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Sample records for signaling protein networking

  1. Protein modules and signalling networks

    NASA Astrophysics Data System (ADS)

    Pawson, Tony

    1995-02-01

    Communication between cells assumes particular importance in multicellular organisms. The growth, migration and differentiation of cells in the embryo, and their organization into specific tissues, depend on signals transmitted from one cell to another. In the adult, cell signalling orchestrates normal cellular behaviour and responses to wounding and infection. The consequences of breakdowns in this signalling underlie cancer, diabetes and disorders of the immune and cardiovascular systems. Conserved protein domains that act as key regulatory participants in many of these different signalling pathways are highlighted.

  2. 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

  3. 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

  4. 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. PMID:26691180

  5. Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks.

    PubMed

    White, Forest M; Wolf-Yadlin, Alejandro

    2016-06-12

    Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks. PMID:27049636

  6. Methods for the Analysis of Protein Phosphorylation–Mediated Cellular Signaling Networks

    NASA Astrophysics Data System (ADS)

    White, Forest M.; Wolf-Yadlin, Alejandro

    2016-06-01

    Protein phosphorylation–mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

  7. Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks

    PubMed Central

    Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

    2015-01-01

    As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw. PMID:26469276

  8. The cost and capacity of signaling in the Escherichia coli protein reaction network

    NASA Astrophysics Data System (ADS)

    Axelsen, Jacob Bock; Krishna, Sandeep; Sneppen, Kim

    2008-01-01

    In systems biology new ways are required to analyze the large amount of existing data on regulation of cellular processes. Recent work can be roughly classified into either dynamical models of well-described subsystems, or coarse-grained descriptions of the topology of the molecular networks at the scale of the whole organism. In order to bridge these two disparate approaches one needs to develop simplified descriptions of dynamics and topological measures which address the propagation of signals in molecular networks. Transmission of a signal across a reaction node depends on the presence of other reactants. It will typically be more demanding to transmit a signal across a reaction node with more input links. Sending signals along a path with several subsequent reaction nodes also increases the constraints on the presence of other proteins in the overall network. Therefore counting in and out links along reactions of a potential pathway can give insight into the signaling properties of a particular molecular network. Here, we consider the directed network of protein regulation in E. coli, characterizing its modularity in terms of its potential to transmit signals. We demonstrate that the simplest measure based on identifying subnetworks of strong components, within which each node could send a signal to every other node, does indeed partition the network into functional modules. We suggest that the total number of reactants needed to send a signal between two nodes in the network can be considered as the cost associated with transmitting this signal. Similarly we define spread as the number of reaction products that could be influenced by transmission of a successful signal. Our considerations open for a new class of network measures that implicitly utilize the constrained repertoire of chemical modifications of any biological molecule. The counting of cost and spread connects the topology of networks to the specificity of signaling across the network. Thereby, we

  9. 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

    2015-01-01

    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

  10. 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

  11. The network of P(II) signalling protein interactions in unicellular cyanobacteria.

    PubMed

    Forchhammer, Karl

    2010-01-01

    P(II) signalling proteins constitute a large superfamily of signal perception and transduction proteins, which is represented in all domains of life and whose members play central roles in coordinating nitrogen assimilation. Generally, P(II) proteins act as sensors of the cellular adenylylate energy charge and 2-oxoglutarate level, and in response to these signals, they regulate central nitrogen assimilatory processes at various levels of control (from nutrient transport to gene expression) through protein-protein interactions with P(II) receptor proteins. An examination of the phylogeny of cyanobacteria reveals that specific functions of P(II) signalling evolved in this microbial lineage, which are not found in other prokaryotes. At least one of these functions, regulation of arginine biosynthesis by controlling the key enzyme N-acetyl-L: -glutamate kinase (NAGK), was transmitted by the ancestral cyanobacterium, which gave rise to chloroplasts, into the eukaryotic domain and was conserved during the evolution of planta. We have investigated in some detail the P(II) signalling protein, its signal perception and its interactions with receptors in the unicellular cyanobacteria Synechococcus elongatus PCC 7942 and Synechocystis PCC 6803 and have performed comparative analysis with Arabidopsis thaliana P(II)-NAGK interaction. This chapter will summarize these studies and will describe the emerging picture of a complex network of P(II) protein interactions in the unicellular cyanobacteria. PMID:20532736

  12. Structural and functional protein network analyses predict novel signaling functions for rhodopsin

    PubMed Central

    Kiel, Christina; Vogt, Andreas; Campagna, Anne; Chatr-aryamontri, Andrew; Swiatek-de Lange, Magdalena; Beer, Monika; Bolz, Sylvia; Mack, Andreas F; Kinkl, Norbert; Cesareni, Gianni; Serrano, Luis; Ueffing, Marius

    2011-01-01

    Orchestration of signaling, photoreceptor structural integrity, and maintenance needed for mammalian vision remain enigmatic. By integrating three proteomic data sets, literature mining, computational analyses, and structural information, we have generated a multiscale signal transduction network linked to the visual G protein-coupled receptor (GPCR) rhodopsin, the major protein component of rod outer segments. This network was complemented by domain decomposition of protein–protein interactions and then qualified for mutually exclusive or mutually compatible interactions and ternary complex formation using structural data. The resulting information not only offers a comprehensive view of signal transduction induced by this GPCR but also suggests novel signaling routes to cytoskeleton dynamics and vesicular trafficking, predicting an important level of regulation through small GTPases. Further, it demonstrates a specific disease susceptibility of the core visual pathway due to the uniqueness of its components present mainly in the eye. As a comprehensive multiscale network, it can serve as a basis to elucidate the physiological principles of photoreceptor function, identify potential disease-associated genes and proteins, and guide the development of therapies that target specific branches of the signaling pathway. PMID:22108793

  13. 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

  14. Multiplexed visualization of dynamic signaling networks using genetically encoded fluorescent protein-based biosensors

    PubMed Central

    Depry, Charlene; Mehta, Sohum; Zhang, Jin

    2012-01-01

    Cells rely on a complex, interconnected network of signaling pathways to sense and interpret changes in their extracellular environment. The development of genetically encoded fluorescent protein (FP)-based biosensors has made it possible for researchers to directly observe and characterize the spatiotemporal dynamics of these intracellular signaling pathways in living cells. However, detailed information regarding the precise temporal and spatial relationships between intersecting pathways is often lost when individual signaling events are monitored in isolation. As the development of biosensor technology continues to advance, it is becoming increasingly feasible to image multiple FP-based biosensors concurrently, permitting greater insights into the intricate coordination of intracellular signaling networks by enabling parallel monitoring of distinct signaling events within the same cell. In this review, we discuss several strategies for multiplexed imaging of FP-based biosensors, while also underscoring some of the challenges associated with these techniques and highlighting additional avenues that could lead to further improvements in parallel monitoring of intracellular signaling events. PMID:23138230

  15. Temporal regulation of EGF signaling networks by the scaffold protein Shc1

    PubMed Central

    Zheng, Yong; Zhang, Cunjie; Croucher, David R.; Soliman, Mohamed A.; St-Denis, Nicole; Pasculescu, Adrian; Taylor, Lorne; Tate, Stephen A.; Hardy, Rod W.; Colwill, Karen; Dai, Anna Yue; Bagshaw, Rick; Dennis, James W.; Gingras, Anne-Claude; Daly, Roger J.; Pawson, Tony

    2016-01-01

    Cell-surface receptors frequently employ scaffold proteins to recruit cytoplasmic targets, but the rationale for this is uncertain. Activated receptor tyrosine kinases, for example, engage scaffolds such as Shc1 that contain phosphotyrosine (pTyr) binding (PTB) domains. Using quantitative mass spectrometry, we find that Shc1 responds to epidermal growth factor (EGF) stimulation through multiple waves of distinct phosphorylation events and protein interactions. Following stimulation, Shc1 rapidly binds a group of proteins that activate pro-mitogenic/survival pathways dependent on recruitment of the Grb2 adaptor to Shc1 pTyr sites. Akt-mediated feedback phosphorylation of Shc1 Ser29 then recruits the Ptpn12 tyrosine phosphatase. This is followed by a sub-network of proteins involved in cytoskeletal reorganization, trafficking and signal termination that binds Shc1 with delayed kinetics, largely through the SgK269 pseudokinase/adaptor protein. Ptpn12 acts as a switch to convert Shc1 from pTyr/Grb2-based signaling to SgK269-mediated pathways that regulate cell invasion and morphogenesis. The Shc1 scaffold therefore directs the temporal flow of signaling information following EGF stimulation. PMID:23846654

  16. 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

  17. 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

  18. Nodes with high centrality in protein interaction networks are responsible for driving signaling pathways in diabetic nephropathy

    PubMed Central

    Abedi, Maryam

    2015-01-01

    In spite of huge efforts, chronic diseases remain an unresolved problem in medicine. Systems biology could assist to develop more efficient therapies through providing quantitative holistic sights to these complex disorders. In this study, we have re-analyzed a microarray dataset to identify critical signaling pathways related to diabetic nephropathy. GSE1009 dataset was downloaded from Gene Expression Omnibus database and the gene expression profile of glomeruli from diabetic nephropathy patients and those from healthy individuals were compared. The protein-protein interaction network for differentially expressed genes was constructed and enriched. In addition, topology of the network was analyzed to identify the genes with high centrality parameters and then pathway enrichment analysis was performed. We found 49 genes to be variably expressed between the two groups. The network of these genes had few interactions so it was enriched and a network with 137 nodes was constructed. Based on different parameters, 34 nodes were considered to have high centrality in this network. Pathway enrichment analysis with these central genes identified 62 inter-connected signaling pathways related to diabetic nephropathy. Interestingly, the central nodes were more informative for pathway enrichment analysis compared to all network nodes and also 49 differentially expressed genes. In conclusion, we here show that central nodes in protein interaction networks tend to be present in pathways that co-occur in a biological state. Also, this study suggests a computational method for inferring underlying mechanisms of complex disorders from raw high-throughput data. PMID:26557424

  19. Using transgenic modulation of protein synthesis and accumulation to probe protein signaling networks in Arabidopsis thaliana

    PubMed Central

    Warnasooriya, Sankalpi N

    2011-01-01

    Deployment of new model species in the plant biology community requires the development and/or improvement of numerous genetic tools. Sequencing of the Arabidopsis thaliana genome opened up a new challenge of assigning biological function to each gene. As many genes exhibit spatiotemporal or other conditional regulation of biological processes, probing for gene function necessitates applications that can be geared toward temporal, spatial and quantitative functional analysis in vivo. The continuing quest to establish new platforms to examine plant gene function has resulted in the availability of numerous genomic and proteomic tools. Classical and more recent genome-wide experimental approaches include conventional mutagenesis, tagged DNA insertional mutagenesis, ectopic expression of transgenes, activation tagging, RNA interference and two-component transactivation systems. The utilization of these molecular tools has resulted in conclusive evidence for the existence of many genes, and expanded knowledge on gene structure and function. This review covers several molecular tools that have become increasingly useful in basic plant research. We discuss their advantages and limitations for probing cellular protein function while emphasizing the contributions made to lay the fundamental groundwork for genetic manipulation of crops using plant biotechnology. PMID:21862868

  20. 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

  1. 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

  2. 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

  3. Automated modelling of signal transduction networks

    PubMed Central

    2002-01-01

    Background Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. Results We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale two-hybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. Conclusion We show that our technique accurately reconstructs MAP Kinase signaling networks in Saccharomyces cerevisiae. This approach should enhance our ability to model signaling networks and to discover new components of known networks. More generally, it provides a method for synthesizing molecular data, either individual transcript abundance measurements or pairwise protein interactions, into higher level structures, such as pathways and networks. PMID:12413400

  4. 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

  5. TLR-signaling Networks

    PubMed Central

    Brown, J.; Wang, H.; Hajishengallis, G.N.; Martin, M.

    2011-01-01

    Toll-like receptors play a critical role in innate immunity by detecting invading pathogens. The ability of TLRs to engage different intracellular signaling molecules and cross-talk with other regulatory pathways is an important factor in shaping the type, magnitude, and duration of the inflammatory response. The present review will cover the fundamental signaling pathways utilized by TLRs and how these pathways regulate the innate immune response to pathogens. Abbreviations: TLR, Toll-like receptor; PRR, pattern recognition receptor; PAMP, pathogen-associated molecular pattern; LPS, lipopolysaccharide; APC, antigen-presenting cell; IL, interleukin; TIR, Toll/IL-1R homology; MyD88, myeloid differentiation factor 88; IFN, interferon; TRIF, TIR-domain-containing adapter-inducing interferon-β; IRAK, IL-1R-associated kinase; TAK1, TGF-β-activated kinase; TAB1, TAK1-binding protein; NF-κB, nuclear factor kappa-light-chain-enhancer of activated B-cells; MAPK, mitogen-activated protein kinase; NLR, NOD-like receptors; LRR, leucine-rich repeats; DC, dendritic cell; PI3K, phosphoinositide 3-kinases; GSK3, glycogen synthase kinase-3; mTOR, mammalian target of rapamycin; DAF, decay-accelerating factor; IKK, IκB kinase; IRF, interferon regulatory factors; TBK1, TANK-binding kinase 1; CARD, caspase activation and recruitment domain; PYD, pyrin N-terminal homology domain; ATF, activating transcription factor; and PTEN, phosphatase and tensin homolog. PMID:20940366

  6. Protein Regulation in Signal Transduction.

    PubMed

    Lee, Michael J; Yaffe, Michael B

    2016-01-01

    SUMMARYCells must respond to a diverse, complex, and ever-changing mix of signals, using a fairly limited set of parts. Changes in protein level, protein localization, protein activity, and protein-protein interactions are critical aspects of signal transduction, allowing cells to respond highly specifically to a nearly limitless set of cues and also to vary the sensitivity, duration, and dynamics of the response. Signal-dependent changes in levels of gene expression and protein synthesis play an important role in regulation of protein levels, whereas posttranslational modifications of proteins regulate their degradation, localization, and functional interactions. Protein ubiquitylation, for example, can direct proteins to the proteasome for degradation or provide a signal that regulates their interactions and/or location within the cell. Similarly, protein phosphorylation by specific kinases is a key mechanism for augmenting protein activity and relaying signals to other proteins that possess domains that recognize the phosphorylated residues. PMID:27252361

  7. The role of serine/threonine protein phosphatase type 5 (PP5) in the regulation of stress-induced signaling networks and cancer.

