein (PrP{sup C}), whose physiological function remains elusive, is anchored to the surface of a variety of cell types including neurons and cells of the lymphoreticular system. In this study, we investigated the response of a mouse monocyte/macrophage cell line to exposure with PrP{sup C} fusion proteins synthesized with a human Fc-tag. PrP{sup C} fusion proteins showed an attachment to the surface of monocyte/macrophages in nanomolar concentrations. This was accompanied by an increase of cellular tyrosine phosphorylation as a result of activated signaling pathways. Detailed investigations exhibited activation of downstream pathways through a stimulation with PrP fusion proteins, which include phosphorylation of ERK{sub 1,2} and Akt kinase. Macrophages opsonize and present antigenic structures, contact lymphocytes, and deliver cytokines. The findings reported here may become the basis of understanding the molecular function of PrP{sup C} in monocytes and macrophages.

  4. Protein complexes and functional modules in molecular networks

    NASA Astrophysics Data System (ADS)

    Spirin, Victor; Mirny, Leonid A.

    2003-10-01

    Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

  5. NAPS: Network Analysis of Protein Structures.

    PubMed

    Chakrabarty, Broto; Parekh, Nita

    2016-07-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  6. TGF-beta signaling proteins and the Protein Ontology

    PubMed Central

    Arighi, Cecilia N; Liu, Hongfang; Natale, Darren A; Barker, Winona C; Drabkin, Harold; Blake, Judith A; Smith, Barry; Wu, Cathy H

    2009-01-01

    Background The Protein Ontology (PRO) is designed as a formal and principled Open Biomedical Ontologies (OBO) Foundry ontology for proteins. The components of PRO extend from a classification of proteins on the basis of evolutionary relationships at the homeomorphic level to the representation of the multiple protein forms of a gene, including those resulting from alternative splicing, cleavage and/or post-translational modifications. Focusing specifically on the TGF-beta signaling proteins, we describe the building, curation, usage and dissemination of PRO. Results PRO is manually curated on the basis of PrePRO, an automatically generated file with content derived from standard protein data sources. Manual curation ensures that the treatment of the protein classes and the internal and external relationships conform to the PRO framework. The current release of PRO is based upon experimental data from mouse and human proteins wherein equivalent protein forms are represented by single terms. In addition to the PRO ontology, the annotation of PRO terms is released as a separate PRO association file, which contains, for each given PRO term, an annotation from the experimentally characterized sub-types as well as the corresponding database identifiers and sequence coordinates. The annotations are added in the form of relationship to other ontologies. Whenever possible, equivalent forms in other species are listed to facilitate cross-species comparison. Splice and allelic variants, gene fusion products and modified protein forms are all represented as entities in the ontology. Therefore, PRO provides for the representation of protein entities and a resource for describing the associated data. This makes PRO useful both for proteomics studies where isoforms and modified forms must be differentiated, and for studies of biological pathways, where representations need to take account of the different ways in which the cascade of events may depend on specific protein

  7. Identifying the hub proteins from complicated membrane protein network systems.

    PubMed

    Shen, Yi-Zhen; Ding, Yong-Sheng; Gu, Quan; Chou, Kuo-Chen

    2010-05-01

    The so-called "hub proteins" are those proteins in a protein-protein interaction network system that have remarkably higher interaction relations (or degrees) than the others. Therefore, the information of hub proteins can provide very useful insights for selecting or prioritizing targets during drug development. In this paper, by combining the multi-agent-based method with the graphical spectrum analysis and immune-genetic algorithm, a novel simulator for identifying the hub proteins from membrane protein interaction networks is proposed. As a demonstration of using the simulator, two hub membrane proteins, YPL227C and YIL147C, were identified from a complicated network system consisting of 1500 membrane proteins. Meanwhile, along with the two identified hub proteins, their molecular functions, biological processes, and cellular components were also revealed. It is anticipated that the hub-protein-simulator may become a very useful tool for system biology and drug development, particularly in deciphering unknown protein functions, determining protein complexes, and in identifying the key targets from a complicated disease system. PMID:20507268

  8. Embryonic stem cells: protein interaction networks*

    PubMed Central

    Ng, Patricia Miang-Lon; Lufkin, Thomas

    2012-01-01

    Embryonic stem cells have the ability to differentiate into nearly all cell types. However, the molecular mechanism of its pluripotency is still unclear. Oct3/4, Sox2 and Nanog are important factors of pluripotency. Oct3/4 (hereafter referred to as Oct4), in particular, has been an irreplaceable factor in the induction of pluripotency in adult cells. Proteins interacting with Oct4 and Nanog have been identified via affinity purification and mass spectrometry. These data, together with iterative purifications of interacting proteins allowed a protein interaction network to be constructed. The network currently includes 77 transcription factors, all of which are interconnected in one network. In-depth studies of some of these transcription factors show that they all recruit the NuRD complex. Hence, transcription factor clustering and chromosomal remodeling are key mechanism used by embryonic stem cells. Studies using RNA interference suggest that more pluripotency genes are yet to be discovered via protein-protein interactions. More work is required to complete and curate the embryonic stem cell protein interaction network. Analysis of a saturated protein interaction network by system biology tools can greatly aid in the understanding of the embryonic stem cell pluripotency network. PMID:22639699

  9. NAPS: Network Analysis of Protein Structures

    PubMed Central

    Chakrabarty, Broto; Parekh, Nita

    2016-01-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  10. Dynamic interactions of proteins in complex networks

    SciTech Connect

    Appella, E.; Anderson, C.

    2009-10-01

    Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact with the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

  11. Fluorescent protein-based biosensors: resolving spatiotemporal dynamics of signaling

    PubMed Central

    DiPilato, Lisa M.; Zhang, Jin

    2009-01-01

    Summary Cellular processes are orchestrated by the precise coordination and regulation of molecular events in the cell. Fluorescent protein-based biosensors coupled with live-cell imaging have enabled the visualization of these events in real time and helped shape some of the current concepts of signal transduction, such as spatial compartmentation. The quantitative information produced by these tools has been incorporated into mathematical models that are capable of predicting highly complex and dynamic behaviors of cellular signaling networks, thus providing a systems level understanding of how pathways interact to produce a functional response. Finally, with technological advances in high throughput and in vivo imaging, these molecular tools promise to continually engender significant contributions to our understanding of cellular processes under normal and diseased conditions. PMID:19910237

  12. Fluorescent protein-based biosensors: resolving spatiotemporal dynamics of signaling.

    PubMed

    DiPilato, Lisa M; Zhang, Jin

    2010-02-01

    Cellular processes are orchestrated by the precise coordination and regulation of molecular events in the cell. Fluorescent protein-based biosensors coupled with live-cell imaging have enabled the visualization of these events in real time and helped shape some of the current concepts of signal transduction, such as spatial compartmentation. The quantitative information produced by these tools has been incorporated into mathematical models that are capable of predicting highly complex and dynamic behaviors of cellular signaling networks, thus providing a systems level understanding of how pathways interact to produce a functional response. Finally, with technological advances in high-throughput and in vivo imaging, these molecular tools promise to continually engender significant contributions to our understanding of cellular processes under normal and diseased conditions.

  13. Dopamine D1 signaling organizes network dynamics underlying working memory

    PubMed Central

    Roffman, Joshua L.; Tanner, Alexandra S.; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J.; Ho, New Fei; Nitenson, Adam Z.; Chonde, Daniel B.; Greve, Douglas N.; Abi-Dargham, Anissa; Buckner, Randy L.; Manoach, Dara S.; Rosen, Bruce R.; Hooker, Jacob M.; Catana, Ciprian

    2016-01-01

    Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory–emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits. PMID:27386561

  14. Eukaryotic G Protein Signaling Evolved to Require G Protein–Coupled Receptors for Activation

    PubMed Central

    Bradford, William; Buckholz, Adam; Morton, John; Price, Collin; Jones, Alan M.; Urano, Daisuke

    2016-01-01

    Although bioinformatic analysis of the increasing numbers of diverse genome sequences and amount of functional data has provided insight into the evolution of signaling networks, bioinformatics approaches have limited application for understanding the evolution of highly divergent protein families. We used biochemical analyses to determine the in vitro properties of selected divergent components of the heterotrimeric guanine nucleotide–binding protein (G protein) signaling network to investigate signaling network evolution. In animals, G proteins are activated by cell-surface seven-transmembrane (7TM) receptors, which are named G protein–coupled receptors (GPCRs) and function as guanine nucleotide exchange factors (GEFs). In contrast, the plant G protein is intrinsically active, and a 7TM protein terminates G protein activity by functioning as a guanosine triphosphatase–activating protein (GAP). We showed that ancient regulation of the G protein active state is GPCR-independent and “self-activating,” a property that is maintained in Bikonts, one of the two fundamental evolutionary clades containing eukaryotes, whereas G proteins of the other clade, the Unikonts, evolved from being GEF-independent to being GEF-dependent. Self-activating G proteins near the base of the Eukaryota are controlled by 7TM-GAPs, suggesting that the ancestral regulator of G protein activation was a GAP-functioning receptor, not a GEF-functioning GPCR. Our findings indicate that the GPCR paradigm describes a recently evolved network architecture found in a relatively small group of Eukaryota and suggest that the evolution of signaling network architecture is constrained by the availability of molecules that control the activation state of nexus proteins. PMID:23695163

  15. Heat dissipation guides activation in signaling proteins

    PubMed Central

    Weber, Jeffrey K.; Shukla, Diwakar; Pande, Vijay S.

    2015-01-01

    Life is fundamentally a nonequilibrium phenomenon. At the expense of dissipated energy, living things perform irreversible processes that allow them to propagate and reproduce. Within cells, evolution has designed nanoscale machines to do meaningful work with energy harnessed from a continuous flux of heat and particles. As dictated by the Second Law of Thermodynamics and its fluctuation theorem corollaries, irreversibility in nonequilibrium processes can be quantified in terms of how much entropy such dynamics produce. In this work, we seek to address a fundamental question linking biology and nonequilibrium physics: can the evolved dissipative pathways that facilitate biomolecular function be identified by their extent of entropy production in general relaxation processes? We here synthesize massive molecular dynamics simulations, Markov state models (MSMs), and nonequilibrium statistical mechanical theory to probe dissipation in two key classes of signaling proteins: kinases and G-protein–coupled receptors (GPCRs). Applying machinery from large deviation theory, we use MSMs constructed from protein simulations to generate dynamics conforming to positive levels of entropy production. We note the emergence of an array of peaks in the dynamical response (transient analogs of phase transitions) that draw the proteins between distinct levels of dissipation, and we see that the binding of ATP and agonist molecules modifies the observed dissipative landscapes. Overall, we find that dissipation is tightly coupled to activation in these signaling systems: dominant entropy-producing trajectories become localized near important barriers along known biological activation pathways. We go on to classify an array of equilibrium and nonequilibrium molecular switches that harmonize to promote functional dynamics. PMID:26240354

  16. Construction of cell type-specific logic models of signaling networks using CellNOpt.

    PubMed

    Morris, Melody K; Melas, Ioannis; Saez-Rodriguez, Julio

    2013-01-01

    Mathematical models are useful tools for understanding protein signaling networks because they provide an integrated view of pharmacological and toxicological processes at the molecular level. Here we describe an approach previously introduced based on logic modeling to generate cell-specific, mechanistic and predictive models of signal transduction. Models are derived from a network encoding prior knowledge that is trained to signaling data, and can be either binary (based on Boolean logic) or quantitative (using a recently developed formalism, constrained fuzzy logic). The approach is implemented in the freely available tool CellNetOptimizer (CellNOpt). We explain the process CellNOpt uses to train a prior knowledge network to data and illustrate its application with a toy example as well as a realistic case describing signaling networks in the HepG2 liver cancer cell line.

  17. Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome.

    PubMed

    Poirot, Olivier; Timsit, Youri

    2016-01-01

    From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through "molecular synapses", ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the "sensory-proteins" innervate the functional ribosomal sites, while the "inter-proteins" interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing. PMID:27225526

  18. Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

    NASA Astrophysics Data System (ADS)

    Yeger-Lotem, Esti; Sattath, Shmuel; Kashtan, Nadav; Itzkovitz, Shalev; Milo, Ron; Pinter, Ron Y.; Alon, Uri; Margalit, Hanah

    2004-04-01

    Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

  19. The N and C Termini of ZO-1 Are Surrounded by Distinct Proteins and Functional Protein Networks*

    PubMed Central

    Van Itallie, Christina M.; Aponte, Angel; Tietgens, Amber Jean; Gucek, Marjan; Fredriksson, Karin; Anderson, James Melvin

    2013-01-01

    The proteins and functional protein networks of the tight junction remain incompletely defined. Among the currently known proteins are barrier-forming proteins like occludin and the claudin family; scaffolding proteins like ZO-1; and some cytoskeletal, signaling, and cell polarity proteins. To define a more complete list of proteins and infer their functional implications, we identified the proteins that are within molecular dimensions of ZO-1 by fusing biotin ligase to either its N or C terminus, expressing these fusion proteins in Madin-Darby canine kidney epithelial cells, and purifying and identifying the resulting biotinylated proteins by mass spectrometry. Of a predicted proteome of ∼9000, we identified more than 400 proteins tagged by biotin ligase fused to ZO-1, with both identical and distinct proteins near the N- and C-terminal ends. Those proximal to the N terminus were enriched in transmembrane tight junction proteins, and those proximal to the C terminus were enriched in cytoskeletal proteins. We also identified many unexpected but easily rationalized proteins and verified partial colocalization of three of these proteins with ZO-1 as examples. In addition, functional networks of interacting proteins were tagged, such as the basolateral but not apical polarity network. These results provide a rich inventory of proteins and potential novel insights into functions and protein networks that should catalyze further understanding of tight junction biology. Unexpectedly, the technique demonstrates high spatial resolution, which could be generally applied to defining other subcellular protein compartmentalization. PMID:23553632

  20. Multiplexed imaging of intracellular protein networks.

    PubMed

    Grecco, Hernán E; Imtiaz, Sarah; Zamir, Eli

    2016-08-01

    Cellular functions emerge from the collective action of a large number of different proteins. Understanding how these protein networks operate requires monitoring their components in intact cells. Due to intercellular and intracellular molecular variability, it is important to monitor simultaneously multiple components at high spatiotemporal resolution. However, inherent trade-offs narrow the boundaries of achievable multiplexed imaging. Pushing these boundaries is essential for a better understanding of cellular processes. Here the motivations, challenges and approaches for multiplexed imaging of intracellular protein networks are discussed. © 2016 International Society for Advancement of Cytometry. PMID:27183498

  1. Neuroblastoma Tyrosine Kinase Signaling Networks Involve FYN and LYN in Endosomes and Lipid Rafts

    PubMed Central

    Guo, Ailan; Stokes, Matthew P.; Kuehn, Emily D.; George, Lynn; Comb, Michael; Grimes, Mark L.

    2015-01-01

    Protein phosphorylation plays a central role in creating a highly dynamic network of interacting proteins that reads and responds to signals from growth factors in the cellular microenvironment. Cells of the neural crest employ multiple signaling mechanisms to control migration and differentiation during development. It is known that defects in these mechanisms cause neuroblastoma, but how multiple signaling pathways interact to govern cell behavior is unknown. In a phosphoproteomic study of neuroblastoma cell lines and cell fractions, including endosomes and detergent-resistant membranes, 1622 phosphorylated proteins were detected, including more than half of the receptor tyrosine kinases in the human genome. Data were analyzed using a combination of graph theory and pattern recognition techniques that resolve data structure into networks that incorporate statistical relationships and protein-protein interaction data. Clusters of proteins in these networks are indicative of functional signaling pathways. The analysis indicates that receptor tyrosine kinases are functionally compartmentalized into distinct collaborative groups distinguished by activation and intracellular localization of SRC-family kinases, especially FYN and LYN. Changes in intracellular localization of activated FYN and LYN were observed in response to stimulation of the receptor tyrosine kinases, ALK and KIT. The results suggest a mechanism to distinguish signaling responses to activation of different receptors, or combinations of receptors, that govern the behavior of the neural crest, which gives rise to neuroblastoma. PMID:25884760

  2. Photoreceptor signaling networks in plant responses to shade.

    PubMed

    Casal, Jorge J

    2013-01-01

    The dynamic light environment of vegetation canopies is perceived by phytochromes, cryptochromes, phototropins, and UV RESISTANCE LOCUS 8 (UVR8). These receptors control avoidance responses to preclude exposure to limiting or excessive light and acclimation responses to cope with conditions that cannot be avoided. The low red/far-red ratios of shade light reduce phytochrome B activity, which allows PHYTOCHROME INTERACTING FACTORS (PIFs) to directly activate the transcription of auxin-synthesis genes, leading to shade-avoidance responses. Direct PIF interaction with DELLA proteins links gibberellin and brassinosteroid signaling to shade avoidance. Shade avoidance also requires CONSTITUTIVE PHOTOMORPHOGENESIS 1 (COP1), a target of cryptochromes, phytochromes, and UVR8. Multiple regulatory loops and the input of the circadian clock create a complex network able to respond even to subtle threats of competition with neighbors while still compensating for major environmental fluctuations such as the day-night cycles.

  3. Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics.

    PubMed

    Karthikeyan, Bagavathy Shanmugam; Akbarsha, Mohammad Abdulkader; Parthasarathy, Subbiah

    2016-06-21

    Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way. PMID:27194593

  4. Protein enriched pasta: structure and digestibility of its protein network.

    PubMed

    Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

    2016-02-01

    Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

  5. Protein enriched pasta: structure and digestibility of its protein network.

    PubMed

    Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

    2016-02-01

    Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest. PMID:26829164

  6. The calcineurin signaling network evolves via conserved kinase-phosphatase modules that transcend substrate identity.

    PubMed

    Goldman, Aaron; Roy, Jagoree; Bodenmiller, Bernd; Wanka, Stefanie; Landry, Christian R; Aebersold, Ruedi; Cyert, Martha S

    2014-08-01

    To define a functional network for calcineurin, the conserved Ca(2+)/calmodulin-regulated phosphatase, we systematically identified its substrates in S. cerevisiae using phosphoproteomics and bioinformatics, followed by copurification and dephosphorylation assays. This study establishes new calcineurin functions and reveals mechanisms that shape calcineurin network evolution. Analyses of closely related yeasts show that many proteins were recently recruited to the network by acquiring a calcineurin-recognition motif. Calcineurin substrates in yeast and mammals are distinct due to network rewiring but, surprisingly, are phosphorylated by similar kinases. We postulate that corecognition of conserved substrate features, including phosphorylation and docking motifs, preserves calcineurin-kinase opposition during evolution. One example we document is a composite docking site that confers substrate recognition by both calcineurin and MAPK. We propose that conserved kinase-phosphatase pairs define the architecture of signaling networks and allow other connections between kinases and phosphatases to develop that establish common regulatory motifs in signaling networks.

  7. Radar signal categorization using a neural network

    NASA Technical Reports Server (NTRS)

    Anderson, James A.; Gately, Michael T.; Penz, P. Andrew; Collins, Dean R.

    1991-01-01

    Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications.

  8. NetworkAnalyst--integrative approaches for protein-protein interaction network analysis and visual exploration.

    PubMed

    Xia, Jianguo; Benner, Maia J; Hancock, Robert E W

    2014-07-01

    Biological network analysis is a powerful approach to gain systems-level understanding of patterns of gene expression in different cell types, disease states and other biological/experimental conditions. Three consecutive steps are required--identification of genes or proteins of interest, network construction and network analysis and visualization. To date, researchers have to learn to use a combination of several tools to accomplish this task. In addition, interactive visualization of large networks has been primarily restricted to locally installed programs. To address these challenges, we have developed NetworkAnalyst, taking advantage of state-of-the-art web technologies, to enable high performance network analysis with rich user experience. NetworkAnalyst integrates all three steps and presents the results via a powerful online network visualization framework. Users can upload gene or protein lists, single or multiple gene expression datasets to perform comprehensive gene annotation and differential expression analysis. Significant genes are mapped to our manually curated protein-protein interaction database to construct relevant networks. The results are presented through standard web browsers for network analysis and interactive exploration. NetworkAnalyst supports common functions for network topology and module analyses. Users can easily search, zoom and highlight nodes or modules, as well as perform functional enrichment analysis on these selections. The networks can be customized with different layouts, colors or node sizes, and exported as PNG, PDF or GraphML files. Comprehensive FAQs, tutorials and context-based tips and instructions are provided. NetworkAnalyst currently supports protein-protein interaction network analysis for human and mouse and is freely available at http://www.networkanalyst.ca. PMID:24861621

  9. Network Compression as a Quality Measure for Protein Interaction Networks

    PubMed Central

    Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

    2012-01-01

    With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

  10. Bio-inspired signal transduction with heterogeneous networks of nanoscillators

    NASA Astrophysics Data System (ADS)

    Cervera, Javier; Manzanares, José A.; Mafé, Salvador

    2012-02-01

    Networks of single-electron transistors mimic some of the essential properties of neuron populations, because weak electrical signals trigger network oscillations with a frequency proportional to the input signal. Input potentials representing the pixel gray level of a grayscale image can then be converted into rhythms and the image can be recovered from these rhythms. Networks of non-identical nanoscillators complete the noisy transduction more reliably than identical ones. These results are important for signal processing schemes and could support recent studies suggesting that neuronal variability enhances the processing of biological information.

  11. Pairwise alignment of protein interaction networks.

    PubMed

    Koyutürk, Mehmet; Kim, Yohan; Topkara, Umut; Subramaniam, Shankar; Szpankowski, Wojciech; Grama, Ananth

    2006-03-01

    With an ever-increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discovery of conserved patterns in these networks becomes an important problem. Although available data on protein-protein interactions is currently limited, recently developed algorithms have been shown to convey novel biological insights through employment of elegant mathematical models. The main challenge in aligning PPI networks is to define a graph theoretical measure of similarity between graph structures that captures underlying biological phenomena accurately. In this respect, modeling of conservation and divergence of interactions, as well as the interpretation of resulting alignments, are important design parameters. In this paper, we develop a framework for comprehensive alignment of PPI networks, which is inspired by duplication/divergence models that focus on understanding the evolution of protein interactions. We propose a mathematical model that extends the concepts of match, mismatch, and gap in sequence alignment to that of match, mismatch, and duplication in network alignment and evaluates similarity between graph structures through a scoring function that accounts for evolutionary events. By relying on evolutionary models, the proposed framework facilitates interpretation of resulting alignments in terms of not only conservation but also divergence of modularity in PPI networks. Furthermore, as in the case of sequence alignment, our model allows flexibility in adjusting parameters to quantify underlying evolutionary relationships. Based on the proposed model, we formulate PPI network alignment as an optimization problem and present fast algorithms to solve this problem. Detailed experimental results from an implementation of the proposed framework show that our algorithm is able to discover conserved interaction patterns very effectively, in terms of both accuracies and computational

  12. Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

    PubMed

    Yang, Lei; Zhao, Xudong; Tang, Xianglong

    2014-01-01

    Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

  13. SP-NET: A draft signal processor network protocol

    NASA Astrophysics Data System (ADS)

    Burns, David M.

    SP-net, a synchronous high-speed switched network that has been designed for signal processor backplanes, is discussed. The network uses bit-slicing to improve fault tolerance and to allow growth in the width of the data path. In addition, single-bit error detection has been included in the protocol. Although no company at present is building a network to the draft SP-net specifications, SP-net has several similarities to signal processor network designs by major defense contractors.

  14. An extended signal control strategy for urban network traffic flow

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Tian, Fuli; Shi, Zhongke

    2016-03-01

    Traffic flow patterns are in general repeated on a daily or weekly basis. To improve the traffic conditions by using the inherent repeatability of traffic flow, a novel signal control strategy for urban networks was developed via iterative learning control (ILC) approach. Rigorous analysis shows that the proposed learning control method can guarantee the asymptotic convergence. The impacts of the ILC-based signal control strategy on the macroscopic fundamental diagram (MFD) were analyzed by simulations on a test road network. The results show that the proposed ILC strategy can evenly distribute the accumulation in the network and improve the network mobility.

  15. Interaction Energy Based Protein Structure Networks

    PubMed Central

    Vijayabaskar, M.S.; Vishveshwara, Saraswathi

    2010-01-01

    The three-dimensional structure of a protein is formed and maintained by the noncovalent interactions among the amino-acid residues of the polypeptide chain. These interactions can be represented collectively in the form of a network. So far, such networks have been investigated by considering the connections based on distances between the amino-acid residues. Here we present a method of constructing the structure network based on interaction energies among the amino-acid residues in the protein. We have investigated the properties of such protein energy-based networks (PENs) and have shown correlations to protein structural features such as the clusters of residues involved in stability, formation of secondary and super-secondary structural units. Further we demonstrate that the analysis of PENs in terms of parameters such as hubs and shortest paths can provide a variety of biologically important information, such as the residues crucial for stabilizing the folded units and the paths of communication between distal residues in the protein. Finally, the energy regimes for different levels of stabilization in the protein structure have clearly emerged from the PEN analysis. PMID:21112295

  16. Integrative Signaling Networks of Membrane Guanylate Cyclases: Biochemistry and Physiology

    PubMed Central

    Sharma, Rameshwar K.; Duda, Teresa; Makino, Clint L.

    2016-01-01

    This monograph presents a historical perspective of cornerstone developments on the biochemistry and physiology of mammalian membrane guanylate cyclases (MGCs), highlighting contributions made by the authors and their collaborators. Upon resolution of early contentious studies, cyclic GMP emerged alongside cyclic AMP, as an important intracellular second messenger for hormonal signaling. However, the two signaling pathways differ in significant ways. In the cyclic AMP pathway, hormone binding to a G protein coupled receptor leads to stimulation or inhibition of an adenylate cyclase, whereas the cyclic GMP pathway dispenses with intermediaries; hormone binds to an MGC to affect its activity. Although the cyclic GMP pathway is direct, it is by no means simple. The modular design of the molecule incorporates regulation by ATP binding and phosphorylation. MGCs can form complexes with Ca2+-sensing subunits that either increase or decrease cyclic GMP synthesis, depending on subunit identity. In some systems, co-expression of two Ca2+ sensors, GCAP1 and S100B with ROS-GC1 confers bimodal signaling marked by increases in cyclic GMP synthesis when intracellular Ca2+ concentration rises or falls. Some MGCs monitor or are modulated by carbon dioxide via its conversion to bicarbonate. One MGC even functions as a thermosensor as well as a chemosensor; activity reaches a maximum with a mild drop in temperature. The complexity afforded by these multiple limbs of operation enables MGC networks to perform transductions traditionally reserved for G protein coupled receptors and Transient Receptor Potential (TRP) ion channels and to serve a diverse array of functions, including control over cardiac vasculature, smooth muscle relaxation, blood pressure regulation, cellular growth, sensory transductions, neural plasticity and memory. PMID:27695398

  17. Integrative Signaling Networks of Membrane Guanylate Cyclases: Biochemistry and Physiology

    PubMed Central

    Sharma, Rameshwar K.; Duda, Teresa; Makino, Clint L.

    2016-01-01

    This monograph presents a historical perspective of cornerstone developments on the biochemistry and physiology of mammalian membrane guanylate cyclases (MGCs), highlighting contributions made by the authors and their collaborators. Upon resolution of early contentious studies, cyclic GMP emerged alongside cyclic AMP, as an important intracellular second messenger for hormonal signaling. However, the two signaling pathways differ in significant ways. In the cyclic AMP pathway, hormone binding to a G protein coupled receptor leads to stimulation or inhibition of an adenylate cyclase, whereas the cyclic GMP pathway dispenses with intermediaries; hormone binds to an MGC to affect its activity. Although the cyclic GMP pathway is direct, it is by no means simple. The modular design of the molecule incorporates regulation by ATP binding and phosphorylation. MGCs can form complexes with Ca2+-sensing subunits that either increase or decrease cyclic GMP synthesis, depending on subunit identity. In some systems, co-expression of two Ca2+ sensors, GCAP1 and S100B with ROS-GC1 confers bimodal signaling marked by increases in cyclic GMP synthesis when intracellular Ca2+ concentration rises or falls. Some MGCs monitor or are modulated by carbon dioxide via its conversion to bicarbonate. One MGC even functions as a thermosensor as well as a chemosensor; activity reaches a maximum with a mild drop in temperature. The complexity afforded by these multiple limbs of operation enables MGC networks to perform transductions traditionally reserved for G protein coupled receptors and Transient Receptor Potential (TRP) ion channels and to serve a diverse array of functions, including control over cardiac vasculature, smooth muscle relaxation, blood pressure regulation, cellular growth, sensory transductions, neural plasticity and memory.

  18. Analysis and logical modeling of biological signaling transduction networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  19. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  20. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  1. Sorting and targeting of melanosomal membrane proteins: signals, pathways, and mechanisms.

    PubMed

    Setaluri, V

    2000-06-01

    Newly synthesized melanosomal proteins, like many other cellular proteins, traverse through a series of intracellular compartments en route to melanosomes. Entry and exit of proteins through these compartments is orchestrated by cellular sorting machinery that recognize specific sorting signals. Melanosomal membrane proteins begin their intracellular journey upon co-translational importation into the endoplasmic reticulum (ER). The biosynthetic output of tyrosinase, the key melanogenic enzyme, appears to be regulated by quality-control events at the ER, the 'port of entry' to the secretory pathway. Following maturation in the ER and through the Golgi, the sorting of these proteins in the trans-Golgi network for intracellular retention and transport along endosome/lysosome pathway requires cytoplasmically exposed signals. A di-leucine motif, present in the cytoplasmic tails of most melanosomal proteins, and its interaction with adaptor protein (AP) complexes, specifically AP-3, are critical for these events. Defects in sorting signals and the cytosolic components that interact with these signals result in a number of murine coat color phenotypes and cause human pigmentary disorders. Thus, missense or frame-shift mutations that produce truncated tyrosinase lacking the melanosomal sorting signal(s) appear to be responsible for murine platinum coat color phenotypes and a proportion of human oculocutaneous albinism-1; mutations in AP-3 appear to be responsible for the mocha phenotype in mice and Hermansky-Pudlak-like syndrome in man. Additional signals and sorting steps downstream of AP-3 appear to be required for endosomal sorting and targeting proteins to melanosomes. Signals and mechanisms that sequester melanosomal proteins from endosomes/lysosomes are not understood. Potential candidates that mediate such processes include proteins encoded by lyst and pallid genes. The common occurrence of abnormalities in melanosomes in many storage-pool disorders suggests that

  2. An Interaction Library for the FcεRI Signaling Network.

    PubMed

    Chylek, Lily A; Holowka, David A; Baird, Barbara A; Hlavacek, William S

    2014-01-01

    Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein-protein and protein-lipid interactions. This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP3 at the plasma membrane and the soluble second messenger IP3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.

  3. Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

    PubMed Central

    Poirot, Olivier; Timsit, Youri

    2016-01-01

    From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing. PMID:27225526

  4. Signal transduction in the activation of spermatozoa compared to other signalling pathways: a biological networks study.

    PubMed

    Bernabò, Nicola; Mattioli, Mauro; Barboni, Barbara

    2015-01-01

    In this paper we represented Spermatozoa Activation (SA) the process that leads male gametes to reach their fertilising ability of sea urchin, Caenorhabditis elegans and human as biological networks, i.e. as networks of nodes (molecules) linked by edges (their interactions). Then, we compared them with networks representing ten pathways of relevant physio-pathological importance and with a computer-generated network. We have found that the number of nodes and edges composing each network is not related with the amount of published papers on each specific topic and that all the topological parameters examined are similar in all the networks, thus conferring them a scale free topology and small world behaviour. In conclusion, SA topology, independently from the reproductive biology of considered organism, as others signalling networks is characterised by robustness against random failure, controllability and efficiency in signal transmission. PMID:26489142

  5. Signaling and Gene Regulatory Networks Governing Definitive Endoderm Derivation From Pluripotent Stem Cells.

    PubMed

    Mohammadnia, Abdulshakour; Yaqubi, Moein; Pourasgari, Farzaneh; Neely, Eric; Fallahi, Hossein; Massumi, Mohammad

    2016-09-01

    The generation of definitive endoderm (DE) from pluripotent stem cells (PSCs) is a fundamental stage in the formation of highly organized visceral organs, such as the liver and pancreas. Currently, there is a need for a comprehensive study that illustrates the involvement of different signaling pathways and their interactions in the derivation of DE cells from PSCs. This study aimed to identify signaling pathways that have the greatest influence on DE formation using analyses of transcriptional profiles, protein-protein interactions, protein-DNA interactions, and protein localization data. Using this approach, signaling networks involved in DE formation were constructed using systems biology and data mining tools, and the validity of the predicted networks was confirmed experimentally by measuring the mRNA levels of hub genes in several PSCs-derived DE cell lines. Based on our analyses, seven signaling pathways, including the BMP, ERK1-ERK2, FGF, TGF-beta, MAPK, Wnt, and PIP signaling pathways and their interactions, were found to play a role in the derivation of DE cells from PSCs. Lastly, the core gene regulatory network governing this differentiation process was constructed. The results of this study could improve our understanding surrounding the efficient generation of DE cells for the regeneration of visceral organs. J. Cell. Physiol. 231: 1994-2006, 2016. © 2016 Wiley Periodicals, Inc. PMID:26755186

  6. Identification of four nuclear transport signal-binding proteins that interact with diverse transport signals.

    PubMed

    Yamasaki, L; Kanda, P; Lanford, R E

    1989-07-01

    The transport of proteins into the nucleus requires not only the presence of a nuclear transport signal on the targeted protein but also the signal recognition proteins and the nuclear pore translocation apparatus. Complicating the search for the signal recognition proteins is the fact that the nuclear transport signals identified share little obvious homology. In this study, synthetic peptides homologous to the nuclear transport signals from the simian virus 40 large T antigen, Xenopus oocyte nucleoplasmin, adenovirus E1A, and Saccharomyces cerevisiae MAT alpha 2 proteins were coupled to a UV-photoactivable cross-linker and iodinated for use in an in vitro cross-linking reaction with cellular lysates. Four proteins, p140, p100, p70, and p55, which specifically interacted with the nuclear transport signal peptides were identified. Unique patterns of reactivity were observed with closely related pairs of nuclear transport signal peptides. Competition experiments with labeled and unlabeled peptides demonstrated that heterologous signals were able to bind the same protein and suggested that diverse signals use a common transport pathway. The subcellular distribution of the four nuclear transport signal-binding proteins suggested that nuclear transport involves both cytoplasmic and nuclear receptors. The four proteins were not bound by wheat germ agglutinin and were not associated tightly with the nuclear pore complex.

  7. Emerging Roles of Protein Deamidation in Innate Immune Signaling

    PubMed Central

    Zhao, Jun; Li, Junhua; Xu, Simin

    2016-01-01

    Protein deamidation has been considered a nonenzymatic process associated with protein functional decay or “aging.” Recent studies implicate protein deamidation in regulating signal transduction in fundamental biological processes, such as innate immune responses. Work investigating gammaherpesviruses and bacterial pathogens indicates that microbial pathogens deploy deamidases or enzyme-deficient homologues (pseudoenzymes) to induce deamidation of key signaling components and evade host immune responses. Here, we review studies on protein deamidation in innate immune signaling and present several imminent questions concerning the roles of protein deamidation in infection and immunity. PMID:26889032

  8. Network measures for protein folding state discrimination

    PubMed Central

    Menichetti, Giulia; Fariselli, Piero; Remondini, Daniel

    2016-01-01

    Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there is not a first-principle model to explain this different behavior. We exploit the network properties of protein structures by introducing novel observables to address the problem of classifying the different types of folding kinetics. These observables display a plain physical meaning, in terms of vibrational modes, possible configurations compatible with the native protein structure, and folding cooperativity. The relevance of these observables is supported by a classification performance up to 90%, even with simple classifiers such as discriminant analysis. PMID:27464796

  9. Network measures for protein folding state discrimination.

    PubMed

    Menichetti, Giulia; Fariselli, Piero; Remondini, Daniel

    2016-01-01

    Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there is not a first-principle model to explain this different behavior. We exploit the network properties of protein structures by introducing novel observables to address the problem of classifying the different types of folding kinetics. These observables display a plain physical meaning, in terms of vibrational modes, possible configurations compatible with the native protein structure, and folding cooperativity. The relevance of these observables is supported by a classification performance up to 90%, even with simple classifiers such as discriminant analysis. PMID:27464796

  10. Integrated signaling networks in plant responses to sedentary endoparasitic nematodes: a perspective.

    PubMed

    Li, Ruijuan; Rashotte, Aaron M; Singh, Narendra K; Weaver, David B; Lawrence, Kathy S; Locy, Robert D

    2015-01-01

    Sedentary plant endoparasitic nematodes can cause detrimental yield losses in crop plants making the study of detailed cellular, molecular, and whole plant responses to them a subject of importance. In response to invading nematodes and nematode-secreted effectors, plant susceptibility/resistance is mainly determined by the coordination of different signaling pathways including specific plant resistance genes or proteins, plant hormone synthesis and signaling pathways, as well as reactive oxygen signals that are generated in response to nematode attack. Crosstalk between various nematode resistance-related elements can be seen as an integrated signaling network regulated by transcription factors and small RNAs at the transcriptional, posttranscriptional, and/or translational levels. Ultimately, the outcome of this highly controlled signaling network determines the host plant susceptibility/resistance to nematodes.

  11. Human Identification with Electrocardiogram Signals: a Neural Network Approach

    NASA Astrophysics Data System (ADS)

    Wan, Yongbo; Yao, Jianchu

    2009-05-01

    This paper presents a neural network developed to identify human subjects using electrocardiogram (ECG) signals collected from an "in-house" wearable electrocardiogram (ECG) sensor. In this project, noises were first removed from the raw signals with wavelet filters. ECG cycles were then extracted from the filtered signals and decomposed into wavelet coefficient structures. These coefficient structures were used as input vectors to a 3-layer feedforward neural network that generates the identification results. In the current study, 61 datasets collected from 23 subjects were utilized to train the neural network, which thereafter was tested with 15 new datasets from 15 different subjects. All the 15 subjects in the experiment were successfully identified. The testing results demonstrate that the neural network is effective.

  12. Protein-protein interaction network analysis of cirrhosis liver disease

    PubMed Central

    Safaei, Akram; Rezaei Tavirani, Mostafa; Arefi Oskouei, Afsaneh; Zamanian Azodi, Mona; Mohebbi, Seyed Reza; Nikzamir, Abdol Rahim

    2016-01-01

    Aim: Evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. Background: In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. Evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. Since the early detection of cirrhosis is a clinical problem, achieving a sensitive, specific and predictive novel method based on biomarkers is an important task. Methods: Essential analysis, such as gene ontology (GO) enrichment and protein-protein interactions (PPI) was undergone EXPASy, STRING Database and DAVID Bioinformatics Resources query. Results: Based on GO analysis, most of proteins are located in the endoplasmic reticulum lumen, intracellular organelle lumen, membrane-enclosed lumen, and extracellular region. The relevant molecular functions are actin binding, metal ion binding, cation binding and ion binding. Cell adhesion, biological adhesion, cellular amino acid derivative, metabolic process and homeostatic process are the related processes. Protein-protein interaction network analysis introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta), lectin, Lectin galactoside-binding soluble 3 binding protein and apolipoprotein A-I) as hub and bottleneck proteins. Conclusion: Our result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease. More investigation of above mentioned proteins will provide a better understanding of cirrhosis disease. PMID:27099671

  13. Network-Based Protein Biomarker Discovery Platforms

    PubMed Central

    Kim, Minhyung

    2016-01-01

    The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms. PMID:27103885

  14. Timing and time signal distribution in digital communications networks

    NASA Astrophysics Data System (ADS)

    Kihara, Masami; Imaoka, Atushi

    1992-06-01

    The timing signal distribution characteristics of a digital communications network are evaluated to determine the Maximum Time Interval Error (MTIE) of the network; reference is made to the performance of network components such as transmission systems, slave clocks and timing distribution systems in intraoffices. The MTIE of each component is measured and used to determine the allowable MTIE of that component. The maximum number of slave node chains is shown to be 20. Time signal distribution performance is detailed. It is shown that time synchronization accuracy is of the order of submicroseconds between nodes separated by 2400 km over a two year period. For intra-office time signal distribution, the relative time accuracy is less than 3 nanoseconds using an 8 Mb/s round trip digital interface to connect a time signal supply in an office to dispersed equipment.

  15. Structural permeability of complex networks to control signals

    NASA Astrophysics Data System (ADS)

    Lo Iudice, Francesco; Garofalo, Franco; Sorrentino, Francesco

    2015-09-01

    Many biological, social and technological systems can be described as complex networks. The goal of affecting their behaviour has motivated recent work focusing on the relationship between the network structure and its propensity to be controlled. While this work has provided insight into several relevant problems, a comprehensive approach to address partial and complete controllability of networks is still lacking. Here, we bridge this gap by developing a framework to maximize the diffusion of the control signals through a network, while taking into account physical and economic constraints that inevitably arise in applications. This approach allows us to introduce the network permeability, a unified metric of the propensity of a network to be controllable. The analysis of the permeability of several synthetic and real networks enables us to extract some structural features that deepen our quantitative understanding of the ease with which specific controllability requirements can be met.

  16. Predicting the fission yeast protein interaction network.

    PubMed

    Pancaldi, Vera; Saraç, Omer S; Rallis, Charalampos; McLean, Janel R; Převorovský, Martin; Gould, Kathleen; Beyer, Andreas; Bähler, Jürg

    2012-04-01

    A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein-protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70-80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).