    PubMed

    Golden, Teresa; Swingle, Mark; Honkanen, Richard E

    2008-06-01

    Although the aberrant actions of protein kinases have long been known to contribute to tumor promotion and carcinogenesis, roles for protein phosphatases in the development of human cancer have only emerged in the last decade. In this review, we discuss the data obtained from studies examining the biological and pathological roles of a serine/threonine protein phosphatase, PP5, which suggest that PP5 is a potentially important regulator of both hormone- and stress-induced signaling networks that enable a cell to respond appropriately to genomic stress. PMID:18253812

  8. 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

  9. Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells

    PubMed Central

    Kulbe, Hagen; Iorio, Francesco; Chakravarty, Probir; Milagre, Carla S.; Moore, Robert; Thompson, Richard G.; Everitt, Gemma; Canosa, Monica; Montoya, Alexander; Drygin, Denis; Braicu, Ioana; Sehouli, Jalid; Saez-Rodriguez, Julio; Cutillas, Pedro R.; Balkwill, Frances R.

    2016-01-01

    We previously showed how key pathways in cancer-related inflammation and Notch signaling are part of an autocrine malignant cell network in ovarian cancer. This network, which we named the “TNF network”, has paracrine actions within the tumor microenvironment, influencing angiogenesis and the immune cell infiltrate. The aim of this study was to identify critical regulators in the signaling pathways of the TNF network in ovarian cancer cells that might be therapeutic targets. To achieve our aim, we used a systems biology approach, combining data from phospho-proteomic mass spectrometry and gene expression array analysis. Among the potential therapeutic kinase targets identified was the protein kinase Casein kinase II (CK2). Knockdown of CK2 expression in malignant cells by siRNA or treatment with the specific CK2 inhibitor CX-4945 significantly decreased Notch signaling and reduced constitutive cytokine release in ovarian cancer cell lines that expressed the TNF network as well as malignant cells isolated from high grade serous ovarian cancer ascites. The expression of the same cytokines was also inhibited after treatment with CX-4945 in a 3D organotypic model. CK2 inhibition was associated with concomitant inhibition of proliferative activity, reduced angiogenesis and experimental peritoneal ovarian tumor growth. In conclusion, we have identified kinases, particularly CK2, associated with the TNF network that may play a central role in sustaining the cytokine network and/or mediating its effects in ovarian cancer. PMID:26871292

  10. Quantitative Analysis of Protein Phosphorylations and Interactions by Multi-Colour IP-FCM as an Input for Kinetic Modelling of Signalling Networks

    PubMed Central

    Deswal, Sumit; Schulze, Anna K.; Höfer, Thomas; Schamel, Wolfgang W. A.

    2011-01-01

    Background To understand complex biological signalling mechanisms, mathematical modelling of signal transduction pathways has been applied successfully in last few years. However, precise quantitative measurements of signal transduction events such as activation-dependent phosphorylation of proteins, remains one bottleneck to this success. Methodology/Principal Findings We use multi-colour immunoprecipitation measured by flow cytometry (IP-FCM) for studying signal transduction events to unrivalled precision. In this method, antibody-coupled latex beads capture the protein of interest from cellular lysates and are then stained with differently fluorescent-labelled antibodies to quantify the amount of the immunoprecipitated protein, of an interaction partner and of phosphorylation sites. The fluorescence signals are measured by FCM. Combining this procedure with beads containing defined amounts of a fluorophore allows retrieving absolute numbers of stained proteins, and not only relative values. Using IP-FCM we derived multidimensional data on the membrane-proximal T-cell antigen receptor (TCR-CD3) signalling network, including the recruitment of the kinase ZAP70 to the TCR-CD3 and subsequent ZAP70 activation by phosphorylation in the murine T-cell hybridoma and primary murine T cells. Counter-intuitively, these data showed that cell stimulation by pervanadate led to a transient decrease of the phospho-ZAP70/ZAP70 ratio at the TCR. A mechanistic mathematical model of the underlying processes demonstrated that an initial massive recruitment of non-phosphorylated ZAP70 was responsible for this behaviour. Further, the model predicted a temporal order of multisite phosphorylation of ZAP70 (with Y319 phosphorylation preceding phosphorylation at Y493) that we subsequently verified experimentally. Conclusions/Significance The quantitative data sets generated by IP-FCM are one order of magnitude more precise than Western blot data. This accuracy allowed us to gain unequalled

  11. Interplant signalling through hyphal networks.

    PubMed

    Johnson, David; Gilbert, Lucy

    2015-03-01

    Mycorrhizal fungi can form common mycelial networks (CMNs) that interconnect plants. Here, we provide an insight into recent findings demonstrating that CMNs can be conduits for interplant signalling, influencing defence against insect herbivores and foliar necrotrophic fungi. A likely mechanism is direct transfer of signalling molecules within hyphae. However, electrical signals, which can be induced by wounding, may also enable signalling over relatively long distances, because the biophysical constraints imposed by liquid transport in hyphae and interaction with soil are relieved. We do not yet understand the ecological, evolutionary and agronomic implications of interplant signalling via CMNs. Identifying the mechanism of interplant signalling will help to address these gaps. PMID:25421970

  12. Possible target-related proteins and signal network of bufalin in A549 cells suggested by both iTRAQ-based and label-free proteomic analysis.

    PubMed

    Zhang, Dong-Mei; Feng, Li-Xing; Liu, Miao; Jin, Wen-Hai; Luo, Ji; Nie, Ai-Ying; Zhou, Yue; Li, Yin; Wu, Wan-Ying; Jiang, Bao-Hong; Yang, Min; Hu, Li-Hong; Guo, De-An; Liu, Xuan

    2016-03-01

    Bufalin (BF) exhibited antiproliferation and antimigration effects on human A549 lung cancer cells. To search its target-related proteins, protein expression profiles of BF-treated and control cells were compared using two quantitative proteomic methods, iTRAQ-based and label-free proteomic analysis. A total of 5428 proteins were identified in iTRAQ-based analysis while 6632 proteins were identified in label-free analysis. The number of common identified proteins of both methods was 4799 proteins. By application of 1.20-fold for upregulated and 0.83-fold for downregulated cutoff values, 273 and 802 differentially expressed proteins were found in iTRAQ-based and label-free analysis, respectively. The number of common differentially expressed proteins of both methods was 45 proteins. Results of bioinformational analysis using Metacore(TM) showed that the two proteomic methods were complementary and both suggested the involvement of oxidative stress and regulation of gene expression in the effects of BF, and fibronectin-related pathway was suggested to be an important pathway affected by BF. Western blotting assay results confirmed BF-induced change in levels of fibronectin and other related proteins. Overexpression of fibronectin by plasmid transfection ameliorated antimigration effects of BF. Results of the present study provided information about possible target-related proteins and signal network of BF. PMID:26787099

  13. Single-Molecule Microscopy Reveals Plasma Membrane Microdomains Created by Protein-Protein Networks that Exclude or Trap Signaling Molecules in T Cells

    PubMed Central

    Douglass, Adam D.; Vale, Ronald D.

    2010-01-01

    Summary Membrane subdomains have been implicated in T cell signaling, although their properties and mechanisms of formation remain controversial. Here, we have used single-molecule and scanning confocal imaging to characterize the behavior of GFP-tagged signaling proteins in Jurkat T cells. We show that the coreceptor CD2, the adaptor protein LAT, and tyrosine kinase Lck cocluster in discrete microdomains in the plasma membrane of signaling T cells. These microdomains require protein-protein interactions mediated through phosphorylation of LAT and are not maintained by interactions with actin or lipid rafts. Using a two color imaging approach that allows tracking of single molecules relative to the CD2/LAT/Lck clusters, we demonstrate that these microdomains exclude and limit the free diffusion of molecules in the membrane but also can trap and immobilize specific proteins. Our data suggest that diffusional trapping through protein-protein interactions creates microdomains that concentrate or exclude cell surface proteins to facilitate T cell signaling. PMID:15960980

  14. 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.

  15. 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

  16. ZASP Interacts with the Mechanosensing Protein Ankrd2 and p53 in the Signalling Network of Striated Muscle

    PubMed Central

    Martinelli, Valentina C.; Kyle, W. Buck; Kojic, Snezana; Vitulo, Nicola; Li, Zhaohui; Belgrano, Anna; Maiuri, Paolo; Banks, Lawrence; Vatta, Matteo; Valle, Giorgio; Faulkner, Georgine

    2014-01-01

    ZASP is a cytoskeletal PDZ-LIM protein predominantly expressed in striated muscle. It forms multiprotein complexes and plays a pivotal role in the structural integrity of sarcomeres. Mutations in the ZASP protein are associated with myofibrillar myopathy, left ventricular non-compaction and dilated cardiomyopathy. The ablation of its murine homologue Cypher results in neonatal lethality. ZASP has several alternatively spliced isoforms, in this paper we clarify the nomenclature of its human isoforms as well as their dynamics and expression pattern in striated muscle. Interaction is demonstrated between ZASP and two new binding partners both of which have roles in signalling, regulation of gene expression and muscle differentiation; the mechanosensing protein Ankrd2 and the tumour suppressor protein p53. These proteins and ZASP form a triple complex that appears to facilitate poly-SUMOylation of p53. We also show the importance of two of its functional domains, the ZM-motif and the PDZ domain. The PDZ domain can bind directly to both Ankrd2 and p53 indicating that there is no competition between it and p53 for the same binding site on Ankrd2. However there is competition for this binding site between p53 and a region of the ZASP protein lacking the PDZ domain, but containing the ZM-motif. ZASP is negative regulator of p53 in transactivation experiments with the p53-responsive promoters, MDM2 and BAX. Mutations in the ZASP ZM-motif induce modification in protein turnover. In fact, two mutants, A165V and A171T, were not able to bind Ankrd2 and bound only poorly to alpha-actinin2. This is important since the A165V mutation is responsible for zaspopathy, a well characterized autosomal dominant distal myopathy. Although the mechanism by which this mutant causes disease is still unknown, this is the first indication of how a ZASP disease associated mutant protein differs from that of the wild type ZASP protein. PMID:24647531

  17. 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

  18. Computational Modeling of Mammalian Signaling Networks

    PubMed Central

    Hughey, Jacob J; Lee, Timothy K; Covert, Markus W

    2011-01-01

    One of the most exciting developments in signal transduction research has been the proliferation of studies in which a biological discovery was initiated by computational modeling. Here we review the major efforts that enable such studies. First, we describe the experimental technologies that are generally used to identify the molecular components and interactions in, and dynamic behavior exhibited by, a network of interest. Next, we review the mathematical approaches that are used to model signaling network behavior. Finally, we focus on three specific instances of “model-driven discovery”: cases in which computational modeling of a signaling network has led to new insights which have been verified experimentally. Signal transduction networks are the bridge between the extraordinarily complex extracellular environment and a carefully orchestrated cellular response. These networks are largely composed of proteins which can interact, move to specific cellular locations, or be modified or degraded. The integration of these events often leads to the activation or inactivation of transcription factors, which then induce or repress the expression of thousands of genes. Because of this critical role in translating environmental cues to cellular behaviors, malfunctioning signaling networks can lead to a variety of pathologies. One example is cancer, in which many of the key genes found to be involved in cancer onset and development are components of signaling pathways [1, 2]. A detailed understanding of the cellular signaling networks underlying such diseases would likely be extremely useful in developing new treatments. However, the complexity of signaling networks is such that their integrated functions cannot be determined without computational simulation. In recent years, mathematical modeling of signal transduction has led to some exciting new findings and biological discoveries. Here, we review the work that has enabled computational modeling of mammalian

  19. Quantitative phosphoproteomic analysis of signaling downstream of the prostaglandin e2/g-protein coupled receptor in human synovial fibroblasts: potential antifibrotic networks.

    PubMed

    Gerarduzzi, Casimiro; He, QingWen; Antoniou, John; Di Battista, John A

    2014-11-01

    The Prostaglandin E2 (PGE2) signaling mechanism within fibroblasts is of growing interest as it has been shown to prevent numerous fibrotic features of fibroblast activation with limited evidence of downstream pathways. To understand the mechanisms of fibroblasts producing tremendous amounts of PGE2 with autocrine effects, we apply a strategy of combining a wide-screening of PGE2-induced kinases with quantitative phosphoproteomics. Our large-scale proteomic approach identified a PKA signal transmitted through phosphorylation of its substrates harboring the R(R/X)X(S*/T*) motif. We documented 115 substrates, of which 72 had 89 sites with a 2.5-fold phosphorylation difference in PGE2-treated cells than in untreated cells, where approximately half of such sites were defined as being novel. They were compiled by networking software to focus on highlighted activities and to associate them with a functional readout of fibroblasts. The substrates were associated with a variety of cellular functions including cytoskeletal structures (migration/motility), regulators of G-protein coupled receptor function, protein kinases, and transcriptional/translational regulators. For the first time, we extended the PGE2 pathway into an elaborate network of interconnecting phosphoproteins, providing vital information to a once restricted signalosome. These data provide new insights into eicosanoid-initiated cell signaling with regards to the regulation of fibroblast activation and the identification of new targets for evidenced-based pharmacotherapy against fibrosis. PMID:25223752

  20. 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

  1. 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

  2. Auxiliary and Autonomous Proteoglycan Signaling Networks

    PubMed Central

    Elfenbein, Arye; Simons, Michael

    2013-01-01

    Proteoglycans represent a structurally heterogeneous family of proteins that typically undergo extensive posttranslational modification with sulfated sugar chains. Although historically believed to affect signaling pathways exclusively as growth factor coreceptors, proteoglycans are now understood to initiate and modulate signal transduction cascades independently of other receptors. From within the extracellular matrix, proteoglycans are able to shield protein growth factors from circulating proteases and establish gradients that guide cell migration. Extracellular proteoglycans are also critical in the maintenance of growth factor stores and are thus instrumental in modulating paracrine signaling. At the cell membrane, proteoglycans stabilize ligand–receptor interactions, creating potentiated ternary signaling complexes that regulate cell proliferation, endocytosis, migration, growth factor sensitivity, and matrix adhesion. In some cases, proteoglycans are able to independently activate various signaling cascades, attenuate the signaling of growth factors, or orchestrate multimeric intracellular signaling complexes. Signaling between cells is also modulated by proteoglycan activity at the cell membrane, as exemplified by the proteoglycan requirement for effective synaptogenesis between neurons. Finally, proteoglycans are able to regulate signaling from intracellular compartments, particularly in the context of storage granule formation and maintenance. These proteoglycans are also major determinants of exocytic vesicle fate and other vesicular trafficking pathways. In contrast to the mechanisms underlying classical ligand-receptor signaling, proteoglycan signaling is frequently characterized by ligand promiscuity and low-affinity binding; likewise, these events commonly do not exhibit the same degree of reliance on intermolecular structure or charge configurations as other ligand-receptor interactions. Such unique features often defy conventional mechanisms of

  3. BH3-only proteins are part of a regulatory network that control the sustained signalling of the unfolded protein response sensor IRE1α

    PubMed Central

    Rodriguez, Diego A; Zamorano, Sebastian; Lisbona, Fernanda; Rojas-Rivera, Diego; Urra, Hery; Cubillos-Ruiz, Juan R; Armisen, Ricardo; Henriquez, Daniel R; H Cheng, Emily; Letek, Michal; Vaisar, Tomas; Irrazabal, Thergiory; Gonzalez-Billault, Christian; Letai, Anthony; Pimentel-Muiños, Felipe X; Kroemer, Guido; Hetz, Claudio

    2012-01-01

    Adaptation to endoplasmic reticulum (ER) stress depends on the activation of the unfolded protein response (UPR) stress sensor inositol-requiring enzyme 1α (IRE1α), which functions as an endoribonuclease that splices the mRNA of the transcription factor XBP-1 (X-box-binding protein-1). Through a global proteomic approach we identified the BCL-2 family member PUMA as a novel IRE1α interactor. Immun oprecipitation experiments confirmed this interaction and further detected the association of IRE1α with BIM, another BH3-only protein. BIM and PUMA double-knockout cells failed to maintain sustained XBP-1 mRNA splicing after prolonged ER stress, resulting in early inactivation. Mutation in the BH3 domain of BIM abrogated the physical interaction with IRE1α, inhibiting its effects on XBP-1 mRNA splicing. Unexpectedly, this regulation required BCL-2 and was antagonized by BAD or the BH3 domain mimetic ABT-737. The modulation of IRE1α RNAse activity by BH3-only proteins was recapitulated in a cell-free system suggesting a direct regulation. Moreover, BH3-only proteins controlled XBP-1 mRNA splicing in vivo and affected the ER stress-regulated secretion of antibodies by primary B cells. We conclude that a subset of BCL-2 family members participates in a new UPR-regulatory network, thus assuming apoptosis-unrelated functions. PMID:22510886

  4. 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.

  5. Universality in Protein Residue Networks

    PubMed Central

    Estrada, Ernesto

    2010-01-01

    Abstract Residue networks representing 595 nonhomologous proteins are studied. These networks exhibit universal topological characteristics as they belong to the topological class of modular networks formed by several highly interconnected clusters separated by topological cavities. There are some networks that tend to deviate from this universality. These networks represent small-size proteins having <200 residues. This article explains such differences in terms of the domain structure of these proteins. On the other hand, the topological cavities characterizing proteins residue networks match very well with protein binding sites. This study investigates the effect of the cutoff value used in building the residue network. For small cutoff values, <5 Å, the cavities found are very large corresponding almost to the whole protein surface. On the contrary, for large cutoff value, >10.0 Å, only very large cavities are detected and the networks look very homogeneous. These findings are useful for practical purposes as well as for identifying protein-like complex networks. Finally, this article shows that the main topological class of residue networks is not reproduced by random networks growing according to Erdös-Rényi model or the preferential attachment method of Barabási-Albert. However, the Watts-Strogatz model reproduces very well the topological class as well as other topological properties of residue network. A more biologically appealing modification of the Watts-Strogatz model to describe residue networks is proposed. PMID:20197043

  6. Information transfer by leaky, heterogeneous, protein kinase signaling systems

    PubMed Central

    Voliotis, Margaritis; Perrett, Rebecca M.; McWilliams, Chris; McArdle, Craig A.; Bowsher, Clive G.

    2014-01-01

    Cells must sense extracellular signals and transfer the information contained about their environment reliably to make appropriate decisions. To perform these tasks, cells use signal transduction networks that are subject to various sources of noise. Here, we study the effects on information transfer of two particular types of noise: basal (leaky) network activity and cell-to-cell variability in the componentry of the network. Basal activity is the propensity for activation of the network output in the absence of the signal of interest. We show, using theoretical models of protein kinase signaling, that the combined effect of the two types of noise makes information transfer by such networks highly vulnerable to the loss of negative feedback. In an experimental study of ERK signaling by single cells with heterogeneous ERK expression levels, we verify our theoretical prediction: In the presence of basal network activity, negative feedback substantially increases information transfer to the nucleus by both preventing a near-flat average response curve and reducing sensitivity to variation in substrate expression levels. The interplay between basal network activity, heterogeneity in network componentry, and feedback is thus critical for the effectiveness of protein kinase signaling. Basal activity is widespread in signaling systems under physiological conditions, has phenotypic consequences, and is often raised in disease. Our results reveal an important role for negative feedback mechanisms in protecting the information transfer function of saturable, heterogeneous cell signaling systems from basal activity. PMID:24395805

  7. 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

  8. 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.

  9. 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

  10. Eph/ephrin signaling: networks

    PubMed Central

    Arvanitis, Dina; Davy, Alice

    2008-01-01

    Bidirectional signaling has emerged as an important signature by which Ephs and ephrins control biological functions. Eph/ephrin signaling participates in a wide spectrum of developmental processes, and cross-regulation with other communication pathways lies at the heart of the complexity underlying their function in vivo. Here, we review in vitro and in vivo data describing molecular, functional, and genetic interactions between Eph/ephrin and other cell surface signaling pathways. The complexity of Eph/ephrin function is discussed in terms of the pathways that regulate Eph/ephrin signaling and also the pathways that are regulated by Eph/ephrin signaling. PMID:18281458

  11. Apolipoprotein E*4 (APOE*4) Genotype Is Associated with Altered Levels of Glutamate Signaling Proteins and Synaptic Coexpression Networks in the Prefrontal Cortex in Mild to Moderate Alzheimer Disease.

    PubMed

    Sweet, Robert A; MacDonald, Matthew L; Kirkwood, Caitlin M; Ding, Ying; Schempf, Tadhg; Jones-Laughner, Jackie; Kofler, Julia; Ikonomovic, Milos D; Lopez, Oscar L; Garver, Megan E; Fitz, Nicholas F; Koldamova, Radosveta; Yates, Nathan A

    2016-07-01

    It has been hypothesized that Alzheimer disease (AD) is primarily a disorder of the synapse. However, assessment of the synaptic proteome in AD subjects has been limited to a small number of proteins and often included subjects with end-stage pathology. Protein from prefrontal cortex gray matter of 59 AD subjects with mild to moderate dementia and 12 normal elderly subjects was assayed using targeted mass spectrometry to quantify 191 synaptically expressed proteins. The profile of synaptic protein expression clustered AD subjects into two groups. One of these was characterized by reduced expression of glutamate receptor proteins, significantly increased synaptic protein network coexpression, and associated withApolipoprotein E*4 (APOE*4) carrier status. The second group, by contrast, showed few differences from control subjects. A subset of AD subjects had altered prefrontal cortex synaptic proteostasis for glutamate receptors and their signaling partners. Efforts to therapeutically target glutamate receptors in AD may have outcomes dependent on APOE*4 genotype. PMID:27103636

  12. 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)

  13. Network Features and Pathway Analyses of a Signal Transduction Cascade

    PubMed Central

    Yanashima, Ryoji; Kitagawa, Noriyuki; Matsubara, Yoshiya; Weatheritt, Robert; Oka, Kotaro; Kikuchi, Shinichi; Tomita, Masaru; Ishizaki, Shun

    2008-01-01

    The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path. PMID:19543432

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

    PubMed Central

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

    2014-01-01

    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. PMID:24928042

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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. PMID:26269596

  20. 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. PMID:26527104

  1. 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

  2. Bacterial signal transduction network in a genomic perspective†

    PubMed Central

    Galperin, Michael Y.

    2005-01-01

    Summary Bacterial signalling network includes an array of numerous interacting components that monitor environmental and intracellular parameters and effect cellular response to changes in these parameters. The complexity of bacterial signalling systems makes comparative genome analysis a particularly valuable tool for their studies. Comparative studies revealed certain general trends in the organization of diverse signalling systems. These include (i) modular structure of signalling proteins; (ii) common organization of signalling components with the flow of information from N-terminal sensory domains to the C-terminal transmitter or signal output domains (N-to-C flow); (iii) use of common conserved sensory domains by different membrane receptors; (iv) ability of some organisms to respond to one environmental signal by activating several regulatory circuits; (v) abundance of intracellular signalling proteins, typically consisting of a PAS or GAF sensor domains and various output domains; (vi) importance of secondary messengers, cAMP and cyclic diguanylate; and (vii) crosstalk between components of different signalling pathways. Experimental characterization of the novel domains and domain combinations would be needed for achieving a better understanding of the mechanisms of signalling response and the intracellular hierarchy of different signalling pathways. PMID:15142243

  3. Transmitter and receiver modules in bacterial signaling proteins.

    PubMed Central

    Kofoid, E C; Parkinson, J S

    1988-01-01

    Prokaryotes are capable of sophisticated sensory behaviors. We have detected sequence motifs in bacterial signaling proteins that may act as transmitter or receiver modules in mediating protein-protein communication. These modules appear to retain their functional identities in many protein hosts, implying that they are structurally independent elements. We propose that the fundamental activity characterizing these domains is specific recognition and association of matched modules, accompanied by conformational changes in one or both of the interacting elements. Signal propagation is a natural consequence of this behavior. The versatility of this information-processing strategy is evident in the chemotaxis machinery of Escherichia coli, where proteins containing transmitters or receivers are linked in "dyadic relays" to form complex signaling networks. Images PMID:3293046

  4. 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.

  5. 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.

  6. 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

  7. New mechanistic links between sugar and hormone signalling networks.

    PubMed

    Ljung, Karin; Nemhauser, Jennifer L; Perata, Pierdomenico

    2015-06-01

    Plant growth and development must be coordinated with metabolism, notably with the efficiency of photosynthesis and the uptake of nutrients. This coordination requires local connections between hormonal response and metabolic state, as well as long-distance connections between shoot and root tissues. Recently, several molecular mechanisms have been proposed to explain the integration of sugar signalling with hormone pathways. In this work, DELLA and PIF proteins have emerged as hubs in sugar-hormone cross-regulation networks. PMID:26037392

  8. 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. PMID:26476687

  9. 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

  10. 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

  11. Signal dispersion within a hippocampal neural network

    NASA Technical Reports Server (NTRS)

    Horowitz, J. M.; Mates, J. W. B.

    1975-01-01

    A model network is described, representing two neural populations coupled so that one population is inhibited by activity it excites in the other. Parameters and operations within the model represent EPSPs, IPSPs, neural thresholds, conduction delays, background activity and spatial and temporal dispersion of signals passing from one population to the other. Simulations of single-shock and pulse-train driving of the network are presented for various parameter values. Neuronal events from 100 to 300 msec following stimulation are given special consideration in model calculations.