  17. Designed Proteins To Modulate Cellular Networks

    PubMed Central

    Cortajarena, Aitziber L.; Liu, Tina Y.; Hochstrasser, Mark; Regan, Lynne

    2012-01-01

    A major challenge of protein design is to create useful new proteins that interact specifically with biological targets in living cells. Such binding modules have many potential applications, including the targeted perturbation of protein networks. As a general approach to create such modules, we designed a library with approximately 109 different binding specificities based on a small 3-tetratricopeptide repeat (TPR) motif framework. We employed a novel strategy, based on split GFP reassembly, to screen the library for modules with the desired binding specificity. Using this approach, we identified modules that bind tightly and specifically to Dss1, a small human protein that interacts with the tumor suppressor protein BRCA2. We showed that these modules also bind the yeast homologue of Dss1, Sem1. Furthermore, we demonstrated that these modules inhibit Sem1 activity in yeast. This strategy will be generally applicable to make novel genetically encoded tools for systems/synthetic biology applications. PMID:20020775

  18. The protist, Monosiga brevicollis, has a tyrosine kinase signaling network more elaborate and diverse than found in any known metazoan

    PubMed Central

    Manning, Gerard; Young, Susan L.; Miller, W. Todd; Zhai, Yufeng

    2008-01-01

    Tyrosine kinase signaling has long been considered a hallmark of intercellular communication, unique to multicellular animals. Our genomic analysis of the unicellular choanoflagellate Monosiga brevicollis discovers a remarkable count of 128 tyrosine kinases, 38 tyrosine phosphatases, and 123 phosphotyrosine (pTyr)-binding SH2 proteins, all higher counts than seen in any metazoan. This elaborate signaling network shows little orthology to metazoan counterparts yet displays many innovations reminiscent of metazoans. These include extracellular domains structurally related to those of metazoan receptor kinases, alternative methods for membrane anchoring and phosphotyrosine interaction in cytoplasmic kinases, and domain combinations that link kinases to small GTPase signaling and transcription. These proteins also display a wealth of combinations of known signaling domains. This uniquely divergent and elaborate signaling network illuminates the early evolution of pTyr signaling, explores innovative ways to traverse the cellular signaling circuitry, and shows extensive convergent evolution, highlighting pervasive constraints on pTyr signaling. PMID:18621719

  19. Apoptosis regulatory protein-protein interaction demonstrates hierarchical scale-free fractal network.

    PubMed

    Nafis, Shazia; Kalaiarasan, Ponnusamy; Brojen Singh, R K; Husain, Mohammad; Bamezai, Rameshwar N K

    2015-07-01

    Dysregulation or inhibition of apoptosis favors cancer and many other diseases. Understanding of the network interaction of the genes involved in apoptotic pathway, therefore, is essential, to look for targets of therapeutic intervention. Here we used the network theory methods, using experimentally validated 25 apoptosis regulatory proteins and identified important genes for apoptosis regulation, which demonstrated a hierarchical scale-free fractal protein-protein interaction network. TP53, BRCA1, UBIQ and CASP3 were recognized as a four key regulators. BRCA1 and UBIQ were also individually found to control highly clustered modules and play an important role in the stability of the overall network. The connection among the BRCA1, UBIQ and TP53 proteins was found to be important for regulation, which controlled their own respective communities and the overall network topology. The feedback loop regulation motif was identified among NPM1, BRCA1 and TP53, and these crucial motif topologies were also reflected in high frequency. The propagation of the perturbed signal from hubs was found to be active upto some distance, after which propagation started decreasing and TP53 was the most efficient signal propagator. From the functional enrichment analysis, most of the apoptosis regulatory genes associated with cardiovascular diseases and highly expressed in brain tissues were identified. Apart from TP53, BRCA1 was observed to regulate apoptosis by influencing motif, propagation of signals and module regulation, reflecting their biological significance. In future, biochemical investigation of the observed hub-interacting partners could provide further understanding about their role in the pathophysiology of cancer.

  20. Plant gravitropic signal transduction: A network analysis leads to gene discovery

    NASA Astrophysics Data System (ADS)

    Wyatt, Sarah

    Gravity plays a fundamental role in plant growth and development. Although a significant body of research has helped define the events of gravity perception, the role of the plant growth regulator auxin, and the mechanisms resulting in the gravity response, the events of signal transduction, those that link the biophysical action of perception to a biochemical signal that results in auxin redistribution, those that regulate the gravitropic effects on plant growth, remain, for the most part, a “black box.” Using a cold affect, dubbed the gravity persistent signal (GPS) response, we developed a mutant screen to specifically identify components of the signal transduction pathway. Cloning of the GPS genes have identified new proteins involved in gravitropic signaling. We have further exploited the GPS response using a multi-faceted approach including gene expression microarrays, proteomics analysis, and bioinformatics analysis and continued mutant analysis to identified additional genes, physiological and biochemical processes. Gene expression data provided the foundation of a regulatory network for gravitropic signaling. Based on these gene expression data and related data sets/information from the literature/repositories, we constructed a gravitropic signaling network for Arabidopsis inflorescence stems. To generate the network, both a dynamic Bayesian network approach and a time-lagged correlation coefficient approach were used. The dynamic Bayesian network added existing information of protein-protein interaction while the time-lagged correlation coefficient allowed incorporation of temporal regulation and thus could incorporate the time-course metric from the data set. Thus the methods complemented each other and provided us with a more comprehensive evaluation of connections. Each method generated a list of possible interactions associated with a statistical significance value. The two networks were then overlaid to generate a more rigorous, intersected

  1. An integrated signal transduction network of macrophage migration inhibitory factor.

    PubMed

    Subbannayya, Tejaswini; Variar, Prathyaksha; Advani, Jayshree; Nair, Bipin; Shankar, Subramanian; Gowda, Harsha; Saussez, Sven; Chatterjee, Aditi; Prasad, T S Keshava

    2016-06-01

    Macrophage migration inhibitory factor (MIF) is a glycosylated multi-functional protein that acts as an enzyme as well as a cytokine. MIF mediates its actions through a cell surface class II major histocompatibility chaperone, CD74 and co-receptors such as CD44, CXCR2, CXCR4 or CXCR7. MIF has been implicated in the pathogenesis of several acute and chronic inflammatory diseases. Although MIF is a molecule of biomedical importance, a public resource of MIF signaling pathway is currently lacking. In view of this, we carried out detailed data mining and documentation of the signaling events pertaining to MIF from published literature and developed an integrated reaction map of MIF signaling. This resulted in the cataloguing of 68 molecules belonging to MIF signaling pathway, which includes 24 protein-protein interactions, 44 post-translational modifications, 11 protein translocation events and 8 activation/inhibition events. In addition, 65 gene regulation events at the mRNA levels induced by MIF signaling have also been catalogued. This signaling pathway has been integrated into NetPath ( http://www.netpath.org ), a freely available human signaling pathway resource developed previously by our group. The MIF pathway data is freely available online in various community standard data exchange formats. We expect that data on signaling events and a detailed signaling map of MIF will provide the scientific community with an improved platform to facilitate further molecular as well as biomedical investigations on MIF. PMID:27139435

  2. Pclust: protein network visualization highlighting experimental data

    PubMed Central

    Li, Wenlin; Kinch, Lisa N.; Grishin, Nick V.

    2013-01-01

    Summary: One approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. ‘reference proteins’. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such ‘reference proteins’ and providing access to their full information in source databases, e.g. articles in PubMed. The identification of ‘reference proteins’ and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest. Availability: The Pclust server is freely available at http://prodata.swmed.edu/pclust Contact: grishin@chop.swmed.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23918248

  3. Phospho-tyrosine dependent protein–protein interaction network

    PubMed Central

    Grossmann, Arndt; Benlasfer, Nouhad; Birth, Petra; Hegele, Anna; Wachsmuth, Franziska; Apelt, Luise; Stelzl, Ulrich

    2015-01-01

    Post-translational protein modifications, such as tyrosine phosphorylation, regulate protein–protein interactions (PPIs) critical for signal processing and cellular phenotypes. We extended an established yeast two-hybrid system employing human protein kinases for the analyses of phospho-tyrosine (pY)-dependent PPIs in a direct experimental, large-scale approach. We identified 292 mostly novel pY-dependent PPIs which showed high specificity with respect to kinases and interacting proteins and validated a large fraction in co-immunoprecipitation experiments from mammalian cells. About one-sixth of the interactions are mediated by known linear sequence binding motifs while the majority of pY-PPIs are mediated by other linear epitopes or governed by alternative recognition modes. Network analysis revealed that pY-mediated recognition events are tied to a highly connected protein module dedicated to signaling and cell growth pathways related to cancer. Using binding assays, protein complementation and phenotypic readouts to characterize the pY-dependent interactions of TSPAN2 (tetraspanin 2) and GRB2 or PIK3R3 (p55γ), we exemplarily provide evidence that the two pY-dependent PPIs dictate cellular cancer phenotypes. PMID:25814554

  4. Regulation of the BMP Signaling-Responsive Transcriptional Network in the Drosophila Embryo

    PubMed Central

    Saunders, Abbie; Wilcockson, Scott G.; Zeef, Leo A. H.; Donaldson, Ian J.; Ashe, Hilary L.

    2016-01-01

    The BMP signaling pathway has a conserved role in dorsal-ventral axis patterning during embryonic development. In Drosophila, graded BMP signaling is transduced by the Mad transcription factor and opposed by the Brinker repressor. In this study, using the Drosophila embryo as a model, we combine RNA-seq with Mad and Brinker ChIP-seq to decipher the BMP-responsive transcriptional network underpinning differentiation of the dorsal ectoderm during dorsal-ventral axis patterning. We identify multiple new BMP target genes, including positive and negative regulators of EGF signaling. Manipulation of EGF signaling levels by loss- and gain-of-function studies reveals that EGF signaling negatively regulates embryonic BMP-responsive transcription. Therefore, the BMP gene network has a self-regulating property in that it establishes a balance between its activity and that of the antagonistic EGF signaling pathway to facilitate correct patterning. In terms of BMP-dependent transcription, we identify key roles for the Zelda and Zerknüllt transcription factors in establishing the resulting expression domain, and find widespread binding of insulator proteins to the Mad and Brinker-bound genomic regions. Analysis of embryos lacking the BEAF-32 insulator protein shows reduced transcription of a peak BMP target gene and a reduction in the number of amnioserosa cells, the fate specified by peak BMP signaling. We incorporate our findings into a model for Mad-dependent activation, and discuss its relevance to BMP signal interpretation in vertebrates. PMID:27379389

  5. Compartmentalization role of A-kinase anchoring proteins (AKAPs) in mediating protein kinase A (PKA) signaling and cardiomyocyte hypertrophy.

    PubMed

    Rababa'h, Abeer; Singh, Sonal; Suryavanshi, Santosh V; Altarabsheh, Salah Eldien; Deo, Salil V; McConnell, Bradley K

    2014-12-24

    The Beta-adrenergic receptors (β-ARs) stimulation enhances contractility through protein kinase-A (PKA) substrate phosphorylation. This PKA signaling is conferred in part by PKA binding to A-kinase anchoring proteins (AKAPs). AKAPs coordinate multi-protein signaling networks that are targeted to specific intracellular locations, resulting in the localization of enzyme activity and transmitting intracellular actions of neurotransmitters and hormones to its target substrates. In particular, mAKAP (muscle-selective AKAP) has been shown to be present on the nuclear envelope of cardiomyocytes with various proteins including: PKA-regulatory subunit (RIIα), phosphodiesterase-4D3, protein phosphatase-2A, and ryanodine receptor (RyR2). Therefore, through the coordination of spatial-temporal signaling of proteins and enzymes, mAKAP controls cyclic-adenosine monophosphate (cAMP) levels very tightly and functions as a regulator of PKA-mediated substrate phosphorylation leading to changes in calcium availability and myofilament calcium sensitivity. The goal of this review is to elucidate the critical compartmentalization role of mAKAP in mediating PKA signaling and regulating cardiomyocyte hypertrophy by acting as a scaffolding protein. Based on our literature search and studying the structure-function relationship between AKAP scaffolding protein and its binding partners, we propose possible explanations for the mechanism by which mAKAP promotes cardiac hypertrophy.

  6. The RGS proteins add to the diversity of soybean heterotrimeric G-protein signaling

    PubMed Central

    Choudhury, Swarup Roy; Westfall, Corey S.; Pandey, Sona

    2012-01-01

    Regulator of G-protein signaling (RGS) proteins are a family of highly diverse, multifunctional proteins that function primarily as GTPase accelerating proteins (GAPs). RGS proteins increase the rate of GTP hydrolysis by Gα proteins and essentially regulate the duration of active signaling. Recently, we have identified two chimeric RGS proteins from soybean and reported their distinct GAP activities on individual Gα proteins. A single amino acid substitution (Alanine 357 to Valine) of RGS2 is responsible for differential GAP activity. Surprisingly, most monocot plant genomes do not encode for a RGS protein homolog. Here we discuss the soybean RGS proteins in the context of their evolution in plants, their relatedness to non-plant RGS protein homologs and the effect they might have on the heterotrimeric G-protein signaling mechanisms. We also provide experimental evidence to show that the interaction interface between plant RGS and Gα proteins is different from what is predicted based on mammalian models. PMID:22899066

  7. Module organization and variance in protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Lin, Chun-Yu; Lee, Tsai-Ling; Chiu, Yi-Yuan; Lin, Yi-Wei; Lo, Yu-Shu; Lin, Chih-Ta; Yang, Jinn-Moon

    2015-03-01

    A module is a group of closely related proteins that act in concert to perform specific biological functions through protein-protein interactions (PPIs) that occur in time and space. However, the underlying module organization and variance remain unclear. In this study, we collected module templates to infer respective module families, including 58,041 homologous modules in 1,678 species, and PPI families using searches of complete genomic database. We then derived PPI evolution scores and interface evolution scores to describe the module elements, including core and ring components. Functions of core components were highly correlated with those of essential genes. In comparison with ring components, core proteins/PPIs were conserved across multiple species. Subsequently, protein/module variance of PPI networks confirmed that core components form dynamic network hubs and play key roles in various biological functions. Based on the analyses of gene essentiality, module variance, and gene co-expression, we summarize the observations of module organization and variance as follows: 1) a module consists of core and ring components; 2) core components perform major biological functions and collaborate with ring components to execute certain functions in some cases; 3) core components are more conserved and essential during organizational changes in different biological states or conditions.

  8. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

    PubMed Central

    Jebaseeli Samuelraj, Ananthi; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point. PMID:26366431

  9. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

    PubMed

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

  10. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

    PubMed

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point. PMID:26366431

  11. WD40 proteins propel cellular networks.

    PubMed

    Stirnimann, Christian U; Petsalaki, Evangelia; Russell, Robert B; Müller, Christoph W

    2010-10-01

    Recent findings indicate that WD40 domains play central roles in biological processes by acting as hubs in cellular networks; however, they have been studied less intensely than other common domains, such as the kinase, PDZ or SH3 domains. As suggested by various interactome studies, they are among the most promiscuous interactors. Structural studies suggest that this property stems from their ability, as scaffolds, to interact with diverse proteins, peptides or nucleic acids using multiple surfaces or modes of interaction. A general scaffolding role is supported by the fact that no WD40 domain has been found with intrinsic enzymatic activity despite often being part of large molecular machines. We discuss the WD40 domain distributions in protein networks and structures of WD40-containing assemblies to demonstrate their versatility in mediating critical cellular functions.

  12. Signaling for fast restoration in heterogeneous optical mesh networks

    NASA Astrophysics Data System (ADS)

    Rajagopalan, Bala; Saha, Debanjan; Bernstein, Greg; Sharma, Vishal

    2001-10-01

    With the advent of optical mesh networks, certain new protection schemes have been defined. This encompasses both local span and end-to-end path protection. But the implementations of these protection schemes have so far been based on proprietary mechanisms developed by each vendor. This has made it virtually impractical to construct a heterogeneous network with interoperable mesh protection schemes. Also, while the notion of a standard IP-centric control plane for optical networks based on Generalized Multi-Protocol Label Switching (GMPLS) has gained wide acceptance, the work in this area has so far focused exclusively on connection provisioning rather than restoration. This paper defines standard, IP-based signaling protocols for restoration in optical mesh networks. These protocols focus on a new local span protection mode and end-to-end shared protection. The main requirements on these protocols are simplicity and speed. The signaling mechanisms described in this paper are complimentary to the GMPLS provisioning mechanisms.

  13. Integrating In Silico Resources to Map a Signaling Network

    PubMed Central

    Liu, Hanqing; Beck, Tim N.; Golemis, Erica A.; Serebriiskii, Ilya G.

    2013-01-01

    The abundance of publicly available life science databases offer a wealth of information that can support interpretation of experimentally derived data and greatly enhance hypothesis generation. Protein interaction and functional networks are not simply new renditions of existing data: they provide the opportunity to gain insights into the specific physical and functional role a protein plays as part of the biological system. In this chapter, we describe different in silico tools that can quickly and conveniently retrieve data from existing data repositories and discuss how the available tools are best utilized for different purposes. While emphasizing protein-protein interaction databases (e.g., BioGrid and IntAct), we also introduce metasearch platforms such as STRING and GeneMANIA, pathway databases (e.g., BioCarta and Pathway Commons), text mining approaches (e.g., PubMed and Chilibot), and resources for drug-protein interactions, genetic information for model organisms and gene expression information based on microarray data mining. Furthermore, we provide a simple step-by-step protocol to building customized protein-protein interaction networks in Cytoscape, a powerful network assembly and visualization program, integrating data retrieved from these various databases. As we illustrate, generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature. PMID:24233784

  14. The dynamic control of signal transduction networks in cancer cells.

    PubMed

    Kolch, Walter; Halasz, Melinda; Granovskaya, Marina; Kholodenko, Boris N

    2015-09-01

    Cancer is often considered a genetic disease. However, much of the enormous plasticity of cancer cells to evolve different phenotypes, to adapt to challenging microenvironments and to withstand therapeutic assaults is encoded by the structure and spatiotemporal dynamics of signal transduction networks. In this Review, we discuss recent concepts concerning how the rich signalling dynamics afforded by these networks are regulated and how they impinge on cancer cell proliferation, survival, invasiveness and drug resistance. Understanding this dynamic circuitry by mathematical modelling could pave the way to new therapeutic approaches and personalized treatments.

  15. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  16. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    PubMed Central

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  17. Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions.

    PubMed

    Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala; Peisajovich, Sergio G

    2016-08-04

    All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor-ligand pair can evolve through network-altering mutations independently of receptor-ligand binding, and suggest a potential role for such mutations in disease.

  18. Analyzing the Homeostasis of Signaling Proteins by a Combination of Western Blot and Fluorescence Correlation Spectroscopy

    PubMed Central

    Chung, Yi-Da; Sinzinger, Michael D.; Bovee-Geurts, Petra; Krause, Marina; Dinkla, Sip; Joosten, Irma; Koopman, Werner J.; Adjobo-Hermans, Merel J.W.; Brock, Roland

    2011-01-01

    The determination of intracellular protein concentrations is a prerequisite for understanding protein interaction networks in systems biology. Today, protein quantification is based either on mass spectrometry, which requires large cell numbers and sophisticated measurement protocols, or on quantitative Western blotting, which requires the expression and purification of a recombinant protein as a reference. Here, we present a method that uses a transiently expressed fluorescent fusion protein of the protein-of-interest as an easily accessible reference in small volumes of crude cell lysates. The concentration of the fusion protein is determined by fluorescence correlation spectroscopy, and this concentration is used to calibrate the intensity of bands on a Western blot. We applied this method to address cellular protein homeostasis by determining the concentrations of the plasma membrane-located transmembrane scaffolding protein LAT and soluble signaling proteins in naïve T cells and transformed T-cell lymphoma (Jurkat) cells (with the latter having nine times the volume of the former). Strikingly, the protein numbers of soluble proteins scaled with the cell volume, whereas that of the transmembrane protein LAT scaled with the membrane surface. This leads to significantly different stoichiometries of signaling proteins in transformed and naïve cells in concentration ranges that may translate directly into differences in complex formation. PMID:22261070

  19. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer.

    PubMed

    Latysheva, Natasha S; Oates, Matt E; Maddox, Louis; Flock, Tilman; Gough, Julian; Buljan, Marija; Weatheritt, Robert J; Babu, M Madan

    2016-08-18

    Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer. PMID:27540857

  20. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer.

    PubMed

    Latysheva, Natasha S; Oates, Matt E; Maddox, Louis; Flock, Tilman; Gough, Julian; Buljan, Marija; Weatheritt, Robert J; Babu, M Madan

    2016-08-18

    Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer.

  1. VLSI Neural Networks Help To Compress Video Signals

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.

    1996-01-01

    Advanced analog/digital electronic system for compression of video signals incorporates artificial neural networks. Performs motion-estimation and image-data-compression processing. Effectively eliminates temporal and spatial redundancies of sequences of video images; processes video image data, retaining only nonredundant parts to be transmitted, then transmits resulting data stream in form of efficient code. Reduces bandwidth and storage requirements for transmission and recording of video signal.

  2. An artificial network model for estimating the network structure underlying partially observed neuronal signals.

    PubMed

    Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

    2014-01-01

    Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed.

  3. Regulation, Signaling, and Physiological Functions of G-Proteins.

    PubMed

    Syrovatkina, Viktoriya; Alegre, Kamela O; Dey, Raja; Huang, Xin-Yun

    2016-09-25

    Heterotrimeric guanine-nucleotide-binding regulatory proteins (G-proteins) mainly relay the information from G-protein-coupled receptors (GPCRs) on the plasma membrane to the inside of cells to regulate various biochemical functions. Depending on the targeted cell types, tissues, and organs, these signals modulate diverse physiological functions. The basic schemes of heterotrimeric G-proteins have been outlined. In this review, we briefly summarize what is known about the regulation, signaling, and physiological functions of G-proteins. We then focus on a few less explored areas such as the regulation of G-proteins by non-GPCRs and the physiological functions of G-proteins that cannot be easily explained by the known G-protein signaling pathways. There are new signaling pathways and physiological functions for G-proteins to be discovered and further interrogated. With the advancements in structural and computational biological techniques, we are closer to having a better understanding of how G-proteins are regulated and of the specificity of G-protein interactions with their regulators. PMID:27515397

  4. Regulation, Signaling, and Physiological Functions of G-Proteins.

    PubMed

    Syrovatkina, Viktoriya; Alegre, Kamela O; Dey, Raja; Huang, Xin-Yun

    2016-09-25

    Heterotrimeric guanine-nucleotide-binding regulatory proteins (G-proteins) mainly relay the information from G-protein-coupled receptors (GPCRs) on the plasma membrane to the inside of cells to regulate various biochemical functions. Depending on the targeted cell types, tissues, and organs, these signals modulate diverse physiological functions. The basic schemes of heterotrimeric G-proteins have been outlined. In this review, we briefly summarize what is known about the regulation, signaling, and physiological functions of G-proteins. We then focus on a few less explored areas such as the regulation of G-proteins by non-GPCRs and the physiological functions of G-proteins that cannot be easily explained by the known G-protein signaling pathways. There are new signaling pathways and physiological functions for G-proteins to be discovered and further interrogated. With the advancements in structural and computational biological techniques, we are closer to having a better understanding of how G-proteins are regulated and of the specificity of G-protein interactions with their regulators.

  5. Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

    PubMed Central

    Dzeja, Petras; Terzic, Andre

    2009-01-01

    Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7) are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network. PMID:19468337

  6. Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

    PubMed Central

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

    2013-01-01

    Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

  7. Neurodegeneration in Alzheimer Disease: Role of Amyloid Precursor Protein and Presenilin 1 Intracellular Signaling

    PubMed Central

    Nizzari, Mario; Thellung, Stefano; Corsaro, Alessandro; Villa, Valentina; Pagano, Aldo; Porcile, Carola; Russo, Claudio; Florio, Tullio

    2012-01-01

    Alzheimer disease (AD) is a heterogeneous neurodegenerative disorder characterized by (1) progressive loss of synapses and neurons, (2) intracellular neurofibrillary tangles, composed of hyperphosphorylated Tau protein, and (3) amyloid plaques. Genetically, AD is linked to mutations in few proteins amyloid precursor protein (APP) and presenilin 1 and 2 (PS1 and PS2). The molecular mechanisms underlying neurodegeneration in AD as well as the physiological function of APP are not yet known. A recent theory has proposed that APP and PS1 modulate intracellular signals to induce cell-cycle abnormalities responsible for neuronal death and possibly amyloid deposition. This hypothesis is supported by the presence of a complex network of proteins, clearly involved in the regulation of signal transduction mechanisms that interact with both APP and PS1. In this review we discuss the significance of novel finding related to cell-signaling events modulated by APP and PS1 in the development of neurodegeneration. PMID:22496686

  8. GPCR: G protein complexes--the fundamental signaling assembly.

    PubMed

    Jastrzebska, Beata

    2013-12-01

    G protein coupled receptors (GPCR) constitute the largest group of cell surface receptors that transmit various signals across biological membranes through the binding and activation of heterotrimeric G proteins, which amplify the signal and activate downstream effectors leading to the biological responses. Thus, the first critical step in this signaling cascade is the interaction between receptor and its cognate G protein. Understanding this critical event at the molecular level is of high importance because abnormal function of GPCRs is associated with many diseases. Thus, these receptors are targets for drug development.

  9. Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets

    PubMed Central

    Chu, Liang-Hui; Chen, Bor-Sen

    2008-01-01

    Background Cancer is caused by genetic abnormalities, such as mutations of oncogenes or tumor suppressor genes, which alter downstream signal transduction pathways and protein-protein interactions. Comparisons of the interactions of proteins in cancerous and normal cells can shed light on the mechanisms of carcinogenesis. Results We constructed initial networks of protein-protein interactions involved in the apoptosis of cancerous and normal cells by use of two human yeast two-hybrid data sets and four online databases. Next, we applied a nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC) to eliminate false-positive protein-protein interactions in our initial protein interaction networks by use of microarray data. Comparisons of the networks of apoptosis in HeLa (human cervical carcinoma) cells and in normal primary lung fibroblasts provided insight into the mechanism of apoptosis and allowed identification of potential drug targets. The potential targets include BCL2, caspase-3 and TP53. Our comparison of cancerous and normal cells also allowed derivation of several party hubs and date hubs in the human protein-protein interaction networks involved in caspase activation. Conclusion Our method allows identification of cancer-perturbed protein-protein interactions involved in apoptosis and identification of potential molecular targets for development of anti-cancer drugs. PMID:18590547

  10. Comparing signaling networks between normal and transformed hepatocytes using discrete logical models.

    PubMed

    Saez-Rodriguez, Julio; Alexopoulos, Leonidas G; Zhang, Mingsheng; Morris, Melody K; Lauffenburger, Douglas A; Sorger, Peter K

    2011-08-15

    Substantial effort in recent years has been devoted to constructing and analyzing large-scale gene and protein networks on the basis of "omic" data and literature mining. These interaction graphs provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or drugs. Conversely, traditional approaches to analyzing cell signaling are narrow in scope and cannot easily make use of network-level data. Here, we combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data. Specifically, we created Boolean logic models of immediate-early signaling in liver cells by training a literature-based prior knowledge network against biochemical data obtained from primary human hepatocytes and 4 hepatocellular carcinoma cell lines exposed to combinations of cytokines and small-molecule kinase inhibitors. Distinct families of models were recovered for each cell type, and these families clustered topologically into normal and diseased sets.

  11. Tetramer formation in Arabidopsis MADS domain proteins: analysis of a protein-protein interaction network

    PubMed Central

    2014-01-01

    Background MADS domain proteins are transcription factors that coordinate several important developmental processes in plants. These proteins interact with other MADS domain proteins to form dimers, and it has been proposed that they are able to associate as tetrameric complexes that regulate transcription of target genes. Whether the formation of functional tetramers is a widespread property of plant MADS domain proteins, or it is specific to few of these transcriptional regulators remains unclear. Results We analyzed the structure of the network of physical interactions among MADS domain proteins in Arabidopsis thaliana. We determined the abundance of subgraphs that represent the connection pattern expected for a MADS domain protein heterotetramer. These subgraphs were significantly more abundant in the MADS domain protein interaction network than in randomized analogous networks. Importantly, these subgraphs are not significantly frequent in a protein interaction network of TCP plant transcription factors, when compared to expectation by chance. In addition, we found that MADS domain proteins in tetramer-like subgraphs are more likely to be expressed jointly than proteins in other subgraphs. This effect is mainly due to proteins in the monophyletic MIKC clade, as there is no association between tetramer-like subgraphs and co-expression for proteins outside this clade. Conclusions Our results support that the tendency to form functional tetramers is widespread in the MADS domain protein-protein interaction network. Our observations also suggest that this trend is prevalent, or perhaps exclusive, for proteins in the MIKC clade. Because it is possible to retrodict several experimental results from our analyses, our work can be an important aid to make new predictions and facilitates experimental research on plant MADS domain proteins. PMID:24468197

  12. Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies

    PubMed Central

    Kolch, Walter; Kholodenko, Boris N.; Ambrosi, Cristina De; Barla, Annalisa; Biganzoli, Elia M.; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

    2015-01-01

    The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. PMID:25671297

  13. Data-driven quantification of robustness and sensitivity of cell signaling networks

    PubMed Central

    Mukherjee, Sayak; Seok, Sang-Cheol; Vieland, Veronica J.; Das, Jayajit

    2013-01-01

    Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data driven Maximum Entropy (MaxEnt) based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems. PMID:24164951

  14. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  15. Subsurface event detection and classification using Wireless Signal Networks.

    PubMed

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  16. Thematic minireview series: cell biology of G protein signaling.

    PubMed

    Dohlman, Henrik G

    2015-03-13

    This thematic series is on the topic of cell signaling from a cell biology perspective, with a particular focus on G proteins. G protein-coupled receptors (GPCRs, also known as seven-transmembrane receptors) are typically found at the cell surface. Upon agonist binding, these receptors will activate a GTP-binding G protein at the cytoplasmic face of the plasma membrane. Additionally, there is growing evidence that G proteins can also be activated by non-receptor binding partners, and they can signal from non-plasma membrane compartments. The production of second messengers at multiple, spatially distinct locations represents a type of signal encoding that has been largely neglected. The first minireview in the series describes biosensors that are being used to monitor G protein signaling events in live cells. The second describes the implementation of antibody-based biosensors to dissect endosome signaling by G proteins and their receptors. The third describes the function of a non-receptor, cytoplasmic activator of G protein signaling, called GIV (Girdin). Collectively, the advances described in these articles provide a deeper understanding and emerging opportunities for new pharmacology.

  17. Thematic Minireview Series: Cell Biology of G Protein Signaling

    PubMed Central

    Dohlman, Henrik G.

    2015-01-01

    This thematic series is on the topic of cell signaling from a cell biology perspective, with a particular focus on G proteins. G protein-coupled receptors (GPCRs, also known as seven-transmembrane receptors) are typically found at the cell surface. Upon agonist binding, these receptors will activate a GTP-binding G protein at the cytoplasmic face of the plasma membrane. Additionally, there is growing evidence that G proteins can also be activated by non-receptor binding partners, and they can signal from non-plasma membrane compartments. The production of second messengers at multiple, spatially distinct locations represents a type of signal encoding that has been largely neglected. The first minireview in the series describes biosensors that are being used to monitor G protein signaling events in live cells. The second describes the implementation of antibody-based biosensors to dissect endosome signaling by G proteins and their receptors. The third describes the function of a non-receptor, cytoplasmic activator of G protein signaling, called GIV (Girdin). Collectively, the advances described in these articles provide a deeper understanding and emerging opportunities for new pharmacology. PMID:25605716

  18. Identification of Major Signaling Pathways in Prion Disease Progression Using Network Analysis.

    PubMed

    Newaz, Khalique; Sriram, K; Bera, Debajyoti

    2015-01-01

    Prion diseases are transmissible neurodegenerative diseases that arise due to conformational change of normal, cellular prion protein (PrPC) to protease-resistant isofrom (rPrPSc). Deposition of misfolded PrpSc proteins leads to an alteration of many signaling pathways that includes immunological and apoptotic pathways. As a result, this culminates in the dysfunction and death of neuronal cells. Earlier works on transcriptomic studies have revealed some affected pathways, but it is not clear which is (are) the prime network pathway(s) that change during the disease progression and how these pathways are involved in crosstalks with each other from the time of incubation to clinical death. We perform network analysis on large-scale transcriptomic data of differentially expressed genes obtained from whole brain in six different mouse strain-prion strain combination models to determine the pathways involved in prion diseases, and to understand the role of crosstalks in disease propagation. We employ a notion of differential network centrality measures on protein interaction networks to identify the potential biological pathways involved. We also propose a crosstalk ranking method based on dynamic protein interaction networks to identify the core network elements involved in crosstalk with different pathways. We identify 148 DEGs (differentially expressed genes) potentially related to the prion disease progression. Functional association of the identified genes implicates a strong involvement of immunological pathways. We extract a bow-tie structure that is potentially dysregulated in prion disease. We also propose an ODE model for the bow-tie network. Predictions related to diseased condition suggests the downregulation of the core signaling elements (PI3Ks and AKTs) of the bow-tie network. In this work, we show using transcriptomic data that the neuronal dysfunction in prion disease is strongly related to the immunological pathways. We conclude that these

  19. Neural network approach to classification of infrasound signals

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Chang

    As part of the International Monitoring Systems of the Preparatory Commissions for the Comprehensive Nuclear Test-Ban Treaty Organization, the Infrasound Group at the University of Alaska Fairbanks maintains and operates two infrasound stations to monitor global nuclear activity. In addition, the group specializes in detecting and classifying the man-made and naturally produced signals recorded at both stations by computing various characterization parameters (e.g. mean of the cross correlation maxima, trace velocity, direction of arrival, and planarity values) using the in-house developed weighted least-squares algorithm. Classifying commonly observed low-frequency (0.015--0.1 Hz) signals at out stations, namely mountain associated waves and high trace-velocity signals, using traditional approach (e.g. analysis of power spectral density) presents a problem. Such signals can be separated statistically by setting a window to the trace-velocity estimate for each signal types, and the feasibility of such technique is demonstrated by displaying and comparing various summary plots (e.g. universal, seasonal and azimuthal variations) produced by analyzing infrasound data (2004--2007) from the Fairbanks and Antarctic arrays. Such plots with the availability of magnetic activity information (from the College International Geophysical Observatory located at Fairbanks, Alaska) leads to possible physical sources of the two signal types. Throughout this thesis a newly developed robust algorithm (sum of squares of variance ratios) with improved detection quality (under low signal to noise ratios) over two well-known detection algorithms (mean of the cross correlation maxima and Fisher Statistics) are investigated for its efficacy as a new detector. A neural network is examined for its ability to automatically classify the two signals described above against clutter (spurious signals with common characteristics). Four identical perceptron networks are trained and validated (with

  20. Disentangling biological signaling networks by dynamic coupling of signaling lipids to modifying enzymes.

    PubMed

    Blind, Raymond D

    2014-01-01

    An unresolved problem in biological signal transduction is how particular branches of highly interconnected signaling networks can be decoupled, allowing activation of specific circuits within complex signaling architectures. Although signaling dynamics and spatiotemporal mechanisms serve critical roles, it remains unclear if these are the only ways cells achieve specificity within networks. The transcription factor Steroidogenic Factor-1 (SF-1) is an excellent model to address this question, as it forms dynamic complexes with several chemically distinct lipid species (phosphatidylinositols, phosphatidylcholines and sphingolipids). This property is important since lipids bound to SF-1 are modified by lipid signaling enzymes (IPMK & PTEN), regulating SF-1 biological activity in gene expression. Thus, a particular SF-1/lipid complex can interface with a lipid signaling enzyme only if SF-1 has been loaded with a chemically compatible lipid substrate. This mechanism permits dynamic downstream responsiveness to constant upstream input, disentangling specific pathways from the full network. The potential of this paradigm to apply generally to nuclear lipid signaling is discussed, with particular attention given to the nuclear receptor superfamily of transcription factors and their phospholipid ligands.

  1. SSL: Signal Similarity-Based Localization for Ocean Sensor Networks

    PubMed Central

    Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

    2015-01-01

    Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes’ positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes’ relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks. PMID:26610520

  2. Optogenetic pharmacology for control of native neuronal signaling proteins.

    PubMed

    Kramer, Richard H; Mourot, Alexandre; Adesnik, Hillel

    2013-07-01

    The optical neuroscience revolution is transforming how we study neural circuits. By providing a precise way to manipulate endogenous neuronal signaling proteins, it also has the potential to transform our understanding of molecular neuroscience. Recent advances in chemical biology have produced light-sensitive compounds that photoregulate a wide variety of proteins underlying signaling between and within neurons. Chemical tools for optopharmacology include caged agonists and antagonists and reversibly photoswitchable ligands. These reagents act on voltage-gated ion channels and neurotransmitter receptors, enabling control of neuronal signaling with a high degree of spatial and temporal precision. By covalently attaching photoswitch molecules to genetically tagged proteins, the newly emerging methodology of optogenetic pharmacology allows biochemically precise control in targeted subsets of neurons. Now that the tools for manipulating endogenous neuronal signaling proteins are available, they can be implemented in vivo to enhance our understanding of the molecular bases of brain function and dysfunctions. PMID:23799474

  3. Serotonin signaling mediates protein valuation and aging

    PubMed Central

    Ro, Jennifer; Pak, Gloria; Malec, Paige A; Lyu, Yang; Allison, David B; Kennedy, Robert T; Pletcher, Scott D

    2016-01-01

    Research into how protein restriction improves organismal health and lengthens lifespan has largely focused on cell-autonomous processes. In certain instances, however, nutrient effects on lifespan are independent of consumption, leading us to test the hypothesis that central, cell non-autonomous processes are important protein restriction regulators. We characterized a transient feeding preference for dietary protein after modest starvation in the fruit fly, Drosophila melanogaster, and identified tryptophan hydroxylase (Trh), serotonin receptor 2a (5HT2a), and the solute carrier 7-family amino acid transporter, JhI-21, as required for this preference through their role in establishing protein value. Disruption of any one of these genes increased lifespan up to 90% independent of food intake suggesting the perceived value of dietary protein is a critical determinant of its effect on lifespan. Evolutionarily conserved neuromodulatory systems that define neural states of nutrient demand and reward are therefore sufficient to control aging and physiology independent of food consumption. DOI: http://dx.doi.org/10.7554/eLife.16843.001 PMID:27572262

  4. Serotonin signaling mediates protein valuation and aging.

    PubMed

    Ro, Jennifer; Pak, Gloria; Malec, Paige A; Lyu, Yang; Allison, David B; Kennedy, Robert T; Pletcher, Scott D

    2016-01-01

    Research into how protein restriction improves organismal health and lengthens lifespan has largely focused on cell-autonomous processes. In certain instances, however, nutrient effects on lifespan are independent of consumption, leading us to test the hypothesis that central, cell non-autonomous processes are important protein restriction regulators. We characterized a transient feeding preference for dietary protein after modest starvation in the fruit fly, Drosophila melanogaster, and identified tryptophan hydroxylase (Trh), serotonin receptor 2a (5HT2a), and the solute carrier 7-family amino acid transporter, JhI-21, as required for this preference through their role in establishing protein value. Disruption of any one of these genes increased lifespan up to 90% independent of food intake suggesting the perceived value of dietary protein is a critical determinant of its effect on lifespan. Evolutionarily conserved neuromodulatory systems that define neural states of nutrient demand and reward are therefore sufficient to control aging and physiology independent of food consumption. PMID:27572262

  5. Multiplexed Signal Distribution Using Fiber Network For Radar Applications

    NASA Astrophysics Data System (ADS)

    Meena, D.; Prakasam, L. G. M.; Pandey, D. C.; Shivaleela, E. S.; Srinivas, T.

    2011-10-01

    Most of the modern Active phased Array Radars consist of multiple receive modules in an Antenna array. This demands the distribution of various Local Oscillator Signals (LOs) for the down conversion of received signals to the Intermediate Frequency (IF) band signals. This is normally achieved through Radio Frequency (RF) cables with Complex distribution networks which adds additional weight to the Arrays. Similarly these kinds of receivers require Control/Clock signals which are digital in nature, for the synchronization of all receive modules of the radar system which are also distributed through electrical cables. In addition some of the control messages (Digital in nature) are distributed through Optical interfaces. During Transmit operation, the RF transmit Signal is also distributed through the same receiver modules which will in turn distribute to all the elements of the Array which require RF cables which are bulky in nature. So it is very essential to have a multiplexed Signal distribution scheme through the existing Optical Interface for distribution of these signals which are RF and Digital in nature. This paper discusses about various distribution schemes for the realization in detail. We propose a distribution network architecture where existing fibers can be further extended for the distribution of other types of signals also. In addition, it also briefs about a comparative analysis done on these schemes by considering the complexity and space constraint factors. Thus we bring out an optimum scheme which will lead to the reduction in both hardware complexity and weight of the array systems. In addition, being an Optical network it is free from Electromagnetic interference which is a crucial requirement in an array environment.

  6. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    PubMed

    Coyle, Scott M

    2016-07-01

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems. PMID:27128855

  7. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    PubMed

    Coyle, Scott M

    2016-07-01

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

  8. Control of protein signaling using a computationally designed GTPase/GEF orthogonal pair.

    PubMed

    Kapp, Gregory T; Liu, Sen; Stein, Amelie; Wong, Derek T; Reményi, Attila; Yeh, Brian J; Fraser, James S; Taunton, Jack; Lim, Wendell A; Kortemme, Tanja

    2012-04-01

    Signaling pathways depend on regulatory protein-protein interactions; controlling these interactions in cells has important applications for reengineering biological functions. As many regulatory proteins are modular, considerable progress in engineering signaling circuits has been made by recombining commonly occurring domains. Our ability to predictably engineer cellular functions, however, is constrained by complex crosstalk observed in naturally occurring domains. Here we demonstrate a strategy for improving and simplifying protein network engineering: using computational design to create orthogonal (non-crossreacting) protein-protein interfaces. We validated the design of the interface between a key signaling protein, the GTPase Cdc42, and its activator, Intersectin, biochemically and by solving the crystal structure of the engineered complex. The designed GTPase (orthoCdc42) is activated exclusively by its engineered cognate partner (orthoIntersectin), but maintains the ability to interface with other GTPase signaling circuit components in vitro. In mammalian cells, orthoCdc42 activity can be regulated by orthoIntersectin, but not wild-type Intersectin, showing that the designed interaction can trigger complex processes. Computational design of protein interfaces thus promises to provide specific components that facilitate the predictable engineering of cellular functions. PMID:22403064

  9. Regulation of Wnt/β-Catenin Signaling by Protein Kinases

    PubMed Central

    Verheyen, Esther M.; Gottardi, Cara J.