  12. Computation of signal delays in RC networks

    NASA Technical Reports Server (NTRS)

    Hidalgo, Juan Carlos; Narendran, Paliath; Chaiken, Seth

    1993-01-01

    A model for signal delay computation in RC networks is presented. The strength of the paradigm is its generality and simplicity. The definition of delay is applicable to RC meshes with potential resistive attenuating paths to ground. The algorithms can also be applied to undriven circuits (static charge sharing) and circuits with initial charge. To compute the delays, each node in the network is explored locally to derive a system of sparse linear equations. The solutions of the system are delay values based on the Elmore time constant at each point in the circuit.

  13. Computation of signal delays in RC networks

    NASA Astrophysics Data System (ADS)

    Hidalgo, Juan Carlos; Narendran, Paliath; Chaiken, Seth

    A model for signal delay computation in RC networks is presented. The strength of the paradigm is its generality and simplicity. The definition of delay is applicable to RC meshes with potential resistive attenuating paths to ground. The algorithms can also be applied to undriven circuits (static charge sharing) and circuits with initial charge. To compute the delays, each node in the network is explored locally to derive a system of sparse linear equations. The solutions of the system are delay values based on the Elmore time constant at each point in the circuit.

  14. STIM proteins: dynamic calcium signal transducers

    PubMed Central

    Soboloff, Jonathan; Rothberg, Brad S.; Madesh, Muniswamy; Gill, Donald L.

    2012-01-01

    Stromal interaction molecule (STIM) proteins function in cells as dynamic coordinators of cellular calcium (Ca2+) signals. Spanning the endoplasmic reticulum (ER) membrane, they sense tiny changes in the levels of Ca2+ stored within the ER lumen. As ER Ca2+ is released to generate primary Ca2+ signals, STIM proteins undergo an intricate activation reaction and rapidly translocate into junctions formed between the ER and the plasma membrane. There, STIM proteins tether and activate the highly Ca2+-selective Orai channels to mediate finely controlled Ca2+ signals and to homeostatically balance cellular Ca2+. Details are emerging on the remarkable organization within these STIM-induced junctional microdomains and the identification of new regulators and alternative target proteins for STIM. PMID:22914293

  15. 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

  16. Numeric Simulation of Plant Signaling Networks1

    PubMed Central

    Genoud, Thierry; Trevino Santa Cruz, Marcela B.; Métraux, Jean-Pierre

    2001-01-01

    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

  17. Acoustic signal propagation characterization of conduit networks

    NASA Astrophysics Data System (ADS)

    Khan, Muhammad Safeer

    Analysis of acoustic signal propagation in conduit networks has been an important area of research in acoustics. One major aspect of analyzing conduit networks as acoustic channels is that a propagating signal suffers frequency dependent attenuation due to thermo-viscous boundary layer effects and the presence of impedance mismatches such as side branches. The signal attenuation due to side branches is strongly influenced by their numbers and dimensions such as diameter and length. Newly developed applications for condition based monitoring of underground conduit networks involve measurement of acoustic signal attenuation through tests in the field. In many cases the exact installation layout of the field measurement location may not be accessible or actual installation may differ from the documented layout. The lack of exact knowledge of numbers and lengths of side branches, therefore, introduces uncertainty in the measurements of attenuation and contributes to the random variable error between measured results and those predicted from theoretical models. There are other random processes in and around conduit networks in the field that also affect the propagation of an acoustic signal. These random processes include but are not limited to the presence of strong temperature and humidity gradients within the conduits, blockages of variable sizes and types, effects of aging such as cracks, bends, sags and holes, ambient noise variations and presence of variable layer of water. It is reasonable to consider that the random processes contributing to the error in the measured attenuation are independent and arbitrarily distributed. The error, contributed by a large number of independent sources of arbitrary probability distributions, is best described by an approximately normal probability distribution in accordance with the central limit theorem. Using an analytical approach to model the attenuating effect of each of the random variable sources can be very complex and

  18. Signal transduction by guanine nucleotide binding proteins.

    PubMed

    Spiegel, A M

    1987-01-01

    High affinity binding of guanine nucleotides and the ability to hydrolyze bound GTP to GDP are characteristics of an extended family of intracellular proteins. Subsets of this family include cytosolic initiation and elongation factors involved in protein synthesis, and cytoskeletal proteins such as tubulin (Hughes, S.M. (1983) FEBS Lett. 164, 1-8). A distinct subset of guanine nucleotide binding proteins is membrane-associated; members of this subset include the ras gene products (Ellis, R.W. et al. (1981) Nature 292, 506-511) and the heterotrimeric G-proteins (also termed N-proteins) (Gilman, A.G. (1984) Cell 36, 577-579). Substantial evidence indicates that G-proteins act as signal transducers by coupling receptors (R) to effectors (E). A similar function has been suggested but not proven for the ras gene products. Known G-proteins include Gs and Gi, the G-proteins associated with stimulation and inhibition, respectively, of adenylate cyclase; transducin (TD), the G-protein coupling rhodopsin to cGMP phosphodiesterase in rod photoreceptors (Bitensky, M.W. et al. (1981) Curr. Top. Membr. Transp. 15, 237-271; Stryer, L. (1986) Annu. Rev. Neurosci. 9, 87-119), and Go, a G-protein of unknown function that is highly abundant in brain (Sternweis, P.C. and Robishaw, J.D. (1984) J. Biol. Chem. 259, 13806-13813; Neer, E.J. et al. (1984) J. Biol. Chem. 259, 14222-14229). G-proteins also participate in other signal transduction pathways, notably that involving phosphoinositide breakdown. In this review, I highlight recent progress in our understanding of the structure, function, and diversity of G-proteins. PMID:2435586

  19. Osmotic stress signaling via protein kinases.

    PubMed

    Fujii, Hiroaki; Zhu, Jian-Kang

    2012-10-01

    Plants face various kinds of environmental stresses, including drought, salinity, and low temperature, which cause osmotic stress. An understanding of the plant signaling pathways that respond to osmotic stress is important for both basic biology and agriculture. In this review, we summarize recent investigations concerning the SNF1-related protein kinase (SnRK) 2 kinase family, which play central roles in osmotic stress responses. SnRK2s are activated by osmotic stress, and a mutant lacking SnRK2s is hypersensitive to osmotic stress. Many questions remain about the signaling pathway upstream and downstream of SnRK2s. Because some SnRK2s also functions in the abscisic acid (ABA) signaling pathway, which has recently been well clarified, study of SnRK2s in ABA signaling can provide clues regarding their roles in osmotic stress signaling. PMID:22828864

  20. Cleavage of Signal Regulatory Protein α (SIRPα) Enhances Inflammatory Signaling.

    PubMed

    Londino, James D; Gulick, Dexter; Isenberg, Jeffrey S; Mallampalli, Rama K

    2015-12-25

    Signal regulatory protein α (SIRPα) is a membrane glycoprotein immunoreceptor abundant in cells of monocyte lineage. SIRPα ligation by a broadly expressed transmembrane protein, CD47, results in phosphorylation of the cytoplasmic immunoreceptor tyrosine-based inhibitory motifs, resulting in the inhibition of NF-κB signaling in macrophages. Here we observed that proteolysis of SIRPα during inflammation is regulated by a disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), resulting in the generation of a membrane-associated cleavage fragment in both THP-1 monocytes and human lung epithelia. We mapped a charge-dependent putative cleavage site near the membrane-proximal domain necessary for ADAM10-mediated cleavage. In addition, a secondary proteolytic cleavage within the membrane-associated SIRPα fragment by γ-secretase was identified. Ectopic expression of a SIRPα mutant plasmid encoding a proteolytically resistant form in HeLa cells inhibited activation of the NF-κB pathway and suppressed STAT1 phosphorylation in response to TNFα to a greater extent than expression of wild-type SIRPα. Conversely, overexpression of plasmids encoding the proteolytically cleaved SIRPα fragments in cells resulted in enhanced STAT-1 and NF-κB pathway activation. Thus, the data suggest that combinatorial actions of ADAM10 and γ-secretase on SIRPα cleavage promote inflammatory signaling. PMID:26534964

  1. 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.

  2. Domain-mediated protein interaction prediction: From genome to network.

    PubMed

    Reimand, Jüri; Hui, Shirley; Jain, Shobhit; Law, Brian; Bader, Gary D

    2012-08-14

    Protein-protein interactions (PPIs), involved in many biological processes such as cellular signaling, are ultimately encoded in the genome. Solving the problem of predicting protein interactions from the genome sequence will lead to increased understanding of complex networks, evolution and human disease. We can learn the relationship between genomes and networks by focusing on an easily approachable subset of high-resolution protein interactions that are mediated by peptide recognition modules (PRMs) such as PDZ, WW and SH3 domains. This review focuses on computational prediction and analysis of PRM-mediated networks and discusses sequence- and structure-based interaction predictors, techniques and datasets for identifying physiologically relevant PPIs, and interpreting high-resolution interaction networks in the context of evolution and human disease. PMID:22561014

  3. Sweet Taste Receptor Signaling Network: Possible Implication for Cognitive Functioning

    PubMed Central

    Welcome, Menizibeya O.; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

    2015-01-01

    Sweet taste receptors are transmembrane protein network specialized in the transmission of information from special “sweet” molecules into the intracellular domain. These receptors can sense the taste of a range of molecules and transmit the information downstream to several acceptors, modulate cell specific functions and metabolism, and mediate cell-to-cell coupling through paracrine mechanism. Recent reports indicate that sweet taste receptors are widely distributed in the body and serves specific function relative to their localization. Due to their pleiotropic signaling properties and multisubstrate ligand affinity, sweet taste receptors are able to cooperatively bind multiple substances and mediate signaling by other receptors. Based on increasing evidence about the role of these receptors in the initiation and control of absorption and metabolism, and the pivotal role of metabolic (glucose) regulation in the central nervous system functioning, we propose a possible implication of sweet taste receptor signaling in modulating cognitive functioning. PMID:25653876

  4. Physical signals for protein-DNA recognition

    NASA Astrophysics Data System (ADS)

    Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

    2009-09-01

    This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein-DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do.

  5. 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

  6. 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

  7. 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

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

    PubMed

    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

    2016-06-01

    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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. A Modular Analysis of the Auxin Signalling Network

    PubMed Central

    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. PMID:25807071

  14. Signal integration in the galactose network of Escherichia coli.

    PubMed

    Semsey, Szabolcs; Krishna, Sandeep; Sneppen, Kim; Adhya, Sankar

    2007-07-01

    The gal regulon of Escherichia coli contains genes involved in galactose transport and metabolism. Transcription of the gal regulon genes is regulated in different ways by two iso-regulatory proteins, Gal repressor (GalR) and Gal isorepressor (GalS), which recognize the same binding sites in the absence of d-galactose. DNA binding by both GalR and GalS is inhibited in the presence of d-galactose. Many of the gal regulon genes are activated in the presence of the adenosine cyclic-3',5'-monophosphate (cAMP)-cAMP receptor protein (CRP) complex. We studied transcriptional regulation of the gal regulon promoters simultaneously in a purified system and attempted to integrate the two small molecule signals, d-galactose and cAMP, that modulate the isoregulators and CRP respectively, at each promoter, using Boolean logic. Results show that similarly organized promoters can have different input functions. We also found that in some cases the activity of the promoter and the cognate gene can be described by different logic gates. We combined the transcriptional network of the galactose regulon, obtained from our experiments, with literature data to construct an integrated map of the galactose network. Structural analysis of the network shows that at the interface of the genetic and metabolic network, feedback loops are by far the most common motif. PMID:17630975

  15. 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

  16. The Hippo signal transduction network for exercise physiologists.

    PubMed

    Gabriel, Brendan M; Hamilton, D Lee; Tremblay, Annie M; Wackerhage, Henning

    2016-05-15

    The ubiquitous transcriptional coactivators Yap (gene symbol Yap1) and Taz (gene symbol Wwtr1) regulate gene expression mainly by coactivating the Tead transcription factors. Being at the center of the Hippo signaling network, Yap and Taz are regulated by the Hippo kinase cassette and additionally by a plethora of exercise-associated signals and signaling modules. These include mechanotransduction, the AKT-mTORC1 network, the SMAD transcription factors, hypoxia, glucose homeostasis, AMPK, adrenaline/epinephrine and angiotensin II through G protein-coupled receptors, and IL-6. Consequently, exercise should alter Hippo signaling in several organs to mediate at least some aspects of the organ-specific adaptations to exercise. Indeed, Tead1 overexpression in muscle fibers has been shown to promote a fast-to-slow fiber type switch, whereas Yap in muscle fibers and cardiomyocytes promotes skeletal muscle hypertrophy and cardiomyocyte adaptations, respectively. Finally, genome-wide association studies in humans have linked the Hippo pathway members LATS2, TEAD1, YAP1, VGLL2, VGLL3, and VGLL4 to body height, which is a key factor in sports. PMID:26940657

  17. 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

  18. Dynamic network analysis of protein interactions

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind; Deri, Joya

    2007-03-01

    Network approaches have recently become a popular tool to study complex systems such as cellular metabolism and protein interactions. A substantial number of analyses of the protein interaction network (PIN) of the yeast Saccharomyces cerevisiae have considered this network as a static entity, not taking the network's dynamic nature into account. Here, we examine the time-variation of gene regulation superimposed on the PIN by defining mRNA expression profiles throughout the cell cycle as node weights. To characterize these network dynamics, we have both developed a set of novel network measures as well as studied previously published measures for weighted networks. We expect that our approach will provide a deeper understanding of protein regulation during the cell cycle.

  19. Reconstruction of the temporal signaling network in Salmonella-infected human cells

    PubMed Central

    Budak, Gungor; Eren Ozsoy, Oyku; Aydin Son, Yesim; Can, Tolga; Tuncbag, Nurcan

    2015-01-01

    Salmonella enterica is a bacterial pathogen that usually infects its host through food sources. Translocation of the pathogen proteins into the host cells leads to changes in the signaling mechanism either by activating or inhibiting the host proteins. Given that the bacterial infection modifies the response network of the host, a more coherent view of the underlying biological processes and the signaling networks can be obtained by using a network modeling approach based on the reverse engineering principles. In this work, we have used a published temporal phosphoproteomic dataset of Salmonella-infected human cells and reconstructed the temporal signaling network of the human host by integrating the interactome and the phosphoproteomic dataset. We have combined two well-established network modeling frameworks, the Prize-collecting Steiner Forest (PCSF) approach and the Integer Linear Programming (ILP) based edge inference approach. The resulting network conserves the information on temporality, direction of interactions, while revealing hidden entities in the signaling, such as the SNARE binding, mTOR signaling, immune response, cytoskeleton organization, and apoptosis pathways. Targets of the Salmonella effectors in the host cells such as CDC42, RHOA, 14-3-3δ, Syntaxin family, Oxysterol-binding proteins were included in the reconstructed signaling network although they were not present in the initial phosphoproteomic data. We believe that integrated approaches, such as the one presented here, have a high potential for the identification of clinical targets in infectious diseases, especially in the Salmonella infections. PMID:26257716

  20. Neural network-based sensor signal accelerator.

    SciTech Connect

    Vogt, M. C.

    2000-10-16

    A strategy has been developed to computationally accelerate the response time of a generic electronic sensor. The strategy can be deployed as an algorithm in a control system or as a physical interface (on an embedded microcontroller) between a slower responding external sensor and a higher-speed control system. Optional code implementations are available to adjust algorithm performance when computational capability is limited. In one option, the actual sensor signal can be sampled at the slower rate with adaptive linear neural networks predicting the sensor's future output and interpolating intermediate synthetic output values. In another option, a synchronized collection of predictors sequentially controls the corresponding synthetic output voltage. Error is adaptively corrected in both options. The core strategy has been demonstrated with automotive oxygen sensor data. A prototype interface device is under construction. The response speed increase afforded by this strategy could greatly offset the cost of developing a replacement sensor with a faster physical response time.

  1. Systematic computational prediction of protein interaction networks.

    PubMed

    Lees, J G; Heriche, J K; Morilla, I; Ranea, J A; Orengo, C A

    2011-06-01

    Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use. PMID:21572181

  2. Optimized Null Model for Protein Structure Networks

    PubMed Central

    Lappe, Michael; Pržulj, Nataša

    2009-01-01

    Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by

  3. Molecular signaling involving intrinsically disordered proteins in prostate cancer.

    PubMed

    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

  4. 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

  5. Protein sensing by nanofluidic crystal and its signal enhancement.

    PubMed

    Sang, Jianming; Du, Hongtan; Wang, Wei; Chu, Ming; Wang, Yuedan; Li, Haichao; Alice Zhang, Haixia; Wu, Wengang; Li, Zhihong

    2013-01-01

    Nanofluidics has a unique property that ionic conductance across a nanometer-sized confined space is strongly affected by the space surface charge density, which can be utilized to construct electrical read-out biosensor. Based on this principle, this work demonstrated a novel protein sensor along with a sandwich signal enhancement approach. Nanoparticles with designed aptamer onside are assembled in a suspended micropore to form a 3-dimensional network of nanometer-sized interstices, named as nanofluidic crystal hereafter, as the basic sensing unit. Proteins captured by aptamers will change the surface charge density of nanoparticles and thereby can be detected by monitoring the ionic conductance across this nanofluidic crystal. Another aptamer can further enlarge the variations of the surface charge density by forming a sandwich structure (capturing aptamer/protein/signal enhancement aptamer) and the read-out conductance as well. The preliminary experimental results indicated that human α-thrombin was successfully detected by the corresponding aptamer modified nanofluidic crystal with the limit of detection of 5 nM (0.18 μg/ml) and the read-out signal was enhanced up to 3 folds by using another thrombin aptamer. Being easy to graft probe, facile and low-cost to prepare the nano-device, and having an electrical read-out, the present nanofluidic crystal scheme is a promising and universal strategy for protein sensing. PMID:24404017

  6. Discovering pathways by orienting edges in protein interaction networks

    PubMed Central

    Gitter, Anthony; Klein-Seetharaman, Judith; Gupta, Anupam; Bar-Joseph, Ziv

    2011-01-01

    Modern experimental technology enables the identification of the sensory proteins that interact with the cells’ environment or various pathogens. Expression and knockdown studies can determine the downstream effects of these interactions. However, when attempting to reconstruct the signaling networks and pathways between these sources and targets, one faces a substantial challenge. Although pathways are directed, high-throughput protein interaction data are undirected. In order to utilize the available data, we need methods that can orient protein interaction edges and discover high-confidence pathways that explain the observed experimental outcomes. We formalize the orientation problem in weighted protein interaction graphs as an optimization problem and present three approximation algorithms based on either weighted Boolean satisfiability solvers or probabilistic assignments. We use these algorithms to identify pathways in yeast. Our approach recovers twice as many known signaling cascades as a recent unoriented signaling pathway prediction technique and over 13 times as many as an existing network orientation algorithm. The discovered paths match several known signaling pathways and suggest new mechanisms that are not currently present in signaling databases. For some pathways, including the pheromone signaling pathway and the high-osmolarity glycerol pathway, our method suggests interesting and novel components that extend current annotations. PMID:21109539

  7. 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

  8. Signal Propagation in Proteins and Relation to Equilibrium Fluctuations

    PubMed Central

    Chennubhotla, Chakra; Bahar, Ivet

    2007-01-01

    Elastic network (EN) models have been widely used in recent years for describing protein dynamics, based on the premise that the motions naturally accessible to native structures are relevant to biological function. We posit that equilibrium motions also determine communication mechanisms inherent to the network architecture. To this end, we explore the stochastics of a discrete-time, discrete-state Markov process of information transfer across the network of residues. We measure the communication abilities of residue pairs in terms of hit and commute times, i.e., the number of steps it takes on an average to send and receive signals. Functionally active residues are found to possess enhanced communication propensities, evidenced by their short hit times. Furthermore, secondary structural elements emerge as efficient mediators of communication. The present findings provide us with insights on the topological basis of communication in proteins and design principles for efficient signal transduction. While hit/commute times are information-theoretic concepts, a central contribution of this work is to rigorously show that they have physical origins directly relevant to the equilibrium fluctuations of residues predicted by EN models. PMID:17892319

  9. Extreme multifunctional proteins identified from a human protein interaction network

    PubMed Central

    Chapple, Charles E.; Robisson, Benoit; Spinelli, Lionel; Guien, Céline; Becker, Emmanuelle; Brun, Christine

    2015-01-01

    Moonlighting proteins are a subclass of multifunctional proteins whose functions are unrelated. Although they may play important roles in cells, there has been no large-scale method to identify them, nor any effort to characterize them as a group. Here, we propose the first method for the identification of ‘extreme multifunctional' proteins from an interactome as a first step to characterize moonlighting proteins. By combining network topological information with protein annotations, we identify 430 extreme multifunctional proteins (3% of the human interactome). We show that the candidates form a distinct sub-group of proteins, characterized by specific features, which form a signature of extreme multifunctionality. Overall, extreme multifunctional proteins are enriched in linear motifs and less intrinsically disordered than network hubs. We also provide MoonDB, a database containing information on all the candidates identified in the analysis and a set of manually curated human moonlighting proteins. PMID:26054620

  10. Modular architecture of protein structures and allosteric communications: potential implications for signaling proteins and regulatory linkages

    PubMed Central

    del Sol, Antonio; Araúzo-Bravo, Marcos J; Amoros, Dolors; Nussinov, Ruth

    2007-01-01

    Background Allosteric communications are vital for cellular signaling. Here we explore a relationship between protein architectural organization and shortcuts in signaling pathways. Results We show that protein domains consist of modules interconnected by residues that mediate signaling through the shortest pathways. These mediating residues tend to be located at the inter-modular boundaries, which are more rigid and display a larger number of long-range interactions than intra-modular regions. The inter-modular boundaries contain most of the residues centrally conserved in the protein fold, which may be crucial for information transfer between amino acids. Our approach to modular decomposition relies on a representation of protein structures as residue-interacting networks, and removal of the most central residue contacts, which are assumed to be crucial for allosteric communications. The modular decomposition of 100 multi-domain protein structures indicates that modules constitute the building blocks of domains. The analysis of 13 allosteric proteins revealed that modules characterize experimentally identified functional regions. Based on the study of an additional functionally annotated dataset of 115 proteins, we propose that high-modularity modules include functional sites and are the basic functional units. We provide examples (the Gαs subunit and P450 cytochromes) to illustrate that the modular architecture of active sites is linked to their functional specialization. Conclusion Our method decomposes protein structures into modules, allowing the study of signal transmission between functional sites. A modular configuration might be advantageous: it allows signaling proteins to expand their regulatory linkages and may elicit a broader range of control mechanisms either via modular combinations or through modulation of inter-modular linkages. PMID:17531094

  11. Statistical signal processing in sensor networks

    NASA Astrophysics Data System (ADS)

    Guerriero, Marco

    In this dissertation we focus on decentralized signal processing in Sensor Networks (SN). Four topics are studied: (i) Direction of Arrival (DOA) estimation using a Wireless Sensor network (WSN), (ii) multiple target tracking in large SN, (iii) decentralized target detection in SN and (iv) decentralized sequential detection in SN with communication constraints. The first topic of this thesis addresses the problem of estimating the DOA of an acoustic wavefront using a a WSN made of isotropic (hence individually useless) sensors. The WSN was designed according to the SENMA (SEnsor Network with Mobile Agents) architecture with a mobile agent (MA) that successively queries the sensors lying inside its field of view. We propose both fast/simple and optimal DOA-estimation schemes, and an optimization of the MAs observation management is also carried out, with the surprising finding that the MA ought to orient itself at an oblique angle to the expected DOA, rather than directly toward it. We also consider the extension to multiple sources; intriguingly, per-source DOA accuracy is higher when there is more than one source. In all cases, performance is investigated by simulation and compared, when appropriate, with asymptotic bounds; these latter are usually met after a moderate number of MA dwells. In the second topic, we study the problem of tracking multiple targets in large SN. While these networks hold significant potential for surveillance, it is of interest to address fundamental limitations in large-scale implementations. We first introduce a simple analytical tracker performance model. Analysis of this model suggests that scan-based tracking performance improves with increasing numbers of sensors, but only to a certain point beyond which degradation is observed. Correspondingly, we address model-based optimization of the local sensor detection threshold and the number of sensors. Next, we propose a two-stage tracking approach (fuse-before-track) as a possible

  12. 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

  13. 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.

  14. NatalieQ: A web server for protein-protein interaction network querying

    PubMed Central

    2014-01-01

    Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks. We recently developed Natalie, which computes high-quality network alignments via advanced methods from combinatorial optimization. Results Here, we present NatalieQ, a web server for topology-based alignment of a specified query protein-protein interaction network to a selected target network using the Natalie algorithm. By incorporating similarity at both the sequence and the network level, we compute alignments that allow for the transfer of functional annotation as well as for the prediction of missing interactions. We illustrate the capabilities of NatalieQ with a biological case study involving the Wnt signaling pathway. Conclusions We show that topology-based network alignment can produce results complementary to those obtained by using sequence similarity alone. We also demonstrate that NatalieQ is able to predict putative interactions. The server is available at: http://www.ibi.vu.nl/programs/natalieq/. PMID:24690407

  15. RMOD: a tool for regulatory motif detection in signaling network.

    PubMed

    Kim, Jinki; Yi, Gwan-Su

    2013-01-01

    Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod. PMID:23874612

  16. 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.