    2011-01-01

    The Wnt/β-catenin signaling pathway plays essential roles during development and adult tissue homeostasis. Inappropriate activation of the pathway can result in a variety of malignancies. Protein kinases have emerged as key regulators at multiple steps of the Wnt pathway. In this review, we present a synthesis covering the latest information on how Wnt signaling is regulated by diverse protein kinases. PMID:19623618

  10. Protein phosphorylation and its role in archaeal signal transduction.

    PubMed

    Esser, Dominik; Hoffmann, Lena; Pham, Trong Khoa; Bräsen, Christopher; Qiu, Wen; Wright, Phillip C; Albers, Sonja-Verena; Siebers, Bettina

    2016-09-01

    Reversible protein phosphorylation is the main mechanism of signal transduction that enables cells to rapidly respond to environmental changes by controlling the functional properties of proteins in response to external stimuli. However, whereas signal transduction is well studied in Eukaryotes and Bacteria, the knowledge in Archaea is still rather scarce. Archaea are special with regard to protein phosphorylation, due to the fact that the two best studied phyla, the Euryarchaeota and Crenarchaeaota, seem to exhibit fundamental differences in regulatory systems. Euryarchaeota (e.g. halophiles, methanogens, thermophiles), like Bacteria and Eukaryotes, rely on bacterial-type two-component signal transduction systems (phosphorylation on His and Asp), as well as on the protein phosphorylation on Ser, Thr and Tyr by Hanks-type protein kinases. Instead, Crenarchaeota (e.g. acidophiles and (hyper)thermophiles) only depend on Hanks-type protein phosphorylation. In this review, the current knowledge of reversible protein phosphorylation in Archaea is presented. It combines results from identified phosphoproteins, biochemical characterization of protein kinases and protein phosphatases as well as target enzymes and first insights into archaeal signal transduction by biochemical, genetic and polyomic studies.

  11. Protein phosphorylation and its role in archaeal signal transduction.

    PubMed

    Esser, Dominik; Hoffmann, Lena; Pham, Trong Khoa; Bräsen, Christopher; Qiu, Wen; Wright, Phillip C; Albers, Sonja-Verena; Siebers, Bettina

    2016-09-01

    Reversible protein phosphorylation is the main mechanism of signal transduction that enables cells to rapidly respond to environmental changes by controlling the functional properties of proteins in response to external stimuli. However, whereas signal transduction is well studied in Eukaryotes and Bacteria, the knowledge in Archaea is still rather scarce. Archaea are special with regard to protein phosphorylation, due to the fact that the two best studied phyla, the Euryarchaeota and Crenarchaeaota, seem to exhibit fundamental differences in regulatory systems. Euryarchaeota (e.g. halophiles, methanogens, thermophiles), like Bacteria and Eukaryotes, rely on bacterial-type two-component signal transduction systems (phosphorylation on His and Asp), as well as on the protein phosphorylation on Ser, Thr and Tyr by Hanks-type protein kinases. Instead, Crenarchaeota (e.g. acidophiles and (hyper)thermophiles) only depend on Hanks-type protein phosphorylation. In this review, the current knowledge of reversible protein phosphorylation in Archaea is presented. It combines results from identified phosphoproteins, biochemical characterization of protein kinases and protein phosphatases as well as target enzymes and first insights into archaeal signal transduction by biochemical, genetic and polyomic studies. PMID:27476079

  12. Protein phosphorylation and its role in archaeal signal transduction

    PubMed Central

    Esser, Dominik; Hoffmann, Lena; Pham, Trong Khoa; Bräsen, Christopher; Qiu, Wen; Wright, Phillip C.; Albers, Sonja-Verena; Siebers, Bettina

    2016-01-01

    Reversible protein phosphorylation is the main mechanism of signal transduction that enables cells to rapidly respond to environmental changes by controlling the functional properties of proteins in response to external stimuli. However, whereas signal transduction is well studied in Eukaryotes and Bacteria, the knowledge in Archaea is still rather scarce. Archaea are special with regard to protein phosphorylation, due to the fact that the two best studied phyla, the Euryarchaeota and Crenarchaeaota, seem to exhibit fundamental differences in regulatory systems. Euryarchaeota (e.g. halophiles, methanogens, thermophiles), like Bacteria and Eukaryotes, rely on bacterial-type two-component signal transduction systems (phosphorylation on His and Asp), as well as on the protein phosphorylation on Ser, Thr and Tyr by Hanks-type protein kinases. Instead, Crenarchaeota (e.g. acidophiles and (hyper)thermophiles) only depend on Hanks-type protein phosphorylation. In this review, the current knowledge of reversible protein phosphorylation in Archaea is presented. It combines results from identified phosphoproteins, biochemical characterization of protein kinases and protein phosphatases as well as target enzymes and first insights into archaeal signal transduction by biochemical, genetic and polyomic studies. PMID:27476079

  13. Signal peptides are allosteric activators of the protein translocase

    PubMed Central

    Gouridis, Giorgos; Karamanou, Spyridoula; Gelis, Ioannis; Kalodimos, Charalampos G.; Economou, Anastassios

    2010-01-01

    Extra-cytoplasmic polypeptides are usually synthesized as “preproteins” carrying aminoterminal, cleavable signal peptides1 and secreted across membranes by translocases. The main bacterial translocase comprises the SecYEG protein-conducting channel and the peripheral ATPase motor SecA2,3. Most proteins destined for the periplasm and beyond are exported post-translationally by SecA2,3. Preprotein targeting to SecA is thought to involve signal peptides4 and chaperones like SecB5,6. Here we reveal that signal peptides have a novel role beyond targeting: they are essential allosteric activators of the translocase. Upon docking on their binding groove on SecA, signal peptides act in trans to drive three successive states: first, “triggering” that drives the translocase to a lower activation energy state; then “trapping” that engages non-native preprotein mature domains docked with high affinity on the secretion apparatus and, finally, “secretion” during which trapped mature domains undergo multiple turnovers of translocation in segments7. A significant contribution by mature domains renders signal peptides less critical in bacterial secretory protein targeting than currently assumed. Rather, it is their function as allosteric activators of the translocase that renders signal peptides essential for protein secretion. A role for signal peptides and targeting sequences as allosteric activators may be universal in protein translocases. PMID:19924216

  14. Protein carbonylation as a novel mechanism in redox signaling.

    PubMed

    Wong, Chi Ming; Cheema, Amrita K; Zhang, Lihua; Suzuki, Yuichiro J

    2008-02-15

    Reactive oxygen species serve as second messengers for signal transduction; however, molecular targets of oxidant signaling have not been defined. Here, we show that ligand-receptor-mediated signaling promotes reactive oxygen species-dependent protein carbonylation. Treatment of pulmonary artery smooth muscle cells with endothelin-1 increased protein carbonyls. Carbonylation of the majority of proteins occurred transiently, suggesting that there is also a mechanism for decarbonylation induced by endothelin-1. Decarbonylation was suppressed by inhibition of thioredoxin reductase, and cellular thioredoxin was upregulated during the decarbonylation phase. These results indicate that endothelin-1 promotes oxidant signaling as well as thioredoxin-mediated reductive signaling to regulate carbonylation and decarbonylation mechanisms. In cells treated with endothelin receptor antagonists, hydrogen peroxide scavengers, or an iron chelator, we identified, via mass spectrometry, proteins that are carbonylated in a receptor- and Fenton reaction-dependent manner, including annexin A1, which promotes apoptosis and suppresses cell growth. Carbonylation of annexin A1 by endothelin-1 was followed by proteasome-dependent degradation of this protein. We propose that carbonylation and subsequent degradation of annexin A1 may play a role in endothelin-mediated cell growth and survival, important events in pulmonary vascular remodeling. Protein carbonylation in response to ligand-receptor interactions represents a novel mechanism in redox signaling.

  15. Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

    PubMed Central

    Uzoma, Ijeoma; Zhu, Heng

    2013-01-01

    A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein–DNA interactions, posttranslational protein modifications (PTMs), lectin–glycan recognition, pathogen–host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier. PMID:23395178

  16. PACRG, a protein linked to ciliary motility, mediates cellular signaling

    PubMed Central

    Loucks, Catrina M.; Bialas, Nathan J.; Dekkers, Martijn P. J.; Walker, Denise S.; Grundy, Laura J.; Li, Chunmei; Inglis, P. Nick; Kida, Katarzyna; Schafer, William R.; Blacque, Oliver E.; Jansen, Gert; Leroux, Michel R.

    2016-01-01

    Cilia are microtubule-based organelles that project from nearly all mammalian cell types. Motile cilia generate fluid flow, whereas nonmotile (primary) cilia are required for sensory physiology and modulate various signal transduction pathways. Here we investigate the nonmotile ciliary signaling roles of parkin coregulated gene (PACRG), a protein linked to ciliary motility. PACRG is associated with the protofilament ribbon, a structure believed to dictate the regular arrangement of motility-associated ciliary components. Roles for protofilament ribbon–associated proteins in nonmotile cilia and cellular signaling have not been investigated. We show that PACRG localizes to a small subset of nonmotile cilia in Caenorhabditis elegans, suggesting an evolutionary adaptation for mediating specific sensory/signaling functions. We find that it influences a learning behavior known as gustatory plasticity, in which it is functionally coupled to heterotrimeric G-protein signaling. We also demonstrate that PACRG promotes longevity in C. elegans by acting upstream of the lifespan-promoting FOXO transcription factor DAF-16 and likely upstream of insulin/IGF signaling. Our findings establish previously unrecognized sensory/signaling functions for PACRG and point to a role for this protein in promoting longevity. Furthermore, our work suggests additional ciliary motility-signaling connections, since EFHC1 (EF-hand containing 1), a potential PACRG interaction partner similarly associated with the protofilament ribbon and ciliary motility, also positively regulates lifespan. PMID:27193298

  17. PACRG, a protein linked to ciliary motility, mediates cellular signaling.

    PubMed

    Loucks, Catrina M; Bialas, Nathan J; Dekkers, Martijn P J; Walker, Denise S; Grundy, Laura J; Li, Chunmei; Inglis, P Nick; Kida, Katarzyna; Schafer, William R; Blacque, Oliver E; Jansen, Gert; Leroux, Michel R

    2016-07-01

    Cilia are microtubule-based organelles that project from nearly all mammalian cell types. Motile cilia generate fluid flow, whereas nonmotile (primary) cilia are required for sensory physiology and modulate various signal transduction pathways. Here we investigate the nonmotile ciliary signaling roles of parkin coregulated gene (PACRG), a protein linked to ciliary motility. PACRG is associated with the protofilament ribbon, a structure believed to dictate the regular arrangement of motility-associated ciliary components. Roles for protofilament ribbon-associated proteins in nonmotile cilia and cellular signaling have not been investigated. We show that PACRG localizes to a small subset of nonmotile cilia in Caenorhabditis elegans, suggesting an evolutionary adaptation for mediating specific sensory/signaling functions. We find that it influences a learning behavior known as gustatory plasticity, in which it is functionally coupled to heterotrimeric G-protein signaling. We also demonstrate that PACRG promotes longevity in C. elegans by acting upstream of the lifespan-promoting FOXO transcription factor DAF-16 and likely upstream of insulin/IGF signaling. Our findings establish previously unrecognized sensory/signaling functions for PACRG and point to a role for this protein in promoting longevity. Furthermore, our work suggests additional ciliary motility-signaling connections, since EFHC1 (EF-hand containing 1), a potential PACRG interaction partner similarly associated with the protofilament ribbon and ciliary motility, also positively regulates lifespan. PMID:27193298

  18. Orchestrating Redox Signaling Networks Through Regulatory Cysteine Switches

    PubMed Central

    Paulsen, Candice E.; Carroll, Kate S.

    2015-01-01

    Hydrogen peroxide (H2O2) acts as a second messenger that can mediate intracellular signal transduction via chemoselective oxidation of cysteine residues in signaling proteins. This Review presents current mechanistic insights into signal-mediated H2O2 production and highlights recent advances in methods to detect reactive oxygen species (ROS) and cysteine oxidation both in vitro and in cells. Selected examples from the recent literature are used to illustrate the diverse mechanisms by which H2O2 can regulate protein function. The continued development of methods to detect and quantify discrete cysteine oxoforms should further our mechanistic understanding of redox regulation of protein function and may lead to the development of new therapeutic strategies. PMID:19957967

  19. Orchestrating redox signaling networks through regulatory cysteine switches.

    PubMed

    Paulsen, Candice E; Carroll, Kate S

    2010-01-15

    Hydrogen peroxide (H(2)O(2)) acts as a second messenger that can mediate intracellular signal transduction via chemoselective oxidation of cysteine residues in signaling proteins. This Review presents current mechanistic insights into signal-mediated H(2)O(2) production and highlights recent advances in methods to detect reactive oxygen species (ROS) and cysteine oxidation both in vitro and in cells. Selected examples from the recent literature are used to illustrate the diverse mechanisms by which H(2)O(2) can regulate protein function. The continued development of methods to detect and quantify discrete cysteine oxoforms should further our mechanistic understanding of redox regulation of protein function and may lead to the development of new therapeutic strategies.

  20. Multiplex matrix network analysis of protein complexes in the human TCR signalosome.

    PubMed

    Smith, Stephen E P; Neier, Steven C; Reed, Brendan K; Davis, Tessa R; Sinnwell, Jason P; Eckel-Passow, Jeanette E; Sciallis, Gabriel F; Wieland, Carilyn N; Torgerson, Rochelle R; Gil, Diana; Neuhauser, Claudia; Schrum, Adam G

    2016-08-02

    Multiprotein complexes transduce cellular signals through extensive interaction networks, but the ability to analyze these networks in cells from small clinical biopsies is limited. To address this, we applied an adaptable multiplex matrix system to physiologically relevant signaling protein complexes isolated from a cell line or from human patient samples. Focusing on the proximal T cell receptor (TCR) signalosome, we assessed 210 pairs of PiSCES (proteins in shared complexes detected by exposed surface epitopes). Upon stimulation of Jurkat cells with superantigen-loaded antigen-presenting cells, this system produced high-dimensional data that enabled visualization of network activity. A comprehensive analysis platform generated PiSCES biosignatures by applying unsupervised hierarchical clustering, principal component analysis, an adaptive nonparametric with empirical cutoff analysis, and weighted correlation network analysis. We generated PiSCES biosignatures from 4-mm skin punch biopsies from control patients or patients with the autoimmune skin disease alopecia areata. This analysis distinguished disease patients from the controls, detected enhanced basal TCR signaling in the autoimmune patients, and identified a potential signaling network signature that may be indicative of disease. Thus, generation of PiSCES biosignatures represents an approach that can provide information about the activity of protein signaling networks in samples including low-abundance primary cells from clinical biopsies.

  1. Discriminating lysosomal membrane protein types using dynamic neural network.

    PubMed

    Tripathi, Vijay; Gupta, Dwijendra Kumar

    2014-01-01

    This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

  2. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT

    PubMed Central

    Choudhary, Kumari Sonal; Rohatgi, Neha; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

    2016-01-01

    Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend. PMID:27253373

  3. Network Analysis of Neurodegenerative Disease Highlights a Role of Toll-Like Receptor Signaling

    PubMed Central

    Nguyen, Thanh-Phuong; Morine, Melissa J.

    2014-01-01

    Despite significant advances in the study of the molecular mechanisms altered in the development and progression of neurodegenerative diseases (NDs), the etiology is still enigmatic and the distinctions between diseases are not always entirely clear. We present an efficient computational method based on protein-protein interaction network (PPI) to model the functional network of NDs. The aim of this work is fourfold: (i) reconstruction of a PPI network relating to the NDs, (ii) construction of an association network between diseases based on proximity in the disease PPI network, (iii) quantification of disease associations, and (iv) inference of potential molecular mechanism involved in the diseases. The functional links of diseases not only showed overlap with the traditional classification in clinical settings, but also offered new insight into connections between diseases with limited clinical overlap. To gain an expanded view of the molecular mechanisms involved in NDs, both direct and indirect connector proteins were investigated. The method uncovered molecular relationships that are in common apparently distinct diseases and provided important insight into the molecular networks implicated in disease pathogenesis. In particular, the current analysis highlighted the Toll-like receptor signaling pathway as a potential candidate pathway to be targeted by therapy in neurodegeneration. PMID:24551850

  4. Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases.

    PubMed

    Tan, Chris Soon Heng; Bodenmiller, Bernd; Pasculescu, Adrian; Jovanovic, Marko; Hengartner, Michael O; Jørgensen, Claus; Bader, Gary D; Aebersold, Ruedi; Pawson, Tony; Linding, Rune

    2009-01-01

    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.

  5. Network Evolution: Rewiring and Signatures of Conservation in Signaling

    PubMed Central

    Costanzo, Michael; Boone, Charles; Kim, Philip M.

    2012-01-01

    The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules. PMID:22438796

  6. Dissecting Arabidopsis G beta signal transduction on the protein surface

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The heterotrimeric G protein complex provides signal amplification and target specificity. The Arabidopsis Gbeta subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its ta...

  7. Collective signaling behavior in a networked-oscillator model

    NASA Astrophysics Data System (ADS)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  8. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

  9. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  10. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing.

  11. A Comprehensive Statistical Model for Cell Signaling and Protein Activity Inference

    PubMed Central

    Yörük, Erdem; Ochs, Michael F.; Geman, Donald; Younes, Laurent

    2010-01-01

    Protein signaling networks play a central role in transcriptional regulation and the etiology of many diseases. Statistical methods, particularly Bayesian networks, have been widely used to model cell signaling, mostly for model organisms and with focus on uncovering connectivity rather than inferring aberrations. Extensions to mammalian systems have not yielded compelling results, due likely to greatly increased complexity and limited proteomic measurements in vivo. In this study, we propose a comprehensive statistical model that is anchored to a predefined core topology, has a limited complexity due to parameter sharing and uses micorarray data of mRNA transcripts as the only observable components of signaling. Specifically, we account for cell heterogeneity and a multi-level process, representing signaling as a Bayesian network at the cell level, modeling measurements as ensemble averages at the tissue level and incorporating patient-to-patient differences at the population level. Motivated by the goal of identifying individual protein abnormalities as potential therapeutical targets, we applied our method to the RAS-RAF network using a breast cancer study with 118 patients. We demonstrated rigorous statistical inference, established reproducibility through simulations and the ability to recover receptor status from available microarray data. PMID:20855924

  12. The evolution and origin of animal Toll-like receptor signaling pathway revealed by network-level molecular evolutionary analyses.

    PubMed

    Song, Xiaojun; Jin, Ping; Qin, Sheng; Chen, Liming; Ma, Fei

    2012-01-01

    Genes carry out their biological functions through pathways in complex networks consisting of many interacting molecules. Studies on the effect of network architecture on the evolution of individual proteins will provide valuable information for understanding the origin and evolution as well as functional conservation of signaling pathways. However, the relationship between the network architecture and the individual protein sequence evolution is yet little known. In current study, we carried out network-level molecular evolution analysis on TLR (Toll-like receptor ) signaling pathway, which plays an important role in innate immunity in insects and mammals, and we found that: 1) The selection constraint of genes was negatively correlated with its position along TLR signaling pathway; 2) all genes in TLR signaling pathway were highly conserved and underwent strong purifying selection; 3) the distribution of selective pressure along the pathway was driven by differential nonsynonymous substitution levels; 4) The TLR signaling pathway might present in a common ancestor of sponges and eumetazoa, and evolve via the TLR, IKK, IκB and NF-κB genes underwent duplication events as well as adaptor molecular enlargement, and gene structure and conservation motif of NF-κB genes shifted in their evolutionary history. Our results will improve our understanding on the evolutionary history of animal TLR signaling pathway as well as the relationship between the network architecture and the sequences evolution of individual protein.

  13. The Evolution and Origin of Animal Toll-Like Receptor Signaling Pathway Revealed by Network-Level Molecular Evolutionary Analyses

    PubMed Central

    Qin, Sheng; Chen, Liming; Ma, Fei

    2012-01-01

    Genes carry out their biological functions through pathways in complex networks consisting of many interacting molecules. Studies on the effect of network architecture on the evolution of individual proteins will provide valuable information for understanding the origin and evolution as well as functional conservation of signaling pathways. However, the relationship between the network architecture and the individual protein sequence evolution is yet little known. In current study, we carried out network-level molecular evolution analysis on TLR (Toll-like receptor ) signaling pathway, which plays an important role in innate immunity in insects and mammals, and we found that: 1) The selection constraint of genes was negatively correlated with its position along TLR signaling pathway; 2) all genes in TLR signaling pathway were highly conserved and underwent strong purifying selection; 3) the distribution of selective pressure along the pathway was driven by differential nonsynonymous substitution levels; 4) The TLR signaling pathway might present in a common ancestor of sponges and eumetazoa, and evolve via the TLR, IKK, IκB and NF-κB genes underwent duplication events as well as adaptor molecular enlargement, and gene structure and conservation motif of NF-κB genes shifted in their evolutionary history. Our results will improve our understanding on the evolutionary history of animal TLR signaling pathway as well as the relationship between the network architecture and the sequences evolution of individual protein. PMID:23236523

  14. Notum deacylates Wnt proteins to suppress signalling activity.

    PubMed

    Kakugawa, Satoshi; Langton, Paul F; Zebisch, Matthias; Howell, Steven A; Chang, Tao-Hsin; Liu, Yan; Feizi, Ten; Bineva, Ganka; O'Reilly, Nicola; Snijders, Ambrosius P; Jones, E Yvonne; Vincent, Jean-Paul

    2015-03-12

    Signalling by Wnt proteins is finely balanced to ensure normal development and tissue homeostasis while avoiding diseases such as cancer. This is achieved in part by Notum, a highly conserved secreted feedback antagonist. Notum has been thought to act as a phospholipase, shedding glypicans and associated Wnt proteins from the cell surface. However, this view fails to explain specificity, as glypicans bind many extracellular ligands. Here we provide genetic evidence in Drosophila that Notum requires glypicans to suppress Wnt signalling, but does not cleave their glycophosphatidylinositol anchor. Structural analyses reveal glycosaminoglycan binding sites on Notum, which probably help Notum to co-localize with Wnt proteins. They also identify, at the active site of human and Drosophila Notum, a large hydrophobic pocket that accommodates palmitoleate. Kinetic and mass spectrometric analyses of human proteins show that Notum is a carboxylesterase that removes an essential palmitoleate moiety from Wnt proteins and thus constitutes the first known extracellular protein deacylase. PMID:25731175

  15. Protein-spanning water networks and implications for prediction of protein-protein interactions mediated through hydrophobic effects.

    PubMed

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

    Hydrophobic effects, often conflated with hydrophobic forces, are implicated as major determinants in biological association and self-assembly processes. Protein-protein interactions involved in signaling pathways in living systems are a prime example where hydrophobic effects have profound implications. In the context of protein-protein interactions, a priori knowledge of relevant binding interfaces (i.e., clusters of residues involved directly with binding interactions) is difficult. In the case of hydrophobically mediated interactions, use of hydropathy-based methods relying on single residue hydrophobicity properties are routinely and widely used to predict propensities for such residues to be present in hydrophobic interfaces. However, recent studies suggest that consideration of hydrophobicity for single residues on a protein surface require accounting of the local environment dictated by neighboring residues and local water. In this study, we use a method derived from percolation theory to evaluate spanning water networks in the first hydration shells of a series of small proteins. We use residue-based water density and single-linkage clustering methods to predict hydrophobic regions of proteins; these regions are putatively involved in binding interactions. We find that this simple method is able to predict with sufficient accuracy and coverage the binding interface residues of a series of proteins. The approach is competitive with automated servers. The results of this study highlight the importance of accounting of local environment in determining the hydrophobic nature of individual residues on protein surfaces.

  16. Hedgehog signalling in the mouse requires intraflagellar transport proteins.

    PubMed

    Huangfu, Danwei; Liu, Aimin; Rakeman, Andrew S; Murcia, Noel S; Niswander, Lee; Anderson, Kathryn V

    2003-11-01

    Intraflagellar transport (IFT) proteins were first identified as essential factors for the growth and maintenance of flagella in the single-celled alga Chlamydomonas reinhardtii. In a screen for embryonic patterning mutations induced by ethylnitrosourea, here we identify two mouse mutants, wimple (wim) and flexo (fxo), that lack ventral neural cell types and show other phenotypes characteristic of defects in Sonic hedgehog signalling. Both mutations disrupt IFT proteins: the wim mutation is an allele of the previously uncharacterized mouse homologue of IFT172; and fxo is a new hypomorphic allele of polaris, the mouse homologue of IFT88. Genetic analysis shows that Wim, Polaris and the IFT motor protein Kif3a are required for Hedgehog signalling at a step downstream of Patched1 (the Hedgehog receptor) and upstream of direct targets of Hedgehog signalling. Our data show that IFT machinery has an essential and vertebrate-specific role in Hedgehog signal transduction. PMID:14603322

  17. Protein kinase A signalling in Schistosoma mansoni cercariae and schistosomules.

    PubMed

    Hirst, Natasha L; Lawton, Scott P; Walker, Anthony J

    2016-06-01

    Cyclic AMP (cAMP)-dependent protein kinase/protein kinase A regulates multiple processes in eukaryotes by phosphorylating diverse cellular substrates, including metabolic and signalling enzymes, ion channels and transcription factors. Here we provide insight into protein kinase A signalling in cercariae and 24h in vitro cultured somules of the blood parasite, Schistosoma mansoni, which causes human intestinal schistosomiasis. Functional mapping of activated protein kinase A using anti-phospho protein kinase A antibodies and confocal laser scanning microscopy revealed activated protein kinase A in the central and peripheral nervous system, oral-tip sensory papillae, oesophagus and excretory system of intact cercariae. Cultured 24h somules, which biologically represent the skin-resident stage of the parasite, exhibited similar activation patterns in oesophageal and nerve tissues but also displayed striking activation at the tegument and activation in a region resembling the germinal 'stem' cell cluster. The adenylyl cyclase activator, forskolin, stimulated somule protein kinase A activation and produced a hyperkinesia phenotype. The biogenic amines, serotonin and dopamine known to be present in skin also induced protein kinase A activation in somules, whereas neuropeptide Y or [Leu(31),Pro(34)]-neuropeptide Y attenuated protein kinase A activation. However, neuropeptide Y did not block the forskolin-induced somule hyperkinesia. Bioinformatic investigation of potential protein associations revealed 193 medium confidence and 59 high confidence protein kinase A interacting partners in S. mansoni, many of which possess putative protein kinase A phosphorylation sites. These data provide valuable insight into the intricacies of protein kinase A signalling in S. mansoni and a framework for further physiological investigations into the roles of protein kinase A in schistosomes, particularly in the context of interactions between the parasite and the host. PMID:26777870

  18. Analysis of the protein-protein interaction networks of differentially expressed genes in pulmonary embolism.

    PubMed

    Wang, Hao; Wang, Chen; Zhang, Lei; Lu, Yinghua; Duan, Qianglin; Gong, Zhu; Liang, Aibin; Song, Haoming; Wang, Lemin

    2015-04-01

    The aim of the present study was to explore the function and interaction of differentially expressed genes (DEGs) in pulmonary embolism (PE). The gene expression profile GSE13535, was downloaded from the Gene Expression Omnibus database. The DEGs 2 and 18 h post‑PE initiation were identified using the affy package in R software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs were analyzed using Database for Annotation Visualization and Integrated Discovery (DAVID) online analytical tools. In addition, protein‑protein interaction (PPI) networks of the DEGs were constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. The PPI network at 18 h was modularized using Clusterone, and a functional enrichment analysis of the DEGs in the top three modules was performed with DAVID. Overall, 80 and 346 DEGs were identified 2 and 18 h after PE initiation, respectively. The KEGG pathways, including chemokine signaling and toll‑like receptor signaling, were shown to be significantly enriched. The five highest degree nodes in the PPI networks at 2 or 18 h were screened. The module analysis of the PPI network at 18 h revealed 11 hub nodes. A Gene Ontology terms analysis demonstrated that the DEGs in the top three modules were associated with the inflammatory, defense and immune responses. The results of the present study suggest that the DEGs identified, including chemokine‑related genes TFPI2 and TNF, may be potential target genes for the treatment of PE. The chemokine signaling pathway, inflammatory response and immune response were explored, and it may be suggested that these pathways have important roles in PE.

  19. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  20. The Signaling State of Orange Carotenoid Protein

    PubMed Central

    Maksimov, Eugene G.; Shirshin, Evgeny A.; Sluchanko, Nikolai N.; Zlenko, Dmitry V.; Parshina, Evgenia Y.; Tsoraev, Georgy V.; Klementiev, Konstantin E.; Budylin, Gleb S.; Schmitt, Franz-Josef; Friedrich, Thomas; Fadeev, Victor V.; Paschenko, Vladimir Z.; Rubin, Andrew B.

    2015-01-01

    Orange carotenoid protein (OCP) is the photoactive protein that is responsible for high light tolerance in cyanobacteria. We studied the kinetics of the OCP photocycle by monitoring changes in its absorption spectrum, intrinsic fluorescence, and fluorescence of the Nile red dye bound to OCP. It was demonstrated that all of these three methods provide the same kinetic parameters of the photocycle, namely, the kinetics of OCP relaxation in darkness was biexponential with a ratio of two components equal to 2:1 independently of temperature. Whereas the changes of the absorption spectrum of OCP characterize the geometry and environment of its chromophore, the intrinsic fluorescence of OCP reveals changes in its tertiary structure, and the fluorescence properties of Nile red indicate the exposure of hydrophobic surface areas of OCP to the solvent following the photocycle. The results of molecular-dynamics studies indicated the presence of two metastable conformations of 3′-hydroxyechinenone, which is consistent with characteristic changes in the Raman spectra. We conclude that rotation of the β-ionylidene ring in the C-terminal domain of OCP could be one of the first conformational rearrangements that occur during photoactivation. The obtained results suggest that the photoactivated form of OCP represents a molten globule-like state that is characterized by increased mobility of tertiary structure elements and solvent accessibility. PMID:26244741

  1. Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

    PubMed

    Wallach, Thomas; Schellenberg, Katja; Maier, Bert; Kalathur, Ravi Kiran Reddy; Porras, Pablo; Wanker, Erich E; Futschik, Matthias E; Kramer, Achim

    2013-03-01

    Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner. PMID:23555304

  2. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases

    PubMed Central

    Lin, Peng-Lin; Yu, Ya-Wen

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn’s disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn’s disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  3. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases.

    PubMed

    Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn's disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn's disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  4. Evolution of biomolecular networks: lessons from metabolic and protein interactions.

    PubMed

    Yamada, Takuji; Bork, Peer

    2009-11-01

    Despite only becoming popular at the beginning of this decade, biomolecular networks are now frameworks that facilitate many discoveries in molecular biology. The nodes of these networks are usually proteins (specifically enzymes in metabolic networks), whereas the links (or edges) are their interactions with other molecules. These networks are made up of protein-protein interactions or enzyme-enzyme interactions through shared metabolites in the case of metabolic networks. Evolutionary analysis has revealed that changes in the nodes and links in protein-protein interaction and metabolic networks are subject to different selection pressures owing to distinct topological features. However, many evolutionary constraints can be uncovered only if temporal and spatial aspects are included in the network analysis.

  5. Protein function prediction using neighbor relativity in protein-protein interaction network.

    PubMed

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network.

  6. Signaling networks regulating leukocyte podosome dynamics and function

    PubMed Central

    Dovas, Athanassios; Cox, Dianne

    2011-01-01

    Podosomes are ventral adhesion structures prominent in cells of the myeloid lineage. A common aspect of these cells is that they are highly motile and are required to traverse multiple tissue barriers in order to perform their functions. Recently podosomes have gathered attention from researchers as important cellular structures that can influence cell adhesion, motility and matrix remodeling. Adhesive and soluble ligands act via transmembrane receptors and propagate signals to the leukocyte cytoskeleton via small G proteins of the Rho family, tyrosine kinases and scaffold proteins and are able to induce podosome formation and rearrangements. Manipulation of the signals that regulate podosome formation and dynamics can therefore be a strategy to interfere with leukocyte functions in a multitude of pathological settings, such as infections, atherosclerosis and arthritis. Here, we review the major signaling molecules that act in the formation and regulation of podosomes. PMID:21342664

  7. Hormone signaling through protein destruction: a lesson from plants.

    PubMed

    Tan, Xu; Zheng, Ning

    2009-02-01

    Ubiquitin-dependent protein degradation has emerged as a major pathway regulating eukaryotic biology. By employing a variety of ubiquitin ligases to target specific cellular proteins, the ubiquitin-proteasome system controls physiological processes in a highly regulated fashion. Recent studies on a plant hormone auxin have unveiled a novel paradigm of signal transduction in which ubiquitin ligases function as hormone receptors. Perceived by the F-box protein subunit of the SCF(TIR1) ubiquitin ligase, auxin directly promotes the recruitment of a family of transcriptional repressors for ubiquitination, thereby activating extensive transcriptional programs. Structural studies have revealed that auxin functions through a "molecular glue" mechanism to enhance protein-protein interactions with the assistance of another small molecule cofactor, inositol hexakisphosphate. Given the extensive repertoire of similar ubiquitin ligases in eukaryotic cells, this novel and widely adopted hormone-signaling mechanism in plants may also exist in other organisms.

  8. Rap G protein signal in normal and disordered lymphohematopoiesis.

    PubMed

    Minato, Nagahiro

    2013-09-10

    Rap proteins (Rap1, Rap2a, b, c) are small molecular weight GTPases of the Ras family. Rap G proteins mediate diverse cellular events such as cell adhesion, proliferation, and gene activation through various signaling pathways. Activation of Rap signal is regulated tightly by several specific regulatory proteins including guanine nucleotide exchange factors and GTPase-activating proteins. Beyond cell biological studies, increasing attempts have been made in the past decade to define the roles of Rap signal in specific functions of normal tissue systems as well as in cancer. In the immune and hematopoietic systems, Rap signal plays crucial roles in the development and function of essentially all lineages of lymphocytes and hematopoietic cells, and importantly, deregulated Rap signal may lead to unique pathological conditions depending on the affected cell types, including various types of leukemia and autoimmunity. The phenotypical studies have unveiled novel, even unexpected functional aspects of Rap signal in cells from a variety of tissues, providing potentially important clues for controlling human diseases, including malignancy.

  9. Rap G protein signal in normal and disordered lymphohematopoiesis

    SciTech Connect

    Minato, Nagahiro

    2013-09-10

    Rap proteins (Rap1, Rap2a, b, c) are small molecular weight GTPases of the Ras family. Rap G proteins mediate diverse cellular events such as cell adhesion, proliferation, and gene activation through various signaling pathways. Activation of Rap signal is regulated tightly by several specific regulatory proteins including guanine nucleotide exchange factors and GTPase-activating proteins. Beyond cell biological studies, increasing attempts have been made in the past decade to define the roles of Rap signal in specific functions of normal tissue systems as well as in cancer. In the immune and hematopoietic systems, Rap signal plays crucial roles in the development and function of essentially all lineages of lymphocytes and hematopoietic cells, and importantly, deregulated Rap signal may lead to unique pathological conditions depending on the affected cell types, including various types of leukemia and autoimmunity. The phenotypical studies have unveiled novel, even unexpected functional aspects of Rap signal in cells from a variety of tissues, providing potentially important clues for controlling human diseases, including malignancy.

  10. Regulation of Latent Membrane Protein 1 Signaling through Interaction with Cytoskeletal Proteins

    PubMed Central

    Holthusen, Kirsten; Talaty, Pooja

    2015-01-01

    ABSTRACT Latent membrane protein 1 (LMP1) of Epstein-Barr virus (EBV) induces constitutive signaling in EBV-infected cells to ensure the survival of the latently infected cells. LMP1 is localized to lipid raft domains to induce signaling. In the present study, a genome-wide screen based on bimolecular fluorescence complementation (BiFC) was performed to identify LMP1-binding proteins. Several actin cytoskeleton-associated proteins were identified in the screen. Overexpression of these proteins affected LMP1-induced signaling. BiFC between the identified proteins and LMP1 was localized to lipid raft domains and was dependent on LMP1-induced signaling. Proximity biotinylation assays with LMP1 induced biotinylation of the actin-associated proteins, which were shifted in molecular mass. Together, the findings of this study suggest that the association of LMP1 with lipid rafts is mediated at least in part through interactions with the actin cytoskeleton. IMPORTANCE LMP1 signaling requires oligomerization, lipid raft partitioning, and binding to cellular adaptors. The current study utilized a genome-wide screen to identify several actin-associated proteins as candidate LMP1-binding proteins. The interaction between LMP1 and these proteins was localized to lipid rafts and dependent on LMP1 signaling. This suggests that the association of LMP1 with lipid rafts is mediated through interactions with actin-associated proteins. PMID:25948738

  11. Revisiting Apoplastic Auxin Signaling Mediated by AUXIN BINDING PROTEIN 1

    PubMed Central

    Feng, Mingxiao; Kim, Jae-Yean

    2015-01-01

    It has been suggested that AUXIN BINDING PROTEIN 1 (ABP1) functions as an apoplastic auxin receptor, and is known to be involved in the post-transcriptional process, and largely independent of the already well-known SKP-cullin-F-box-transport inhibitor response (TIR1) /auxin signaling F-box (AFB) (SCFTIR1/AFB) pathway. In the past 10 years, several key components downstream of ABP1 have been reported. After perceiving the auxin signal, ABP1 interacts, directly or indirectly, with plasma membrane (PM)-localized transmembrane proteins, transmembrane kinase (TMK) or SPIKE1 (SPK1), or other unidentified proteins, which transfer the signal into the cell to the Rho of plants (ROP). ROPs interact with their effectors, such as the ROP interactive CRIB motif-containing protein (RIC), to regulate the endocytosis/exocytosis of the auxin efflux carrier PIN-FORMED (PIN) proteins to mediate polar auxin transport across the PM. Additionally, ABP1 is a negative regulator of the traditional SCFTIR1/AFB auxin signaling pathway. However, Gao et al. (2015) very recently reported that ABP1 is not a key component in auxin signaling, and the famous abp1-1 and abp1-5 mutant Arabidopsis lines are being called into question because of possible additional mutantion sites, making it necessary to reevaluate ABP1. In this review, we will provide a brief overview of the history of ABP1 research. PMID:26467289

  12. Revisiting Apoplastic Auxin Signaling Mediated by AUXIN BINDING PROTEIN 1.

    PubMed

    Feng, Mingxiao; Kim, Jae-Yean

    2015-10-01

    It has been suggested that AUXIN BINDING PROTEIN 1 (ABP1) functions as an apoplastic auxin receptor, and is known to be involved in the post-transcriptional process, and largely independent of the already well-known SKP-cullin-F-box-transport inhibitor response (TIR1) /auxin signaling F-box (AFB) (SCF(TIR1/AFB)) pathway. In the past 10 years, several key components downstream of ABP1 have been reported. After perceiving the auxin signal, ABP1 interacts, directly or indirectly, with plasma membrane (PM)-localized transmembrane proteins, transmembrane kinase (TMK) or SPIKE1 (SPK1), or other unidentified proteins, which transfer the signal into the cell to the Rho of plants (ROP). ROPs interact with their effectors, such as the ROP interactive CRIB motif-containing protein (RIC), to regulate the endocytosis/exocytosis of the auxin efflux carrier PIN-FORMED (PIN) proteins to mediate polar auxin transport across the PM. Additionally, ABP1 is a negative regulator of the traditional SCF(TIR1/AFB) auxin signaling pathway. However, Gao et al. (2015) very recently reported that ABP1 is not a key component in auxin signaling, and the famous abp1-1 and abp1-5 mutant Arabidopsis lines are being called into question because of possible additional mutantion sites, making it necessary to reevaluate ABP1. In this review, we will provide a brief overview of the history of ABP1 research.

  13. Wireless sensor networks for monitoring physiological signals of multiple patients.

    PubMed

    Dilmaghani, R S; Bobarshad, H; Ghavami, M; Choobkar, S; Wolfe, C

    2011-08-01

    This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time. PMID:23851949

  14. Wireless sensor networks for monitoring physiological signals of multiple patients.

    PubMed

    Dilmaghani, R S; Bobarshad, H; Ghavami, M; Choobkar, S; Wolfe, C

    2011-08-01

    This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time.

  15. Protein-protein interaction network-based detection of functionally similar proteins within species.

    PubMed

    Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

    2012-07-01

    Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent.

  16. The Calcineurin Signaling Network Evolves Via Conserved Kinase–Phosphatase Modules That Transcend Substrate Identity

    PubMed Central

    Bodenmiller, Bernd; Wanka, Stefanie; Landry, Christian R.; Aebersold, Ruedi; Cyert, Martha S.