  17. 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

  18. 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

  19. Structures of the agouti signaling protein.

    PubMed

    McNulty, Joseph C; Jackson, Pilgrim J; Thompson, Darren A; Chai, Biaoxin; Gantz, Ira; Barsh, Gregory S; Dawson, Philip E; Millhauser, Glenn L

    2005-03-01

    Expression of the agouti signaling protein (ASIP) during hair growth produces the red/yellow pigment pheomelanin. ASIP, and its neuropeptide homolog the agouti-related protein (AgRP) involved in energy balance, are novel, paracrine signaling molecules that act as inverse agonists at distinct subsets of melanocortin receptors. Ubiquitous ASIP expression in mice gives rise to a pleiotropic phenotype characterized by a uniform yellow coat color, obesity, overgrowth, and metabolic derangements similar to type II diabetes in humans. Here we report the synthesis and NMR structure of ASIP's active, cysteine-rich, C-terminal domain. ASIP adopts the inhibitor cystine knot fold and, along with AgRP, are the only known mammalian proteins in this structure class. Moreover, ASIP populates two distinct conformers resulting from a cis peptide bond at Pro102-Pro103 and a coexistence of cis/trans isomers of Ala104-Pro105. Pharmacologic studies of Pro-->Ala mutants demonstrate that the minor conformation with two cis peptide bonds is responsible for activity at all MCRs. The loop containing the heterogeneous Ala-Pro peptide bond is conserved in mammals, and suggests that ASIP is either trapped by evolution in this unusual configuration or possesses function outside of strict MCR antagonism. PMID:15701517

  20. ATR inhibition rewires cellular signaling networks induced by replication stress.

    PubMed

    Wagner, Sebastian A; Oehler, Hannah; Voigt, Andrea; Dalic, Denis; Freiwald, Anja; Serve, Hubert; Beli, Petra

    2016-02-01

    The slowing down or stalling of replication forks is commonly known as replication stress and arises from multiple causes such as DNA lesions, nucleotide depletion, RNA-DNA hybrids, and oncogene activation. The ataxia telangiectasia and Rad3-related kinase (ATR) plays an essential role in the cellular response to replication stress and inhibition of ATR has emerged as therapeutic strategy for the treatment of cancers that exhibit high levels of replication stress. However, the cellular signaling induced by replication stress and the substrate spectrum of ATR has not been systematically investigated. In this study, we employed quantitative MS-based proteomics to define the cellular signaling after nucleotide depletion-induced replication stress and replication fork collapse following ATR inhibition. We demonstrate that replication stress results in increased phosphorylation of a subset of proteins, many of which are involved in RNA splicing and transcription and have previously not been associated with the cellular replication stress response. Furthermore, our data reveal the ATR-dependent phosphorylation following replication stress and discover novel putative ATR target sites on MCM6, TOPBP1, RAD51AP1, and PSMD4. We establish that ATR inhibition rewires cellular signaling networks induced by replication stress and leads to the activation of the ATM-driven double-strand break repair signaling. PMID:26572502

  1. The centrality of cancer proteins in human protein-protein interaction network: a revisit.

    PubMed

    Xiong, Wei; Xie, Luyu; Zhou, Shuigeng; Liu, Hui; Guan, Jihong

    2014-01-01

    Topological analysis of protein-protein interaction (PPI) networks has been widely applied to the investigation on cancer mechanisms. However, there is still a debate on whether cancer proteins exhibit more topological centrality compared to the other proteins in the human PPI network. To resolve this debate, we first identified four sets of human proteins, and then mapped these proteins into the yeast PPI network by homologous genes. Finally, we compared these proteins' properties in human and yeast PPI networks. Experiments over two real datasets demonstrated that cancer proteins tend to have higher degree and smaller clustering coefficient than non-cancer proteins. Experimental results also validated that cancer proteins have larger betweenness centrality compared to the other proteins on the STRING dataset. However, on the BioGRID dataset, the average betweenness centrality of cancer proteins is larger than that of disease and control proteins, but smaller than that of essential proteins. PMID:24878726

  2. Heat dissipation guides activation in signaling proteins.

    PubMed

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

    2015-08-18

    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

  3. Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data

    PubMed Central

    Kramer, Frank; Pukrop, Tobias; Beißbarth, Tim; Bleckmann, Annalen

    2015-01-01

    important in this context. The topology of these networks can be further refined in the future by integration with complementary data such as protein-protein interactions, in order to gain greater insight into signaling processes. PMID:26632845

  4. Topology and dynamics of signaling networks: in search of transcriptional control of the inflammatory response.

    PubMed

    Androulakis, Ioannis P; Kamisoglu, Kubra; Mattick, John S

    2013-01-01

    Over the past several decades, to develop a fundamental understanding of inflammation's progression, research has focused on extracellular mediators, such as cytokines, as characteristic components of inflammatory response. These efforts have recently been complemented by advances in proteomics that allow analysis of multiple signaling proteins in parallel, to provide more complete mechanistic models of inflammation. In this review, we discuss various techniques for assessing protein activity, as well as computational techniques that are well suited for interpreting large amounts of proteomic data to generate signaling networks or for modeling the dynamics of known network interactions. We also discuss examples that explore these experimental and computational techniques in tandem to generate signaling networks under various conditions and that link those networks to transcriptional activity. Further advancements in this field will likely provide an explicit description of inflammatory response, paving the way for better diagnostics and therapies in clinic. PMID:23862674

  5. 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

  6. Anti-apoptotic ARC protein confers chemoresistance by controlling leukemia-microenvironment interactions through a NFκB/IL1β signaling network

    PubMed Central

    Carter, Bing Z.; Mak, Po Yee; Chen, Ye; Mak, Duncan H.; Mu, Hong; Jacamo, Rodrigo; Ruvolo, Vivian; Arold, Stefan T.; Ladbury, John E.; Burks, Jared K.; Kornblau, Steven; Andreeff, Michael

    2016-01-01

    To better understand how the apoptosis repressor with caspase recruitment domain (ARC) protein confers drug resistance in acute myeloid leukemia (AML), we investigated the role of ARC in regulating leukemia-mesenchymal stromal cell (MSC) interactions. In addition to the previously reported effect on AML apoptosis, we have demonstrated that ARC enhances migration and adhesion of leukemia cells to MSCs both in vitro and in a novel human extramedullary bone/bone marrow mouse model. Mechanistic studies revealed that ARC induces IL1β expression in AML cells and increases CCL2, CCL4, and CXCL12 expression in MSCs, both through ARC-mediated activation of NFκB. Expression of these chemokines in MSCs increased by AML cells in an ARC/IL1β-dependent manner; likewise, IL1β expression was elevated when leukemia cells were co-cultured with MSCs. Further, cells from AML patients expressed the receptors for and migrated toward CCL2, CCL4, and CXCL12. Inhibition of IL1β suppressed AML cell migration and sensitized the cells co-cultured with MSCs to chemotherapy. Our results suggest the existence of a complex ARC-regulated circuit that maintains intimate connection of AML with the tumor microenvironment through NFκB/IL1β-regulated chemokine receptor/ligand axes and reciprocal crosstalk resulting in cytoprotection. The data implicate ARC as a promising drug target to potentially sensitize AML cells to chemotherapy. PMID:26956049

  7. 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

  8. 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

  9. 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

  10. 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

  11. Prediction and characterization of protein-protein interaction network in Bacillus licheniformis WX-02.

    PubMed

    Han, Yi-Chao; Song, Jia-Ming; Wang, Long; Shu, Cheng-Cheng; Guo, Jing; Chen, Ling-Ling

    2016-01-01

    In this study, we constructed a protein-protein interaction (PPI) network of B. licheniformis strain WX-02 with interolog method and domain-based method, which contained 15,864 edges and 2,448 nodes. Although computationally predicted networks have relatively low coverage and high false-positive rate, our prediction was confirmed from three perspectives: local structural features, functional similarities and transcriptional correlations. Further analysis of the COG heat map showed that protein interactions in B. licheniformis WX-02 mainly occurred in the same functional categories. By incorporating the transcriptome data, we found that the topological properties of the PPI network were robust under normal and high salt conditions. In addition, 267 different protein complexes were identified and 117 poorly characterized proteins were annotated with certain functions based on the PPI network. Furthermore, the sub-network showed that a hub protein CcpA jointed directly or indirectly many proteins related to γ-PGA synthesis and regulation, such as PgsB, GltA, GltB, ProB, ProJ, YcgM and two signal transduction systems ComP-ComA and DegS-DegU. Thus, CcpA might play an important role in the regulation of γ-PGA synthesis. This study therefore will facilitate the understanding of the complex cellular behaviors and mechanisms of γ-PGA synthesis in B. licheniformis WX-02. PMID:26782814

  12. Prediction and characterization of protein-protein interaction network in Bacillus licheniformis WX-02

    PubMed Central

    Han, Yi-Chao; Song, Jia-Ming; Wang, Long; Shu, Cheng-Cheng; Guo, Jing; Chen, Ling-Ling

    2016-01-01

    In this study, we constructed a protein-protein interaction (PPI) network of B. licheniformis strain WX-02 with interolog method and domain-based method, which contained 15,864 edges and 2,448 nodes. Although computationally predicted networks have relatively low coverage and high false-positive rate, our prediction was confirmed from three perspectives: local structural features, functional similarities and transcriptional correlations. Further analysis of the COG heat map showed that protein interactions in B. licheniformis WX-02 mainly occurred in the same functional categories. By incorporating the transcriptome data, we found that the topological properties of the PPI network were robust under normal and high salt conditions. In addition, 267 different protein complexes were identified and 117 poorly characterized proteins were annotated with certain functions based on the PPI network. Furthermore, the sub-network showed that a hub protein CcpA jointed directly or indirectly many proteins related to γ-PGA synthesis and regulation, such as PgsB, GltA, GltB, ProB, ProJ, YcgM and two signal transduction systems ComP-ComA and DegS-DegU. Thus, CcpA might play an important role in the regulation of γ-PGA synthesis. This study therefore will facilitate the understanding of the complex cellular behaviors and mechanisms of γ-PGA synthesis in B. licheniformis WX-02. PMID:26782814

  13. 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

  14. 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

  15. Design principles of nuclear receptor signaling: how complex networking improves signal transduction

    PubMed Central

    Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

    2010-01-01

    The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

  16. The RalGEF-Ral Effector Signaling Network

    PubMed Central

    Neel, Nicole F.; Martin, Timothy D.; Stratford, Jeran K.; Zand, Tanya P.; Reiner, David J.; Der, Channing J.

    2011-01-01

    The high frequency of RAS mutations in human cancers (33%) has stimulated intense interest in the development of anti-Ras inhibitors for cancer therapy. Currently, the major focus of these efforts is centered on inhibitors of components involved in Ras downstream effector signaling. In particular, more than 40 inhibitors of the Raf-MEK-ERK mitogen-activated protein kinase cascade and phosphoinositide 3-kinase-AKT-mTOR effector signaling networks are currently under clinical evaluation. However, these efforts are complicated by the fact that Ras can utilize at least 9 additional functionally distinct effectors, with at least 3 additional effectors with validated roles in Ras-mediated oncogenesis. Of these, the guanine nucleotide exchange factors of the Ras-like (Ral) small GTPases (RalGEFs) have emerged as important effectors of mutant Ras in pancreatic, colon, and other cancers. In this review, we summarize the evidence for the importance of this effector pathway in cancer and discuss possible directions for therapeutic inhibition of aberrant Ral activation and signaling. PMID:21779498

  17. 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

  18. 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.

  19. Interface-Resolved Network of Protein-Protein Interactions

    PubMed Central

    Johnson, Margaret E.; Hummer, Gerhard

    2013-01-01

    We define an interface-interaction network (IIN) to capture the specificity and competition between protein-protein interactions (PPI). This new type of network represents interactions between individual interfaces used in functional protein binding and thereby contains the detail necessary to describe the competition and cooperation between any pair of binding partners. Here we establish a general framework for the construction of IINs that merges computational structure-based interface assignment with careful curation of available literature. To complement limited structural data, the inclusion of biochemical data is critical for achieving the accuracy and completeness necessary to analyze the specificity and competition between the protein interactions. Firstly, this procedure provides a means to clarify the information content of existing data on purported protein interactions and to remove indirect and spurious interactions. Secondly, the IIN we have constructed here for proteins involved in clathrin-mediated endocytosis (CME) exhibits distinctive topological properties. In contrast to PPI networks with their global and relatively dense connectivity, the fragmentation of the IIN into distinctive network modules suggests that different functional pressures act on the evolution of its topology. Large modules in the IIN are formed by interfaces sharing specificity for certain domain types, such as SH3 domains distributed across different proteins. The shared and distinct specificity of an interface is necessary for effective negative and positive design of highly selective binding targets. Lastly, the organization of detailed structural data in a network format allows one to identify pathways of specific binding interactions and thereby predict effects of mutations at specific surfaces on a protein and of specific binding inhibitors, as we explore in several examples. Overall, the endocytosis IIN is remarkably complex and rich in features masked in the coarser

  20. Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

    PubMed Central

    Ollivier, Julien F.; Soyer, Orkun S.

    2016-01-01

    Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

  1. 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

  2. Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network

    PubMed Central

    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. PMID:25013377

  3. 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.

  4. 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.

  5. Information routing driven by background chatter in a signaling network.

    PubMed

    Domedel-Puig, Núria; Rué, Pau; Pons, Antonio J; García-Ojalvo, Jordi

    2011-12-01

    Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity -or chatter- that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios. PMID:22174668

  6. Network-based prediction of protein function

    PubMed Central

    Sharan, Roded; Ulitsky, Igor; Shamir, Ron

    2007-01-01

    Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community. PMID:17353930

  7. 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.

  8. Protein conservation and variation suggest mechanisms of cell type-specific modulation of signaling pathways.

    PubMed

    Schaefer, Martin H; Yang, Jae-Seong; Serrano, Luis; Kiel, Christina

    2014-06-01

    Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservation onto functional pathway components and topological layers in the pathway hierarchy. We found that the input (receptors) and the output (transcription factors) layers evolve more rapidly than proteins in the intermediary transmission layer. In contrast, protein expression variability decreases from the input to the output layer. We observed that the differences in protein variability between the input and transmission layer can be attributed to both the network position and the tendency of variable proteins to physically interact with constitutively expressed proteins. Differences in protein expression variability and conservation are also accompanied by the tendency of conserved and constitutively expressed proteins to acquire somatic mutations, while germline mutations tend to occur in cell type-specific proteins. Thus, conserved core proteins in the transmission layer could perform a fundamental role in most cell types and are therefore less tolerant to germline mutations. In summary, we propose that the core signal transmission machinery is largely modulated by a variable input layer through physical protein interactions. We hypothesize that the bow-tie organization of cellular signaling on the level of protein abundance variability contributes to the specificity of the signal response in different cell types. PMID:24922536

  9. Crosstalk between pathways enhances the controllability of signalling networks.

    PubMed

    Wang, Dingjie; Jin, Suoqin; Zou, Xiufen

    2016-02-01

    The control of complex networks is one of the most challenging problems in the fields of biology and engineering. In this study, the authors explored the controllability and control energy of several signalling networks, which consisted of many interconnected pathways, including networks with a bow-tie architecture. On the basis of the theory of structure controllability, they revealed that biological mechanisms, such as cross-pathway interactions, compartmentalisation and so on make the networks easier to fully control. Furthermore, using numerical simulations for two realistic examples, they demonstrated that the control energy of normal networks with crosstalk is lower than in networks without crosstalk. These results indicate that the biological networks are optimally designed to achieve their normal functions from the viewpoint of the control theory. The authors' work provides a comprehensive understanding of the impact of network structures and properties on controllability. PMID:26816393

  10. Enhanced photoacoustic signal from DNA assembled gold nanoparticle networks

    NASA Astrophysics Data System (ADS)

    Buchkremer, A.; Beckmann, M. F.; Linn, M.; Ruff, J.; Rosencrantz, R. R.; von Plessen, G.; Schmitz, G.; Simon, U.

    2014-12-01

    We report an experimental finding of photoacoustic signal enhancement from finite sized DNA-gold nanoparticle networks. We synthesized DNA-functionalized hollow and solid gold nanospheres (AuNS) to form finite sized networks, which were characterized by means of optical extinction spectroscopy, dynamic light scattering, and scanning electron microscopy in transmission mode. It is shown that the signal amplification scales with network size for networks comprising either hollow or solid AuNS as well as networks consisting of both types of nanoparticles. The laser intensities applied in our multispectral setup (λ = 650 nm, 850 nm, 905 nm) were low enough to maintain the structural integrity of the networks. This reflects that the binding and recognition properties of the temperature-sensitive cross-linking DNA-molecules are retained.

  11. 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

  12. 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

  13. Signal propagation through feedforward neuronal networks with different operational modes

    NASA Astrophysics Data System (ADS)

    Li, Jie; Liu, Feng; Xu, Ding; Wang, Wei

    2009-02-01

    How neuronal activity is propagated across multiple layers of neurons is a fundamental issue in neuroscience. Using numerical simulations, we explored how the operational mode of neurons —coincidence detector or temporal integrator— could affect the propagation of rate signals through a 10-layer feedforward network with sparse connectivity. Our study was based on two kinds of neuron models. The Hodgkin-Huxley (HH) neuron can function as a coincidence detector, while the leaky integrate-and-fire (LIF) neuron can act as a temporal integrator. When white noise is afferent to the input layer, rate signals can be stably propagated through both networks, while neurons in deeper layers fire synchronously in the absence of background noise; but the underlying mechanism for the development of synchrony is different. When an aperiodic signal is presented, the network of HH neurons can represent the temporal structure of the signal in firing rate. Meanwhile, synchrony is well developed and is resistant to background noise. In contrast, rate signals are somewhat distorted during the propagation through the network of LIF neurons, and only weak synchrony occurs in deeper layers. That is, coincidence detectors have a performance advantage over temporal integrators in propagating rate signals. Therefore, given weak synaptic conductance and sparse connectivity between layers in both networks, synchrony does greatly subserve the propagation of rate signals with fidelity, and coincidence detection could be of considerable functional significance in cortical processing.

  14. Multifunctional proteins revealed by overlapping clustering in protein interaction network

    PubMed Central

    Chapple, Charles E.; Guénoche, Alain; Brun, Christine

    2012-01-01

    Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters. Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overlapping clusters and which is, therefore, capable of correct assignment of multifunctional proteins. The principle of OCG is to cover the graph with initial overlapping classes that are iteratively fused into a hierarchy according to an extension of Newman's modularity function. By applying OCG to a human protein–protein interaction network, we show that multifunctional proteins are revealed at the intersection of clusters and demonstrate that the method outperforms other existing methods on simulated graphs and PPI networks. Availability: This software can be downloaded from http://tagc.univ-mrs.fr/welcome/spip.php?rubrique197 Contact: brun@tagc.univ-mrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22080466

  15. Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks

    PubMed Central

    2013-01-01

    Background Large scale understanding of complex and dynamic alterations in cellular and subcellular levels during cancer in contrast to normal condition has facilitated the emergence of sophisticated systemic approaches like network biology in recent times. As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e.g. detection of molecular complexes (potential modules or clusters) and identification of crucial nodes forming the overlapping modules have been considered in this regard. Methods In the current study, the computational analysis of previously published protein interaction networks (PINs) has been conducted to identify the molecular complexes and crucial nodes of the networks. Protein molecules involved in ten major cancer signal transduction pathways were used to construct the networks based on expression data of five tissues e.g. bone, breast, colon, kidney and liver in both normal and cancer conditions. MCODE (molecular complex detection) and ModuLand methods have been used to identify the molecular complexes and crucial nodes of the networks respectively. Results In case of all tissues, cancer PINs show higher level of clustering (formation of molecular complexes) than the normal ones. In contrast, lower level modular overlapping is found in cancer PINs than the normal ones. Thus a proposition can be made regarding the formation of some giant nodes in the cancer networks with very high degree and resulting in reduced overlapping among the network modules though the predicted molecular complex numbers are higher in cancer conditions. Conclusion The study predicts some major molecular complexes that might act as the important regulators in cancer progression. The crucial nodes identified in this study can be potential drug targets to combat cancer. PMID

  16. 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

  17. Control of Striatal Signaling by G Protein Regulators

    PubMed Central

    Xie, Keqiang; Martemyanov, Kirill A.

    2011-01-01

    Signaling via heterotrimeric G proteins plays a crucial role in modulating the responses of striatal neurons that ultimately shape core behaviors mediated by the basal ganglia circuitry, such as reward valuation, habit formation, and movement coordination. Activation of G protein-coupled receptors (GPCRs) by extracellular signals activates heterotrimeric G proteins by promoting the binding of GTP to their α subunits. G proteins exert their effects by influencing the activity of key effector proteins in this region, including ion channels, second messenger enzymes, and protein kinases. Striatal neurons express a staggering number of GPCRs whose activation results in the engagement of downstream signaling pathways and cellular responses with unique profiles but common molecular mechanisms. Studies over the last decade have revealed that the extent and duration of GPCR signaling are controlled by a conserved protein family named regulator of G protein signaling (RGS). RGS proteins accelerate GTP hydrolysis by the α subunits of G proteins, thus promoting deactivation of GPCR signaling. In this review, we discuss the progress made in understanding the roles of RGS proteins in controlling striatal G protein signaling and providing integration and selectivity of signal transmission. We review evidence on the formation of a macromolecular complex between RGS proteins and other components of striatal signaling pathways, their molecular regulatory mechanisms and impacts on GPCR signaling in the striatum obtained from biochemical studies and experiments involving genetic mouse models. Special emphasis is placed on RGS9-2, a member of the RGS family that is highly enriched in the striatum and plays critical roles in drug addiction and motor control. PMID:21852966

  18. From Topology to Phenotype in Protein-Protein Interaction Networks

    NASA Astrophysics Data System (ADS)

    Pržulj, Nataša

    We have recently witnessed an explosion in biological network data along with the development of computational approaches for their analyses. This new interdisciplinary research area is an integral part of systems biology, promising to provide new insights into organizational principles of life, as well as into evolution and disease. However, there is a danger that the area might become hindered by several emerging issues. In particular, there is typically a weak link between biological and computational scientists, resulting in the use of simple computational techniques of limited potential to explain these complex biological data. Hence, there is a danger that the community might view the topological features of network data as mere statistics, ignoring the value of the information contained in these data. This might result in the imposition of scientific doctrines, such as scale-free-centric (on the modelling side) and genome-centric (on the biological side) opinions onto this nascent research area. In this chapter, we take a network science perspective and present a brief, high-level overview of the area, commenting on possible challenges ahead. We focus on protein-protein interaction networks (PINs) in which nodes correspond to proteins in a cell and edges to physical bindings between the proteins.

  19. 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

  20. The Role of Inhibitory G Proteins and Regulators of G Protein Signaling in the in vivo Control of Heart Rate and Predisposition to Cardiac Arrhythmias

    PubMed Central

    Ang, Richard; Opel, Aaisha; Tinker, Andrew

    2012-01-01

    Inhibitory heterotrimeric G proteins and the control of heart rate. The activation of cell signaling pathways involving inhibitory heterotrimeric G proteins acts to slow the heart rate via modulation of ion channels. A large number of Regulators of G protein signalings (RGSs) can act as GTPase accelerating proteins to inhibitory G proteins and thus it is important to understand the network of RGS\\G-protein interaction. We will review our recent findings on in vivo heart rate control in mice with global genetic deletion of various inhibitory G protein alpha subunits. We will discuss potential central and peripheral contributions to the phenotype and the controversies in the literature. PMID:22783193

  1. The Role of Inhibitory G Proteins and Regulators of G Protein Signaling in the in vivo Control of Heart Rate and Predisposition to Cardiac Arrhythmias.

    PubMed

    Ang, Richard; Opel, Aaisha; Tinker, Andrew

    2012-01-01

    Inhibitory heterotrimeric G proteins and the control of heart rate. The activation of cell signaling pathways involving inhibitory heterotrimeric G proteins acts to slow the heart rate via modulation of ion channels. A large number of Regulators of G protein signalings (RGSs) can act as GTPase accelerating proteins to inhibitory G proteins and thus it is important to understand the network of RGS\\G-protein interaction. We will review our recent findings on in vivo heart rate control in mice with global genetic deletion of various inhibitory G protein alpha subunits. We will discuss potential central and peripheral contributions to the phenotype and the controversies in the literature. PMID:22783193

  2. 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

  3. 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.

  4. Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics

    PubMed Central

    Pandini, Alessandro; Fornili, Arianna; Fraternali, Franca; Kleinjung, Jens

    2012-01-01

    Allostery offers a highly specific way to modulate protein function. Therefore, understanding this mechanism is of increasing interest for protein science and drug discovery. However, allosteric signal transmission is difficult to detect experimentally and to model because it is often mediated by local structural changes propagating along multiple pathways. To address this, we developed a method to identify communication pathways by an information-theoretical analysis of molecular dynamics simulations. Signal propagation was described as information exchange through a network of correlated local motions, modeled as transitions between canonical states of protein fragments. The method was used to describe allostery in two-component regulatory systems. In particular, the transmission from the allosteric site to the signaling surface of the receiver domain NtrC was shown to be mediated by a layer of hub residues. The location of hubs preferentially connected to the allosteric site was found in close agreement with key residues experimentally identified as involved in the signal transmission. The comparison with the networks of the homologues CheY and FixJ highlighted similarities in their dynamics. In particular, we showed that a preorganized network of fragment connections between the allosteric and functional sites exists already in the inactive state of all three proteins.—Pandini, A., Fornili, A., Fraternali, F., Kleinjung, J. Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics. PMID:22071506

  5. 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

  6. 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.