    2014-01-01

    Summary To define the first functional network for calcineurin, the conserved Ca2+/calmodulin-regulated phosphatase, we systematically identified its substrates in S. cerevisiae using phosphoproteomics and bioinformatics, followed by co-purification and dephosphorylation assays. This study establishes new calcineurin functions and reveals mechanisms that shape calcineurin network evolution. Analyses of closely related yeasts show that many proteins were recently recruited to the network by acquiring a calcineurin-recognition motif. Calcineurin substrates in yeast and mammals are distinct due to network rewiring but surprisingly are phosphorylated by similar kinases. We postulate that co-recognition of conserved substrate features, including phosphorylation and docking motifs, preserves calcineurin-kinase opposition during evolution. One example we document is a composite docking site that confers substrate recognition by both calcineurin and MAPK. We propose that conserved kinase-phosphatase pairs define the architecture of signaling networks and allow other connections between kinases and phosphatases to develop and establish common regulatory motifs in signaling networks. PMID:24930733

  17. Multitask learning of signaling and regulatory networks with application to studying human response to flu.

    PubMed

    Jain, Siddhartha; Gitter, Anthony; Bar-Joseph, Ziv

    2014-12-01

    Reconstructing regulatory and signaling response networks is one of the major goals of systems biology. While several successful methods have been suggested for this task, some integrating large and diverse datasets, these methods have so far been applied to reconstruct a single response network at a time, even when studying and modeling related conditions. To improve network reconstruction we developed MT-SDREM, a multi-task learning method which jointly models networks for several related conditions. In MT-SDREM, parameters are jointly constrained across the networks while still allowing for condition-specific pathways and regulation. We formulate the multi-task learning problem and discuss methods for optimizing the joint target function. We applied MT-SDREM to reconstruct dynamic human response networks for three flu strains: H1N1, H5N1 and H3N2. Our multi-task learning method was able to identify known and novel factors and genes, improving upon prior methods that model each condition independently. The MT-SDREM networks were also better at identifying proteins whose removal affects viral load indicating that joint learning can still lead to accurate, condition-specific, networks. Supporting website with MT-SDREM implementation: http://sb.cs.cmu.edu/mtsdrem. PMID:25522349

  18. Regulation of Bone Morphogenetic Protein Signaling by ADP-ribosylation*

    PubMed Central

    Watanabe, Yukihide; Papoutsoglou, Panagiotis; Maturi, Varun; Tsubakihara, Yutaro; Hottiger, Michael O.; Heldin, Carl-Henrik; Moustakas, Aristidis

    2016-01-01

    We previously established a mechanism of negative regulation of transforming growth factor β signaling mediated by the nuclear ADP-ribosylating enzyme poly-(ADP-ribose) polymerase 1 (PARP1) and the deribosylating enzyme poly-(ADP-ribose) glycohydrolase (PARG), which dynamically regulate ADP-ribosylation of Smad3 and Smad4, two central signaling proteins of the pathway. Here we demonstrate that the bone morphogenetic protein (BMP) pathway can also be regulated by the opposing actions of PARP1 and PARG. PARG positively contributes to BMP signaling and forms physical complexes with Smad5 and Smad4. The positive role PARG plays during BMP signaling can be neutralized by PARP1, as demonstrated by experiments where PARG and PARP1 are simultaneously silenced. In contrast to PARG, ectopic expression of PARP1 suppresses BMP signaling, whereas silencing of endogenous PARP1 enhances signaling and BMP-induced differentiation. The two major Smad proteins of the BMP pathway, Smad1 and Smad5, interact with PARP1 and can be ADP-ribosylated in vitro, whereas PARG causes deribosylation. The overall outcome of this mode of regulation of BMP signal transduction provides a fine-tuning mechanism based on the two major enzymes that control cellular ADP-ribosylation. PMID:27129221

  19. Signaling by the G12 class of G proteins.

    PubMed

    Dhanasekaran, N; Dermott, J M

    1996-06-01

    The G12 class of G proteins are defined by the alpha-subunits of mammalian G12 and G13. Biochemical and mutational characterization of G alpha 12/13 have identified several novel signaling pathways regulated by these alpha-subunits. Studies with the constitutively activated mutants of G alpha 12 and G alpha 13 have indicated that they stimulate mitogenic signaling pathways leading to the oncogenic transformation of fibroblast cell lines. Recent analyses have indicated that G alpha 12 and G alpha 13 regulate cytoplasmic as well as nuclear signaling events such as activation of the Jun N-terminal kinase signaling module, Na+/H+ exchangers, focal adhesion assemblies, and transcriptional activation of specific primary response genes. The emerging view suggests that these signaling events represent an integrated response regulated by G12 and G13. This review discusses the diverse signaling responses regulated by G12 and G13, and the interrelationship of these responses. PMID:8842523

  20. Analysis of membrane proteins in metagenomics: networks of correlated environmental features and protein families.

    PubMed

    Patel, Prianka V; Gianoulis, Tara A; Bjornson, Robert D; Yip, Kevin Y; Engelman, Donald M; Gerstein, Mark B

    2010-07-01

    Recent metagenomics studies have begun to sample the genomic diversity among disparate habitats and relate this variation to features of the environment. Membrane proteins are an intuitive, but thus far overlooked, choice in this type of analysis as they directly interact with the environment, receiving signals from the outside and transporting nutrients. Using global ocean sampling (GOS) data, we found nearly approximately 900,000 membrane proteins in large-scale metagenomic sequence, approximately a fifth of which are completely novel, suggesting a large space of hitherto unexplored protein diversity. Using GPS coordinates for the GOS sites, we extracted additional environmental features via interpolation from the World Ocean Database, the National Center for Ecological Analysis and Synthesis, and empirical models of dust occurrence. This allowed us to study membrane protein variation in terms of natural features, such as phosphate and nitrate concentrations, and also in terms of human impacts, such as pollution and climate change. We show that there is widespread variation in membrane protein content across marine sites, which is correlated with changes in both oceanographic variables and human factors. Furthermore, using these data, we developed an approach, protein families and environment features network (PEN), to quantify and visualize the correlations. PEN identifies small groups of covarying environmental features and membrane protein families, which we call "bimodules." Using this approach, we find that the affinity of phosphate transporters is related to the concentration of phosphate and that the occurrence of iron transporters is connected to the amount of shipping, pollution, and iron-containing dust.

  1. Global multiple protein-protein interaction network alignment by combining pairwise network alignments

    PubMed Central

    2015-01-01

    Background A wealth of protein interaction data has become available in recent years, creating an urgent need for powerful analysis techniques. In this context, the problem of finding biologically meaningful correspondences between different protein-protein interaction networks (PPIN) is of particular interest. The PPIN of a species can be compared with that of other species through the process of PPIN alignment. Such an alignment can provide insight into basic problems like species evolution and network component function determination, as well as translational problems such as target identification and elucidation of mechanisms of disease spread. Furthermore, multiple PPINs can be aligned simultaneously, expanding the analytical implications of the result. While there are several pairwise network alignment algorithms, few methods are capable of multiple network alignment. Results We propose SMAL, a MNA algorithm based on the philosophy of scaffold-based alignment. SMAL is capable of converting results from any global pairwise alignment algorithms into a MNA in linear time. Using this method, we have built multiple network alignments based on combining pairwise alignments from a number of publicly available (pairwise) network aligners. We tested SMAL using PPINs of eight species derived from the IntAct repository and employed a number of measures to evaluate performance. Additionally, as part of our experimental investigations, we compared the effectiveness of SMAL while aligning up to eight input PPINs, and examined the effect of scaffold network choice on the alignments. Conclusions A key advantage of SMAL lies in its ability to create MNAs through the use of pairwise network aligners for which native MNA implementations do not exist. Experiments indicate that the performance of SMAL was comparable to that of the native MNA implementation of established methods such as IsoRankN and SMETANA. However, in terms of computational time, SMAL was significantly faster

  2. Cell signaling through protein kinase C oxidation and activation.

    PubMed

    Cosentino-Gomes, Daniela; Rocco-Machado, Nathália; Meyer-Fernandes, José Roberto

    2012-01-01

    Due to the growing importance of cellular signaling mediated by reactive oxygen species (ROS), proteins that are reversibly modulated by these reactant molecules are of high interest. In this context, protein kinases and phosphatases, which act coordinately in the regulation of signal transduction through the phosphorylation and dephosphorylation of target proteins, have been described to be key elements in ROS-mediated signaling events. The major mechanism by which these proteins may be modified by oxidation involves the presence of key redox-sensitive cysteine residues. Protein kinase C (PKC) is involved in a variety of cellular signaling pathways. These proteins have been shown to contain a unique structural feature that is susceptible to oxidative modification. A large number of scientific studies have highlighted the importance of ROS as a second messenger in numerous cellular processes, including cell proliferation, gene expression, adhesion, differentiation, senescence, and apoptosis. In this context, the goal of this review is to discuss the mechanisms by which PKCs are modulated by ROS and how these processes are involved in the cellular response. PMID:23109817

  3. Robustness and Evolvability of the Human Signaling Network

    PubMed Central

    Kim, Jeong-Rae; Munoz, Amaya Garcia; Kolch, Walter; Cho, Kwang-Hyun

    2014-01-01

    Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores. PMID:25077791

  4. Small G proteins and their regulators in cellular signalling.

    PubMed

    Csépányi-Kömi, Roland; Lévay, Magdolna; Ligeti, Erzsébet

    2012-04-28

    Small molecular weight GTPases (small G proteins) are essential in the transduction of signals from different plasma membrane receptors. Due to their endogenous GTP-hydrolyzing activity, these proteins function as time-dependent biological switches controlling diverse cellular functions including cell shape and migration, cell proliferation, gene transcription, vesicular transport and membrane-trafficking. This review focuses on endocrine diseases linked to small G proteins. We provide examples for the regulation of the activity of small G proteins by various mechanisms such as posttranslational modifications, guanine nucleotide exchange factors (GEFs), GTPase activating proteins (GAPs) or guanine nucleotide dissociation inhibitors (GDIs). Finally we summarize endocrine diseases where small G proteins or their regulatory proteins have been revealed as the cause.

  5. A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protien-mediated kinetic scaffolding.

    PubMed

    Zhong, Huailing; Wade, Susan M; Woolf, Peter J; Linderman, Jennifer J; Traynor, John R; Neubig, Richard R

    2003-02-28

    Regulators of G protein signaling (RGS) are GTPase-accelerating proteins (GAPs), which can inhibit heterotrimeric G protein pathways. In this study, we provide experimental and theoretical evidence that high concentrations of receptors (as at a synapse) can lead to saturation of GDP-GTP exchange making GTP hydrolysis rate-limiting. This results in local depletion of inactive heterotrimeric G-GDP, which is reversed by RGS GAP activity. Thus, RGS enhances receptor-mediated G protein activation even as it deactivates the G protein. Evidence supporting this model includes a GTP-dependent enhancement of guanosine 5'-3-O-(thio)triphosphate (GTPgammaS) binding to G(i) by RGS. The RGS domain of RGS4 is sufficient for this, not requiring the NH(2)- or COOH-terminal extensions. Furthermore, a kinetic model including only the GAP activity of RGS replicates the GTP-dependent enhancement of GTPgammaS binding observed experimentally. Finally in a Monte Carlo model, this mechanism results in a dramatic "spatial focusing" of active G protein. Near the receptor, G protein activity is maintained even with RGS due to the ability of RGS to reduce depletion of local Galpha-GDP levels permitting rapid recoupling to receptor and maintained G protein activation near the receptor. In contrast, distant signals are suppressed by the RGS, since Galpha-GDP is not depleted there. Thus, a novel RGS-mediated "kinetic scaffolding" mechanism is proposed which narrows the spatial range of active G protein around a cluster of receptors limiting the spill-over of G protein signals to more distant effector molecules, thus enhancing the specificity of G(i) protein signals. PMID:12446706

  6. A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protien-mediated kinetic scaffolding.

    PubMed

    Zhong, Huailing; Wade, Susan M; Woolf, Peter J; Linderman, Jennifer J; Traynor, John R; Neubig, Richard R

    2003-02-28

    Regulators of G protein signaling (RGS) are GTPase-accelerating proteins (GAPs), which can inhibit heterotrimeric G protein pathways. In this study, we provide experimental and theoretical evidence that high concentrations of receptors (as at a synapse) can lead to saturation of GDP-GTP exchange making GTP hydrolysis rate-limiting. This results in local depletion of inactive heterotrimeric G-GDP, which is reversed by RGS GAP activity. Thus, RGS enhances receptor-mediated G protein activation even as it deactivates the G protein. Evidence supporting this model includes a GTP-dependent enhancement of guanosine 5'-3-O-(thio)triphosphate (GTPgammaS) binding to G(i) by RGS. The RGS domain of RGS4 is sufficient for this, not requiring the NH(2)- or COOH-terminal extensions. Furthermore, a kinetic model including only the GAP activity of RGS replicates the GTP-dependent enhancement of GTPgammaS binding observed experimentally. Finally in a Monte Carlo model, this mechanism results in a dramatic "spatial focusing" of active G protein. Near the receptor, G protein activity is maintained even with RGS due to the ability of RGS to reduce depletion of local Galpha-GDP levels permitting rapid recoupling to receptor and maintained G protein activation near the receptor. In contrast, distant signals are suppressed by the RGS, since Galpha-GDP is not depleted there. Thus, a novel RGS-mediated "kinetic scaffolding" mechanism is proposed which narrows the spatial range of active G protein around a cluster of receptors limiting the spill-over of G protein signals to more distant effector molecules, thus enhancing the specificity of G(i) protein signals.

  7. Towards Systematic Discovery of Signaling Networks in Budding Yeast Filamentous Growth Stress Response Using Interventional Phosphorylation Data

    PubMed Central

    Zhang, Yan; Kweon, Hye Kyong; Shively, Christian; Kumar, Anuj; Andrews, Philip C.

    2013-01-01

    Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number of detectable sites per protein. Here, we propose a comprehensive quantitative analysis pipeline customized for phosphoproteome data from interventional experiments for identifying key proteins in specific pathways, discovering the protein-protein interactions and inferring the signaling network. We also made an effort to partially compensate for the missing value problem, a chronic issue for proteomics studies. The dataset used for this study was generated using SILAC (Stable Isotope Labeling with Amino acids in Cell culture) technique with interventional experiments (kinase-dead mutations). The major components of the pipeline include phosphopeptide meta-analysis, correlation network analysis and causal relationship discovery. We have successfully applied our pipeline to interventional experiments identifying phosphorylation events underlying the transition to a filamentous growth form in Saccharomyces cerevisiae. We identified 5 high-confidence proteins from meta-analysis, and 19 hub proteins from correlation analysis (Pbi2p and Hsp42p were identified by both analyses). All these proteins are involved in stress responses. Nine of them have direct or indirect evidence of involvement in filamentous growth. In addition, we tested four of our predicted proteins, Nth1p, Pbi2p, Pdr12p and Rcn2p, by interventional phenotypic experiments and all of them present differential invasive growth, providing prospective validation of our approach. This comprehensive pipeline presents a

  8. Signaling Network Map of Endothelial TEK Tyrosine Kinase.

    PubMed

    Khan, Aafaque Ahmad; Sandhya, Varot K; Singh, Priyata; Parthasarathy, Deepak; Kumar, Awinav; Advani, Jayshree; Gattu, Rudrappa; Ranjit, Dhanya V; Vaidyanathan, Rama; Mathur, Premendu Prakash; Prasad, T S Keshava; Mac Gabhann, F; Pandey, Akhilesh; Raju, Rajesh; Gowda, Harsha

    2014-01-01

    TEK tyrosine kinase is primarily expressed on endothelial cells and is most commonly referred to as TIE2. TIE2 is a receptor tyrosine kinase modulated by its ligands, angiopoietins, to regulate the development and remodeling of vascular system. It is also one of the critical pathways associated with tumor angiogenesis and familial venous malformations. Apart from the vascular system, TIE2 signaling is also associated with postnatal hematopoiesis. Despite the involvement of TIE2-angiopoietin system in several diseases, the downstream molecular events of TIE2-angiopoietin signaling are not reported in any pathway repository. Therefore, carrying out a detailed review of published literature, we have documented molecular signaling events mediated by TIE2 in response to angiopoietins and developed a network map of TIE2 signaling. The pathway information is freely available to the scientific community through NetPath, a manually curated resource of signaling pathways. We hope that this pathway resource will provide an in-depth view of TIE2-angiopoietin signaling and will lead to identification of potential therapeutic targets for TIE2-angiopoietin associated disorders.

  9. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    SciTech Connect

    Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  10. Computational models of signalling networks for non-linear control.

    PubMed

    Fuente, Luis A; Lones, Michael A; Turner, Alexander P; Stepney, Susan; Caves, Leo S; Tyrrell, Andy M

    2013-05-01

    Artificial signalling networks (ASNs) are a computational approach inspired by the signalling processes inside cells that decode outside environmental information. Using evolutionary algorithms to induce complex behaviours, we show how chaotic dynamics in a conservative dynamical system can be controlled. Such dynamics are of particular interest as they mimic the inherent complexity of non-linear physical systems in the real world. Considering the main biological interpretations of cellular signalling, in which complex behaviours and robust cellular responses emerge from the interaction of multiple pathways, we introduce two ASN representations: a stand-alone ASN and a coupled ASN. In particular we note how sophisticated cellular communication mechanisms can lead to effective controllers, where complicated problems can be divided into smaller and independent tasks.

  11. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    PubMed Central

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  12. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    PubMed

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  13. Bone Morphogenetic Protein (BMP) signaling in development and human diseases

    PubMed Central

    Wang, Richard N.; Green, Jordan; Wang, Zhongliang; Deng, Youlin; Qiao, Min; Peabody, Michael; Zhang, Qian; Ye, Jixing; Yan, Zhengjian; Denduluri, Sahitya; Idowu, Olumuyiwa; Li, Melissa; Shen, Christine; Hu, Alan; Haydon, Rex C.; Kang, Richard; Mok, James; Lee, Michael J.; Luu, Hue L.; Shi, Lewis L.

    2014-01-01

    Bone Morphogenetic Proteins (BMPs) are a group of signaling molecules that belongs to the Transforming Growth Factor-β (TGF-β) superfamily of proteins. Initially discovered for their ability to induce bone formation, BMPs are now known to play crucial roles in all organ systems. BMPs are important in embryogenesis and development, and also in maintenance of adult tissue homeostasis. Mouse knockout models of various components of the BMP signaling pathway result in embryonic lethality or marked defects, highlighting the essential functions of BMPs. In this review, we first outline the basic aspects of BMP signaling and then focus on genetically manipulated mouse knockout models that have helped elucidate the role of BMPs in development. A significant portion of this review is devoted to the prominent human pathologies associated with dysregulated BMP signaling. PMID:25401122

  14. Heterotrimeric G protein signaling in polycystic kidney disease.

    PubMed

    Hama, Taketsugu; Park, Frank

    2016-07-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a signalopathy of renal tubular epithelial cells caused by naturally occurring mutations in two distinct genes, polycystic kidney disease 1 (PKD1) and 2 (PKD2). Genetic variants in PKD1, which encodes the polycystin-1 (PC-1) protein, remain the predominant factor associated with the pathogenesis of nearly two-thirds of all patients diagnosed with PKD. Although the relationship between defective PC-1 with renal cystic disease initiation and progression remains to be fully elucidated, there are numerous clinical studies that have focused upon the control of effector systems involving heterotrimeric G protein regulation. A major regulator in the activation state of heterotrimeric G proteins are G protein-coupled receptors (GPCRs), which are defined by their seven transmembrane-spanning regions. PC-1 has been considered to function as an unconventional GPCR, but the mechanisms by which PC-1 controls signal processing, magnitude, or trafficking through heterotrimeric G proteins remains to be fully known. The diversity of heterotrimeric G protein signaling in PKD is further complicated by the presence of non-GPCR proteins in the membrane or cytoplasm that also modulate the functional state of heterotrimeric G proteins within the cell. Moreover, PC-1 abnormalities promote changes in hormonal systems that ultimately interact with distinct GPCRs in the kidney to potentially amplify or antagonize signaling output from PC-1. This review will focus upon the canonical and noncanonical signaling pathways that have been described in PKD with specific emphasis on which heterotrimeric G proteins are involved in the pathological reorganization of the tubular epithelial cell architecture to exacerbate renal cystogenic pathways. PMID:27199453

  15. Heterotrimeric G protein signaling in polycystic kidney disease.

    PubMed

    Hama, Taketsugu; Park, Frank

    2016-07-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a signalopathy of renal tubular epithelial cells caused by naturally occurring mutations in two distinct genes, polycystic kidney disease 1 (PKD1) and 2 (PKD2). Genetic variants in PKD1, which encodes the polycystin-1 (PC-1) protein, remain the predominant factor associated with the pathogenesis of nearly two-thirds of all patients diagnosed with PKD. Although the relationship between defective PC-1 with renal cystic disease initiation and progression remains to be fully elucidated, there are numerous clinical studies that have focused upon the control of effector systems involving heterotrimeric G protein regulation. A major regulator in the activation state of heterotrimeric G proteins are G protein-coupled receptors (GPCRs), which are defined by their seven transmembrane-spanning regions. PC-1 has been considered to function as an unconventional GPCR, but the mechanisms by which PC-1 controls signal processing, magnitude, or trafficking through heterotrimeric G proteins remains to be fully known. The diversity of heterotrimeric G protein signaling in PKD is further complicated by the presence of non-GPCR proteins in the membrane or cytoplasm that also modulate the functional state of heterotrimeric G proteins within the cell. Moreover, PC-1 abnormalities promote changes in hormonal systems that ultimately interact with distinct GPCRs in the kidney to potentially amplify or antagonize signaling output from PC-1. This review will focus upon the canonical and noncanonical signaling pathways that have been described in PKD with specific emphasis on which heterotrimeric G proteins are involved in the pathological reorganization of the tubular epithelial cell architecture to exacerbate renal cystogenic pathways.

  16. Emerging insights into heterotrimeric G protein signaling in plants.

    PubMed

    Xu, Quan; Zhao, Mingzhu; Wu, Kun; Fu, Xiangdong; Liu, Qian

    2016-08-20

    Heterotrimeric guanine nucleotide-binding protein (G protein) signaling is an evolutionarily conserved mechanism in diverse eukaryotic organisms. In plants, the repertoire of the heterotrimeric G protein complex, which is composed of the Gα, Gβ, and Gγ subunits, is much simpler than that in metazoans, and the identity of typical G protein-coupled receptors (GPCRs) together with their ligands still remains unclear. Comparative phenotypic analysis in Arabidopsis and rice plants using gain- and loss-of-function mutants of G protein components revealed that heterotrimeric G protein signaling plays important roles in a wide variety of plant growth and developmental processes. Grain yield is a complex trait determined by quantitative trait loci (QTL) and is influenced by soil nitrogen availability and environmental changes. Recent studies have shown that the manipulation of two non-canonical Gγ subunits, GS3 (GRAIN SIZE 3) and DEP1 (DENSE AND ERECT PANICLE 1), represents new strategies to simultaneously increase grain yield and nitrogen use efficiency in rice. This review discusses the latest advances in our understanding of the heterotrimeric G protein signal transduction pathway and its application in improving yield and stress tolerance in crops. PMID:27520410

  17. Detecting overlapping protein complexes by rough-fuzzy clustering in protein-protein interaction networks.

    PubMed

    Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks.

  18. Bone morphogenetic protein (BMP) signaling regulates mitotic checkpoint protein levels in human breast cancer cells.

    PubMed

    Yan, Hualong; Zhu, Songcheng; Song, Chenlin; Liu, Naifa; Kang, Jiuhong

    2012-04-01

    Aberrant expression of mitotic checkpoint genes compromises mitotic checkpoint, leads to chromosome instability and tumorigenesis. However, the cell signals that control mitotic checkpoint gene expression have not been reported so far. In the present study we show that, in human breast cancer cells, chemical inhibition of Bone morphogenetic proteins (BMPs), but not Transforming Growth Factor-β (TGF-β), abrogates the mitotic arrest induced by nocodazole. Protein expression analysis reveals that inhibition of BMP signaling dramatically down regulates protein levels of mitotic checkpoint components BUB3, Hec1, TTK and MAD2, but inhibition of TGF-β has relatively minor effect on the expression of these proteins. Activation of BMP signaling specifically up regulates BUB3, and activation of Activin A signaling globally down regulates these proteins level. Furthermore, overexpressing MAD2, TTK, BUB3 or Hec1 significantly rescues the mitotic arrest defect caused by BMP inhibition. Our results demonstrated for the first time that TGF-β family cytokines are cellular signals regulating mitotic checkpoint and perturbations in intrinsic BMP signaling could lead to suppression of mitotic checkpoint signaling by downregulating key checkpoint proteins. The results suggest a possible mechanism by which dysregulation of TGF-β signaling causes mitotic checkpoint defects and drives tumorigenesis. The finding also provides a potential and more specific strategy for cancer prevention by targeting BMP and mitotic checkpoint connection. PMID:22234345

  19. G protein signaling in the parasite Entamoeba histolytica

    PubMed Central

    Bosch, Dustin E; Siderovski, David P

    2013-01-01

    The parasite Entamoeba histolytica causes amebic colitis and systemic amebiasis. Among the known amebic factors contributing to pathogenesis are signaling pathways involving heterotrimeric and Ras superfamily G proteins. Here, we review the current knowledge of the roles of heterotrimeric G protein subunits, Ras, Rho and Rab GTPase families in E. histolytica pathogenesis, as well as of their downstream signaling effectors and nucleotide cycle regulators. Heterotrimeric G protein signaling likely modulates amebic motility and attachment to and killing of host cells, in part through activation of an RGS-RhoGEF (regulator of G protein signaling–Rho guanine nucleotide exchange factor) effector. Rho family GTPases, as well as RhoGEFs and Rho effectors (formins and p21-activated kinases) regulate the dynamic actin cytoskeleton of E. histolytica and associated pathogenesis-related cellular processes, such as migration, invasion, phagocytosis and evasion of the host immune response by surface receptor capping. A remarkably large family of 91 Rab GTPases has multiple roles in a complex amebic vesicular trafficking system required for phagocytosis and pinocytosis and secretion of known virulence factors, such as amebapores and cysteine proteases. Although much remains to be discovered, recent studies of G protein signaling in E. histolytica have enhanced our understanding of parasitic pathogenesis and have also highlighted possible targets for pharmacological manipulation. PMID:23519208

  20. Optoelectronic signal processing using finite impulse response neural networks

    NASA Astrophysics Data System (ADS)

    H. B. Xavier da Silveira, Paulo Eduardo

    2001-08-01

    This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the

  1. Cellular Signaling Pathways and Posttranslational Modifications Mediated by Nematode Effector Proteins1

    PubMed Central

    Hewezi, Tarek

    2015-01-01

    Plant-parasitic cyst and root-knot nematodes synthesize and secrete a suite of effector proteins into infected host cells and tissues. These effectors are the major virulence determinants mediating the transformation of normal root cells into specialized feeding structures. Compelling evidence indicates that these effectors directly hijack or manipulate refined host physiological processes to promote the successful parasitism of host plants. Here, we provide an update on recent progress in elucidating the molecular functions of nematode effectors. In particular, we emphasize how nematode effectors modify plant cell wall structure, mimic the activity of host proteins, alter auxin signaling, and subvert defense signaling and immune responses. In addition, we discuss the emerging evidence suggesting that nematode effectors target and recruit various components of host posttranslational machinery in order to perturb the host signaling networks required for immunity and to regulate their own activity and subcellular localization. PMID:26315856

  2. Arabidopsis pentatricopeptide repeat protein SOAR1 plays a critical role in abscisic acid signalling

    PubMed Central

    Mei, Chao; Jiang, Shang-Chuan; Lu, Yan-Fen; Wu, Fu-Qing; Yu, Yong-Tao; Liang, Shan; Feng, Xiu-Jing; Portoles Comeras, Sergi; Lu, Kai; Wu, Zhen; Wang, Xiao-Fang; Zhang, Da-Peng

    2014-01-01

    A dominant suppressor of the ABAR overexpressor, soar1-1D, from CHLH/ABAR [coding for Mg-chelatase H subunit/putative abscisic acid (ABA) receptor (ABAR)] overexpression lines was screened to explore the mechanism of the ABAR-mediated ABA signalling. The SOAR1 gene encodes a pentatricopeptide repeat (PPR) protein which localizes to both the cytosol and nucleus. Down-regulation of SOAR1 strongly enhances, but up-regulation of SOAR1 almost completely impairs, ABA responses, revealing that SOAR1 is a critical, negative, regulator of ABA signalling. Further genetic evidence supports that SOAR1 functions downstream of ABAR and probably upstream of an ABA-responsive transcription factor ABI5. Changes in the SOAR1 expression alter expression of a subset of ABA-responsive genes including ABI5. These findings provide important information to elucidate further the functional mechanism of PPR proteins and the complicated ABA signalling network. PMID:25005137

  3. Analysis of nitrated proteins in Saccharomyces cerevisiae involved in mating signal transduction.

    PubMed

    Kang, Jeong Won; Lee, Na Young; Cho, Kyung-Cho; Lee, Min Young; Choi, Do-Young; Park, Sang-Hyun; Kim, Kwang Pyo

    2015-01-01

    Protein tyrosine nitration (PTN) is a PTM that regulates signal transduction and inflammatory responses, and is related to neurodegenerative and cardiovascular diseases. The cellular function of PTN remains unclear because the low stoichiometry of PTN limits the identification and quantification of nitrated peptides. Effective enrichment is an important aspect of PTN analysis. In this study, we analyzed the in vivo nitroproteome elicited by mating signal transduction in Saccharomyces cerevisiae using a novel chemical enrichment method followed by LC-MS/MS. Nitroproteome profiling successfully identified changes in the nitration states of 14 proteins during mating signal transduction in S. cerevisiae, making this the first reported in vivo nitroproteome in yeast. We investigated the biological functions of these nitroproteins and their relationships to mating signal transduction in S. cerevisiae using a protein-protein interaction network. Our results suggest that PTN and denitration may be involved in nonreactive nitrogen species-mediated signal transduction and can provide clues for understanding the functional roles of PTN in vivo.

  4. Protein modifications involved in neurotransmitter and gasotransmitter signaling

    PubMed Central

    Sen, Nilkantha; Snyder, Solomon H.

    2010-01-01

    Covalent modifications of intracellular proteins, such as phosphorylation, are generally thought to occur as secondary or tertiary responses to neurotransmitters, following the intermediation of membrane receptors and second messengers such as cyclic AMP. By contrast, the gasotransmitter nitric oxide directly S-nitrosylates cysteine residues in diverse intracellular proteins. Recently, hydrogen sulfide has been acknowledged as a gaso-transmitter, which analogously sulfhydrates cysteine residues in proteins. Cysteine residues are also modified by palmitoylation in response to neurotransmitter signaling, possibly in reciprocity with S-nitrosylation. Neurotransmission also elicits sumoylation and acetylation of lysine residues within diverse proteins. This review addresses how these recently appreciated protein modifications impact our thinking about ways in which neurotransmission regulates intracellular protein disposition. PMID:20843563

  5. Type I Signal Peptidase and Protein Secretion in Staphylococcus aureus

    PubMed Central

    Schallenberger, Mark A.; Niessen, Sherry; Shao, Changxia; Fowler, Bruce J.

    2012-01-01

    Staphylococcus aureus is an important human pathogen whose virulence relies on the secretion of many different proteins. In general, the secretion of most proteins in S. aureus, as well as other bacteria, is dependent on the type I signal peptidase (SPase)-mediated cleavage of the N-terminal signal peptide that targets a protein to the general secretory pathway. The arylomycins are a class of natural product antibiotics that inhibit SPase, suggesting that they may be useful chemical biology tools for characterizing the secretome. While wild-type S. aureus (NCTC 8325) is naturally resistant to the arylomycins, sensitivity is conferred via a point mutation in its SPase. Here, we use a synthetic arylomycin along with a sensitized strain of S. aureus and multidimensional protein identification technology (MudPIT) mass spectrometry to identify 46 proteins whose extracellular accumulation requires SPase activity. Forty-four possess identifiable Sec-type signal peptides and thus are likely canonically secreted proteins, while four also appear to possess cell wall retention signals. We also identified the soluble C-terminal domains of two transmembrane proteins, lipoteichoic acid synthase, LtaS, and O-acyteltransferase, OatA, both of which appear to have noncanonical, internal SPase cleavage sites. Lastly, we identified three proteins, HtrA, PrsA, and SAOUHSC_01761, whose secretion is induced by arylomycin treatment. In addition to elucidating fundamental aspects of the physiology and pathology of S. aureus, the data suggest that an arylomycin-based therapeutic would reduce virulence while simultaneously eradicating an infection. PMID:22447899

  6. Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network

    PubMed Central

    Dong, Yongcheng; Kuang, Qifan; Dai, Xu; Li, Rong; Wu, Yiming; Leng, Weijia; Li, Yizhou; Li, Menglong

    2015-01-01

    The human papillomavirus 16 (HPV16) has high risk to lead various cancers and afflictions, especially, the cervical cancer. Therefore, investigating the pathogenesis of HPV16 is very important for public health. Protein-protein interaction (PPI) network between HPV16 and human was used as a measure to improve our understanding of its pathogenesis. By adopting sequence and topological features, a support vector machine (SVM) model was built to predict new interactions between HPV16 and human proteins. All interactions were comprehensively investigated and analyzed. The analysis indicated that HPV16 enlarged its scope of influence by interacting with human proteins as much as possible. These interactions alter a broad array of cell cycle progression. Furthermore, not only was HPV16 highly prone to interact with hub proteins and bottleneck proteins, but also it could effectively affect a breadth of signaling pathways. In addition, we found that the HPV16 evolved into high carcinogenicity on the condition that its own reproduction had been ensured. Meanwhile, this work will contribute to providing potential new targets for antiviral therapeutics and help experimental research in the future. PMID:25961044

  7. CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

    2014-12-01

    Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

  8. Phosphoinositides Regulate Ciliary Protein Trafficking to Modulate Hedgehog Signaling

    PubMed Central

    Roberson, Elle C.; Garcia, Galo; Abedin, Monika; Schurmans, Stéphane; Inoue, Takanari; Reiter, Jeremy F.

    2015-01-01

    SUMMARY Primary cilia interpret vertebrate Hedgehog (Hh) signals. Why cilia are essential for signaling is unclear. One possibility is that some forms of signaling require a distinct membrane lipid composition, found at cilia. We found that the ciliary membrane contains a particular phosphoinositide, PI(4)P, whereas a different phosphoinositide, PI(4,5)P2, is restricted to the membrane of the ciliary base. This distribution is created by Inpp5e, a ciliary phosphoinositide 5-phosphatase. Without Inpp5e, ciliary PI(4,5)P2 levels are elevated and Hh signaling is disrupted. Inpp5e limits the ciliary levels of inhibitors of Hh signaling, including Gpr161 and the PI(4,5)P2-binding protein Tulp3. Increasing ciliary PI(4,5)P2 levels or conferring the ability to bind PI(4)P on Tulp3 increases the ciliary localization of Tulp3. Lowering Tulp3 in cells lacking Inpp5e reduces ciliary Gpr161 levels and restores Hh signaling. Therefore, Inpp5e regulates ciliary membrane phosphoinositide composition, and Tulp3 reads out ciliary phosphoinositides to control ciliary protein localization, enabling Hh signaling. PMID:26305592

  9. PII Signal Transduction Proteins, Pivotal Players in Microbial Nitrogen Control

    PubMed Central

    Arcondéguy, Tania; Jack, Rachael; Merrick, Mike

    2001-01-01

    The PII family of signal transduction proteins are among the most widely distributed signal proteins in the bacterial world. First identified in 1969 as a component of the glutamine synthetase regulatory apparatus, PII proteins have since been recognized as playing a pivotal role in control of prokaryotic nitrogen metabolism. More recently, members of the family have been found in higher plants, where they also potentially play a role in nitrogen control. The PII proteins can function in the regulation of both gene transcription, by modulating the activity of regulatory proteins, and the catalytic activity of enzymes involved in nitrogen metabolism. There is also emerging evidence that they may regulate the activity of proteins required for transport of nitrogen compounds into the cell. In this review we discuss the history of the PII proteins, their structures and biochemistry, and their distribution and functions in prokaryotes. We survey data emerging from bacterial genome sequences and consider other likely or potential targets for control by PII proteins. PMID:11238986

  10. Dietary proteins and food-related reward signals

    PubMed Central

    Peuhkuri, Katri; Sihvola, Nora; Korpela, Riitta

    2011-01-01

    Proteins play a crucial role in almost all biological processes. Dietary proteins are generally considered as energy yielding nutrients and as a source of amino acids for various purposes. In addition, they may have a role in food-related reward signals. The purpose of this review was to give an overview of the role of dietary proteins in food-related reward and possible mechanisms behind such effects. Dietary proteins may elicit food-related reward by several different postprandial mechanisms, including neural and humoral signals from the gastrointestinal tract to the brain. In order to exert rewarding effects, protein have to be absorbed from the intestine and reach the target cells in sufficient concentrations, or act via receptors ad cell signalling in the gut without absorption. Complex interactions between different possible mechanisms make it very difficult to gain a clear view on the role and intesity of each mechanism. It is concluded that, in principle, dietary proteins may have a role in food-related reward. However, the evidence is based mostly on experiments with animal models and one should be careful in drawing conclusions of clinical relevance. PMID:21909291

  11. Biasing vector network analyzers using variable frequency and amplitude signals.

    PubMed

    Nobles, J E; Zagorodnii, V; Hutchison, A; Celinski, Z

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal. PMID:27587141

  12. Biasing vector network analyzers using variable frequency and amplitude signals

    NASA Astrophysics Data System (ADS)

    Nobles, J. E.; Zagorodnii, V.; Hutchison, A.; Celinski, Z.

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal.

  13. [RGS proteins (regulators of G protein signaling) and their roles in regulation of immune response].

    PubMed

    Lewandowicz, Anna M; Kowalski, Marek L; Pawliczak, Rafał

    2004-01-01

    RGS proteins (Regulators of G-protein Signaling) comprise a protein family responsible for regulating G proteins. By enhancing the GTPase activity of the a subunit, they speed up the reconstruction of the heterotrimeric structure of G protein, thus inhibiting its signal transduction. Sst2 protein in yeast Saccharomyces cervisiae, FlbA in fungus Aspergillus nidulans, and Egl-10 in the nematode Caenorhabditis elegans are the first native G regulators with GTPase activity (GAPs:--GTPase-activating proteins). The existence of over 30 RGS human proteins has been confirmed thus far, and they have been grouped and classified into six subfamilies. In immunocompetent cells, RGS proteins are entangled in a complicate net of different interrelating signal pathways. They are connected with B- and T-cell chemokine susceptibility, efficient T cell proliferation, and the regulation of B cell maturation. They also take an essential part in inflammation. High hopes are held for drugs, which handle would be RGS proteins and which would further provide the possibility of modifying the pharmacokinetics of drugs acting through G protein- coupled receptors. The aim of this review is to discuss the new RGS protein family and explain the potential involvement of RGS proteins in the modulation of the immune response PMID:15459549

  14. Bcl-2 proteins and calcium signaling: complexity beneath the surface.

    PubMed

    Vervliet, T; Parys, J B; Bultynck, G

    2016-09-29

    Antiapoptotic Bcl-2-family members are well known for their 'mitochondrial' functions as critical neutralizers of proapoptotic Bcl-2-family members, including the executioner multidomain proteins Bax and Bak and the BH3-only proteins. It has been clear for more than 20 years that Bcl-2 proteins can impact intracellular Ca(2+) homeostasis and dynamics. Moreover, altered Ca(2+) signaling is increasingly linked to oncogenic behavior. Specifically targeting the Ca(2+)-signaling machinery may thus prove to be a valuable strategy for cancer treatment. Over 10 years ago a major controversy was recognized concerning whether or not Bcl-2 proteins exerted their antiapoptotic functions via Ca(2+) signaling through lowering the filling state of the endoplasmic reticulum (ER) Ca(2+) stores or by suppressing Ca(2+) release from the ER without affecting the filling state of this Ca(2+) store. Further research from different laboratories indicated a wide variety of mechanisms by which Bcl-2-family members can impact Ca(2+) signaling. In this review, we propose that antiapoptotic Bcl-2-family members are multimodal regulators of intracellular Ca(2+)-signaling events in cell survival and cell death. We will discuss how different Bcl-2-family members impact cell survival and cell death by regulating Ca(2+) transport systems at the ER, mitochondria and plasma membrane and by impacting the organization of organelles and how these insights can be exploited for causing cell death in cancer cells. Finally, we propose that the existing controversy reflects the diversity of links between Bcl-2 proteins and Ca(2+) signaling, as certainly not all targets or mechanisms will be operative in every cell type and every condition.

  15. Constitutive and ligand-induced EGFR signaling triggers distinct and mutually exclusive downstream signaling networks

    PubMed Central

    Chakraborty, Sharmistha; Li, Li; Puliyappadamba, VineshkumarThidil; Guo, Gao; Hatanpaa, Kimmo J.; Mickey, Bruce; Souza, Rhonda F.; Vo, Peggy; Herz, Joachim; Chen, Mei-Ru; Boothman, David A.; Pandita, Tej K.; Wang, David H.; Sen, Ganes C.; Habib, Amyn A.

    2014-01-01

    EGFR overexpression plays an important oncogenic role in cancer. Regular EGFR protein levels are increased in cancer cells and the receptor then becomes constitutively active. However, downstream signals generated by constitutively activated EGFR are unknown. Here we report that the overexpressed EGFR oscillates between two distinct and mutually exclusive modes of signaling. Constitutive or non-canonical EGFR signaling activates the transcription factor IRF3 leading to expression of IFI27, IFIT1, and TRAIL. Ligand-mediated activation of EGFR switches off IRF3 dependent transcription, activates canonical ERK and Akt signals, and confers sensitivity to chemotherapy and virus-induced cell death. Mechanistically, the distinct downstream signals result from a switch of EGFR associated proteins. EGFR constitutively complexes with IRF3 and TBK1 leading to TBK1 and IRF3 phosphorylation. Addition of EGF dissociates TBK1, IRF3, and EGFR leading to a loss of IRF3 activity, Shc-EGFR association and ERK activation. Finally, we provide evidence for non-canonical EGFR signaling in glioblastoma. PMID:25503978

  16. A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GIST

    PubMed Central

    Wiesinger, Monique; Bahlawane, Christelle; Haan, Serge; Sauter, Thomas

    2016-01-01

    Background Signal transduction networks are increasingly studied with mathematical modelling approaches while each of them is suited for a particular problem. For the contextualisation and analysis of signalling networks with steady-state protein data, we identified probabilistic Boolean network (PBN) as a promising framework which could capture quantitative changes of molecular changes at steady-state with a minimal parameterisation. Results and Conclusion In our case study, we successfully applied the PBN approach to model and analyse the deregulated Platelet-Derived Growth Factor (PDGF) signalling pathway in Gastrointestinal Stromal Tumour (GIST). We experimentally determined a rich and accurate dataset of steady-state profiles of selected downstream kinases of PDGF-receptor-alpha mutants in combination with inhibitor treatments. Applying the tool optPBN, we fitted a literature-derived candidate network model to the training dataset consisting of single perturbation conditions. Model analysis suggested several important crosstalk interactions. The validity of these predictions was further investigated experimentally pointing to relevant ongoing crosstalk from PI3K to MAPK signalling in tumour cells. The refined model was evaluated with a validation dataset comprising multiple perturbation conditions. The model thereby showed excellent performance allowing to quantitatively predict the combinatorial responses from the individual treatment results in this cancer setting. The established optPBN pipeline is also widely applicable to gain a better understanding of other signalling networks at steady-state in a context-specific fashion. PMID:27232499

  17. Manipulation of Mitogen-Activated Protein Kinase Kinase Signaling in the Arabidopsis Stomatal Lineage Reveals Motifs That Contribute to Protein Localization and Signaling Specificity[W][OPEN

    PubMed Central

    Lampard, Gregory R.; Wengier, Diego L.; Bergmann, Dominique C.

    2014-01-01

    When multiple mitogen-activated protein kinase (MAPK) components are recruited recurrently to transduce signals of different origins, and often opposing outcomes, mechanisms to enforce signaling specificity are of utmost importance. These mechanisms are largely uncharacterized in plant MAPK signaling networks. The Arabidopsis thaliana stomatal lineage was previously used to show that when rendered constitutively active, four MAPK kinases (MKKs), MKK4/5/7/9, are capable of perturbing stomatal development and that these kinases comprise two pairs, MKK4/5 and MKK7/9, with both overlapping and divergent functions. We characterized the contributions of specific structural domains of these four “stomatal” MKKs to MAPK signaling output and specificity both in vitro and in vivo within the three discrete cell types of the stomatal lineage. These results verify the influence of functional docking (D) domains of MKKs on MAPK signal output and identify novel regulatory functions for previously uncharacterized structures within the N termini of MKK4/5. Beyond this, we present a novel function of the D-domains of MKK7/9 in regulating the subcellular localization of these kinases. These results provide tools to broadly assess the extent to which these and additional motifs within MKKs function to regulate MAPK signal output throughout the plant. PMID:25172143

  18. Discovery of lung cancer pathways using reverse phase protein microarray and prior-knowledge based Bayesian networks.

    PubMed

    Kim, Dong-Chul; Yang, Chin-Rang; Wang, Xiaoyu; Zhang, Baoju; Wu, Xiaorong; Gao, Jean

    2011-01-01

    The goal of this paper is to infer the signaling pathway related to lung cancer using Reverse Phase Protein Microarray (RPPM), which provides information on post-translational phosphorylation events. The computational inferring of pathways is obtained by performing Bayesian network in combination with prior knowledge from Protein-Protein Interaction (PPI). A clustering based Linear Programming Relaxation is developed for the searching of optimal networks. The PPI prior knowledge is incorporated into a new scoring function definition based on minimum description length (MDL). In the experiment, we first evaluate the algorithm performance with synthetic networks and associated data. Then we show our signaling network inference for lung cancer using RPPM data. Through the study, we expect to derive new signalling pathways and insight on protein regulatory relationships, which are yet to be known for lung cancer study.

  19. Protein Co-Expression Network Analysis (ProCoNA)

    SciTech Connect

    Gibbs, David L.; Baratt, Arie; Baric, Ralph; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Katze, Michael G.; Mcweeney, Shannon K.

    2013-06-01

    Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery.

  20. PDZ Protein Regulation of G Protein-Coupled Receptor Trafficking and Signaling Pathways.

    PubMed

    Dunn, Henry A; Ferguson, Stephen S G

    2015-10-01

    G protein-coupled receptors (GPCRs) contribute to the regulation of every aspect of human physiology and are therapeutic targets for the treatment of numerous diseases. As a consequence, understanding the myriad of mechanisms controlling GPCR signaling and trafficking is essential for the development of new pharmacological strategies for the treatment of human pathologies. Of the many GPCR-interacting proteins, postsynaptic density protein of 95 kilodaltons, disc large, zona occludens-1 (PDZ) domain-containing proteins appear most abundant and have similarly been implicated in disease mechanisms. PDZ proteins play an important role in regulating receptor and channel protein localization within synapses and tight junctions and function to scaffold intracellular signaling protein complexes. In the current study, we review the known functional interactions between PDZ domain-containing proteins and GPCRs and provide insight into the potential mechanisms of action. These PDZ domain-containing proteins include the membrane-associated guanylate-like kinases [postsynaptic density protein of 95 kilodaltons; synapse-associated protein of 97 kilodaltons; postsynaptic density protein of 93 kilodaltons; synapse-associated protein of 102 kilodaltons; discs, large homolog 5; caspase activation and recruitment domain and membrane-associated guanylate-like kinase domain-containing protein 3; membrane protein, palmitoylated 3; calcium/calmodulin-dependent serine protein kinase; membrane-associated guanylate kinase protein (MAGI)-1, MAGI-2, and MAGI-3], Na(+)/H(+) exchanger regulatory factor proteins (NHERFs) (NHERF1, NHERF2, PDZ domain-containing kidney protein 1, and PDZ domain-containing kidney protein 2), Golgi-associated PDZ proteins (Gα-binding protein interacting protein, C-terminus and CFTR-associated ligand), PDZ domain-containing guanine nucleotide exchange factors (GEFs) 1 and 2, regulator of G protein signaling (RGS)-homology-RhoGEFs (PDZ domain-containing RhoGEF and

  1. Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

    SciTech Connect

    YANG, CHIN-RANG

    2013-12-11

    Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

  2. Resolving the network of cell signaling pathways using the evolving yeast two-hybrid system

    PubMed Central

    Ratushny, Vladimir; Golemis, Erica A.

    2008-01-01

    In 1983, while investigators had identified a few human proteins as important regulators of specific biological outcomes, how these proteins acted in the cell was essentially unknown in almost all cases. 25 years on, our knowledge of the mechanistic basis of protein action has been transformed by our increasingly detailed understanding of protein-protein interactions, which have allowed us to define cellular machines. The advent of the yeast two-hybrid (Y2H) system in 1989 marked a milestone in the field of proteomics. Exploiting the modular nature of transcription factors, the Y2H system allows facile measurement of the activation of reporter genes based on interactions between two chimeric or “hybrid” proteins of interest. After a decade of service as a leading platforms for individual investigators to use in exploring the interaction properties of interesting target proteins, the Y2H system has increasing been applied in high throughput applications intended to map genome-scale protein-protein interactions for model organisms and humans. Although some significant technical limitations apply, the Y2H has made a great contribution to our general understanding of the topology of cellular signaling networks. PMID:18474041

  3. Synchronization transmission of target signal within the coupling network with quantum chaos effect

    NASA Astrophysics Data System (ADS)

    Li, Wenlin; Li, Chong; Song, Heshan

    2016-11-01

    In this work, we propose a novel technology to investigate the synchronization transmission of target signal within the coupling network. In this new technology, the network synchronization transmission is realized through the coupling between the network nodes, and the controller is not required to add in the network. Especially, as long as the target signal can be input to an arbitrary node in the network, so all the network nodes are synchronized to the target signal, that is, the target signal has got synchronization transmission.

  4. Dopamine signaling promotes the xenobiotic stress response and protein homeostasis.

    PubMed

    Joshi, Kishore K; Matlack, Tarmie L; Rongo, Christopher

    2016-09-01

    Multicellular organisms encounter environmental conditions that adversely affect protein homeostasis (proteostasis), including extreme temperatures, toxins, and pathogens. It is unclear how they use sensory signaling to detect adverse conditions and then activate stress response pathways so as to offset potential damage. Here, we show that dopaminergic mechanosensory neurons in C. elegans release the neurohormone dopamine to promote proteostasis in epithelia. Signaling through the DA receptor DOP-1 activates the expression of xenobiotic stress response genes involved in pathogenic resistance and toxin removal, and these genes are required for the removal of unstable proteins in epithelia. Exposure to a bacterial pathogen (Pseudomonas aeruginosa) results in elevated removal of unstable proteins in epithelia, and this enhancement requires DA signaling. In the absence of DA signaling, nematodes show increased sensitivity to pathogenic bacteria and heat-shock stress. Our results suggest that dopaminergic sensory neurons, in addition to slowing down locomotion upon sensing a potential bacterial feeding source, also signal to frontline epithelia to activate the xenobiotic stress response so as to maintain proteostasis and prepare for possible infection. PMID:27261197

  5. Inhibitor of apoptosis proteins as intracellular signaling intermediates.

    PubMed

    Kocab, Andrew J; Duckett, Colin S

    2016-01-01

    Inhibitor of apoptosis (IAP) proteins have often been considered inhibitors of cell death due to early reports that described their ability to directly bind and inhibit caspases, the primary factors that implement apoptosis. However, a greater understanding is evolving regarding the vital roles played by IAPs as transduction intermediates in a diverse set of signaling cascades associated with functions ranging from the innate immune response to cell migration to cell-cycle regulation. In this review, we discuss the functions of IAPs in signaling, focusing primarily on the cellular IAP (c-IAP) proteins. The c-IAPs are important components in tumor necrosis factor receptor superfamily signaling cascades, which include activation of the NF-κB transcription factor family. As these receptors modulate cell proliferation and cell death, the involvement of the c-IAPs in these pathways provides an additional means of controlling cellular fate beyond simply inhibiting caspase activity. Additionally, IAP-binding proteins, such as Smac and caspases, which have been described as having cell death-independent roles, may affect c-IAP activity in intracellular signaling. Collectively, the multi-faceted functions and complex regulation of the c-IAPs illustrate their importance as intracellular signaling intermediates.

  6. Natural Genetic Variation Influences Protein Abundances in C. elegans Developmental Signalling Pathways.

    PubMed

    Singh, Kapil Dev; Roschitzki, Bernd; Snoek, L Basten; Grossmann, Jonas; Zheng, Xue; Elvin, Mark; Kamkina, Polina; Schrimpf, Sabine P; Poulin, Gino B; Kammenga, Jan E; Hengartner, Michael O

    2016-01-01

    Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch, and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains N2 (Bristol) and CB4856 (Hawaii) to enable quantitative trait locus (QTL) mapping. About half of the cases from the 44 genes tested showed a statistically significant change in protein abundance between various strains, most of these were however very weak (below 1.3-fold change). We detected a distant QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels. PMID:26985669

  7. Role of Regulators of G Protein Signaling Proteins in Bone Physiology and Pathophysiology

    PubMed Central

    Jules, Joel; Yang, Shuying; Chen, Wei; Li, Yi-Ping

    2016-01-01

    Regulators of G protein signaling (RGS) proteins enhance the intrinsic GTPase activity of α subunits of the heterotrimeric G protein complex of G protein-coupled receptors (GPCRs) and thereby inactivate signal transduction initiated by GPCRs. The RGS family consists of nearly 37 members with a conserved RGS homology domain which is critical for their GTPase accelerating activity. RGS proteins are expressed in most tissues, including heart, lung, brain, kidney, and bone and play essential roles in many physiological and pathological processes. In skeletal development and bone homeostasis as well as in many bone disorders, RGS proteins control the functions of various GPCRs, including the parathyroid hormone receptor type 1 and calcium-sensing receptor and also regulate various critical signaling pathways, such as Wnt and calcium oscillations. This chapter will discuss the current findings on the roles of RGS proteins in regulating signaling of key GPCRs in skeletal development and bone homeostasis. We also will examine the current updates of RGS proteins’ regulation of calcium oscillations in bone physiology and highlight the roles of RGS proteins in selected bone pathological disorders. Despite the recent advances in bone and mineral research, RGS proteins remain understudied in the skeletal system. Further understanding of the roles of RGS proteins in bone should not only provide great insights into the molecular basis of various bone diseases but also generate great therapeutic drug targets for many bone diseases. PMID:26123302

  8. 14-3-3 Proteins in Guard Cell Signaling.

    PubMed

    Cotelle, Valérie; Leonhardt, Nathalie

    2015-01-01

    Guard cells are specialized cells located at the leaf surface delimiting pores which control gas exchanges between the plant and the atmosphere. To optimize the CO2 uptake necessary for photosynthesis while minimizing water loss, guard cells integrate environmental signals to adjust stomatal aperture. The size of the stomatal pore is regulated by movements of the guard cells driven by variations in their volume and turgor. As guard cells perceive and transduce a wide array of environmental cues, they provide an ideal system to elucidate early events of plant signaling. Reversible protein phosphorylation events are known to play a crucial role in the regulation of stomatal movements. However, in some cases, phosphorylation alone is not sufficient to achieve complete protein regulation, but is necessary to mediate the binding of interactors that modulate protein function. Among the phosphopeptide-binding proteins, the 14-3-3 proteins are the best characterized in plants. The 14-3-3s are found as multiple isoforms in eukaryotes and have been shown to be involved in the regulation of stomatal movements. In this review, we describe the current knowledge about 14-3-3 roles in the regulation of their binding partners in guard cells: receptors, ion pumps, channels, protein kinases, and some of their substrates. Regulation of these targets by 14-3-3 proteins is discussed and related to their function in guard cells during stomatal movements in response to abiotic or biotic stresses.

  9. An empirical Bayesian approach for model-based inference of cellular signaling networks

    PubMed Central

    2009-01-01

    Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF) signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements. PMID:19900289

  10. Early-warning signals of topological collapse in interbank networks

    NASA Astrophysics Data System (ADS)

    Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

    2013-11-01

    The financial crisis clearly illustrated the importance of characterizing the level of `systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998-2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear - but unpredictable - signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies.

  11. Topological Analyses of Protein-Ligand Binding: a Network Approach.

    PubMed

    Costanzi, Stefano

    2016-01-01

    Proteins can be conveniently represented as networks of interacting residues, thus allowing the study of several network parameters that can shed light onto several of their structural and functional aspects. With respect to the binding of ligands, which are central for the function of many proteins, network analysis may constitute a possible route to assist the identification of binding sites. As the bulk of this review illustrates, this has generally been easier for enzymes than for non-enzyme proteins, perhaps due to the different topological nature of the binding sites of the former over those of the latter. The article also illustrates how network representations of binding sites can be used to search PDB structures in order to identify proteins that bind similar molecules and, lastly, how codifying proteins as networks can assist the analysis of the conformational changes consequent to ligand binding.

  12. The architectural design of networks of protein domain architectures.

    PubMed

    Hsu, Chia-Hsin; Chen, Chien-Kuo; Hwang, Ming-Jing

    2013-08-23

    Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

  13. The signaling helix: a common functional theme in diverse signaling proteins

    PubMed Central

    Anantharaman, Vivek; Balaji, S; Aravind, L

    2006-01-01

    Background The mechanism by which the signals are transmitted between receptor and effector domains in multi-domain signaling proteins is poorly understood. Results Using sensitive sequence analysis methods we identify a conserved helical segment of around 40 residues in a wide range of signaling proteins, including numerous sensor histidine kinases such as Sln1p, and receptor guanylyl cyclases such as the atrial natriuretic peptide receptor and nitric oxide receptors. We term this helical segment the signaling (S)-helix and present evidence that it forms a novel parallel coiled-coil element, distinct from previously known helical segments in signaling proteins, such as the Dimerization-Histidine phosphotransfer module of histidine kinases, the intra-cellular domains of the chemotaxis receptors, inter-GAF domain helical linkers and the α-helical HAMP module. Analysis of domain architectures allowed us to reconstruct the domain-neighborhood graph for the S-helix, which showed that the S-helix almost always occurs between two signaling domains. Several striking patterns in the domain neighborhood of the S-helix also became evident from the graph. It most often separates diverse N-terminal sensory domains from various C-terminal catalytic signaling domains such as histidine kinases, cNMP cyclase, PP2C phosphatases, NtrC-like AAA+ ATPases and diguanylate cyclases. It might also occur between two sensory domains such as PAS domains and occasionally between a DNA-binding HTH domain and a sensory domain. The sequence conservation pattern of the S-helix revealed the presence of a unique constellation of polar residues in the dimer-interface positions within the central heptad of the coiled-coil formed by the S-helix. Conclusion Combining these observations with previously reported mutagenesis studies on different S-helix-containing proteins we suggest that it functions as a switch that prevents constitutive activation of linked downstream signaling domains. However, upon

  14. Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function: hypotheses and a comprehensive review.

    PubMed

    Csermely, Peter; Sandhu, Kuljeet Singh; Hazai, Eszter; Hoksza, Zsolt; Kiss, Huba J M; Miozzo, Federico; Veres, Dániel V; Piazza, Francesco; Nussinov, Ruth

    2012-02-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into 'cumulus-type', i.e., those similar to puffy (white) clouds, and 'stratus-type', i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an 'energy transfer' mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by 'multi-trajectories'; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach 'rarely visited' but functionally-related states. We also show the role of disorder in 'spatial games' of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks.

  15. Phylogenetic analysis of modularity in protein interaction networks

    PubMed Central

    Erten, Sinan; Li, Xin; Bebek, Gurkan; Li, Jing; Koyutürk, Mehmet

    2009-01-01

    Background In systems biology, comparative analyses of molecular interactions across diverse species indicate that conservation and divergence of networks can be used to understand functional evolution from a systems perspective. A key characteristic of these networks is their modularity, which contributes significantly to their robustness, as well as adaptability. Consequently, analysis of modular network structures from a phylogenetic perspective may be useful in understanding the emergence, conservation, and diversification of functional modularity. Results In this paper, we propose a phylogenetic framework for analyzing network modules, with applications that extend well beyond network-based phylogeny reconstruction. Our approach is based on identification of modular network components from each network separately, followed by projection of these modules onto the networks of other species to compare different networks. Subsequently, we use the conservation of various modules in each network to assess the similarity between different networks. Compared to traditional methods that rely on topological comparisons, our approach has key advantages in (i) avoiding intractable graph comparison problems in comparative network analysis, (ii) accounting for noise and missing data through flexible treatment of network conservation, and (iii) providing insights on the evolution of biological systems through investigation of the evolutionary trajectories of network modules. We test our method, MOPHY, on synthetic data generated by simulation of network evolution, as well as existing protein-protein interaction data for seven diverse species. Comprehensive experimental results show that MOPHY is promising in reconstructing evolutionary histories of extant networks based on conservation of modularity, it is highly robust to noise, and outperforms existing methods that quantify network similarity in terms of conservation of network topology. Conclusion These results establish

  16. Guard Cell Signal Transduction Network: Advances in Understanding Abscisic Acid, CO2, and Ca2+ Signaling

    PubMed Central

    Kim, Tae-Houn; Böhmer, Maik; Hu, Honghong; Nishimura, Noriyuki; Schroeder, Julian I.

    2011-01-01

    Stomatal pores are formed by pairs of specialized epidermal guard cells and serve as major gateways for both CO2 influx into plants from the atmosphere and transpirational water loss of plants. Because they regulate stomatal pore apertures via integration of both endogenous hormonal stimuli and environmental signals, guard cells have been highly developed as a model system to dissect the dynamics and mechanisms of plant-cell signaling. The stress hormone ABA and elevated levels of CO2 activate complex signaling pathways in guard cells that are mediated by kinases/phosphatases, secondary messengers, and ion channel regulation. Recent research in guard cells has led to a new hypothesis for how plants achieve specificity in intracellular calcium signaling: CO2 and ABA enhance (prime) the calcium sensitivity of downstream calcium-signaling mechanisms. Recent progress in identification of early stomatal signaling components are reviewed here, including ABA receptors and CO2-binding response proteins, as well as systems approaches that advance our understanding of guard cell-signaling mechanisms. PMID:20192751

  17. Deep Space Network Capabilities for Receiving Weak Probe Signals

    NASA Technical Reports Server (NTRS)

    Asmar, Sami; Johnston, Doug; Preston, Robert

    2005-01-01

    Planetary probes can encounter mission scenarios where communication is not favorable during critical maneuvers or emergencies. Launch, initial acquisition, landing, trajectory corrections, safing. Communication challenges due to sub-optimum antenna pointing or transmitted power, amplitude/frequency dynamics, etc. Prevent lock-up on signal and extraction of telemetry. Examples: loss of Mars Observer, nutation of Ulysses, Galileo antenna, Mars Pathfinder and Mars Exploration Rovers Entry, Descent, and Landing, and the Cassini Saturn Orbit Insertion. A Deep Space Network capability to handle such cases has been used successfully to receive signals to characterize the scenario. This paper will describe the capability and highlight the cases of the critical communications for the Mars rovers and Saturn Orbit Insertion and preparation radio tracking of the Huygens probe at (non-DSN) radio telescopes.

  18. Chaperones and multitasking proteins in the nucleolus: networking together for survival?

    PubMed

    Bański, Piotr; Kodiha, Mohamed; Stochaj, Ursula

    2010-07-01

    The nucleolus has emerged as a key player that regulates cell growth, survival and the recovery from stress. Progress in proteomics made it possible to sequence the nucleolar proteome under different physiological conditions. Together with other research, this work revealed the presence of multiple chaperones and co-chaperones in the nucleolus. Molecular chaperones are components of a larger network that promotes protein homeostasis, thereby providing continuous adaptation to a changing environment. Recent studies suggest that the cellular chaperone network is divided into individual branches which orchestrate specific functions. Input from separate branches is then combined to 'fine-tune' the cellular proteostasis network. Based on the latest developments in nucleolar and chaperone biology, we speculate that a unique network comprising chaperones, co-chaperones and multitasking proteins is located in nucleoli. This network supports and regulates fundamental biological processes, including ribosome biogenesis, cell signaling, and the stress response.

  19. Biomolecular Simulation of Base Excision Repair and Protein Signaling

    SciTech Connect

    Straatsma, TP; McCammon, J A; Miller, John H; Smith, Paul E; Vorpagel, Erich R; Wong, Chung F; Zacharias, Martin W

    2006-03-03

    The goal of the Biomolecular Simulation of Base Excision Repair and Protein Signaling project is to enhance our understanding of the mechanism of human polymerase-β, one of the key enzymes in base excision repair (BER) and the cell-signaling enzymes cyclic-AMP-dependent protein kinase. This work used molecular modeling and simulation studies to specifically focus on the • dynamics of DNA and damaged DNA • dynamics and energetics of base flipping in DNA • mechanism and fidelity of nucleotide insertion by BER enzyme human polymerase-β • mechanism and inhibitor design for cyclic-AMP-dependent protein kinase. Molecular dynamics simulations and electronic structure calculations have been performed using the computer resources at the Molecular Science Computing Facility at the Environmental Molecular Sciences Laboratory.

  20. Saltational evolution of the heterotrimeric G protein signaling mechanisms in the plant kingdom.

    PubMed

    Urano, Daisuke; Maruta, Natsumi; Trusov, Yuri; Stoian, Richard; Wu, Qingyu; Liang, Ying; Jaiswal, Dinesh Kumar; Thung, Leena; Jackson, David; Botella, José Ramón; Jones, Alan M

    2016-01-01

    Signaling proteins evolved diverse interactions to provide specificity for distinct stimuli. Signaling complexity in the G protein (heterotrimeric guanosine triphosphate-binding protein) network was achieved in animals through subunit duplication and incremental evolution. By combining comprehensive and quantitative phenotypic profiles of Arabidopsis thaliana with protein evolution informatics, we found that plant heterotrimeric G protein machinery evolved by a saltational (jumping) process. Sequence similarity scores mapped onto tertiary structures, and biochemical validation showed that the extra-large Gα (XLG) subunit evolved extensively in the charophycean algae (an aquatic green plant) by gene duplication and gene fusion. In terrestrial plants, further evolution uncoupled XLG from its negative regulator, regulator of G protein signaling, but preserved an α-helix region that enables interaction with its partner Gβγ. The ancestral gene evolved slowly due to the molecular constraints imposed by the need for the protein to maintain interactions with various partners, whereas the genes encoding XLG proteins evolved rapidly to produce three highly divergent members. Analysis of A. thaliana mutants indicated that these Gα and XLG proteins all function with Gβγ and evolved to operate both independently and cooperatively. The XLG-Gβγ machinery specialized in environmental stress responses, whereas the canonical Gα-Gβγ retained developmental roles. Some developmental processes, such as shoot development, involve both Gα and XLG acting cooperatively or antagonistically. These extensive and rapid evolutionary changes in XLG structure compared to those of the canonical Gα subunit contrast with the accepted notion of how pathway diversification occurs through gene duplication with subsequent incremental coevolution of residues among interacting proteins. PMID:27649740

  1. Saltational evolution of the heterotrimeric G protein signaling mechanisms in the plant kingdom.

    PubMed

    Urano, Daisuke; Maruta, Natsumi; Trusov, Yuri; Stoian, Richard; Wu, Qingyu; Liang, Ying; Jaiswal, Dinesh Kumar; Thung, Leena; Jackson, David; Botella, José Ramón; Jones, Alan M

    2016-01-01

    Signaling proteins evolved diverse interactions to provide specificity for distinct stimuli. Signaling complexity in the G protein (heterotrimeric guanosine triphosphate-binding protein) network was achieved in animals through subunit duplication and incremental evolution. By combining comprehensive and quantitative phenotypic profiles of Arabidopsis thaliana with protein evolution informatics, we found that plant heterotrimeric G protein machinery evolved by a saltational (jumping) process. Sequence similarity scores mapped onto tertiary structures, and biochemical validation showed that the extra-large Gα (XLG) subunit evolved extensively in the charophycean algae (an aquatic green plant) by gene duplication and gene fusion. In terrestrial plants, further evolution uncoupled XLG from its negative regulator, regulator of G protein signaling, but preserved an α-helix region that enables interaction with its partner Gβγ. The ancestral gene evolved slowly due to the molecular constraints imposed by the need for the protein to maintain interactions with various partners, whereas the genes encoding XLG proteins evolved rapidly to produce three highly divergent members. Analysis of A. thaliana mutants indicated that these Gα and XLG proteins all function with Gβγ and evolved to operate both independently and cooperatively. The XLG-Gβγ machinery specialized in environmental stress responses, whereas the canonical Gα-Gβγ retained developmental roles. Some developmental processes, such as shoot development, involve both Gα and XLG acting cooperatively or antagonistically. These extensive and rapid evolutionary changes in XLG structure compared to those of the canonical Gα subunit contrast with the accepted notion of how pathway diversification occurs through gene duplication with subsequent incremental coevolution of residues among interacting proteins.

  2. Signaling Pathways and Gene Regulatory Networks in Cardiomyocyte Differentiation

    PubMed Central

    Parikh, Abhirath; Wu, Jincheng; Blanton, Robert M.

    2015-01-01

    Strategies for harnessing stem cells as a source to treat cell loss in heart disease are the subject of intense research. Human pluripotent stem cells (hPSCs) can be expanded extensively in vitro and therefore can potentially provide sufficient quantities of patient-specific differentiated cardiomyocytes. Although multiple stimuli direct heart development, the differentiation process is driven in large part by signaling activity. The engineering of hPSCs to heart cell progeny has extensively relied on establishing proper combinations of soluble signals, which target genetic programs thereby inducing cardiomyocyte specification. Pertinent differentiation strategies have relied as a template on the development of embryonic heart in multiple model organisms. Here, information on the regulation of cardiomyocyte development from in vivo genetic and embryological studies is critically reviewed. A fresh interpretation is provided of in vivo and in vitro data on signaling pathways and gene regulatory networks (GRNs) underlying cardiopoiesis. The state-of-the-art understanding of signaling pathways and GRNs presented here can inform the design and optimization of methods for the engineering of tissues for heart therapies. PMID:25813860

  3. The Yeast Sks1p Kinase Signaling Network Regulates Pseudohyphal Growth and Glucose Response

    PubMed Central

    Johnson, Cole; Kweon, Hye Kyong; Sheidy, Daniel; Shively, Christian A.; Mellacheruvu, Dattatreya; Nesvizhskii, Alexey I.; Andrews, Philip C.; Kumar, Anuj

    2014-01-01

    The yeast Saccharomyces cerevisiae undergoes a dramatic growth transition from its unicellular form to a filamentous state, marked by the formation of pseudohyphal filaments of elongated and connected cells. Yeast pseudohyphal growth is regulated by signaling pathways responsive to reductions in the availability of nitrogen and glucose, but the molecular link between pseudohyphal filamentation and glucose signaling is not fully understood. Here, we identify the glucose-responsive Sks1p kinase as a signaling protein required for pseudohyphal growth induced by nitrogen limitation and coupled nitrogen/glucose limitation. To identify the Sks1p signaling network, we applied mass spectrometry-based quantitative phosphoproteomics, profiling over 900 phosphosites for phosphorylation changes dependent upon Sks1p kinase activity. From this analysis, we report a set of novel phosphorylation sites and highlight Sks1p-dependent phosphorylation in Bud6p, Itr1p, Lrg1p, Npr3p, and Pda1p. In particular, we analyzed the Y309 and S313 phosphosites in the pyruvate dehydrogenase subunit Pda1p; these residues are required for pseudohyphal growth, and Y309A mutants exhibit phenotypes indicative of impaired aerobic respiration and decreased mitochondrial number. Epistasis studies place SKS1 downstream of the G-protein coupled receptor GPR1 and the G-protein RAS2 but upstream of or at the level of cAMP-dependent PKA. The pseudohyphal growth and glucose signaling transcription factors Flo8p, Mss11p, and Rgt1p are required to achieve wild-type SKS1 transcript levels. SKS1 is conserved, and deletion of the SKS1 ortholog SHA3 in the pathogenic fungus Candida albicans results in abnormal colony morphology. Collectively, these results identify Sks1p as an important regulator of filamentation and glucose signaling, with additional relevance towards understanding stress-responsive signaling in C. albicans. PMID:24603354

  4. Genome-Wide Analysis of the TORC1 and Osmotic Stress Signaling Network in Saccharomyces cerevisiae

    PubMed Central

    Worley, Jeremy; Sullivan, Arron; Luo, Xiangxia; Kaplan, Matthew E.; Capaldi, Andrew P.

    2015-01-01

    The Target of Rapamycin kinase Complex I (TORC1) is a master regulator of cell growth and metabolism in eukaryotes. Studies in yeast and human cells have shown that nitrogen/amino acid starvation signals act through Npr2/Npr3 and the small GTPases Gtr1/Gtr2 (Rags in humans) to inhibit TORC1. However, it is unclear how other stress and starvation stimuli inhibit TORC1, and/or act in parallel with the TORC1 pathway, to control cell growth. To help answer these questions, we developed a novel automated pipeline and used it to measure the expression of a TORC1-dependent ribosome biogenesis gene (NSR1) during osmotic stress in 4700 Saccharomyces cerevisiae strains from the yeast knock-out collection. This led to the identification of 440 strains with significant and reproducible defects in NSR1 repression. The cell growth control and stress response proteins deleted in these strains form a highly connected network, including 56 proteins involved in vesicle trafficking and vacuolar function; 53 proteins that act downstream of TORC1 according to a rapamycin assay—including components of the HDAC Rpd3L, Elongator, and the INO80, CAF-1 and SWI/SNF chromatin remodeling complexes; over 100 proteins involved in signaling and metabolism; and 17 proteins that directly interact with TORC1. These data provide an important resource for labs studying cell growth control and stress signaling, and demonstrate the utility of our new, and easily adaptable, method for mapping gene regulatory networks. PMID:26681516

  5. Spatio-temporal Remodeling of Functional Membrane Microdomains Organizes the Signaling Networks of a Bacterium

    PubMed Central

    Schneider, Johannes; Klein, Teresa; Mielich-Süss, Benjamin; Koch, Gudrun; Franke, Christian; Kuipers, Oscar P.; Kovács, Ákos T.; Sauer, Markus; Lopez, Daniel

    2015-01-01

    Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs) that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium. PMID:25909364

  6. pathFinder: a static network analysis tool for pharmacological analysis of signal transduction pathways.

    PubMed

    Samal, Babru B; Eiden, Lee E

    2008-01-01

    The study of signal transduction is becoming a de facto part of the analysis of gene expression and protein profiling techniques. Many online tools are used to cluster genes in various ways or to assign gene products to signal transduction pathways. Among these, pathFinder is a unique tool that can find signal transduction pathways between first, second, or nth messengers and their targets within the cell. pathFinder can identify qualitatively all possible signal transduction pathways connecting any starting component and target within a database of two-component pathways (directional dyads). One or more intermediate pathway components can be excluded to simulate the use of pharmacological inhibitors or genetic deletion (knockout). Missing elements in a pathway connecting the activator or initiator and target can also be inferred from a null pathway result. The value of this static network analysis tool is illustrated by the predication from pathFinder analysis of a novel cyclic AMP-dependent, protein kinase A-independent signaling pathway in neuroendocrine cells, which has been experimentally confirmed.

  7. Network Clustering Revealed the Systemic Alterations of Mitochondrial Protein Expression

    PubMed Central

    Koo, Hyun-Jung; Park, Wook-Ha; Yang, Jae-Seong; Yu, Myeong-Hee; Kim, Sanguk; Pak, Youngmi Kim

    2011-01-01

    The mitochondrial protein repertoire varies depending on the cellular state. Protein component modifications caused by mitochondrial DNA (mtDNA) depletion are related to a wide range of human diseases; however, little is known about how nuclear-encoded mitochondrial proteins (mt proteome) changes under such dysfunctional states. In this study, we investigated the systemic alterations of mtDNA-depleted (ρ0) mitochondria by using network analysis of gene expression data. By modularizing the quantified proteomics data into protein functional networks, systemic properties of mitochondrial dysfunction were analyzed. We discovered that up-regulated and down-regulated proteins were organized into two predominant subnetworks that exhibited distinct biological processes. The down-regulated network modules are involved in typical mitochondrial functions, while up-regulated proteins are responsible for mtDNA repair and regulation of mt protein expression and transport. Furthermore, comparisons of proteome and transcriptome data revealed that ρ0 cells attempted to compensate for mtDNA depletion by modulating the coordinated expression/transport of mt proteins. Our results demonstrate that mt protein composition changed to remodel the functional organization of mitochondrial protein networks in response to dysfunctional cellular states. Human mt protein functional networks provide a framework for understanding how cells respond to mitochondrial dysfunctions. PMID:21738461

  8. Cancer Missense Mutations Alter Binding Properties of Proteins and Their Interaction Networks

    PubMed Central

    Nishi, Hafumi; Tyagi, Manoj; Teng, Shaolei; Shoemaker, Benjamin A.; Hashimoto, Kosuke; Alexov, Emil; Wuchty, Stefan; Panchenko, Anna R.

    2013-01-01

    Many studies have shown that missense mutations might play an important role in carcinogenesis. However, the extent to which cancer mutations might affect biomolecular interactions remains unclear. Here, we map glioblastoma missense mutations on the human protein interactome, model the structures of affected protein complexes and decipher the effect of mutations on protein-protein, protein-nucleic acid and protein-ion binding interfaces. Although some missense mutations over-stabilize protein complexes, we found that the overall effect of mutations is destabilizing, mostly affecting the electrostatic component of binding energy. We also showed that mutations on interfaces resulted in more drastic changes of amino acid physico-chemical properties than mutations occurring outside the interfaces. Analysis of glioblastoma mutations on interfaces allowed us to stratify cancer-related interactions, identify potential driver genes, and propose two dozen additional cancer biomarkers, including those specific to functions of the nervous system. Such an analysis also offered insight into the molecular mechanism of the phenotypic outcomes of mutations, including effects on complex stability, activity, binding and turnover rate. As a result of mutated protein and gene network analysis, we observed that interactions of proteins with mutations mapped on interfaces had higher bottleneck properties compared to interactions with mutations elsewhere on the protein or unaffected interactions. Such observations suggest that genes with mutations directly affecting protein binding properties are preferably located in central network positions and may influence critical nodes and edges in signal transduction networks. PMID:23799087

  9. Characterization of signalling pathways by reverse phase protein arrays.

    PubMed

    Malinowsky, Katharina; Wolff, Claudia; Schott, Christina; Becker, Karl-Friedrich

    2013-01-01

    Reverse phase protein array (RPPA) is a very suitable technique to analyze large numbers of proteins in small samples like for example tumor biopsies. Beside their small size another major hindrance for the analysis of proteins from biopsies is the extraction of proteins from formalin-fixed and paraffin-embedded (FFPE) tissues. Here we describe a protocol, allowing quantitative extraction of large numbers of proteins from FFPE tissues and their subsequent analysis by RPPA. To elucidate the role of epidermal growth factor receptor (EGFR) signalling in ovarian cancer, we analyzed 23 primary tumors and corresponding metastases for the expression of 25 proteins involved in EGFR signalling with special emphasis on epithelial-mesenchymal transition (EMT). We found a significant correlation of Snail with EGFR((Tyr1086)) and p38 MAPK((Thr180/Tyr182)) in primary ovarian carcinoma and with EGFR((Tyr1086)) in their corresponding metastases. Additionally, we showed that high expression levels of the E-cadherin repressor Snail in primary tumors combined with high expression levels of the pp38 MAPK((Thr180/Tyr182)) in metastasis lead to an increased risk for death in ovarian carcinoma patients.

  10. Signalling-dependent interactions between the kinase-coupling protein CheW and chemoreceptors in living cells.

    PubMed

    Pedetta, Andrea; Parkinson, John S; Studdert, Claudia A

    2014-09-01

    Chemical signals sensed on the periplasmic side of bacterial cells by transmembrane chemoreceptors are transmitted to the flagellar motors via the histidine kinase CheA, which controls the phosphorylation level of the effector protein CheY. Chemoreceptor arrays comprise remarkably stable supramolecular structures in which thousands of chemoreceptors are networked through interactions between their cytoplasmic tips, CheA, and the small coupling protein CheW. To explore the conformational changes that occur within this protein assembly during signalling, we used in vivo cross-linking methods to detect close interactions between the coupling protein CheW and the serine receptor Tsr in intact Escherichia coli cells. We identified two signal-sensitive contacts between CheW and the cytoplasmic tip of Tsr. Our results suggest that ligand binding triggers changes in the receptor that alter its signalling contacts with CheW (and/or CheA).

  11. Regulator of G-protein signaling 18 integrates activating and inhibitory signaling in platelets.

    PubMed

    Gegenbauer, Kristina; Elia, Giuliano; Blanco-Fernandez, Alfonso; Smolenski, Albert

    2012-04-19

    Regulator of G-protein signaling 18 (RGS18) is a GTPase-activating protein for the G-α-q and G-α-i subunits of heterotrimeric G-proteins that turns off signaling by G-protein coupled receptors. RGS18 is highly expressed in platelets. In the present study, we show that the 14-3-3γ protein binds to phosphorylated serines 49 and 218 of RGS18. Platelet activation by thrombin, thromboxane A2, or ADP stimulates the association of 14-3-3 and RGS18, probably by increasing the phosphorylation of serine 49. In contrast, treatment of platelets with prostacyclin and nitric oxide, which trigger inhibitory cyclic nucleotide signaling involving cyclic AMP-dependent protein kinase A (PKA) and cyclic GMP-dependent protein kinase I (PKGI), induces the phosphorylation of serine 216 of RGS18 and the detachment of 14-3-3. Serine 216 phosphorylation is able to block 14-3-3 binding to RGS18 even in the presence of thrombin, thromboxane A2, or ADP. 14-3-3-deficient RGS18 is more active compared with 14-3-3-bound RGS18, leading to a more pronounced inhibition of thrombin-induced release of calcium ions from intracellular stores. Therefore, PKA- and PKGI-mediated detachment of 14-3-3 activates RGS18 to block Gq-dependent calcium signaling. These findings indicate cross-talk between platelet activation and inhibition pathways at the level of RGS18 and Gq. PMID:22234696

  12. Mitogen-activated protein kinase and abscisic acid signal transduction.

    PubMed

    Heimovaara-Dijkstra, S; Testerink, C; Wang, M

    2000-01-01

    The phytohormone abscisic acid (ABA) is a classical plant hormone, responsible for regulation of abscission, diverse aspects of plant and seed development, stress responses and germination. It was found that ABA signal transduction in plants can involve the activity of type 2C-phosphatases (PP2C), calcium, potassium, pH and a transient activation of MAP kinase. The ABA signal transduction cascades have been shown to be tissue-specific, the transient activation of MAP kinase has until now only been found in barley aleurone cells. However, type 2C phosphatases are involved in the induction of most ABA responses, as shown by the PP2C-deficient abi-mutants. These phosphatases show high homology with phosphatases that regulate MAP kinase activity in yeast. In addition, the role of farnesyl transferase as a negative regulator of ABA responses also indicates towards involvement of MAP kinase in ABA signal transduction. Farnesyl transferase is known to regulate Ras proteins, Ras proteins in turn are known to regulate MAP kinase activation. Interestingly, Ras-like proteins were detected in barley aleurone cells. Further establishment of the involvement of MAP kinase in ABA signal transduction and its role therein, still awaits more study.

  13. Dissection of the cis-2-decenoic acid signaling network in Pseudomonas aeruginosa using microarray technique

    PubMed Central

    Rahmani-Badi, Azadeh; Sepehr, Shayesteh; Fallahi, Hossein; Heidari-Keshel, Saeed

    2015-01-01

    Many bacterial pathogens use quorum-sensing (QS) signaling to regulate the expression of factors contributing to virulence and persistence. Bacteria produce signals of different chemical classes. The signal molecule, known as diffusible signal factor (DSF), is a cis-unsaturated fatty acid that was first described in the plant pathogen Xanthomonas campestris. Previous works have shown that human pathogen, Pseudomonas aeruginosa, also synthesizes a structurally related molecule, characterized as cis-2-decenoic acid (C10: Δ2, CDA) that induces biofilm dispersal by multiple types of bacteria. Furthermore, CDA has been shown to be involved in inter-kingdom signaling that modulates fungal behavior. Therefore, an understanding of its signaling mechanism could suggest strategies for interference, with consequences for disease control. To identify the components of CDA signaling pathway in this pathogen, a comparative transcritpome analysis was conducted, in the presence and absence of CDA. A protein-protein interaction (PPI) network for differentially expressed (DE) genes with known function was then constructed by STRING and Cytoscape. In addition, the effects of CDA in combination with antimicrobial agents on the biofilm surface area and bacteria viability were evaluated using fluorescence microscopy and digital image analysis. Microarray analysis identified 666 differentially expressed genes in the presence of CDA and gene ontology (GO) analysis revealed that in P. aeruginosa, CDA mediates dispersion of biofilms through signaling pathways, including enhanced motility, metabolic activity, virulence as well as persistence at different temperatures. PPI data suggested that a cluster of five genes (PA4978, PA4979, PA4980, PA4982, PA4983) is involved in the CDA synthesis and perception. Combined treatments using both CDA and antimicrobial agents showed that following exposure of the biofilms to CDA, remaining cells on the surface were easily removed and killed by

  14. Learning signaling network structures with sparsely distributed data.

    PubMed

    Sachs, Karen; Itani, Solomon; Carlisle, Jennifer; Nolan, Garry P; Pe'er, Dana; Lauffenburger, Douglas A

    2009-02-01

    Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is easily scaled to many conditions in high throughput. However, the technology suffers from a dimensionality constraint: at the cutting edge, only about 12 protein species can be measured per cell, far from sufficient for most signaling pathways. Because the structure learning algorithm (in practice) requires that all variables be measured together simultaneously, this restricts structure learning to the number of variables that constitute the flow cytometer's upper dimensionality limit. To address this problem, we present here an algorithm that enables structure learning for sparsely distributed data, allowing structure learning beyond the measurement technology's upper dimensionality limit for simultaneously measurable variables. The algorithm assesses pairwise (or n-wise) dependencies, constructs "Markov neighborhoods" for each variable based on these dependencies, measures each variable in the context of its neighborhood, and performs structure learning using a constrained search.

  15. Role of protein kinase D signaling in pancreatic cancer.

    PubMed

    Guha, Sushovan; Tanasanvimon, Suebpong; Sinnett-Smith, James; Rozengurt, Enrique

    2010-12-15

    Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with dismal survival rates. Its intransigence to conventional therapy renders PDAC an aggressive disease with early metastatic potential. Thus, novel targets for PDAC therapy are urgently needed. Multiple signal transduction pathways are implicated in progression of PDAC. These pathways stimulate production of intracellular messengers in their target cells to modify their behavior, including the lipid-derived diacylglycerol (DAG). One of the prominent intracellular targets of DAG is the protein kinase C (PKC) family. However, the mechanisms by which PKC-mediated signals are decoded by the cell remain incompletely understood. Protein kinase D1 (PKD or PKD1, initially called atypical PKCμ), is the founding member of a novel protein kinase family that includes two additional protein kinases that share extensive overall homology with PKD, termed PKD2, and PKD3. The PKD family occupies a unique position in the signal transduction pathways initiated by DAG and PKC. PKD lies downstream of PKCs in a novel signal transduction pathway implicated in the regulation of multiple fundamental biological processes. We and others have shown that PKD-mediated signaling pathways promote mitogenesis and angiogenesis in PDAC. Our recent observations demonstrate that PKD also potentiates chemoresistance and invasive potential of PDAC cells. This review will briefly highlight diverse biological roles of PKD family in multiple neoplasias including PDAC. Further, this review will underscore our latest advancement with the development of a potent PKD family inhibitor and its effect both in vitro and in vivo in PDAC. PMID:20621068

  16. Using melanopsin to study G protein signaling in cortical neurons.

    PubMed

    McGregor, K M; Bécamel, C; Marin, P; Andrade, R

    2016-09-01

    Our understanding of G protein-coupled receptors (GPCRs) in the central nervous system (CNS) has been hampered by the limited availability of tools allowing for the study of their signaling with precise temporal control. To overcome this, we tested the utility of the bistable mammalian opsin melanopsin to examine G protein signaling in CNS neurons. Specifically, we used biolistic (gene gun) approaches to transfect melanopsin into cortical pyramidal cells maintained in organotypic slice culture. Whole cell recordings from transfected neurons indicated that application of blue light effectively activated the transfected melanopsin to elicit the canonical biphasic modulation of membrane excitability previously associated with the activation of GPCRs coupling to Gαq-11 Remarkably, full mimicry of exogenous agonist concentration could be obtained with pulses as short as a few milliseconds, suggesting that their triggering required a single melanopsin activation-deactivation cycle. The resulting temporal control over melanopsin activation allowed us to compare the activation kinetics of different components of the electrophysiological response. We also replaced the intracellular loops of melanopsin with those of the 5-HT2A receptor to create a light-activated GPCR capable of interacting with the 5-HT2A receptor interacting proteins. The resulting chimera expressed weak activity but validated the potential usefulness of melanopsin as a tool for the study of G protein signaling in CNS neurons. PMID:27306679

  17. Light-regulated translocation of signaling proteins in Drosophila photoreceptors

    PubMed Central

    Frechter, Shahar; Minke, Baruch

    2007-01-01

    Illumination of Drosophila photoreceptor cells induces multi-facet responses, which include generation of the photoreceptor potential, screening pigment migration and translocation of signaling proteins which is the focus of recent extensive research. Translocation of three signaling molecules is covered in this review: (1) Light-dependent translocation of arrestin from the cytosol to the signaling membrane, the rhabdomere, determines the lifetime of activated rhodopsin. Arrestin translocates in PIP3 and NINAC myosin III dependent manner, and specific mutations which disrupt the interaction between arrestin and PIP3 or NINAC also impair the light-dependant translocation of arrestin and the termination of the response to light. (2) Activation of Drosophila visual G protein, DGq, causes a massive and reversible, translocation of the α subunit from the signaling membrane to the cytosol, accompanied by activity-dependent architectural changes. Analysis of the translocation and the recovery kinetics of DGqα in wild-type flies and specific visual mutants indicated that DGqα is necessary but not sufficient for the architectural changes. (3) The TRP-like (TRPL) but not TRP channels translocate in a light-dependent manner between the rhabdomere and the cell body. As a physiological consequence of this light-dependent modulation of the TRP/TRPL ratio, the photoreceptors of dark-adapted flies operate at a wider dynamic range, which allows the photoreceptors enriched with TRPL to function better in darkness and dim background illumination. Altogether, signal-dependent movement of signaling proteins plays a major role in the maintenance and function of photoreceptor cells. PMID:16458490

  18. XB130: A novel adaptor protein in cancer signal transduction

    PubMed Central

    ZHANG, RUIYAO; ZHANG, JINGYAO; WU, QIFEI; MENG, FANDI; LIU, CHANG

    2016-01-01

    Adaptor proteins are functional proteins that contain two or more protein-binding modules to link signaling proteins together, which affect cell growth and shape and have no enzymatic activity. The actin filament-associated protein (AFAP) family is an important member of the adaptor proteins, including AFAP1, AFAP1L1 and AFAP1L2/XB130. AFAP1 and AFAP1L1 share certain common characteristics and function as an actin-binding protein and a cSrc-activating protein. XB130 exhibits certain unique features in structure and function. The mRNA of XB130 is expressed in human spleen, thyroid, kidney, brain, lung, pancreas, liver, colon and stomach, and the most prominent disease associated with XB130 is cancer. XB130 has a controversial effect on cancer. Studies have shown that XB130 can promote cancer progression and downregulation of XB130-reduced growth of tumors derived from certain cell lines. A higher mRNA level of XB130 was shown to be associated with a better survival in non-small cell lung cancer. Previous studies have shown that XB130 can regulate cell growth, migration and invasion and possibly has the effect through the cAMP-cSrc-phosphoinositide 3-kinase/Akt pathway. Except for cancer, XB130 is also associated with other pathological or physiological procedures, such as airway repair and regeneration. PMID:26998266

  19. The Sts Proteins Target Tyrosine Phosphorylated, Ubiquitinated Proteins within TCR Signaling Pathways

    SciTech Connect

    Carpino, N.; Chen, Y; Nassar, N; Oh, H

    2009-01-01

    The T cell receptor (TCR) detects the presence of infectious pathogens and activates numerous intracellular signaling pathways. Protein tyrosine phosphorylation and ubiquitination serve as key regulatory mechanisms downstream of the TCR. Negative regulation of TCR signaling pathways is important in controlling the immune response, and the Suppressor of TCR Signaling proteins (Sts-1 and Sts-2) have been shown to function as critical negative regulators of TCR signaling. Although their mechanism of action has yet to be fully uncovered, it is known that the Sts proteins possess intrinsic phosphatase activity. Here, we demonstrate that Sts-1 and Sts-2 are instrumental in down-modulating proteins that are dually modified by both protein tyrosine phosphorylation and ubiquitination. Specifically, both naive and activated T cells derived from genetically engineered mice that lack the Sts proteins display strikingly elevated levels of tyrosine phosphorylated, ubiquitinated proteins following TCR stimulation. The accumulation of the dually modified proteins is transient, and in activated T cells but not naive T cells is significantly enhanced by co-receptor engagement. Our observations hint at a novel regulatory mechanism downstream of the T cell receptor.

  20. Method for analyzing signaling networks in complex cellular systems.

    PubMed

    Plavec, Ivan; Sirenko, Oksana; Privat, Sylvie; Wang, Yuker; Dajee, Maya; Melrose, Jennifer; Nakao, Brian; Hytopoulos, Evangelos; Berg, Ellen L; Butcher, Eugene C

    2004-02-01

    Now that the human genome has been sequenced, the challenge of assigning function to human genes has become acute. Existing approaches using microarrays or proteomics frequently generate very large volumes of data not directly related to biological function, making interpretation difficult. Here, we describe a technique for integrative systems biology in which: (i) primary cells are cultured under biologically meaningful conditions; (ii) a limited number of biologically meaningful readouts are measured; and (iii) the results obtained under several different conditions are combined for analysis. Studies of human endothelial cells overexpressing different signaling molecules under multiple inflammatory conditions show that this system can capture a remarkable range of functions by a relatively small number of simple measurements. In particular, measurement of seven different protein levels by ELISA under four different conditions is capable of reconstructing pathway associations of 25 different proteins representing four known signaling pathways, implicating additional participants in the NF-kappaBorRAS/mitogen-activated protein kinase pathways and defining additional interactions between these pathways. PMID:14745015

  1. Method for analyzing signaling networks in complex cellular systems

    PubMed Central

    Plavec, Ivan; Sirenko, Oksana; Privat, Sylvie; Wang, Yuker; Dajee, Maya; Melrose, Jennifer; Nakao, Brian; Hytopoulos, Evangelos; Berg, Ellen L.; Butcher, Eugene C.

    2004-01-01

    Now that the human genome has been sequenced, the challenge of assigning function to human genes has become acute. Existing approaches using microarrays or proteomics frequently generate very large volumes of data not directly related to biological function, making interpretation difficult. Here, we describe a technique for integrative systems biology in which: (i) primary cells are cultured under biologically meaningful conditions; (ii) a limited number of biologically meaningful readouts are measured; and (iii) the results obtained under several different conditions are combined for analysis. Studies of human endothelial cells overexpressing different signaling molecules under multiple inflammatory conditions show that this system can capture a remarkable range of functions by a relatively small number of simple measurements. In particular, measurement of seven different protein levels by ELISA under four different conditions is capable of reconstructing pathway associations of 25 different proteins representing four known signaling pathways, implicating additional participants in the NF-κBorRAS/mitogen-activated protein kinase pathways and defining additional interactions between these pathways. PMID:14745015

  2. Self-incompatibility in Papaver: advances in integrating the signalling network.

    PubMed

    Eaves, Deborah J; Flores-Ortiz, Carlos; Haque, Tamanna; Lin, Zongcheng; Teng, Nianjun; Franklin-Tong, Vernonica E

    2014-04-01

    Self-fertilization, which results in reduced fitness of offspring, is a common problem in hermaphrodite angiosperms. To prevent this, many plants utilize SI (self-incompatibility), which is determined by the multi-allelic S-locus, that allows discrimination between self (incompatible) and non-self (compatible) pollen by the pistil. In poppy (Papaver rhoeas), the pistil S-determinant (PrsS) is a small secreted protein which interacts with the pollen S-determinant PrpS, a ~20 kDa novel transmembrane protein. Interaction of matching pollen and pistil S-determinants results in self-recognition, initiating a Ca²⁺-dependent signalling network in incompatible pollen. This triggers several downstream events, including alterations to the cytoskeleton, phosphorylation of sPPases (soluble inorganic pyrophosphatases) and an MAPK (mitogen-activated protein kinase), increases in ROS (reactive oxygen species) and nitric oxide (NO), and activation of several caspase-like activities. This results in the inhibition of pollen tube growth, prevention of self-fertilization and ultimately PCD (programmed cell death) in incompatible pollen. The present review focuses on our current understanding of the integration of these signals with their targets in the SI/PCD network. We also discuss our recent functional expression of PrpS in Arabidopsis thaliana pollen.

  3. Control of cancer-related signal transduction networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2013-03-01

    Intra-cellular signaling networks are crucial to the maintenance of cellular homeostasis and for cell behavior (growth, survival, apoptosis, movement). Mutations or alterations in the expression of elements of cellular signaling networks can lead to incorrect behavioral decisions that could result in tumor development and/or the promotion of cell migration and metastasis. Thus, mitigation of the cascading effects of such dysregulations is an important control objective. My group at Penn State is collaborating with wet-bench biologists to develop and validate predictive models of various biological systems. Over the years we found that discrete dynamic modeling is very useful in molding qualitative interaction information into a predictive model. We recently demonstrated the effectiveness of network-based targeted manipulations on mitigating the disease T cell large granular lymphocyte (T-LGL) leukemia. The root of this disease is the abnormal survival of T cells which, after successfully fighting an infection, should undergo programmed cell death. We synthesized the relevant network of within-T-cell interactions from the literature, integrated it with qualitative knowledge of the dysregulated (abnormal) states of several network components, and formulated a Boolean dynamic model. The model indicated that the system possesses a steady state corresponding to the normal cell death state and a T-LGL steady state corresponding to the abnormal survival state. For each node, we evaluated the restorative manipulation consisting of maintaining the node in the state that is the opposite of its T-LGL state, e.g. knocking it out if it is overexpressed in the T-LGL state. We found that such control of any of 15 nodes led to the disappearance of the T-LGL steady state, leaving cell death as the only potential outcome from any initial condition. In four additional cases the probability of reaching the T-LGL state decreased dramatically, thus these nodes are also possible control

  4. Automated Measurement and Signaling Systems for the Transactional Network

    SciTech Connect

    Piette, Mary Ann; Brown, Richard; Price, Phillip; Page, Janie; Granderson, Jessica; Riess, David; Czarnecki, Stephen; Ghatikar, Girish; Lanzisera, Steven

    2013-12-31

    The Transactional Network Project is a multi-lab activity funded by the US Department of Energy?s Building Technologies Office. The project team included staff from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The team designed, prototyped and tested a transactional network (TN) platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). PNNL was responsible for the development of the TN platform, with agents for this platform developed by each of the three labs. LBNL contributed applications to measure the whole-building electric load response to various changes in building operations, particularly energy efficiency improvements and demand response events. We also provide a demand response signaling agent and an agent for cost savings analysis. LBNL and PNNL demonstrated actual transactions between packaged rooftop units and the electric grid using the platform and selected agents. This document describes the agents and applications developed by the LBNL team, and associated tests of the applications.

  5. Inhibition of Protein-Protein Interactions and Signaling by Small Molecules

    NASA Astrophysics Data System (ADS)

    Freire, Ernesto

    2010-03-01

    Protein-protein interactions are at the core of cell signaling pathways as well as many bacterial and viral infection processes. As such, they define critical targets for drug development against diseases such as cancer, arthritis, obesity, AIDS and many others. Until now, the clinical inhibition of protein-protein interactions and signaling has been accomplished with the use of antibodies or soluble versions of receptor molecules. Small molecule replacements of these therapeutic agents have been extremely difficult to develop; either the necessary potency has been hard to achieve or the expected biological effect has not been obtained. In this presentation, we show that a rigorous thermodynamic approach that combines differential scanning calorimetry (DSC) and isothermal titration calorimetry (ITC) provides a unique platform for the identification and optimization of small molecular weight inhibitors of protein-protein interactions. Recent advances in the development of cell entry inhibitors of HIV-1 using this approach will be discussed.

  6. Biased and G Protein-Independent Signaling of Chemokine Receptors

    PubMed Central

    Steen, Anne; Larsen, Olav; Thiele, Stefanie; Rosenkilde, Mette M.

    2014-01-01

    Biased signaling or functional selectivity occurs when a 7TM-receptor preferentially activates one of several available pathways. It can be divided into three distinct forms: ligand bias, receptor bias, and tissue or cell bias, where it is mediated by different ligands (on the same receptor), different receptors (with the same ligand), or different tissues or cells (for the same ligand–receptor pair). Most often biased signaling is differentiated into G protein-dependent and β-arrestin-dependent signaling. Yet, it may also cover signaling differences within these groups. Moreover, it may not be absolute, i.e., full versus no activation. Here we discuss biased signaling in the chemokine system, including the structural basis for biased signaling in chemokine receptors, as well as in class A 7TM receptors in general. This includes overall helical movements and the contributions of micro-switches based on recently published 7TM crystals and molecular dynamics studies. All three forms of biased signaling are abundant in the chemokine system. This challenges our understanding of “classic” redundancy inevitably ascribed to this system, where multiple chemokines bind to the same receptor and where a single chemokine may bind to several receptors – in both cases with the same functional outcome. The ubiquitous biased signaling confers a hitherto unknown specificity to the chemokine system with a complex interaction pattern that is better described as promiscuous with context-defined roles and different functional outcomes in a ligand-, receptor-, or cell/tissue-defined manner. As the low number of successful drug development plans implies, there are great difficulties in targeting chemokine receptors; in particular with regard to receptor antagonists as anti-inflammatory drugs. Un-defined and putative non-selective targeting of the complete cellular signaling system could be the underlying cause of lack of success. Therefore, biased ligands could be the solution

  7. Regulation of protease-activated receptor 1 signaling by the adaptor protein complex 2 and R4 subfamily of regulator of G protein signaling proteins.

    PubMed

    Chen, Buxin; Siderovski, David P; Neubig, Richard R; Lawson, Mark A; Trejo, Joann

    2014-01-17

    The G protein-coupled protease-activated receptor 1 (PAR1) is irreversibly proteolytically activated by thrombin. Hence, the precise regulation of PAR1 signaling is important for proper cellular responses. In addition to desensitization, internalization and lysosomal sorting of activated PAR1 are critical for the termination of signaling. Unlike most G protein-coupled receptors, PAR1 internalization is mediated by the clathrin adaptor protein complex 2 (AP-2) and epsin-1, rather than β-arrestins. However, the function of AP-2 and epsin-1 in the regulation of PAR1 signaling is not known. Here, we report that AP-2, and not epsin-1, regulates activated PAR1-stimulated phosphoinositide hydrolysis via two different mechanisms that involve, in part, a subset of R4 subfamily of "regulator of G protein signaling" (RGS) proteins. A significantly greater increase in activated PAR1 signaling was observed in cells depleted of AP-2 using siRNA or in cells expressing a PAR1 (420)AKKAA(424) mutant with defective AP-2 binding. This effect was attributed to AP-2 modulation of PAR1 surface expression and efficiency of G protein coupling. We further found that ectopic expression of R4 subfamily members RGS2, RGS3, RGS4, and RGS5 reduced activated PAR1 wild-type signaling, whereas signaling by the PAR1 AKKAA mutant was minimally affected. Intriguingly, siRNA-mediated depletion analysis revealed a function for RGS5 in the regulation of signaling by the PAR1 wild type but not the AKKAA mutant. Moreover, activation of the PAR1 wild type, and not the AKKAA mutant, induced Gαq association with RGS3 via an AP-2-dependent mechanism. Thus, AP-2 regulates activated PAR1 signaling by altering receptor surface expression and through recruitment of RGS proteins. PMID:24297163

  8. Endocytosis of Seven-Transmembrane RGS Protein Activates G- protein Coupled Signaling in Arabidopsis

    PubMed Central

    Urano, Daisuke; Phan, Nguyen; Jones, Janice C.; Yang, Jing; Huang, Jirong; Grigston, Jeffrey; Taylor, J. Philip; Jones, Alan M.

    2012-01-01

    Signal transduction typically begins by ligand-dependent activation of a concomitant partner which is otherwise in its resting state. However, in cases where signal activation is constitutive by default, the mechanism of regulation is unknown. The Arabidopsis thaliana heterotrimeric Gα protein self-activates without accessory proteins, and is kept in its resting state by the negative regulator, AtRGS1 (Regulator of G protein Signaling 1), which is the prototype of a seven transmembrane receptor fused with an RGS domain. Endocytosis of AtRGS1 by ligand-dependent endocytosis physically uncouples the GTPase accelerating activity of AtRGS1 from the Gα protein, permitting sustained activation. Phosphorylation of AtRGS1 by AtWNK8 kinase causes AtRGS1 endocytosis, required both for G protein-mediated sugar signaling and cell proliferation. In animals, receptor endocytosis results in signal desensitization, whereas in plants, endocytosis results in signal activation. These findings reveal how different organisms rearrange a regulatory system to result in opposite outcomes using similar phosphorylation-dependent endocytosis. PMID:22940907

  9. Prioritizing protein complexes implicated in human diseases by network optimization

    PubMed Central

    2014-01-01

    Background The detection of associations between protein complexes and human inherited diseases is of great importance in understanding mechanisms of diseases. Dysfunctions of a protein complex are usually defined by its member disturbance and consequently result in certain diseases. Although individual disease proteins have been widely predicted, computational methods are still absent for systematically investigating disease-related protein complexes. Results We propose a method, MAXCOM, for the prioritization of candidate protein complexes. MAXCOM performs a maximum information flow algorithm to optimize relationships between a query disease and candidate protein complexes through a heterogeneous network that is constructed by combining protein-protein interactions and disease phenotypic similarities. Cross-validation experiments on 539 protein complexes show that MAXCOM can rank 382 (70.87%) protein complexes at the top against protein complexes constructed at random. Permutation experiments further confirm that MAXCOM is robust to the network structure and parameters involved. We further analyze protein complexes ranked among top ten for breast cancer and demonstrate that the SWI/SNF complex is potentially associated with breast cancer. Conclusions MAXCOM is an effective method for the discovery of disease-related protein complexes based on network optimization. The high performance and robustness of this approach can facilitate not only pathologic studies of diseases, but also the design of drugs targeting on multiple proteins. PMID:24565064

  10. Deciphering signaling pathways in clinical tissues for personalized medicine using protein microarrays.

    PubMed

    Malinowsky, K; Wolff, C; Ergin, B; Berg, D; Becker, K F

    2010-11-01

    The current transition in cancer therapy from general treatment approaches, based mainly on chemotherapy and radiotherapy, to more directed approaches that aim to inhibit specific molecular targets has brought about new challenges for pathology. In the past, classical assignment of pathology consisted of tumor diagnosis and staging for further therapy decisions; nowadays, pathologists are asked to predict possible therapeutic results by detecting and quantifying therapeutic targets in tumors such as the human epidermal growth factor receptor 2 (HER2). The best approach to analyze such molecular targets is to provide a tumor-specific protein expression profile prior to therapy. To further elucidate signaling networks underlying cancer development and to identify new targets, it is necessary to implement tools that allow fast, precise, cheap, and simultaneous analysis of many network components while requiring only a small amount of clinical material. Reverse phase protein microarray (RPPA) is a promising technology that meets these requirements while enabling quantitative measurement of proteins. Recently, methods for the extraction of proteins from formalin-fixed, paraffin-embedded (FFPE) tissues have become available. In this article, we demonstrate how the use of RPPA to analyze signaling pathways from FFPE tissues may improve quantification of therapeutic targets and diagnostic markers in the near future.

  11. Engineering modular and tunable genetic amplifiers for scaling transcriptional signals in cascaded gene networks.

    PubMed

    Wang, Baojun; Barahona, Mauricio; Buck, Martin

    2014-08-01

    Synthetic biology aims to control and reprogram signal processing pathways within living cells so as to realize repurposed, beneficial applications. Here we report the design and construction of a set of modular and gain-tunable genetic amplifiers in Escherichia coli capable of amplifying a transcriptional signal with wide tunable-gain control in cascaded gene networks. The devices are engineered using orthogonal genetic components (hrpRS, hrpV and PhrpL) from the hrp (hypersensitive response and pathogenicity) gene regulatory network in Pseudomonas syringae. The amplifiers can linearly scale up to 21-fold the transcriptional input with a large output dynamic range, yet not introducing significant time delay or significant noise during signal amplification. The set of genetic amplifiers achieves different gains and input dynamic ranges by varying the expression levels of the underlying ligand-free activator proteins in the device. As their electronic counterparts, these engineered transcriptional amplifiers can act as fundamental building blocks in the design of biological systems by predictably and dynamically modulating transcriptional signal flows to implement advanced intra- and extra-cellular control functions.

  12. Pattern recognition for electroencephalographic signals based on continuous neural networks.

    PubMed

    Alfaro-Ponce, M; Argüelles, A; Chairez, I

    2016-07-01

    This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method for this kind of continuous NN (CNN) was developed according to the Lyapunov theory stability analysis. A parallel structure with fixed weights was proposed to perform the classification stage. The pattern recognition efficiency was validated by two methods, a generalization-regularization and a k-fold cross validation (k=5). The classifier was applied on two different databases. The first one was made up by signals collected from patients suffering of epilepsy and it is divided in five different classes. The second database was made up by 90 single EEG trials, divided in three classes. Each class corresponds to a different visual evoked potential. The pattern recognition algorithm achieved a maximum correct classification percentage of 97.2% using the information of the entire database. This value was similar to some results previously reported when this database was used for testing pattern classification. However, these results were obtained when only two classes were considered for the testing. The result reported in this study used the whole set of signals (five different classes). In comparison with similar pattern recognition methods that even considered less number of classes, the proposed CNN proved to achieve the same or even better correct classification results.

  13. Pattern recognition for electroencephalographic signals based on continuous neural networks.

    PubMed

    Alfaro-Ponce, M; Argüelles, A; Chairez, I

    2016-07-01

    This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method for this kind of continuous NN (CNN) was developed according to the Lyapunov theory stability analysis. A parallel structure with fixed weights was proposed to perform the classification stage. The pattern recognition efficiency was validated by two methods, a generalization-regularization and a k-fold cross validation (k=5). The classifier was applied on two different databases. The first one was made up by signals collected from patients suffering of epilepsy and it is divided in five different classes. The second database was made up by 90 single EEG trials, divided in three classes. Each class corresponds to a different visual evoked potential. The pattern recognition algorithm achieved a maximum correct classification percentage of 97.2% using the information of the entire database. This value was similar to some results previously reported when this database was used for testing pattern classification. However, these results were obtained when only two classes were considered for the testing. The result reported in this study used the whole set of signals (five different classes). In comparison with similar pattern recognition methods that even considered less number of classes, the proposed CNN proved to achieve the same or even better correct classification results. PMID:27131469

  14. Nanoscale protein domain motion and long-range allostery in signaling proteins— a view from neutron spin echo sprectroscopy

    PubMed Central

    Callaway, David J. E.; Bu, Zimei

    2015-01-01

    Many cellular proteins are multi-domain proteins. Coupled domain-domain interactions in these multidomain proteins are important for the allosteric relay of signals in the cellular signaling networks. We have initiated the application of neutron spin echo spectroscopy to the study of nanoscale protein domain motions on submicrosecond time scales and on nanometer length scale. Our NSE experiments reveal the activation of protein domain motions over a long distance of over more than 100 Å in a multidomain scaffolding protein NHERF1 upon binding to another protein Ezrin. Such activation of nanoscale protein domains motions is correlated with the allosteric assembly of multi-protein complexes by NHERF1 and Ezrin. Here, we summarize the theoretical framework that we have developed, which uses simple concepts from nonequilibrium statistical mechanics to interpret the NSE data, and employs a mobility tensor to describe nanoscale protein domain motion. Extracting nanoscale protein domain motion from the NSE does not require elaborate molecular dynamics simulations, or complex fits to rotational motion, or elastic network models. The approach is thus more robust than multiparameter techniques that require untestable assumptions. We also demonstrate that an experimental scheme of selective deuteration of a protein subunit in a complex can highlight and amplify specific domain dynamics from the abundant global translational and rotational motions in a protein. We expect NSE to provide a unique tool to determine nanoscale protein dynamics for the understanding of protein functions, such as how signals are propagated in a protein over a long distance to a distal domain. PMID:26005503

  15. Simulated evolution of protein-protein interaction networks with realistic topology.

    PubMed

    Peterson, G Jack; Pressé, Steve; Peterson, Kristin S; Dill, Ken A

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.

  16. Simulated evolution of protein-protein interaction networks with realistic topology.

    PubMed

    Peterson, G Jack; Pressé, Steve; Peterson, Kristin S; Dill, Ken A

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution. PMID:22768057

  17. Arabidopsis protein phosphatase DBP1 nucleates a protein network with a role in regulating plant defense.

    PubMed

    Carrasco, José Luis; Castelló, María José; Naumann, Kai; Lassowskat, Ines; Navarrete-Gómez, Marisa; Scheel, Dierk; Vera, Pablo

    2014-01-01

    Arabidopsis thaliana DBP1 belongs to the plant-specific family of DNA-binding protein phosphatases. Although recently identified as a novel host factor mediating susceptibility to potyvirus, little is known about DBP1 targets and partners and the molecular mechanisms underlying its function. Analyzing changes in the phosphoproteome of a loss-of-function dbp1 mutant enabled the identification of 14-3-3λ isoform (GRF6), a previously reported DBP1 interactor, and MAP kinase (MAPK) MPK11 as components of a small protein network nucleated by DBP1, in which GRF6 stability is modulated by MPK11 through phosphorylation, while DBP1 in turn negatively regulates MPK11 activity. Interestingly, grf6 and mpk11 loss-of-function mutants showed altered response to infection by the potyvirus Plum pox virus (PPV), and the described molecular mechanism controlling GRF6 stability was recapitulated upon PPV infection. These results not only contribute to a better knowledge of the biology of DBP factors, but also of MAPK signalling in plants, with the identification of GRF6 as a likely MPK11 substrate and of DBP1 as a protein phosphatase regulating MPK11 activity, and unveils the implication of this protein module in the response to PPV infection in Arabidopsis.

  18. Identification and evolution of structurally dominant nodes in protein-protein interaction networks.

    PubMed

    Wang, Pei; Yu, Xinghuo; Lü, Jinhu

    2014-02-01

    It is well known that protein-protein interaction (PPI) networks are typical evolving complex networks. Identification of important nodes has been an emerging popular topic in complex networks. Many indexes have been proposed to measure the importance of nodes in complex networks, such as degree, closeness, betweenness, k-shell, clustering coefficient, semi-local centrality, eigenvector centrality. Based on multivariate statistical analysis, through integrating the above indexes and further considering the appearances of nodes in network motifs, this paper aims at developing a new measure to characterize the structurally dominant proteins (SDP) in PPI networks. Moreover, we will further investigate the evolution of the defined dominant nodes in temporal evolving real-world and artificial PPI networks. Our results indicate that the constructed artificial networks have some similar statistical properties as those of the real-world evolving networks. In this case, the artificial PPI networks can be used to further investigate the above evolution characteristics of the real-world evolving networks. Simulation results reveal that SDP in the yeast PPI networks are evolutionary conserved, however, the undominant nodes evolve rapidly. Furthermore, PPI networks are very robust against random mutations, while fragile yet with certain robustness to targeted mutations on SDP. Our investigations shed some light on the future applications of the evolving characteristics of bio-molecular networks, such as reengineering of particular networks for technological, synthetic or pharmacological purposes. PMID:24681922

  19. Chapter Two - Heterotrimeric G Protein Ubiquitination as a Regulator of G Protein Signaling.

    PubMed

    Torres, M

    2016-01-01

    Ubiquitin-mediated regulation of G proteins has been known for over 20 years as a result of discoveries made independently in yeast and vertebrate model systems for pheromone and photoreception, respectively. Since that time, several details underlying the cause and effect of G protein ubiquitination have been determined-including the initiating signals, responsible enzymes, trafficking pathways, and their effects on protein structure, function, interactions, and cell signaling. The collective body of evidence suggests that Gα subunits are the primary targets of ubiquitination. However, longstanding and recent results suggest that Gβ and Gγ subunits are also ubiquitinated, in some cases impacting cell polarization-a process essential for chemotaxis and polarized cell growth. More recently, evidence from mass spectrometry (MS)-based proteomics coupled with advances in PTM bioinformatics have revealed that protein families representing G protein subunits contain several structural hotspots for ubiquitination-most of which have not been investigated for a functional role in signal transduction. Taken together, our knowledge and understanding of heterotrimeric G protein ubiquitination as a regulator of G protein signaling-despite 20 years of research-is still emerging. PMID:27378755

  20. FunMod: a Cytoscape plugin for identifying functional modules in undirected protein-protein networks.

    PubMed

    Natale, Massimo; Benso, Alfredo; Di Carlo, Stefano; Ficarra, Elisa

    2014-08-01

    The characterization of the interacting behaviors of complex biological systems is a primary objective in protein-protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein-protein networks and to infer sub-networks of interacting proteins intimately correlated with relevant biological pathways. This plugin may enable the discovery of new pathways involved in diseases. In order to describe the role of each protein within the relevant biological pathways, FunMod computes and scores three topological features of the identified sub-networks. By integrating the results from biological pathway clustering and topological network analysis, FunMod proved to be useful for the data interpretation and the generation of new hypotheses in two case studies.

  1. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network

    PubMed Central

    Hu, Yang; Zhang, Ying; Ren, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence.

  2. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network.

    PubMed

    Hu, Yang; Zhang, Ying; Ren, Jun; Wang, Yadong; Wang, Zhenzhen; Zhang, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence. PMID:27648447

  3. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network

    PubMed Central

    Hu, Yang; Zhang, Ying; Ren, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence. PMID:27648447

  4. A calcium sensor - protein kinase signaling module diversified in plants and is retained in all lineages of Bikonta species.

    PubMed

    Beckmann, Linda; Edel, Kai H; Batistič, Oliver; Kudla, Jörg

    2016-01-01

    Calcium (Ca(2+)) signaling is a universal mechanism of signal transduction and involves Ca(2+) signal formation and decoding of information by Ca(2+) binding proteins. Calcineurin B-like proteins (CBLs), which upon Ca(2+) binding activate CBL-interacting protein kinases (CIPKs) regulate a multitude of physiological processes in plants. Here, we combine phylogenomics and functional analyses to investigate the occurrence and structural conservation of CBL and CIPK proteins in 26 species representing all major clades of eukaryotes. We demonstrate the presence of at least singular CBL-CIPK pairs in representatives of Archaeplastida, Chromalveolates and Excavates and their general absence in Opisthokonta and Amoebozoa. This denotes CBL-CIPK complexes as evolutionary ancient Ca(2+) signaling modules that likely evolved in the ancestor of all Bikonta. Furthermore, we functionally characterize the CBLs and CIPK from the parabasalid human pathogen Trichomonas vaginalis. Our results reveal strict evolutionary conservation of functionally important structural features, preservation of biochemical properties and a remarkable cross-kingdom protein-protein interaction potential between CBLs and CIPKs from Arabidopsis thaliana and T. vaginalis. Together our findings suggest an ancient evolutionary origin of a functional CBL-CIPK signaling module close to the root of eukaryotic evolution and provide insights into the initial evolution of signaling networks and Ca(2+) signaling specificity. PMID:27538881

  5. A calcium sensor – protein kinase signaling module diversified in plants and is retained in all lineages of Bikonta species

    PubMed Central

    Beckmann, Linda; Edel, Kai H.; Batistič, Oliver; Kudla, Jörg

    2016-01-01

    Calcium (Ca2+) signaling is a universal mechanism of signal transduction and involves Ca2+ signal formation and decoding of information by Ca2+ binding proteins. Calcineurin B-like proteins (CBLs), which upon Ca2+ binding activate CBL-interacting protein kinases (CIPKs) regulate a multitude of physiological processes in plants. Here, we combine phylogenomics and functional analyses to investigate the occurrence and structural conservation of CBL and CIPK proteins in 26 species representing all major clades of eukaryotes. We demonstrate the presence of at least singular CBL-CIPK pairs in representatives of Archaeplastida, Chromalveolates and Excavates and their general absence in Opisthokonta and Amoebozoa. This denotes CBL-CIPK complexes as evolutionary ancient Ca2+ signaling modules that likely evolved in the ancestor of all Bikonta. Furthermore, we functionally characterize the CBLs and CIPK from the parabasalid human pathogen Trichomonas vaginalis. Our results reveal strict evolutionary conservation of functionally important structural features, preservation of biochemical properties and a remarkable cross-kingdom protein-protein interaction potential between CBLs and CIPKs from Arabidopsis thaliana and T. vaginalis. Together our findings suggest an ancient evolutionary origin of a functional CBL-CIPK signaling module close to the root of eukaryotic evolution and provide insights into the initial evolution of signaling networks and Ca2+ signaling specificity. PMID:27538881

  6. Intramolecular conformational changes optimize protein kinase C signaling.

    PubMed

    Antal, Corina E; Violin, Jonathan D; Kunkel, Maya T; Skovsø, Søs; Newton, Alexandra C

    2014-04-24

    Optimal tuning of enzyme signaling is critical for cellular homeostasis. We use fluorescence resonance energy transfer reporters in live cells to follow conformational transitions that tune the affinity of a multidomain signal transducer, protein kinase C (PKC), for optimal response to second messengers. This enzyme comprises two diacylglycerol sensors, the C1A and C1B domains, that have a sufficiently high intrinsic affinity for ligand so that the enzyme would be in a ligand-engaged, active state if not for mechanisms that mask its domains. We show that both diacylglycerol sensors are exposed in newly synthesized PKC and that conformational transitions following priming phosphorylations mask the domains so that the lower affinity sensor, the C1B domain, is the primary diacylglycerol binder. The conformational rearrangements of PKC serve as a paradigm for how multimodule transducers optimize their dynamic range of signaling.

  7. Intramolecular conformational changes optimize protein kinase C signaling.

    PubMed

    Antal, Corina E; Violin, Jonathan D; Kunkel, Maya T; Skovsø, Søs; Newton, Alexandra C

    2014-04-24

    Optimal tuning of enzyme signaling is critical for cellular homeostasis. We use fluorescence resonance energy transfer reporters in live cells to follow conformational transitions that tune the affinity of a multidomain signal transducer, protein kinase C (PKC), for optimal response to second messengers. This enzyme comprises two diacylglycerol sensors, the C1A and C1B domains, that have a sufficiently high intrinsic affinity for ligand so that the enzyme would be in a ligand-engaged, active state if not for mechanisms that mask its domains. We show that both diacylglycerol sensors are exposed in newly synthesized PKC and that conformational transitions following priming phosphorylations mask the domains so that the lower affinity sensor, the C1B domain, is the primary diacylglycerol binder. The conformational rearrangements of PKC serve as a paradigm for how multimodule transducers optimize their dynamic range of signaling. PMID:24631122

  8. PANADA: Protein Association Network Annotation, Determination and Analysis

    PubMed Central

    Martin, Alberto J. M.; Walsh, Ian; Domenico, Tomás Di; Mičetić, Ivan; Tosatto, Silvio C. E.

    2013-01-01

    Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/. PMID:24265686

  9. Signaling Perturbations Induced by Invading H. pylori Proteins in the Host Epithelial Cells

    PubMed Central

    Dampier, William; Tozeren, Aydin

    2007-01-01

    Helicobacter pylori (H. pylori), a gram-negative bacterium, infects the stomach of approximately 50% of the world population. H. pylori infection is a risk factor for developing chronic gastric ulcers and gastric cancer. The bacteria produce two main cytotoxic proteins: Vacuolating cytotoxin A (VacA) and Cytotoxin-Associated gene A (CagA). When these proteins enter the host cell they interfere with the host MAP Kinase and Apoptosis signaling pathways leading to aberrant cell growth and premature apoptosis. The present study expanded existing quantitative models of the MAP Kinase and Apoptosis signaling pathways to take into account the protein interactions across species using the CellDesigner tool. The resulting network contained hundreds of differential equations in which the coefficients for the biochemical rate constants were estimated from previously published studies. The effect of VacA and CagA on the function of this network were simulated by increasing levels of bacterial load. Simulations showed that increasing bacterial load affected the MAP Kinase signaling in a dose dependant manner. The introduction of CagA decreased the activation time of mapK signaling and extended activation indefinitely despite normal cellular activity to deactivate the protein. Introduction of VacA produced a similar response in the apoptosis pathway. Bacterial load activated both pathways even in the absence of external stimulation. Time course of emergence of transcription factors associated with cell division and cell death predicted by our simulation showed close agreement with that determined from a publicly accesible microarray dataset of H. pylori infected stomach epithelium. The quantitative model presented in this study lays the foundation for investigating the affects of single nucleotide polymorphisms (SNPs) on the efficiency of drug treatment. PMID:17559886

  10. Regulation of Protease-activated Receptor 1 Signaling by the Adaptor Protein Complex 2 and R4 Subfamily of Regulator of G Protein Signaling Proteins*

    PubMed Central

    Chen, Buxin; Siderovski, David P.; Neubig, Richard R.; Lawson, Mark A.; Trejo, JoAnn

    2014-01-01

    The G protein-coupled protease-activated receptor 1 (PAR1) is irreversibly proteolytically activated by thrombin. Hence, the precise regulation of PAR1 signaling is important for proper cellular responses. In addition to desensitization, internalization and lysosomal sorting of activated PAR1 are critical for the termination of signaling. Unlike most G protein-coupled receptors, PAR1 internalization is mediated by the clathrin adaptor protein complex 2 (AP-2) and epsin-1, rather than β-arrestins. However, the function of AP-2 and epsin-1 in the regulation of PAR1 signaling is not known. Here, we report that AP-2, and not epsin-1, regulates activated PAR1-stimulated phosphoinositide hydrolysis via two different mechanisms that involve, in part, a subset of R4 subfamily of “regulator of G protein signaling” (RGS) proteins. A significantly greater increase in activated PAR1 signaling was observed in cells depleted of AP-2 using siRNA or in cells expressing a PAR1 420AKKAA424 mutant with defective AP-2 binding. This effect was attributed to AP-2 modulation of PAR1 surface expression and efficiency of G protein coupling. We further found that ectopic expression of R4 subfamily members RGS2, RGS3, RGS4, and RGS5 reduced activated PAR1 wild-type signaling, whereas signaling by the PAR1 AKKAA mutant was minimally affected. Intriguingly, siRNA-mediated depletion analysis revealed a function for RGS5 in the regulation of signaling by the PAR1 wild type but not the AKKAA mutant. Moreover, activation of the PAR1 wild type, and not the AKKAA mutant, induced Gαq association with RGS3 via an AP-2-dependent mechanism. Thus, AP-2 regulates activated PAR1 signaling by altering receptor surface expression and through recruitment of RGS proteins. PMID:24297163

  11. Backbone NMR reveals allosteric signal transduction networks in the β1-adrenergic receptor.

    PubMed

    Isogai, Shin; Deupi, Xavier; Opitz, Christian; Heydenreich, Franziska M; Tsai, Ching-Ju; Brueckner, Florian; Schertler, Gebhard F X; Veprintsev, Dmitry B; Grzesiek, Stephan

    2016-02-11

    G protein-coupled receptors (GPCRs) are physiologically important transmembrane signalling proteins that trigger intracellular responses upon binding of extracellular ligands. Despite recent breakthroughs in GPCR crystallography, the details of ligand-induced signal transduction are not well understood owing to missing dynamical information. In principle, such information can be provided by NMR, but so far only limited data of functional relevance on few side-chain sites of eukaryotic GPCRs have been obtained. Here we show that receptor motions can be followed at virtually any backbone site in a thermostabilized mutant of the turkey β1-adrenergic receptor (β1AR). Labelling with [(15)N]valine in a eukaryotic expression system provides over twenty resolved resonances that report on structure and dynamics in six ligand complexes and the apo form. The response to the various ligands is heterogeneous in the vicinity of the binding pocket, but gets transformed into a homogeneous readout at the intracellular side of helix 5 (TM5), which correlates linearly with ligand efficacy for the G protein pathway. The effect of several pertinent, thermostabilizing point mutations was assessed by reverting them to the native sequence. Whereas the response to ligands remains largely unchanged, binding of the G protein mimetic nanobody NB80 and G protein activation are only observed when two conserved tyrosines (Y227 and Y343) are restored. Binding of NB80 leads to very strong spectral changes throughout the receptor, including the extracellular ligand entrance pocket. This indicates that even the fully thermostabilized receptor undergoes activating motions in TM5, but that the fully active state is only reached in presence of Y227 and Y343 by stabilization with a G protein-like partner. The combined analysis of chemical shift changes from the point mutations and ligand responses identifies crucial connections in the allosteric activation pathway, and presents a general experimental

  12. Distinct Lysosomal Network Protein Profiles in Parkinsonian Syndrome Cerebrospinal Fluid

    PubMed Central

    Boman, Andrea; Svensson, Samuel; Boxer, Adam; Rojas, Julio C.; Seeley, William W.; Karydas, Anna; Miller, Bruce; Kågedal, Katarina; Svenningsson, Per

    2016-01-01

    Background: Clinical diagnosis of parkinsonian syndromes like Parkinson’s disease (PD), corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP) is hampered by overlapping symptomatology and lack of diagnostic biomarkers, and definitive diagnosis is only possible post-mortem. Objective: Since impaired protein degradation plays an important role in many neurodegenerative disorders, we hypothesized that profiles of select lysosomal network proteins in cerebrospinal fluid could be differentially expressed in these parkinsonian syndromes. Methods: Cerebrospinal fluid samples were collected from PD patients (n = 18), clinically diagnosed 4-repeat tauopathy patients; corticobasal syndrome (CBS) (n = 3) and PSP (n = 8); and pathologically diagnosed PSP (n = 8) and CBD patients (n = 7). Each patient set was compared to its appropriate control group consisting of age and gender matched individuals. Select lysosomal network protein levels were detected via Western blotting. Factor analysis was used to test the diagnostic sensitivity, specificity and accuracy of the select lysosomal network protein expression profiles. Results: PD, CBD and PSP were markedly different in their cerebrospinal fluid lysosomal network protein profiles. Lysosomal-associated membrane proteins 1 and 2 were significantly decreased in PD; early endosomal antigen 1 was decreased and lysozyme increased in PSP; and lysosomal-associated membrane proteins 1 and 2, microtubule-associated protein 1 light chain 3 and lysozyme were increased in CBD. A panel of lysosomal-associated membrane protein 2, lysozyme and microtubule-associated protein 1 light chain discriminated between controls, PD and 4-repeat tauopathies. Conclusions: This study offers proof of concept that select lysosomal network proteins are differentially expressed in cerebrospinal fluid of Parkinson’s disease, corticobasal syndrome and progressive supranuclear palsy. Lysosomal network protein analysis

  13. Type One Protein Phosphatase 1 and Its Regulatory Protein Inhibitor 2 Negatively Regulate ABA Signaling

    PubMed Central

    Zhao, Yang; Xie, Shaojun; Batelli, Giorgia; Wang, Bangshing; Duan, Cheng-Guo; Wang, Xingang; Xing, Lu; Lei, Mingguang; Yan, Jun; Zhu, Xiaohong; Zhu, Jian-Kang

    2016-01-01

    The phytohormone abscisic acid (ABA) regulates plant growth, development and responses to biotic and abiotic stresses. The core ABA signaling pathway consists of three major components: ABA receptor (PYR1/PYLs), type 2C Protein Phosphatase (PP2C) and SNF1-related protein kinase 2 (SnRK2). Nevertheless, the complexity of ABA signaling remains to be explored. To uncover new components of ABA signal transduction pathways, we performed a yeast two-hybrid screen for SnRK2-interacting proteins. We found that Type One Protein Phosphatase 1 (TOPP1) and its regulatory protein, At Inhibitor-2 (AtI-2), physically interact with SnRK2s and also with PYLs. TOPP1 inhibited the kinase activity of SnRK2.6, and this inhibition could be enhanced by AtI-2. Transactivation assays showed that TOPP1 and AtI-2 negatively regulated the SnRK2.2/3/6-mediated activation of the ABA responsive reporter gene RD29B, supporting a negative role of TOPP1 and AtI-2 in ABA signaling. Consistent with these findings, topp1 and ati-2 mutant plants displayed hypersensitivities to ABA and salt treatments, and transcriptome analysis of TOPP1 and AtI-2 knockout plants revealed an increased expression of multiple ABA-responsive genes in the mutants. Taken together, our results uncover TOPP1 and AtI-2 as negative regulators of ABA signaling. PMID:26943172

  14. Signal Transduction at the Single-Cell Level: Approaches to Study the Dynamic Nature of Signaling Networks.

    PubMed

    Handly, L Naomi; Yao, Jason; Wollman, Roy

    2016-09-25

    Signal transduction, or how cells interpret and react to external events, is a fundamental aspect of cellular function. Traditional study of signal transduction pathways involves mapping cellular signaling pathways at the population level. However, population-averaged readouts do not adequately illuminate the complex dynamics and heterogeneous responses found at the single-cell level. Recent technological advances that observe cellular response, computationally model signaling pathways, and experimentally manipulate cells now enable studying signal transduction at the single-cell level. These studies will enable deeper insights into the dynamic nature of signaling networks.

  15. Extra-Large G Proteins Expand the Repertoire of Subunits in Arabidopsis Heterotrimeric G Protein Signaling.

    PubMed

    Chakravorty, David; Gookin, Timothy E; Milner, Matthew J; Yu, Yunqing; Assmann, Sarah M

    2015-09-01

    Heterotrimeric G proteins, consisting of Gα, Gβ, and Gγ subunits, are a conserved signal transduction mechanism in eukaryotes. However, G protein subunit numbers in diploid plant genomes are greatly reduced as compared with animals and do not correlate with the diversity of functions and phenotypes in which heterotrimeric G proteins have been implicated. In addition to GPA1, the sole canonical Arabidopsis (Arabidopsis thaliana) Gα subunit, Arabidopsis has three related proteins: the extra-large GTP-binding proteins XLG1, XLG2, and XLG3. We demonstrate that the XLGs can bind Gβγ dimers (AGB1 plus a Gγ subunit: AGG1, AGG2, or AGG3) with differing specificity in yeast (Saccharomyces cerevisiae) three-hybrid assays. Our in silico structural analysis shows that XLG3 aligns closely to the crystal structure of GPA1, and XLG3 also competes with GPA1 for Gβγ binding in yeast. We observed interaction of the XLGs with all three Gβγ dimers at the plasma membrane in planta by bimolecular fluorescence complementation. Bioinformatic and localization studies identified and confirmed nuclear localization signals in XLG2 and XLG3 and a nuclear export signal in XLG3, which may facilitate intracellular shuttling. We found that tunicamycin, salt, and glucose hypersensitivity and increased stomatal density are agb1-specific phenotypes that are not observed in gpa1 mutants but are recapitulated in xlg mutants. Thus, XLG-Gβγ heterotrimers provide additional signaling modalities for tuning plant G protein responses and increase the repertoire of G protein heterotrimer combinations from three to 12. The potential for signal partitioning and competition between the XLGs and GPA1 is a new paradigm for plant-specific cell signaling.

  16. Diversity in the origins of proteostasis networks- a driver for protein function in evolution

    PubMed Central

    Powers, Evan T.; Balch, William E.

    2013-01-01

    Although a protein’s primary sequence largely determines its function, proteins can adopt different folding states in response to changes in the environment, some of which may be deleterious to the organism. All organisms, including Bacteria, Archaea and Eukarya, have evolved a protein homeostasis network, or proteostasis network, that consists of chaperones and folding factors, degradation components, signalling pathways and specialized compartmentalized modules that manage protein folding in response to environmental stimuli and variation. Surveying the origins of proteostasis networks reveals that they have co-evolved with the proteome to regulate the physiological state of the cell, reflecting the unique stresses that different cells or organisms experience, and that they have a key role in driving evolution by closely managing the link between the phenotype and the genotype. PMID:23463216

  17. Rapid and profound rewiring of brain lipid signaling networks by acute diacylglycerol lipase inhibition.

    PubMed

    Ogasawara, Daisuke; Deng, Hui; Viader, Andreu; Baggelaar, Marc P; Breman, Arjen; den Dulk, Hans; van den Nieuwendijk, Adrianus M C H; van den Nieuwendijk, Adriann M C H; Soethoudt, Marjolein; van der Wel, Tom; Zhou, Juan; Overkleeft, Herman S; Sanchez-Alavez, Manuel; Mori, Simone; Mo, Simone; Nguyen, William; Conti, Bruno; Liu, Xiaojie; Chen, Yao; Liu, Qing-Song; Cravatt, Benjamin F; van der Stelt, Mario

    2016-01-01

    Diacylglycerol lipases (DAGLα and DAGLβ) convert diacylglycerol to the endocannabinoid 2-arachidonoylglycerol. Our understanding of DAGL function has been hindered by a lack of chemical probes that can perturb these enzymes in vivo. Here, we report a set of centrally active DAGL inhibitors and a structurally related control probe and their use, in combination with chemical proteomics and lipidomics, to determine the impact of acute DAGL blockade on brain lipid networks in mice. Within 2 h, DAGL inhibition produced a striking reorganization of bioactive lipids, including elevations in DAGs and reductions in endocannabinoids and eicosanoids. We also found that DAGLα is a short half-life protein, and the inactivation of DAGLs disrupts cannabinoid receptor-dependent synaptic plasticity and impairs neuroinflammatory responses, including lipopolysaccharide-induced anapyrexia. These findings illuminate the highly interconnected and dynamic nature of lipid signaling pathways in the brain and the central role that DAGL enzymes play in regulating this network.

  18. S-Glutathionylation and Redox Protein Signaling in Drug Addiction

    PubMed Central

    Womersley, Jacqueline S.; Uys, Joachim D.

    2016-01-01

    Drug addiction is a chronic relapsing disorder that comes at a high cost to individuals and society. Therefore understanding the mechanisms by which drugs exert their effects is of prime importance. Drugs of abuse increase the production of reactive oxygen and nitrogen species resulting in oxidative stress. This change in redox homeostasis increases the conjugation of glutathione to protein cysteine residues; a process called S-glutathionylation. Although traditionally regarded as a protective mechanism against irreversible protein oxidation, accumulated evidence suggests a more nuanced role for S-glutathionylation, namely as a mediator in redox-sensitive protein signaling. The reversible modification of protein thiols leading to alteration in function under different physiologic/pathologic conditions provides a mechanism whereby change in redox status can be translated into a functional response. As such, S-glutathionylation represents an understudied means of post-translational protein modification that may be important in the mechanisms underlying drug addiction. This review will discuss the evidence for S-glutathionylation as a redox-sensing mechanism and how this may be involved in the response to drug-induced oxidative stress. The function of S-glutathionylated proteins involved in neurotransmission, dendritic spine structure, and drug-induced behavioral outputs will be reviewed with specific reference to alcohol, cocaine, and heroin. PMID:26809999

  19. S-Glutathionylation and Redox Protein Signaling in Drug Addiction.

    PubMed

    Womersley, Jacqueline S; Uys, Joachim D

    2016-01-01

    Drug addiction is a chronic relapsing disorder that comes at a high cost to individuals and society. Therefore understanding the mechanisms by which drugs exert their effects is of prime importance. Drugs of abuse increase the production of reactive oxygen and nitrogen species resulting in oxidative stress. This change in redox homeostasis increases the conjugation of glutathione to protein cysteine residues; a process called S-glutathionylation. Although traditionally regarded as a protective mechanism against irreversible protein oxidation, accumulated evidence suggests a more nuanced role for S-glutathionylation, namely as a mediator in redox-sensitive protein signaling. The reversible modification of protein thiols leading to alteration in function under different physiologic/pathologic conditions provides a mechanism whereby change in redox status can be translated into a functional response. As such, S-glutathionylation represents an understudied means of post-translational protein modification that may be important in the mechanisms underlying drug addiction. This review will discuss the evidence for S-glutathionylation as a redox-sensing mechanism and how this may be involved in the response to drug-induced oxidative stress. The function of S-glutathionylated proteins involved in neurotransmission, dendritic spine structure, and drug-induced behavioral outputs will be reviewed with specific reference to alcohol, cocaine, and heroin. PMID:26809999

  20. Signals, Synapses, and Synthesis: How New Proteins Control Plasticity

    PubMed Central

    Zukin, R. Suzanne; Richter, Joel D.; Bagni, Claudia

    2009-01-01

    Localization of mRNAs to dendrites and local protein synthesis afford spatial and temporal regulation of gene expression and endow synapses with the capacity to autonomously alter their structure and function. Emerging evidence indicates that RNA binding proteins, ribosomes, translation factors and mRNAs encoding proteins critical to synaptic structure and function localize to neuronal processes. RNAs are transported into dendrites in a translationally quiescent state where they are activated by synaptic stimuli. Two RNA binding proteins that regulate dendritic RNA delivery and translational repression are cytoplasmic polyadenylation element binding protein and fragile X mental retardation protein (FMRP). The fragile X syndrome (FXS) is the most common known genetic cause of autism and is characterized by the loss of FMRP. Hallmark features of the FXS include dysregulation of spine morphogenesis and exaggerated metabotropic glutamate receptor-dependent long term depression, a cellular substrate of learning and memory. Current research focuses on mechanisms whereby mRNAs are transported in a translationally repressed state from soma to distal process and are activated at synaptic sites in response to synaptic signals. PMID:19838324

  1. Fluctuations in Mass-Action Equilibrium of Protein Binding Networks

    NASA Astrophysics Data System (ADS)

    Yan, Koon-Kiu; Walker, Dylan; Maslov, Sergei

    2008-12-01

    We consider two types of fluctuations in the mass-action equilibrium in protein binding networks. The first type is driven by slow changes in total concentrations of interacting proteins. The second type (spontaneous) is caused by quickly decaying thermodynamic deviations away from equilibrium. We investigate the effects of network connectivity on fluctuations by comparing them to scenarios in which the interacting pair is isolated from the network and analytically derives bounds on fluctuations. Collective effects are shown to sometimes lead to large amplification of spontaneous fluctuations. The strength of both types of fluctuations is positively correlated with the complex connectivity and negatively correlated with complex concentration. Our general findings are illustrated using a curated network of protein interactions and multiprotein complexes in baker’s yeast, with empirical protein concentrations.

  2. Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

    PubMed Central

    Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

    2016-01-01

    Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

  3. Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family.

    PubMed

    Uhart, Marina; Flores, Gabriel; Bustos, Diego M

    2016-05-19

    Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems.

  4. Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

    NASA Astrophysics Data System (ADS)

    Wei, Pei; Gu, Rentao; Ji, Yuefeng

    2014-06-01

    As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

  5. Hepatocellular carcinoma: targeting of oncogenic signaling networks in TRAIL resistant cancer cells.

    PubMed

    Fayyaz, Sundas; Yaylim, Ilhan; Turan, Saime; Kanwal, Sobia; Farooqi, Ammad Ahmad

    2014-10-01

    Apoptotic response in hepatocellular carcinoma (HCC) cells is impaired because of interconnectivity of proteins into complexes and signaling networks that are highly divergent in time and space. TNF-related apoptosis-inducing ligand (TRAIL) has emerged as an attractive anticancer agent reported to selectively induce apoptosis in cancer cells. Although diametrically opposed roles of TRAIL are reported both as an inducer of apoptosis and regulator of metastasis, overwhelmingly accumulating experimental evidence highlighting apoptosis inducing activity of TRAIL is directing TRAIL into clinical trials. Insights from TRAIL mediated signaling in HCC research are catalyzing new lines of study that should not only explain molecular mechanisms of disease but also highlight emerging paradigms in restoration of TRAIL mediated apoptosis in resistant cancer cells. It is becoming progressively more understandable that phytochemicals derived from edible plants have shown potential in modelling their interactions with their target proteins. Rapidly accumulating in vitro and in-vivo evidence indicates that phytonutrients have anticancer activity in rodent models of hepatocellular carcinoma. In this review we bring to limelight how phytonutrients restore apoptosis in hepatocellular carcinoma cells by rebalancing pro-apoptotic and anti-apoptotic proteins. Evidence has started to emerge, that reveals how phytonutrients target pharmacologically intractable proteins to suppress cancer. Target-based small-molecule discovery has entered into the mainstream research in the pharmaceutical industry and a better comprehension of the genetics of patients will be essential for identification of responders and non-responders. PMID:25037270

  6. Promotion of Bone Morphogenetic Protein Signaling by Tetraspanins and Glycosphingolipids

    PubMed Central

    Szymczak, Lindsey C.; Aydin, Taner; Yun, Sijung; Constas, Katharine; Schaeffer, Arielle; Ranjan, Sinthu; Kubba, Saad; Alam, Emad; McMahon, Devin E.; He, Jingpeng; Shwartz, Neta; Tian, Chenxi; Plavskin, Yevgeniy; Lindy, Amanda; Dad, Nimra Amir; Sheth, Sunny; Amin, Nirav M.; Zimmerman, Stephanie; Liu, Dennis; Schwarz, Erich M.; Smith, Harold; Krause, Michael W.; Liu, Jun

    2015-01-01

    Bone morphogenetic proteins (BMPs) belong to the transforming growth factor β (TGFβ) superfamily of secreted molecules. BMPs play essential roles in multiple developmental and homeostatic processes in metazoans. Malfunction of the BMP pathway can cause a variety of diseases in humans, including cancer, skeletal disorders and cardiovascular diseases. Identification of factors that ensure proper spatiotemporal control of BMP signaling is critical for understanding how this pathway is regulated. We have used a unique and sensitive genetic screen to identify the plasma membrane-localized tetraspanin TSP-21 as a key new factor in the C. elegans BMP-like “Sma/Mab” signaling pathway that controls body size and postembryonic M lineage development. We showed that TSP-21 acts in the signal-receiving cells and genetically functions at the ligand-receptor level. We further showed that TSP-21 can associate with itself and with two additional tetraspanins, TSP-12 and TSP-14, which also promote Sma/Mab signaling. TSP-12 and TSP-14 can also associate with SMA-6, the type I receptor of the Sma/Mab pathway. Finally, we found that glycosphingolipids, major components of the tetraspanin-enriched microdomains, are required for Sma/Mab signaling. Our findings suggest that the tetraspanin-enriched membrane microdomains are important for proper BMP signaling. As tetraspanins have emerged as diagnostic and prognostic markers for tumor progression, and TSP-21, TSP-12 and TSP-14 are all conserved in humans, we speculate that abnormal BMP signaling due to altered expression or function of certain tetraspanins may be a contributing factor to cancer development. PMID:25978409

  7. NMR analysis of a stress response metabolic signaling network.

    PubMed

    Zhang, Bo; Halouska, Steven; Schiaffo, Charles E; Sadykov, Marat R; Somerville, Greg A; Powers, Robert

    2011-08-01

    We previously hypothesized that Staphylococcus epidermidis senses a diverse set of environmental and nutritional factors associated with biofilm formation through a modulation in the activity of the tricarboxylic acid (TCA) cycle. Herein, we report our further investigation of the impact of additional environmental stress factors on TCA cycle activity and provide a detailed description of our NMR methodology. S. epidermidis wild-type strain 1457 was treated with stressors that are associated with biofilm formation, a sublethal dose of tetracycline, 5% NaCl, 2% glucose, and autoinducer-2 (AI-2). As controls and to integrate our current data with our previous study, 4% ethanol stress and iron-limitation were also used. Consistent with our prior observations, the effect of many environmental stress factors on the S. epidermidis metabolome was essentially identical to the effect of TCA cycle inactivation in the aconitase mutant strain 1457-acnA::tetM. A detailed quantitative analysis of metabolite concentration changes using 2D (1)H-(13)C HSQC and (1)H-(1)H TOCSY spectra identified a network of 37 metabolites uniformly affected by the stressors and TCA cycle inactivation. We postulate that the TCA cycle acts as the central pathway in a metabolic signaling network.

  8. Early-warning signals of topological collapse in interbank networks

    PubMed Central

    Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

    2013-01-01

    The financial crisis clearly illustrated the importance of characterizing the level of ‘systemic’ risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998–2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear – but unpredictable – signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies. PMID:24285089

  9. NMR analysis of a stress response metabolic signaling network.

    PubMed

    Zhang, Bo; Halouska, Steven; Schiaffo, Charles E; Sadykov, Marat R; Somerville, Greg A; Powers, Robert

    2011-08-01

    We previously hypothesized that Staphylococcus epidermidis senses a diverse set of environmental and nutritional factors associated with biofilm formation through a modulation in the activity of the tricarboxylic acid (TCA) cycle. Herein, we report our further investigation of the impact of additional environmental stress factors on TCA cycle activity and provide a detailed description of our NMR methodology. S. epidermidis wild-type strain 1457 was treated with stressors that are associated with biofilm formation, a sublethal dose of tetracycline, 5% NaCl, 2% glucose, and autoinducer-2 (AI-2). As controls and to integrate our current data with our previous study, 4% ethanol stress and iron-limitation were also used. Consistent with our prior observations, the effect of many environmental stress factors on the S. epidermidis metabolome was essentially identical to the effect of TCA cycle inactivation in the aconitase mutant strain 1457-acnA::tetM. A detailed quantitative analysis of metabolite concentration changes using 2D (1)H-(13)C HSQC and (1)H-(1)H TOCSY spectra identified a network of 37 metabolites uniformly affected by the stressors and TCA cycle inactivation. We postulate that the TCA cycle acts as the central pathway in a metabolic signaling network. PMID:21692534

  10. Pin-Align: A New Dynamic Programming Approach to Align Protein-Protein Interaction Networks

    PubMed Central

    2014-01-01

    To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein interaction networks from IntAct, DIP, and the Stanford Network Database and the results are compared with other well-known algorithms. It is shown that Pin-Align has higher sensitivity and specificity in terms of KEGG Ortholog groups. PMID:25435900

  11. Regulation of migration and invasion by Toll-like receptor-9 signaling network in prostate cancer

    PubMed Central

    Qiu, Jian-Ge; Zhang, Wen-Ji; Mei, Xiao-Long; Shi, Zhi; Di, Jin-Ming

    2015-01-01

    Toll-like receptors (TLRs) play an important role in tumorigenesis and progress of prostate cancer. However, the function and mechanism of Toll-like receptor-9 (TLR9) in prostate cancer is not totally understood. Here, we found that high expression of TLR9 was associated with a higher probability of lymph node metastasis and poor prognosis. Further in vitro functional study verified that silence of TLR9 inhibited migration and invasion of PC-3 cells, indicating expression of TLR9 involving in the migration and invasion of cancer cells. The data of microarray exhibited silence of TLR9 induced 205 genes with larger than 2-fold changes in expression levels, including 164 genes down-regulated and 41 genes up-regulated. Functional Gene Ontology (GO) processes annotation demonstrated that the top three scores of molecular and cellular functions were regulation of programmed cell death, regulation of locomotion and response to calcium ion. TLR9 signaling network analysis of the migration and invasion related genes identified several genes, like matrix metallopeptidase 2 (MMP2), matrix metallopeptidase 9 (MMP9), chemokine receptor 4 (CXCR4) and interleukin 8 (IL8), formed the core interaction network based on their known biological relationships. A few genes, such as odontogenic ameloblast-associated protein (ODAM), claudin 2 (CLDN2), gap junction protein beta 1 (GJB1) and Rho-associated coiled-coil containing protein kinase 1 pseudogene 1 (ROCK1P1), so far have not been found to interact with the other genes. This study provided the foundation to discover the new molecular mechanism in signaling networks of invasion and metastasis in prostate cancer. PMID:26087186

  12. Phospholipase D Controls Dictyostelium Development By Regulating G Protein Signaling

    PubMed Central

    Ray, Sibnath; Chen, Yi; Ayoung, Joanna; Hanna, Rachel; Brazill, Derrick

    2010-01-01

    Dictyostelium discoideum cells normally exist as individual amoebae, but will enter a period of multicellular development upon starvation. The initial stages of development involve the aggregation of individual cells, using cAMP as a chemoattractant. Chemotaxis is initiated when cAMP binds to its receptor, cAR1, and activates the associated G protein, Gα2βγ. However, chemotaxis will not occur unless there is a high density of starving cells present, as measured by high levels of the secreted quorum sensing molecule, CMF. We previously demonstrated that cells lacking PldB bypass the need for CMF and can aggregate at low cell density, whereas cells overexpressing pldB do not aggregate even at high cell density. Here, we found that PldB controlled both cAMP chemotaxis and cell sorting. PldB was also required by CMF to regulate G protein signaling. Specifically, CMF used PldB, to regulate the dissociation of Gα2 from Gβγ. Using fluorescence resonance energy transfer (FRET), we found that along with cAMP, CMF increased the dissociation of the G protein. In fact, CMF augmented the dissociation induced by cAMP. This augmentation was lost in cells lacking PldB. PldB appears to mediate the CMF signal through the production of phosphatidic acid, as exogenously added phosphatidic acid phenocopies overexpression of pldB. These results suggest that phospholipase D activity is required for CMF to alter the kinetics of cAMP-induced G protein signaling. PMID:20950684

  13. Network based approaches reveal clustering in protein point patterns

    NASA Astrophysics Data System (ADS)

    Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

    2014-03-01

    Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

  14. Induction of the unfolded protein response by constitutive G-protein signaling in rod photoreceptor cells.

    PubMed

    Wang, Tian; Chen, Jeannie

    2014-10-17

    Phototransduction is a G-protein signal transduction cascade that converts photon absorption to a change in current at the plasma membrane. Certain genetic mutations affecting the proteins in the phototransduction cascade cause blinding disorders in humans. Some of these mutations serve as a genetic source of "equivalent light" that activates the cascade, whereas other mutations lead to amplification of the light response. How constitutive phototransduction causes photoreceptor cell death is poorly understood. We showed that persistent G-protein signaling, which occurs in rod arrestin and rhodopsin kinase knock-out mice, caused a rapid and specific induction of the PERK pathway of the unfolded protein response. These changes were not observed in the cGMP-gated channel knock-out rods, an equivalent light condition that mimics light-stimulated channel closure. Thus transducin signaling, but not channel closure, triggers rapid cell death in light damage caused by constitutive phototransduction. Additionally, we show that in the albino light damage model cell death was not associated with increase in global protein ubiquitination or unfolded protein response induction. Taken together, these observations provide novel mechanistic insights into the cell death pathway caused by constitutive phototransduction and identify the unfolded protein response as a potential target for therapeutic intervention.

  15. Characterization of Protein-Protein Interfaces through a Protein Contact Network Approach.

    PubMed

    Di Paola, Luisa; Platania, Chiara Bianca Maria; Oliva, Gabriele; Setola, Roberto; Pascucci, Federica; Giuliani, Alessandro

    2015-01-01

    Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein-protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node's ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein-protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

  16. Spatial Organization in Protein Kinase A Signaling Emerged at the Base of Animal Evolution.

    PubMed

    Peng, Mao; Aye, Thin Thin; Snel, Berend; van Breukelen, Bas; Scholten, Arjen; Heck, Albert J R

    2015-07-01

    In phosphorylation-directed signaling, spatial and temporal control is organized by complex interaction networks that diligently direct kinases toward distinct substrates to fine-tune specificity. How these protein networks originate and evolve into complex regulatory machineries are among the most fascinating research questions in biology. Here, spatiotemporal signaling is investigated by tracing the evolutionary dynamics of each functional domain of cAMP-dependent protein kinase (PKA) and its diverse set of A-kinase anchoring proteins (AKAPs). Homologues of the catalytic (PKA-C) and regulatory (PKA-R) domains of the (PKA-R)2-(PKA-C)2 holoenzyme were found throughout evolution. Most variation was observed in the RIIa of PKA-R, crucial for dimerization and docking to AKAPs. The RIIa domain was not observed in all PKA-R homologues. In the fungi and distinct protist lineages, the RIIa domain emerges within PKA-R, but it displays large sequence variation. These organisms do not harbor homologues of AKAPs, suggesting that efficient docking to direct spatiotemporal PKA activity evolved in multicellular eukaryotes. To test this in silico hypothesis, we experimentally screened organisms with increasing complexity by cAMP-based chemical proteomics to reveal that the occurrence of PKA-AKAP interactions indeed coincided and expanded within vertebrates, suggesting a crucial role for AKAPs in the advent of metazoan multicellularity. PMID:26066639

  17. Signal Activation and Inactivation by the Gα Helical Domain: A Long-Neglected Partner in G Protein Signaling

    PubMed Central

    Dohlman, Henrik G.; Jones, Janice C.

    2013-01-01

    Heterotrimeric guanine nucleotide–binding proteins (G proteins) are positioned at the top of many signal transduction pathways. The G protein α subunit is composed of two domains, one that resembles Ras and another that is composed entirely of α helices. Historically, most attention has focused on the Ras-like domain, but emerging evidence reveals that the helical domain is an active participant in G protein signaling. PMID:22649098

  18. Prokaryotic ancestry of eukaryotic protein networks mediating innate immunity and apoptosis.

    PubMed

    Dunin-Horkawicz, Stanislaw; Kopec, Klaus O; Lupas, Andrei N

    2014-04-01

    Protein domains characteristic of eukaryotic innate immunity and apoptosis have many prokaryotic counterparts of unknown function. By reconstructing interactomes computationally, we found that bacterial proteins containing these domains are part of a network that also includes other domains not hitherto associated with immunity. This network is connected to the network of prokaryotic signal transduction proteins, such as histidine kinases and chemoreceptors. The network varies considerably in domain composition and degree of paralogy, even between strains of the same species, and its repetitive domains are often amplified recently, with individual repeats sharing up to 100% sequence identity. Both phenomena are evidence of considerable evolutionary pressure and thus compatible with a role in the "arms race" between host and pathogen. In order to investigate the relationship of this network to its eukaryotic counterparts, we performed a cluster analysis of organisms based on a census of its constituent domains across all fully sequenced genomes. We obtained a large central cluster of mainly unicellular organisms, from which multicellular organisms radiate out in two main directions. One is taken by multicellular bacteria, primarily cyanobacteria and actinomycetes, and plants form an extension of this direction, connected via the basal, unicellular cyanobacteria. The second main direction is taken by animals and fungi, which form separate branches with a common root in the α-proteobacteria of the central cluster. This analysis supports the notion that the innate immunity networks of eukaryotes originated from their endosymbionts and that increases in the complexity of these networks accompanied the emergence of multicellularity.

  19. Protein Tyrosine Phosphatases in Hypothalamic Insulin and Leptin Signaling.

    PubMed

    Zhang, Zhong-Yin; Dodd, Garron T; Tiganis, Tony

    2015-10-01

    The hypothalamus is critical to the coordination of energy balance and glucose homeostasis. It responds to peripheral factors, such as insulin and leptin, that convey to the brain the degree of adiposity and the metabolic status of the organism. The development of leptin and insulin resistance in hypothalamic neurons appears to have a key role in the exacerbation of diet-induced obesity. In rodents, this has been attributed partly to the increased expression of the tyrosine phosphatases Protein Tyrosine Phosphatase 1B (PTP1B) and T cell protein tyrosine phosphatase (TCPTP), which attenuate leptin and insulin signaling. Deficiencies in PTP1B and TCPTP in the brain, or specific neurons, promote insulin and leptin signaling and prevent diet-induced obesity, type 2 diabetes mellitus (T2DM), and fatty liver disease. Although targeting phosphatases and hypothalamic circuits remains challenging, recent advances indicate that such hurdles might be overcome. Here, we focus on the roles of PTP1B and TCPTP in insulin and leptin signaling and explore their potential as therapeutic targets.

  20. Trans-species learning of cellular signaling systems with bimodal deep belief networks

    PubMed Central

    Chen, Lujia; Cai, Chunhui; Chen, Vicky; Lu, Xinghua

    2015-01-01

    Motivation: Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli. Results: We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These ‘deep learning’ models include hierarchically organized latent variables capable of capturing the statistical structures in the observed proteomic data in a distributed fashion. The results show that the models significantly outperform two current state-of-the-art classification algorithms. Our study demonstrated the potential of using deep hierarchical models to simulate cellular signaling systems. Availability and implementation: The software is available at the following URL: http://pubreview.dbmi.pitt.edu/TransSpeciesDeepLearning/. The data are available through SBV IMPROVER website, https://www.sbvimprover.com/challenge-2/overview, upon publication of the report by the organizers. Contact: xinghua@pitt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25995230

  1. Crosstalk and Signaling Switches in Mitogen-Activated Protein Kinase Cascades

    PubMed Central

    Fey, Dirk; Croucher, David R.; Kolch, Walter; Kholodenko, Boris N.

    2012-01-01

    Mitogen-activated protein kinase (MAPK) cascades control cell fate decisions, such as proliferation, differentiation, and apoptosis by integrating and processing intra- and extracellular cues. However, similar MAPK kinetic profiles can be associated with opposing cellular decisions depending on cell type, signal strength, and dynamics. This implies that signaling by each individual MAPK cascade has to be considered in the context of the entire MAPK network. Here, we develop a dynamic model of feedback and crosstalk for the three major MAPK cascades; extracellular signal-regulated kinase (ERK), p38 mitogen-activated protein kinase (p38), c-Jun N-terminal kinase (JNK), and also include input from protein kinase B (AKT) signaling. Focusing on the bistable activation characteristics of the JNK pathway, this model explains how pathway crosstalk harmonizes different MAPK responses resulting in pivotal cell fate decisions. We show that JNK can switch from a transient to sustained activity due to multiple positive feedback loops. Once activated, positive feedback locks JNK in a highly active state and promotes cell death. The switch is modulated by the ERK, p38, and AKT pathways. ERK activation enhances the dual specificity phosphatase (DUSP) mediated dephosphorylation of JNK and shifts the threshold of the apoptotic switch to higher inputs. Activation of p38 restores the threshold by inhibiting ERK activity via the PP1 or PP2A phosphatases. Finally, AKT activation inhibits the JNK positive feedback, thus abrogating the apoptotic switch and allowing only proliferative signaling. Our model facilitates understanding of how cancerous deregulations disturb MAPK signal processing and provides explanations for certain drug resistances. We highlight a critical role of DUSP1 and DUSP2 expression patterns in facilitating the switching of JNK activity and show how oncogene induced ERK hyperactivity prevents the normal apoptotic switch explaining the failure of certain drugs to

  2. Protein kinase A signaling during bidirectional axenic differentiation in Leishmania.

    PubMed

    Bachmaier, Sabine; Witztum, Ronit; Tsigankov, Polina; Koren, Roni; Boshart, Michael; Zilberstein, Dan

    2016-02-01

    Parasitic protozoa of the genus Leishmania are obligatory intracellular parasites that cycle between the phagolysosome of mammalian macrophages, where they proliferate as intracellular amastigotes, and the midgut of female sand flies, where they proliferate as extracellular promastigotes. Shifting between the two environments induces signaling pathway-mediated developmental processes that enable adaptation to both host and vector. Developmentally regulated expression and phosphorylation of protein kinase A subunits in Leishmania and in Trypanosoma brucei point to an involvement of protein kinase A in parasite development. To assess this hypothesis in Leishmania donovani, we determined proteome-wide changes in phosphorylation of the conserved protein kinase A phosphorylation motifs RXXS and RXXT, using a phospho-specific antibody. Rapid dephosphorylation of these motifs was observed upon initiation of promastigote to amastigote differentiation in culture. No phosphorylated sites were detected in axenic amastigotes. To analyse the kinetics of (re)phosphorylation during axenic reverse differentiation from L. donovani amastigotes to promastigotes, we first established a map of this process with morphological and molecular markers. Upon initiation, the parasites rested for 6-12 h before proliferation of an asynchronous population resumed. After early changes in cell shape, the major changes in molecular marker expression and flagella biogenesis occurred between 24 and 33 h after initiation. RXXS/T re-phosphorylation and expression of the regulatory subunit PKAR1 correlated with promastigote maturation, indicating a promastigote-specific function of protein kinase A signaling. This is supported by the localization of PKAR1 to the flagellum, an organelle reduced to a remnant in amastigote forms. We conclude that a significant increase in protein kinase A-mediated phosphorylation is part of the ordered changes that characterise the amastigote to promastigote

  3. Functional features and protein network of human sperm-egg interaction.

    PubMed

    Sabetian, Soudabeh; Shamsir, Mohd Shahir; Abu Naser, Mohammed

    2014-12-01

    Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new

  4. Functional features and protein network of human sperm-egg interaction.

    PubMed

    Sabetian, Soudabeh; Shamsir, Mohd Shahir; Abu Naser, Mohammed

    2014-12-01

    Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new

  5. Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions.

    PubMed

    Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala; Peisajovich, Sergio G

    2016-01-01

    All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor-ligand pair can evolve through network-altering mutations independently of receptor-ligand binding, and suggest a potential role for such mutations in disease. PMID:27487915

  6. Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

    PubMed Central

    Di Roberto, Raphaël B.; Chang, Belinda; Trusina, Ala; Peisajovich, Sergio G.

    2016-01-01

    All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor–ligand pair can evolve through network-altering mutations independently of receptor–ligand binding, and suggest a potential role for such mutations in disease. PMID:27487915

  7. The involvement of the interleukin-1 Receptor-Associated Kinases (IRAKs) in cellular signaling networks controlling inflammation

    PubMed Central

    Ringwood, Lorna; Li, Liwu

    2008-01-01

    Innate immunity and inflammation plays a key role in host defense and wound healing. However, Excessive or altered inflammatory processes can contribute to severe and diverse human diseases including cardiovascular disease, diabetes and cancer. The interleukin-1 receptor associated kinases (IRAKs) are critically involved in the regulation of intra-cellular signaling networks controlling inflammation. Collective studies indicate that IRAKs are present in many cell types, and can mediate signals from various cell receptors including Toll-Like-Receptors (TLRs). Consequently, diverse downstream signaling processes can be elicited following the activation of various IRAKs. Given the critical and complex roles IRAK proteins play, it is not surprising that genetic variations in human IRAK genes have been found to be linked with various human inflammatory diseases. This review intends to summarize the recent advances regarding the regulations of various IRAK proteins and their cellular functions in mediating inflammatory signaling processes. PMID:18249132

  8. Regulation of amyloid precursor protein processing by serotonin signaling.

    PubMed

    Pimenova, Anna A; Thathiah, Amantha; De Strooper, Bart; Tesseur, Ina

    2014-01-01

    Proteolytic processing of the amyloid precursor protein (APP) by the β- and γ-secretases releases the amyloid-β peptide (Aβ), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The α-secretase cleaves APP in the Aβ peptide sequence to generate soluble APPα (sAPPα). Upregulation of α-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce Aβ production, amyloid plaque load and to improve cognitive impairment in transgenic mouse models of AD. Consequently, activation of 5-HT4 receptors following agonist stimulation is considered to be a therapeutic strategy for AD treatment; however, the signaling cascade involved in 5-HT4 receptor-stimulated proteolysis of APP remains to be determined. Here we used chemical and siRNA inhibition to identify the proteins which mediate 5-HT4d receptor-stimulated α-secretase activity in the SH-SY5Y human neuronal cell line. We show that G protein and Src dependent activation of phospholipase C are required for α-secretase activity, while, unexpectedly, adenylyl cyclase and cAMP are not involved. Further elucidation of the signaling pathway indicates that inositol triphosphate phosphorylation and casein kinase 2 activation is also a prerequisite for α-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced α-secretase activation.

  9. Regulation of Nuclear Localization of Signaling Proteins by Cytokinin

    SciTech Connect

    Kieber, J.J.

    2010-05-01

    Cytokinins are a class of mitogenic plant hormones that play an important role in most aspects of plant development, including shoot and root growth, vascular and photomorphogenic development and leaf senescence. A model for cytokinin perception and signaling has emerged that is similar to bacterial two-component phosphorelays. In this model, binding of cytokinin to the extracellular domain of the Arabidopsis histidine kinase (AHKs) receptors induces autophosphorylation within the intracellular histidine-kinase domain. The phosphoryl group is subsequently transferred to cytosolic Arabidopsis histidine phosphotransfer proteins (AHPs), which have been suggested to translocate to the nucleus in response to cytokinin treatment, where they then transfer the phosphoryl group to nuclear-localized response regulators (Type-A and Type-B ARRs). We examined the effects of cytokinin on AHP subcellular localization in Arabidopsis and, contrary to expectations, the AHPs maintained a constant nuclear/cytosolic distribution following cytokinin treatment. Furthermore, mutation of the conserved phosphoacceptor histidine residue of the AHP, as well as disruption of multiple cytokinin signaling elements, did not affect the subcellular localization of the AHP proteins. Finally, we present data indicating that AHPs maintain a nuclear/cytosolic distribution by balancing active transport into and out of the nucleus. Our findings suggest that the current models indicating relocalization of AHP protein into the nucleus in response to cytokinin are incorrect. Rather, AHPs actively maintain a consistent nuclear/cytosolic distribution regardless of the status of the cytokinin response pathway.

  10. Regulation of amyloid precursor protein processing by serotonin signaling.

    PubMed

    Pimenova, Anna A; Thathiah, Amantha; De Strooper, Bart; Tesseur, Ina

    2014-01-01

    Proteolytic processing of the amyloid precursor protein (APP) by the β- and γ-secretases releases the amyloid-β peptide (Aβ), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The α-secretase cleaves APP in the Aβ peptide sequence to generate soluble APPα (sAPPα). Upregulation of α-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce Aβ production, amyloid plaque load and to improve cognitive impairment in transgenic mouse models of AD. Consequently, activation of 5-HT4 receptors following agonist stimulation is considered to be a therapeutic strategy for AD treatment; however, the signaling cascade involved in 5-HT4 receptor-stimulated proteolysis of APP remains to be determined. Here we used chemical and siRNA inhibition to identify the proteins which mediate 5-HT4d receptor-stimulated α-secretase activity in the SH-SY5Y human neuronal cell line. We show that G protein and Src dependent activation of phospholipase C are required for α-secretase activity, while, unexpectedly, adenylyl cyclase and cAMP are not involved. Further elucidation of the signaling pathway indicates that inositol triphosphate phosphorylation and casein kinase 2 activation is also a prerequisite for α-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced α-secretase activation. PMID:24466315

  11. JNK Signaling: Regulation and Functions Based on Complex Protein-Protein Partnerships.

    PubMed

    Zeke, András; Misheva, Mariya; Reményi, Attila; Bogoyevitch, Marie A

    2016-09-01

    The c-Jun N-terminal kinases (JNKs), as members of the mitogen-activated protein kinase (MAPK) family, mediate eukaryotic cell responses to a wide range of abiotic and biotic stress insults. JNKs also regulate important physiological processes, including neuronal functions, immunological actions, and embryonic development, via their impact on gene expression, cytoskeletal protein dynamics, and cell death/survival pathways. Although the JNK pathway has been under study for >20 years, its complexity is still perplexing, with multiple protein partners of JNKs underlying the diversity of actions. Here we review the current knowledge of JNK structure and isoforms as well as the partnerships of JNKs with a range of intracellular proteins. Many of these proteins are direct substrates of the JNKs. We analyzed almost 100 of these target proteins in detail within a framework of their classification based on their regulation by JNKs. Examples of these JNK substrates include a diverse assortment of nuclear transcription factors (Jun, ATF2, Myc, Elk1), cytoplasmic proteins involved in cytoskeleton regulation (DCX, Tau, WDR62) or vesicular transport (JIP1, JIP3), cell membrane receptors (BMPR2), and mitochondrial proteins (Mcl1, Bim). In addition, because upstream signaling components impact JNK activity, we critically assessed the involvement of signaling scaffolds and the roles of feedback mechanisms in the JNK pathway. Despite a clarification of many regulatory events in JNK-dependent signaling during the past decade, many other structural and mechanistic insights are just beginning to be revealed. These advances open new opportunities to understand the role of JNK signaling in diverse physiological and pathophysiological states. PMID:27466283

  12. G-Protein/β-Arrestin-Linked Fluctuating Network of G-Protein-Coupled Receptors for Predicting Drug Efficacy and Bias Using Short-Term Molecular Dynamics Simulation

    PubMed Central

    Ichikawa, Osamu; Fujimoto, Kazushi; Yamada, Atsushi; Okazaki, Susumu; Yamazaki, Kazuto

    2016-01-01

    The efficacy and bias of signal transduction induced by a drug at a target protein are closely associated with the benefits and side effects of the drug. In particular, partial agonist activity and G-protein/β-arrestin-biased agonist activity for the G-protein-coupled receptor (GPCR) family, the family with the most target proteins of launched drugs, are key issues in drug discovery. However, designing GPCR drugs with appropriate efficacy and bias is challenging because the dynamic mechanism of signal transduction induced by ligand—receptor interactions is complicated. Here, we identified the G-protein/β-arrestin-linked fluctuating network, which initiates large-scale conformational changes, using sub-microsecond molecular dynamics (MD) simulations of the β2-adrenergic receptor (β2AR) with a diverse collection of ligands and correlation analysis of their G protein/β-arrestin efficacy. The G-protein-linked fluctuating network extends from the ligand-binding site to the G-protein-binding site through the connector region, and the β-arrestin-linked fluctuating network consists of the NPxxY motif and adjacent regions. We confirmed that the averaged values of fluctuation in the fluctuating network detected are good quantitative indexes for explaining G protein/β-arrestin efficacy. These results indicate that short-term MD simulation is a practical method to predict the efficacy and bias of any compound for GPCRs. PMID:27187591

  13. Programming Molecular Association and Viscoelastic Behavior in Protein Networks.

    PubMed

    Dooling, Lawrence J; Buck, Maren E; Zhang, Wen-Bin; Tirrell, David A

    2016-06-01

    A set of recombinant artificial proteins that can be cross-linked, by either covalent bonds or association of helical domains or both, is described. The designed proteins can be used to construct molecular networks in which the mechanism of crosslinking determines the time-dependent responses to mechanical deformation. PMID:27061171

  14. Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

    PubMed

    Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

    2015-01-01

    Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights. PMID:26020784

  15. Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

    PubMed

    Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

    2015-01-01

    Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

  16. GPCR-G Protein-β-Arrestin Super-Complex Mediates Sustained G Protein Signaling.

    PubMed

    Thomsen, Alex R B; Plouffe, Bianca; Cahill, Thomas J; Shukla, Arun K; Tarrasch, Jeffrey T; Dosey, Annie M; Kahsai, Alem W; Strachan, Ryan T; Pani, Biswaranjan; Mahoney, Jacob P; Huang, Liyin; Breton, Billy; Heydenreich, Franziska M; Sunahara, Roger K; Skiniotis, Georgios; Bouvier, Michel; Lefkowitz, Robert J

    2016-08-11

    Classically, G protein-coupled receptor (GPCR) stimulation promotes G protein signaling at the plasma membrane, followed by rapid β-arrestin-mediated desensitization and receptor internalization into endosomes. However, it has been demonstrated that some GPCRs activate G proteins from within internalized cellular compartments, resulting in sustained signaling. We have used a variety of biochemical, biophysical, and cell-based methods to demonstrate the existence, functionality, and architecture of internalized receptor complexes composed of a single GPCR, β-arrestin, and G protein. These super-complexes or "megaplexes" more readily form at receptors that interact strongly with β-arrestins via a C-terminal tail containing clusters of serine/threonine phosphorylation sites. Single-particle electron microscopy analysis of negative-stained purified megaplexes reveals that a single receptor simultaneously binds through its core region with G protein and through its phosphorylated C-terminal tail with β-arrestin. The formation of such megaplexes provides a potential physical basis for the newly appreciated sustained G protein signaling from internalized GPCRs. PMID:27499021

  17. GPCR-G Protein-β-Arrestin Super-Complex Mediates Sustained G Protein Signaling.

    PubMed

    Thomsen, Alex R B; Plouffe, Bianca; Cahill, Thomas J; Shukla, Arun K; Tarrasch, Jeffrey T; Dosey, Annie M; Kahsai, Alem W; Strachan, Ryan T; Pani, Biswaranjan; Mahoney, Jacob P; Huang, Liyin; Breton, Billy; Heydenreich, Franziska M; Sunahara, Roger K; Skiniotis, Georgios; Bouvier, Michel; Lefkowitz, Robert J

    2016-08-11

    Classically, G protein-coupled receptor (GPCR) stimulation promotes G protein signaling at the plasma membrane, followed by rapid β-arrestin-mediated desensitization and receptor internalization into endosomes. However, it has been demonstrated that some GPCRs activate G proteins from within internalized cellular compartments, resulting in sustained signaling. We have used a variety of biochemical, biophysical, and cell-based methods to demonstrate the existence, functionality, and architecture of internalized receptor complexes composed of a single GPCR, β-arrestin, and G protein. These super-complexes or "megaplexes" more readily form at receptors that interact strongly with β-arrestins via a C-terminal tail containing clusters of serine/threonine phosphorylation sites. Single-particle electron microscopy analysis of negative-stained purified megaplexes reveals that a single receptor simultaneously binds through its core region with G protein and through its phosphorylated C-terminal tail with β-arrestin. The formation of such megaplexes provides a potential physical basis for the newly appreciated sustained G protein signaling from internalized GPCRs.

  18. Testicular hyperthermia induces Unfolded Protein Response signaling activation in spermatocyte.

    PubMed

    Kim, Jung-Hak; Park, Sun-Ji; Kim, Tae-Shin; Park, Hyo-Jin; Park, Junghyung; Kim, Bo Kyung; Kim, Gyeong-Ryul; Kim, Jin-Man; Huang, Song Mei; Chae, Jung-Il; Park, Choon-Keun; Lee, Dong-Seok

    2013-05-17

    The testes of most mammals are sensitive to temperature. To survive and adapt under conditions that promote endoplasmic reticulum (ER) stress such as heat shock, cells have a self-protective mechanism against ER stress that has been termed the "Unfolded Protein Response" (UPR). However, the cellular and molecular events underlying spermatogenesis with testicular hyperthermia involved in the UPR signaling pathway under ER stress remain poorly understood. In the present study, we verified that UPR signaling via phospho-eIF2α/ATF4/GADD34, p90ATF6, and phospho-IRE1α/XBP-1 is activated with testicular hyperthermia (43 °C, 15 min/day) and induced ER stress-mediated apoptosis associated with CHOP, phospho-JNK, and caspase-3 after repetitive periods of hyperthermia. Levels of phospho-eIF2α protein of mouse spermatocytes in the testis were rapidly increased by one cycle of testicular hyperthermia. ATF4/GADD34 and p90ATF6 expression gradually increased and decreased, respectively, with repetitive cycles of hyperthermia. Spliced XBP1 mRNA as a marker of IRE1 activity was increased after one, three cycles of hyperthermia and decreased by five cycles of hyperthermia. Although the levels of anti-apoptotic phospho-JNK (p54) were gradually decreased after three cycles of hyperthermia, CHOP expression was rapidly increased. After five cycles of testicular hyperthermia, the levels of cleaved caspase-3 and TUNEL-positive apoptotic spermatocytes cells were significantly increased. Our data demonstrated that testicular hyperthermia induces UPR signaling and repetitive cycles of hyperthermia lead to apoptosis of spermatocytes in mouse testis. These results suggest a link between the UPR signaling pathway and testicular hyperthermia.

  19. P-glycoprotein (ABCB1) inhibited network of mitochondrion transport along microtubule and BMP signal-induced cell shape in chimpanzee left cerebrum by systems-theoretical analysis.

    PubMed

    Lin, Hong; Wang, Lin; Jiang, Minghu; Huang, Juxiang; Qi, Lianxiu

    2012-10-01

    We constructed the significant low-expression P-glycoprotein (ABCB1) inhibited transport and signal network in chimpanzee compared with high-expression (fold change ≥2) the human left cerebrum in GEO data set, by using integration of gene regulatory activated and inhibited network inference method with gene ontology (GO) analysis. Our result showed that ABCB1 transport and signal upstream network RAB2A inhibited ABCB1, and downstream ABCB1-inhibited SMAD1_2, NCK2, SLC25A46, GDF10, RASGRP1, EGFR, LRPPRC, RASSF2, RASA4, CA2, CBLB, UBR5, SLC25A16, ITGB3BP, DDIT4, PDPN, RAB2A in chimpanzee left cerebrum. We obtained that the different biological processes of ABCB1 inhibited transport and signal network repressed carbon dioxide transport, ER to Golgi vesicle-mediated transport, folic acid transport, mitochondrion transport along microtubule, water transport, BMP signaling pathway, Ras protein signal transduction, transforming growth factor beta receptor signaling pathway in chimpanzee compared with the inhibited network of the human left cerebrum, as a result of inducing inhibition of mitochondrion transport along microtubule and BMP signal-induced cell shape in chimpanzee left cerebrum. Our hypothesis was verified by the same and different biological processes of ABCB1 inhibited transport and signal network of chimpanzee compared with the corresponding activated network of chimpanzee and the human left cerebrum, respectively.

  20. The brassinosteroid signaling pathway-new key players and interconnections with other signaling networks crucial for plant development and stress tolerance.

    PubMed

    Gruszka, Damian

    2013-01-01

    Brassinosteroids (BRs) are a class of steroid hormones regulating a wide range of physiological processes during the plant life cycle from seed development to the modulation of flowering and senescence. The last decades, and recent years in particular, have witnessed a significant advance in the elucidation of the molecular mechanisms of BR signaling from perception by the transmembrane receptor complex to the regulation of transcription factors influencing expression of the target genes. Application of the new approaches shed light on the molecular functions of the key players regulating the BR signaling cascade and allowed identification of new factors. Recent studies clearly indicated that some of the components of BR signaling pathway act as multifunctional proteins involved in other signaling networks regulating diverse physiological processes, such as photomorphogenesis, cell death control, stomatal development, flowering, plant immunity to pathogens and metabolic responses to stress conditions, including salinity. Regulation of some of these processes is mediated through a crosstalk between BR signalosome and the signaling cascades of other hormones, including auxin, abscisic acid, ethylene and salicylic acid. Unravelling the complicated mechanisms of BR signaling and its interconnections with other molecular networks may be of great importance for future practical applications in agriculture. PMID:23615468

  1. A Systems Level Analysis of Vasopressin-mediated Signaling Networks in Kidney Distal Convoluted Tubule Cells

    PubMed Central

    Cheng, Lei; Wu, Qi; Kortenoeven, Marleen L. A.; Pisitkun, Trairak; Fenton, Robert A.

    2015-01-01

    The kidney distal convoluted tubule (DCT) plays an essential role in maintaining body sodium balance and blood pressure. The major sodium reabsorption pathway in the DCT is the thiazide-sensitive NaCl cotransporter (NCC), whose functions can be modulated by the hormone vasopressin (VP) acting via uncharacterized signaling cascades. Here we use a systems biology approach centered on stable isotope labeling by amino acids in cell culture (SILAC) based quantitative phosphoproteomics of cultured mouse DCT cells to map global changes in protein phosphorylation upon acute treatment with a VP type II receptor agonist 1-desamino-8-D-arginine vasopressin (dDAVP). 6330 unique proteins, containing 12333 different phosphorylation sites were identified. 185 sites were altered in abundance following dDAVP. Basophilic motifs were preferential targets for upregulated sites upon dDAVP stimulation, whereas proline-directed motifs were prominent for downregulated sites. Kinase prediction indicated that dDAVP increased AGC and CAMK kinase families’ activities and decreased activity of CDK and MAPK families. Network analysis implicated phosphatidylinositol-4,5-bisphosphate 3-kinase or CAMKK dependent pathways in VP-mediated signaling; pharmacological inhibition of which significantly reduced dDAVP induced increases in phosphorylated NCC at an activating site. In conclusion, this study identifies unique VP signaling cascades in DCT cells that may be important for regulating blood pressure. PMID:26239621

  2. Reconstruction of Signaling Networks Regulating Fungal Morphogenesis by Transcriptomics▿ †

    PubMed Central

    Meyer, Vera; Arentshorst, Mark; Flitter, Simon J.; Nitsche, Benjamin M.; Kwon, Min Jin; Reynaga-Peña, Cristina G.; Bartnicki-Garcia, Salomon; van den Hondel, Cees A. M. J. J.; Ram, Arthur F. J.

    2009-01-01

    Coordinated control of hyphal elongation and branching is essential for sustaining mycelial growth of filamentous fungi. In order to study the molecular machinery ensuring polarity control in the industrial fungus Aspergillus niger, we took advantage of the temperature-sensitive (ts) apical-branching ramosa-1 mutant. We show here that this strain serves as an excellent model system to study critical steps of polar growth control during mycelial development and report for the first time a transcriptomic fingerprint of apical branching for a filamentous fungus. This fingerprint indicates that several signal transduction pathways, including TORC2, phospholipid, calcium, and cell wall integrity signaling, concertedly act to control apical branching. We furthermore identified the genetic locus affected in the ramosa-1 mutant by complementation of the ts phenotype. Sequence analyses demonstrated that a single amino acid exchange in the RmsA protein is responsible for induced apical branching of the ramosa-1 mutant. Deletion experiments showed that the corresponding rmsA gene is essential for the growth of A. niger, and complementation analyses with Saccharomyces cerevisiae evidenced that RmsA serves as a functional equivalent of the TORC2 component Avo1p. TORC2 signaling is required for actin polarization and cell wall integrity in S. cerevisiae. Congruently, our microscopic investigations showed that polarized actin organization and chitin deposition are disturbed in the ramosa-1 mutant. The integration of the transcriptomic, genetic, and phenotypic data obtained in this study allowed us to reconstruct a model for cellular events involved in apical branching. PMID:19749177

  3. Stimulus-Dependent Inhibitor of Apoptosis Protein Expression Prolongs the Duration of B Cell Signalling

    PubMed Central

    Shinohara, Hisaaki; Inoue, Kentaro; Yumoto, Noriko; Nagashima, Takeshi; Okada-Hatakeyama, Mariko

    2016-01-01

    Different dynamic behaviours of signalling activity can induce distinct biological responses in a variety of cells. However, the molecular mechanisms that determine the dynamics of kinase activities in immune cells are not well understood. In this study, we showed that the duration of both IκB kinase (IKK) and extracellular signal-regulated kinase (ERK) activities in B cell receptor (BCR)- and CD40-signalling pathways in B cells were regulated by transcriptional feedback loops. We conducted a time-course transcriptome analysis after BCR or CD40 stimulation and identified the following four candidate genes as feedback regulators for IKK and ERK: inhibitor of apoptosis protein (IAP), TNF alpha-induced protein 3, dual-specificity phosphatase 5, and sprouty homolog 2. Quantitative experiments and mathematical modelling suggested that IAP inhibition shortened the duration of IKK and ERK activity following both BCR and CD40 pathway stimulation, indicating a positive role for IAP in B cell signalling. Furthermore, transient kinase activities induced by IAP blockage reduced the levels of delayed expression genes. Together, our findings suggest that IKK and ERK activity durations can be fine-tuned by the coordinated regulation of positive and negative transcriptional feedback and that these network properties determine the biological output of B cells. PMID:27277891

  4. Dynamic rheology of food protein networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Small amplitude oscillatory shear analyses (SAOSA) of samples containing protein are useful for determining the nature of the protein matrix without damaging it. The Dairy Processing and Products Research Unit of the Agricultural Research Service, USDA has pioneered the use of SAOSA in understandin...

  5. Dynamic rheology of food protein networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Small amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. Elastic modulus, viscous modulus, and loss tangent (the ratio of viscous modulus to elastic modulus) give information on the strength of the netw...

  6. Protein-serine/threonine/tyrosine kinases in bacterial signaling and regulation.

    PubMed

    Cousin, Charlotte; Derouiche, Abderahmane; Shi, Lei; Pagot, Yves; Poncet, Sandrine; Mijakovic, Ivan

    2013-09-01

    In this review, we address some recent developments in the field of bacterial protein phosphorylation, focusing specifically on serine/threonine and tyrosine kinases. We present an overview of recent studies outlining the scope of physiological processes that are regulated by phosphorylation, ranging from cell cycle, growth, cell morphology, to metabolism, developmental phenomena, and virulence. Specific emphasis is placed on Mycobacterium tuberculosis as a showcase organism for serine/threonine kinases, and Bacillus subtilis to illustrate the importance of protein phosphorylation in developmental processes. We argue that bacterial serine/threonine and tyrosine kinases have a distinctive feature of phosphorylating multiple substrates and might thus represent integration nodes in the signaling network. Some open questions regarding the evolutionary benefits of relaxed substrate selectivity of these kinases are treated, as well as the notion of nonfunctional 'background' phosphorylation of cellular proteins. We also argue that phosphorylation events for which an immediate regulatory effect is not clearly established should not be dismissed as unimportant, as they may have a role in cross-talk with other post-translational modifications. Finally, recently developed methods for studying protein phosphorylation networks in bacteria are briefly discussed.

  7. Desired Alteration of Protein Affinities: Competitive Selection of Protein Variants Using Yeast Signal Transduction Machinery

    PubMed Central

    Kaishima, Misato; Fukuda, Nobuo; Ishii, Jun; Kondo, Akihiko

    2014-01-01

    Molecules that can control protein-protein interactions (PPIs) have recently drawn attention as new drug pipeline compounds. Here, we report a technique to screen desirable affinity-altered (affinity-enhanced and affinity-attenuated) protein variants. We previously constructed a screening system based on a target protein fused to a mutated G-protein γ subunit (Gγcyto) lacking membrane localization ability. This ability, required for signal transmission, is restored by recruiting Gγcyto into the membrane only when the target protein interacts with an artificially membrane-anchored candidate protein, thereby allowing interacting partners (Gγ recruitment system) to be searched and identified. In the present study, the Gγ recruitment system was altered by integrating the cytosolic expression of a third protein as a competitor to set a desirable affinity threshold. This enabled the reliable selection of both affinity-enhanced and affinity-attenuated protein variants. The presented approach may facilitate the development of therapeutic proteins that allow the control of PPIs. PMID:25244640

  8. Crk adaptor proteins act as key signaling integrators for breast tumorigenesis

    PubMed Central

    2012-01-01

    associated with diminished cell proliferation and was rescued by expression of non-shRNA targeted CrkI/II. Perturbations in tumor progression correlated with altered integrin signaling, including decreased cell spreading, diminished p130Cas phosphorylation, and Cdc42 activation. Conclusions These data highlight the physiological importance of Crk proteins in regulating growth of aggressive basal breast cancer cells and identify Crk-dependent signaling networks as promising therapeutic targets. PMID:22569336

  9. Distinct G protein-coupled receptor recycling pathways allow spatial control of downstream G protein signaling.

    PubMed

    Bowman, Shanna Lynn; Shiwarski, Daniel John; Puthenveedu, Manojkumar A

    2016-09-26

    G protein-coupled receptors (GPCRs) are recycled via a sequence-dependent pathway that is spatially and biochemically distinct from bulk recycling. Why there are two distinct recycling pathways from the endosome is a fundamental question in cell biology. In this study, we show that the separation of these two pathways is essential for normal spatial encoding of GPCR signaling. The prototypical β-2 adrenergic receptor (B2AR) activates Gα stimulatory protein (Gαs) on the endosome exclusively in sequence-dependent recycling tubules marked by actin/sorting nexin/retromer tubular (ASRT) microdomains. B2AR was detected in an active conformation in bulk recycling tubules, but was unable to activate Gαs. Protein kinase A phosphorylation of B2AR increases the fraction of receptors localized to ASRT domains and biases the downstream transcriptional effects of B2AR to genes controlled by endosomal signals. Our results identify the physiological relevance of separating GPCR recycling from bulk recycling and suggest a mechanism to tune downstream responses of GPCR signaling by manipulating the spatial origin of G protein signaling. PMID:27646272

  10. Distinct G protein-coupled receptor recycling pathways allow spatial control of downstream G protein signaling.

    PubMed

    Bowman, Shanna Lynn; Shiwarski, Daniel John; Puthenveedu, Manojkumar A

    2016-09-26

    G protein-coupled receptors (GPCRs) are recycled via a sequence-dependent pathway that is spatially and biochemically distinct from bulk recycling. Why there are two distinct recycling pathways from the endosome is a fundamental question in cell biology. In this study, we show that the separation of these two pathways is essential for normal spatial encoding of GPCR signaling. The prototypical β-2 adrenergic receptor (B2AR) activates Gα stimulatory protein (Gαs) on the endosome exclusively in sequence-dependent recycling tubules marked by actin/sorting nexin/retromer tubular (ASRT) microdomains. B2AR was detected in an active conformation in bulk recycling tubules, but was unable to activate Gαs. Protein kinase A phosphorylation of B2AR increases the fraction of receptors localized to ASRT domains and biases the downstream transcriptional effects of B2AR to genes controlled by endosomal signals. Our results identify the physiological relevance of separating GPCR recycling from bulk recycling and suggest a mechanism to tune downstream responses of GPCR signaling by manipulating the spatial origin of G protein signaling.

  11. Construction of protein interaction network involved in lung adenocarcinomas using a novel algorithm

    PubMed Central

    Chen, Juan; Yang, Hai-Tao; Li, Zhu; Xu, Ning; Yu, Bo; Xu, Jun-Ping; Zhao, Pei-Ge; Wang, Yan; Zhang, Xiu-Juan; Lin, Dian-Jie

    2016-01-01

    Studies that only assess differentially-expressed (DE) genes do not contain the information required to investigate the mechanisms of diseases. A complete knowledge of all the direct and indirect interactions between proteins may act as a significant benchmark in the process of forming a comprehensive description of cellular mechanisms and functions. The results of protein interaction network studies are often inconsistent and are based on various methods. In the present study, a combined network was constructed using selected gene pairs, following the conversion and combination of the scores of gene pairs that were obtained across multiple approaches by a novel algorithm. Samples from patients with and without lung adenocarcinoma were compared, and the RankProd package was used to identify DE genes. The empirical Bayesian (EB) meta-analysis approach, the search tool for the retrieval of interacting genes/proteins database (STRING), the weighted gene coexpression network analysis (WGCNA) package and the differentially-coexpressed genes and links package (DCGL) were used for network construction. A combined network was also constructed with a novel rank-based algorithm using a combined score. The topological features of the 5 networks were analyzed and compared. A total of 941 DE genes were screened. The topological analysis indicated that the gene interaction network constructed using the WGCNA method was more likely to produce a small-world property, which has a small average shortest path length and a large clustering coefficient, whereas the combined network was confirmed to be a scale-free network. Gene pairs that were identified using the novel combined method were mostly enriched in the cell cycle and p53 signaling pathway. The present study provided a novel perspective to the network-based analysis. Each method has advantages and disadvantages. Compared with single methods, the combined algorithm used in the present study may provide a novel method to

  12. Cherry Valley Ducks Mitochondrial Antiviral-Signaling Protein-Mediated Signaling Pathway and Antiviral Activity Research

    PubMed Central

    Li, Ning; Hong, Tianqi; Li, Rong; Wang, Yao; Guo, Mengjiao; Cao, Zongxi; Cai, Yumei; Liu, Sidang; Chai, Tongjie; Wei, Liangmeng

    2016-01-01

    Mitochondrial antiviral-signaling protein (MAVS), an adaptor protein of retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs)-mediated signal pathway, is involved in innate immunity. In this study, Cherry Valley duck MAVS (duMAVS) was cloned from the spleen and analyzed. duMAVS was determined to have a caspase activation and recruitment domain at N-terminal, followed by a proline-rich domain and a transmembrane domain at C-terminal. Quantitative real-time PCR indicated that duMAVS was expressed in all tissues tested across a broad expression spectrum. The expression of duMAVS was significantly upregulated after infection with duck Tembusu virus (DTMUV). Overexpression of duMAVS could drive the activation of interferon (IFN)-β, nuclear factor-κB, interferon regulatory factor 7, and many downstream factors (such as Mx, PKR, OAS, and IL-8) in duck embryo fibroblast cells. What is more, RNA interference further confirmed that duMAVS was an important adaptor for IFN-β activation. The antiviral assay showed that duMAVS could suppress the various viral replications (DTMUV, novel reovirus, and duck plague virus) at early stages of infection. Overall, these results showed that the main signal pathway mediated by duMAVS and it had a broad-spectrum antiviral ability. This research will be helpful to better understanding the innate immune system of ducks. PMID:27708647

  13. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    PubMed

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. PMID:25787689

  14. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    PubMed

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species.

  15. Interaction of silver nanoparticles with proteins: a characteristic protein concentration dependent profile of SPR signal.

    PubMed

    Banerjee, Victor; Das, K P

    2013-11-01

    Silver nanoparticles are finding increasing applications in biological systems, for example as antimicrobial agents and potential candidates for control drug release systems. In all such applications, silver nanoparticles interact with proteins and other biomolecules. Hence, the study of such interactions is of considerable importance. While BSA has been extensively used as a model protein for the study of interaction with the silver nanoparticles, studies using other proteins are rather limited. The interaction of silver nanoparticles with light leads to collective oscillation of the conducting electrons giving rise to surface plasmon resonance (SPR). Here, we have studied the protein concentration dependence of the SPR band profiles for a number of proteins. We found that for all the proteins, with increase in concentration, the SPR band intensity initially decreased, reaching minima and then increased again leading to a characteristic "dip and rise" pattern. Minimum point of the pattern appeared to be related to the isoelectric point of the proteins. Detailed dynamic light scattering and transmission electron microscopy studies revealed that the consistency of SPR profile was dependent on the average particle size and state of association of the silver nanoparticles with the change in the protein concentration. Fluorescence spectroscopic studies showed the binding constants of the proteins with the silver nanoparticles were in the nano molar range with more than one nanoparticle binding to protein molecule. Structural studies demonstrate that protein retains its native-like structure on the nanoparticle surface unless the molar ratio of silver nanoparticles to protein exceeds 10. Our study reveals that nature of the protein concentration dependent profile of SPR signal is a general phenomena and mostly independent of the size and structure of the proteins.

  16. An analysis pipeline for the inference of protein-protein interaction networks

    SciTech Connect

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

    2009-12-01

    An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

  17. p53 as the main traffic controller of the cell signaling network.

    PubMed

    Sebastian, Sinto; Azzariti, Amalia; Silvestris, Nicola; Porcelli, Letizia; Russo, Antonio; Paradiso, Angelo

    2010-01-01

    Among different pathological conditions that affect human beings, cancer has received a great deal of attention primarily because it leads to significant morbidity and mortality. This is essentially due to increasing world-wide incidence of this disease and the inability to discover the cause and molecular mechanisms by which normal human cells acquire the characteristics that define cancer cells. Since the discovery of p53 over a quarter of a century ago, it is now recognized that virtually all cell fate pathways of live cells and the decision to die are under the control of p53. Such extensive involvement indicates that p53 protein is acting as a major traffic controller in the cell signaling network. In cancer cells, many cell signaling pathways of normal human cells are rerouted towards immortalization and this is accomplished by the corruption of the main controllers of cell signaling pathways such as p53. This review highlights how p53 signaling activity is altered in cancer cells so that cells acquire the hallmarks of cancer including deregulated infinite self replicative potential.

  18. Protein S-glutathionlyation links energy metabolism to redox signaling in mitochondria

    PubMed Central

    Mailloux, Ryan J.; Treberg, Jason R.

    2015-01-01

    At its core mitochondrial function relies on redox reactions. Electrons stripped from nutrients are used to form NADH and NADPH, electron carriers that are similar in structure but support different functions. NADH supports ATP production but also generates reactive oxygen species (ROS), superoxide (O2·-) and hydrogen peroxide (H2O2). NADH-driven ROS production is counterbalanced by NADPH which maintains antioxidants in an active state. Mitochondria rely on a redox buffering network composed of reduced glutathione (GSH) and peroxiredoxins (Prx) to quench ROS generated by nutrient metabolism. As H2O2 is quenched, NADPH is expended to reactivate antioxidant networks and reset the redox environment. Thus, the mitochondrial redox environment is in a constant state of flux reflecting changes in nutrient and ROS metabolism. Changes in redox environment can modulate protein function through oxidation of protein cysteine thiols. Typically cysteine oxidation is considered to be mediated by H2O2 which oxidizes protein thiols (SH) forming sulfenic acid (SOH). However, problems begin to emerge when one critically evaluates the regulatory function of SOH. Indeed SOH formation is slow, non-specific, and once formed SOH reacts rapidly with a variety of molecules. By contrast, protein S-glutathionylation (PGlu) reactions involve the conjugation and removal of glutathione moieties from modifiable cysteine residues. PGlu reactions are driven by fluctuations in the availability of GSH and oxidized glutathione (GSSG) and thus should be exquisitely sensitive to changes ROS flux due to shifts in the glutathione pool in response to varying H2O2 availability. Here, we propose that energy metabolism-linked redox signals originating from mitochondria are mediated indirectly by H2O2 through the GSH redox buffering network in and outside mitochondria. This proposal is based on several observations that have shown that unlike other redox modifications PGlu reactions fulfill the requisite

  19. Protein S-glutathionlyation links energy metabolism to redox signaling in mitochondria.

    PubMed

    Mailloux, Ryan J; Treberg, Jason R

    2016-08-01

    At its core mitochondrial function relies on redox reactions. Electrons stripped from nutrients are used to form NADH and NADPH, electron carriers that are similar in structure but support different functions. NADH supports ATP production but also generates reactive oxygen species (ROS), superoxide (O2(·-)) and hydrogen peroxide (H2O2). NADH-driven ROS production is counterbalanced by NADPH which maintains antioxidants in an active state. Mitochondria rely on a redox buffering network composed of reduced glutathione (GSH) and peroxiredoxins (Prx) to quench ROS generated by nutrient metabolism. As H2O2 is quenched, NADPH is expended to reactivate antioxidant networks and reset the redox environment. Thus, the mitochondrial redox environment is in a constant state of flux reflecting changes in nutrient and ROS metabolism. Changes in redox environment can modulate protein function through oxidation of protein cysteine thiols. Typically cysteine oxidation is considered to be mediated by H2O2 which oxidizes protein thiols (SH) forming sulfenic acid (SOH). However, problems begin to emerge when one critically evaluates the regulatory function of SOH. Indeed SOH formation is slow, non-specific, and once formed SOH reacts rapidly with a variety of molecules. By contrast, protein S-glutathionylation (PGlu) reactions involve the conjugation and removal of glutathione moieties from modifiable cysteine residues. PGlu reactions are driven by fluctuations in the availability of GSH and oxidized glutathione (GSSG) and thus should be exquisitely sensitive to changes ROS flux due to shifts in the glutathione pool in response to varying H2O2 availability. Here, we propose that energy metabolism-linked redox signals originating from mitochondria are mediated indirectly by H2O2 through the GSH redox buffering network in and outside mitochondria. This proposal is based on several observations that have shown that unlike other redox modifications PGlu reactions fulfill the requisite

  20. 47 CFR 73.4157 - Network signals which adversely affect affiliate broadcast service.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 4 2011-10-01 2011-10-01 false Network signals which adversely affect affiliate broadcast service. 73.4157 Section 73.4157 Telecommunication FEDERAL COMMUNICATIONS COMMISSION....4157 Network signals which adversely affect affiliate broadcast service. See Public Notice, FCC...

  1. 47 CFR 73.4157 - Network signals which adversely affect affiliate broadcast service.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 4 2010-10-01 2010-10-01 false Network signals which adversely affect affiliate broadcast service. 73.4157 Section 73.4157 Telecommunication FEDERAL COMMUNICATIONS COMMISSION....4157 Network signals which adversely affect affiliate broadcast service. See Public Notice, FCC...

  2. Dynamic Trk and G Protein Signalings Regulate Dopaminergic Neurodifferentiation in Human Trophoblast Stem Cells

    PubMed Central

    Lee, Tony Tung-Yin; Tsai, Cheng-Fang; Chen, Hung-Sheng; Lai, Feng-Jie; Yokoyama, Kazunari K.; Hsieh, Tsung-Hsun; Wu, Ruey-Meei; Lee, Jau-nan

    2015-01-01

    Understanding the mechanisms in the generation of neural stem cells from pluripotent stem cells is a fundamental step towards successful management of neurodegenerative diseases in translational medicine. Albeit all-trans retinoic acid (RA) has been associated with axon outgrowth and nerve regeneration, the maintenance of differentiated neurons, the association with degenerative disease like Parkinson's disease, and its regulatory molecular mechanism from pluripotent stem cells to neural stem cells remain fragmented. We have previously reported that RA is capable of differentiation of human trophoblast stem cells to dopamine (DA) committed progenitor cells. Intracranial implantation of such neural progenitor cells into the 6-OHDA-lesioned substantia nigra pars compacta successfully regenerates dopaminergic neurons and integrity of the nigrostriatal pathway, ameliorating the behavioral deficits in the Parkinson’s disease rat model. Here, we demonstrated a dynamic molecular network in systematic analysis by addressing spatiotemporal molecular expression, intracellular protein-protein interaction and inhibition, imaging study, and genetic expression to explore the regulatory mechanisms of RA induction in the differentiation of human trophoblast stem cells to DA committed progenitor cells. We focused on the tyrosine receptor kinase (Trk), G proteins, canonical Wnt2B/β-catenin, genomic and non-genomic RA signaling transductions with Tyrosine hydroxylase (TH) gene expression as the differentiation endpoint. We found that at the early stage, integration of TrkA and G protein signalings aims for axonogenesis and morphogenesis, involving the novel RXRα/Gαq/11 and RARβ/Gβ signaling pathways. While at the later stage, five distinct signaling pathways together with epigenetic histone modifications emerged to regulate expression of TH, a precursor of dopamine. RA induction generated DA committed progenitor cells in one day. Our results provided substantial mechanistic

  3. Dynamic Trk and G Protein Signalings Regulate Dopaminergic Neurodifferentiation in Human Trophoblast Stem Cells.

    PubMed

    Tsai, Eing-Mei; Wang, Yu-Chih; Lee, Tony Tung-Yin; Tsai, Cheng-Fang; Chen, Hung-Sheng; Lai, Feng-Jie; Yokoyama, Kazunari K; Hsieh, Tsung-Hsun; Wu, Ruey-Meei; Lee, Jau-Nan

    2015-01-01

    Understanding the mechanisms in the generation of neural stem cells from pluripotent stem cells is a fundamental step towards successful management of neurodegenerative diseases in translational medicine. Albeit all-trans retinoic acid (RA) has been associated with axon outgrowth and nerve regeneration, the maintenance of differentiated neurons, the association with degenerative disease like Parkinson's disease, and its regulatory molecular mechanism from pluripotent stem cells to neural stem cells remain fragmented. We have previously reported that RA is capable of differentiation of human trophoblast stem cells to dopamine (DA) committed progenitor cells. Intracranial implantation of such neural progenitor cells into the 6-OHDA-lesioned substantia nigra pars compacta successfully regenerates dopaminergic neurons and integrity of the nigrostriatal pathway, ameliorating the behavioral deficits in the Parkinson's disease rat model. Here, we demonstrated a dynamic molecular network in systematic analysis by addressing spatiotemporal molecular expression, intracellular protein-protein interaction and inhibition, imaging study, and genetic expression to explore the regulatory mechanisms of RA induction in the differentiation of human trophoblast stem cells to DA committed progenitor cells. We focused on the tyrosine receptor kinase (Trk), G proteins, canonical Wnt2B/β-catenin, genomic and non-genomic RA signaling transductions with Tyrosine hydroxylase (TH) gene expression as the differentiation endpoint. We found that at the early stage, integration of TrkA and G protein signalings aims for axonogenesis and morphogenesis, involving the novel RXRα/Gαq/11 and RARβ/Gβ signaling pathways. While at the later stage, five distinct signaling pathways together with epigenetic histone modifications emerged to regulate expression of TH, a precursor of dopamine. RA induction generated DA committed progenitor cells in one day. Our results provided substantial mechanistic

  4. Protein kinase A activity and Hedgehog signaling pathway.

    PubMed

    Kotani, Tomoya

    2012-01-01

    Protein kinase A (PKA) is a well-known kinase that plays fundamental roles in a variety of biological processes. In Hedgehog-responsive cells, PKA plays key roles in proliferation and fate specification by modulating the transduction of Hedgehog signaling. In the absence of Hedgehog, a basal level of PKA activity represses the transcription of Hedgehog target genes. The main substrates of PKA in this process are the Ci/Gli family of bipotential transcription factors, which activate and repress Hedgehog target gene expression. PKA phosphorylates Ci/Gli, promoting the production of the repressor forms of Ci/Gli and thus repressing Hedgehog target gene expression. In contrast, the activation of Hedgehog signaling in response to Hedgehog increases the active forms of Ci/Gli, resulting in Hedgehog target gene expression. Because both decreased and increased levels of PKA activity cause abnormal cell proliferation and alter cell fate specification, the basal level of PKA activity in Hedgehog-responsive cells should be precisely regulated. However, the mechanism by which PKA activity is regulated remains obscure and appears to vary between cell types, tissues, and organisms. To date, two mechanisms have been proposed. One is a classical mechanism in which PKA activity is regulated by a small second messenger, cAMP; the other is a novel mechanism in which PKA activity is regulated by a protein, Misty somites. PMID:22391308

  5. The protein kinase LKB1 negatively regulates bone morphogenetic protein receptor signaling

    PubMed Central

    Raja, Erna; Edlund, Karolina; Kahata, Kaoru; Zieba, Agata; Morén, Anita; Watanabe, Yukihide; Voytyuk, Iryna; Botling, Johan; Söderberg, Ola; Micke, Patrick; Pyrowolakis, George; Heldin, Carl-Henrik; Moustakas, Aristidis

    2016-01-01

    The protein kinase LKB1 regulates cell metabolism and growth and is implicated in intestinal and lung cancer. Bone morphogenetic protein (BMP) signaling regulates cell differentiation during development and tissue homeostasis. We demonstrate that LKB1 physically interacts with BMP type I receptors and requires Smad7 to promote downregulation of the receptor. Accordingly, LKB1 suppresses BMP-induced osteoblast differentiation and affects BMP signaling in Drosophila wing longitudinal vein morphogenesis. LKB1 protein expression and Smad1 phosphorylation analysis in a cohort of non-small cell lung cancer patients demonstrated a negative correlation predominantly in a subset enriched in adenocarcinomas. Lung cancer patient data analysis indicated strong correlation between LKB1 loss-of-function mutations and high BMP2 expression, and these two events further correlated with expression of a gene subset functionally linked to apoptosis and migration. This new mechanism of BMP receptor regulation by LKB1 has ramifications in physiological organogenesis and disease. PMID:26701726

  6. Low-dose radiation affects cardiac physiology: gene networks and molecular signaling in cardiomyocytes.