  7. Structural permeability of complex networks to control signals

    PubMed Central

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

    2015-01-01

    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. PMID:26391186

  8. Fiber fault location utilizing traffic signal in optical network.

    PubMed

    Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

    2013-10-01

    We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols. PMID:24104308

  9. 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

  10. 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

  11. A generative model for protein contact networks.

    PubMed

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

    2016-07-01

    In this paper, we present a generative model for protein contact networks (PCNs). The soundness of the proposed model is investigated by focusing primarily on mesoscopic properties elaborated from the spectra of the graph Laplacian. To complement the analysis, we also study the classical topological descriptors, such as statistics of the shortest paths and the important feature of modularity. Our experiments show that the proposed model results in a considerable improvement with respect to two suitably chosen generative mechanisms, mimicking with better approximation real PCNs in terms of diffusion properties elaborated from the normalized Laplacian spectra. However, as well as the other network models, it does not reproduce with sufficient accuracy the shortest paths structure. To compensate this drawback, we designed a second step involving a targeted edge reconfiguration process. The ensemble of reconfigured networks denotes further improvements that are statistically significant. As an important byproduct of our study, we demonstrate that modularity, a well-known property of proteins, does not entirely explain the actual network architecture characterizing PCNs. In fact, we conclude that modularity, intended as a quantification of an underlying community structure, should be considered as an emergent property of the structural organization of proteins. Interestingly, such a property is suitably optimized in PCNs together with the feature of path efficiency. PMID:26474097

  12. 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

  13. SignaLink 2 – a signaling pathway resource with multi-layered regulatory networks

    PubMed Central

    2013-01-01

    Background Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contains transcription factors and their binding sites on the DNA as well as microRNAs and their mRNA targets. Currently, most signaling and regulatory databases contain only a subsection of this network, making comprehensive analyses highly time-consuming and dependent on specific data handling expertise. The need for detailed mapping of signaling systems is also supported by the fact that several drug development failures were caused by undiscovered cross-talk or regulatory effects of drug targets. We previously created a uniformly curated signaling pathway resource, SignaLink, to facilitate the analysis of pathway cross-talks. Here, we present SignaLink 2, which significantly extends the coverage and applications of its predecessor. Description We developed a novel concept to integrate and utilize different subsections (i.e., layers) of the signaling network. The multi-layered (onion-like) database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The user-friendly website allows the interactive exploration of how each signaling protein is regulated. The customizable download page enables the analysis of any user-specified part of the signaling network. Compared to other signaling resources, distinctive features of SignaLink 2 are the following: 1) it involves experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; 2) combines manual curation with large-scale datasets; 3) provides confidence scores for each interaction; 4) operates a customizable download page with multiple file formats

  14. Regulator of G-protein signaling - 5 (RGS5) is a novel repressor of hedgehog signaling.

    PubMed

    Mahoney, William M; Gunaje, Jagadambika; Daum, Guenter; Dong, Xiu Rong; Majesky, Mark W

    2013-01-01

    Hedgehog (Hh) signaling plays fundamental roles in morphogenesis, tissue repair, and human disease. Initiation of Hh signaling is controlled by the interaction of two multipass membrane proteins, patched (Ptc) and smoothened (Smo). Recent studies identify Smo as a G-protein coupled receptor (GPCR)-like protein that signals through large G-protein complexes which contain the Gαi subunit. We hypothesize Regulator of G-Protein Signaling (RGS) proteins, and specifically RGS5, are endogenous repressors of Hh signaling via their ability to act as GTPase activating proteins (GAPs) for GTP-bound Gαi, downstream of Smo. In support of this hypothesis, we demonstrate that RGS5 over-expression inhibits sonic hedgehog (Shh)-mediated signaling and osteogenesis in C3H10T1/2 cells. Conversely, signaling is potentiated by siRNA-mediated knock-down of RGS5 expression, but not RGS4 expression. Furthermore, using immuohistochemical analysis and co-immunoprecipitation (Co-IP), we demonstrate that RGS5 is present with Smo in primary cilia. This organelle is required for canonical Hh signaling in mammalian cells, and RGS5 is found in a physical complex with Smo in these cells. We therefore conclude that RGS5 is an endogenous regulator of Hh-mediated signaling and that RGS proteins are potential targets for novel therapeutics in Hh-mediated diseases. PMID:23637832

  15. 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

  16. Regulator of G Protein Signaling 17 as a Negative Modulator of GPCR Signaling in Multiple Human Cancers.

    PubMed

    Hayes, Michael P; Roman, David L

    2016-05-01

    Regulators of G protein signaling (RGS) proteins modulate G protein-coupled receptor (GPCR) signaling networks by terminating signals produced by active Gα subunits. RGS17, a member of the RZ subfamily of RGS proteins, is typically only expressed in appreciable amounts in the human central nervous system, but previous works have shown that RGS17 expression is selectively upregulated in a number of malignancies, including lung, breast, prostate, and hepatocellular carcinoma. In addition, this upregulation of RGS17 is associated with a more aggressive cancer phenotype, as increased proliferation, migration, and invasion are observed. Conversely, decreased RGS17 expression diminishes the response of ovarian cancer cells to agents commonly used during chemotherapy. These somewhat contradictory roles of RGS17 in cancer highlight the need for selective, high-affinity inhibitors of RGS17 to use as chemical probes to further the understanding of RGS17 biology. Based on current evidence, these compounds could potentially have clinical utility as novel chemotherapeutics in the treatment of lung, prostate, breast, and liver cancers. Recent advances in screening technologies to identify potential inhibitors coupled with increasing knowledge of the structural requirements of RGS-Gα protein-protein interaction inhibitors make the future of drug discovery efforts targeting RGS17 promising. This review highlights recent findings related to RGS17 as both a canonical and atypical RGS protein, its role in various human disease states, and offers insights on small molecule inhibition of RGS17. PMID:26928451

  17. Wavelet neural network for detection of signals in communications

    NASA Astrophysics Data System (ADS)

    Gomez-Sanchez, Raquel; Andina, Diego

    1998-03-01

    Our objective is the design and simulation of an efficient system for detection of signals in communications in terms of speed and computational complexity. The proposed scheme takes advantage of two powerful frameworks in signal processing: wavelets and neural networks. The decision system will take a decision based on the computation of the a prior probabilities of the input signal. For the estimation of such probability density functions, a wavelet neural network has been chosen. The election has risen under the following considerations: (a) neural networks have been established as a general approximation tool for fitting nonlinear models from input/output data and (b) the increasing popularity of the wavelet decomposition as a powerful tool for approximation. The integration of the above factors leads to the wavelet neural network concept. This network preserves the universal approximation property of wavelet series, with the advantage of the speed and efficient computation of a neural network architecture. The topology and learning algorithm of the network will provide an efficient approximation to the required probability density functions.

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

    PubMed

    Deignan, Lisa; Pinheiro, Marco T; Sutcliffe, Catherine; Saunders, Abbie; Wilcockson, Scott G; Zeef, Leo A H; Donaldson, Ian J; Ashe, Hilary L

    2016-07-01

    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

  19. 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

  20. Role of signal peptides in targeting of proteins in cyanobacteria.

    PubMed Central

    Mackle, M M; Zilinskas, B A

    1994-01-01

    Proteins of cyanobacteria may be transported across one of two membrane systems: the typical eubacterial cell envelope (consisting of an inner membrane, periplasmic space, and an outer membrane) and the photosynthetic thylakoids. To investigate the role of signal peptides in targeting in cyanobacteria, Synechococcus sp. strain PCC 7942 was transformed with vectors carrying the chloramphenicol acetyltransferase reporter gene fused to coding sequences for one of four different signal peptides. These included signal peptides of two proteins of periplasmic space origin (one from Escherichia coli and the other from Synechococcus sp. strain PCC 7942) and two other signal peptides of proteins located in the thylakoid lumen (one from a cyanobacterium and the other from a higher plant). The location of the gene fusion products expressed in Synechococcus sp. strain PCC 7942 was determined by a chloramphenicol acetyltransferase enzyme-linked immunosorbent assay of subcellular fractions. The distribution pattern for gene fusions with periplasmic signal peptides was different from that of gene fusions with thylakoid lumen signal peptides. Primary sequence analysis revealed conserved features in the thylakoid lumen signal peptides that were absent from the periplasmic signal peptides. These results suggest the importance of the signal peptide in protein targeting in cyanobacteria and point to the presence of signal peptide features conserved between chloroplasts and cyanobacteria for targeting of proteins to the thylakoid lumen. Images PMID:8144451

  1. Integrating in silico resources to map a signaling network.

    PubMed

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

    2014-01-01

    The abundance of publicly available life science databases offers 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 we 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 for 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

  2. 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

  3. Dual degradation signals control Gli protein stability and tumor formation

    PubMed Central

    Huntzicker, Erik G.; Estay, Ivette S.; Zhen, Hanson; Lokteva, Ludmila A.; Jackson, Peter K.; Oro, Anthony E.

    2006-01-01

    Regulated protein destruction controls many key cellular processes with aberrant regulation increasingly found during carcinogenesis. Gli proteins mediate the transcriptional effects of the Sonic hedgehog pathway, which is implicated in up to 25% of human tumors. Here we show that Gli is rapidly destroyed by the proteasome and that mouse basal cell carcinoma induction correlates with Gli protein accumulation. We identify two independent destruction signals in Gli1, DN and DC, and show that removal of these signals stabilizes Gli1 protein and rapidly accelerates tumor formation in transgenic animals. These data argue that control of Gli protein accumulation underlies tumorigenesis and suggest a new avenue for antitumor therapy. PMID:16421275

  4. 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

  5. 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

  6. Illuminating Spatial and Temporal Organization of Protein Interaction Networks by Mass Spectrometry-Based Proteomics

    PubMed Central

    Yang, Jiwen; Wagner, Sebastian A.; Beli, Petra

    2015-01-01

    Protein–protein interactions are at the core of all cellular functions and dynamic alterations in protein interactions regulate cellular signaling. In the last decade, mass spectrometry (MS)-based proteomics has delivered unprecedented insights into human protein interaction networks. Affinity purification-MS (AP-MS) has been extensively employed for focused and high-throughput studies of steady state protein–protein interactions. Future challenges remain in mapping transient protein interactions after cellular perturbations as well as in resolving the spatial organization of protein interaction networks. AP-MS can be combined with quantitative proteomics approaches to determine the relative abundance of purified proteins in different conditions, thereby enabling the identification of transient protein interactions. In addition to affinity purification, methods based on protein co-fractionation have been combined with quantitative MS to map transient protein interactions during cellular signaling. More recently, approaches based on proximity tagging that preserve the spatial dimension of protein interaction networks have been introduced. Here, we provide an overview of MS-based methods for analyzing protein–protein interactions with a focus on approaches that aim to dissect the temporal and spatial aspects of protein interaction networks. PMID:26648978

  7. Irregularity and asynchrony in biologic network signals.

    PubMed

    Pincus, S M

    2000-01-01

    ; "r" is chosen as a fixed percentage (often 20%) of the subject's SD. This version of ApEn has the property that it is decorrelated from process SD--it remains unchanged under uniform process magnification, reduction, and translation (shift by a constant). Cross-ApEn is generally applied to compare sequences from two distinct yet interwined variables in a network. Thus we can directly assess network, and not just nodal, evolution, under different settings--e.g., to directly evaluate uncoupling and/or changes in feedback and control. Hence, cross-ApEn facilitates analyses of output from myriad complicated networks, avoiding the requirement to fully model the underlying system. This is especially important, since accurate modeling of (biological) networks is often nearly impossible. Algorithmically and insofar as implementation and reproducibility properties are concerned, cross-ApEn is thematically similar to ApEn. Furthermore, cross-ApEn is shown to be complementary to the two most prominent statistical means of assessing multivariate series, correlation and power spectral methodologies. In particular, we highlight, both theoretically and by case study examples, the many physiological feedback and/or control systems and models for which cross-ApEn can detect significant changes in bivariate asynchrony, yet for which cross-correlation and cross-spectral methods fail to clearly highlight markedly changing features of the data sets under consideration. Finally, we introduce spatial ApEn, which appears to have considerable potential, both theoretically and empirically, in evaluating multidimensional lattice structures, to discern and quantify the extent of changing patterns, and for the emergence and dissolution of traveling waves, throughout multiple contexts within biology and chemistry. PMID:10909056

  8. G-protein signaling: back to the future.

    PubMed

    McCudden, C R; Hains, M D; Kimple, R J; Siderovski, D P; Willard, F S

    2005-03-01

    Heterotrimeric G-proteins are intracellular partners of G-protein-coupled receptors (GPCRs). GPCRs act on inactive Galpha.GDP/Gbetagamma heterotrimers to promote GDP release and GTP binding, resulting in liberation of Galpha from Gbetagamma. Galpha.GTP and Gbetagamma target effectors including adenylyl cyclases, phospholipases and ion channels. Signaling is terminated by intrinsic GTPase activity of Galpha and heterotrimer reformation - a cycle accelerated by 'regulators of G-protein signaling' (RGS proteins). Recent studies have identified several unconventional G-protein signaling pathways that diverge from this standard model. Whereas phospholipase C (PLC) beta is activated by Galpha(q) and Gbetagamma, novel PLC isoforms are regulated by both heterotrimeric and Ras-superfamily G-proteins. An Arabidopsis protein has been discovered containing both GPCR and RGS domains within the same protein. Most surprisingly, a receptor-independent Galpha nucleotide cycle that regulates cell division has been delineated in both Caenorhabditis elegans and Drosophila melanogaster. Here, we revisit classical heterotrimeric G-protein signaling and explore these new, non-canonical G-protein signaling pathways. PMID:15747061

  9. Deciphering Supramolecular Structures with Protein-Protein Interaction Network Modeling

    PubMed Central

    Tsuji, Toshiyuki; Yoda, Takao; Shirai, Tsuyoshi

    2015-01-01

    Many biological molecules are assembled into supramolecules that are essential to perform complicated functions in the cell. However, experimental information about the structures of supramolecules is not sufficient at this point. We developed a method of predicting and modeling the structures of supramolecules in a biological network by combining structural data of the Protein Data Bank (PDB) and interaction data in IntAct databases. Templates for binary complexes in IntAct were extracted from PDB. Modeling was attempted by assembling binary complexes with superposed shared subunits. A total of 3,197 models were constructed, and 1,306 (41% of the total) contained at least one subunit absent from experimental structures. The models also suggested 970 (25% of the total) experimentally undetected subunit interfaces, and 41 human disease-related amino acid variants were mapped onto these model-suggested interfaces. The models demonstrated that protein-protein interaction network modeling is useful to fill the information gap between biological networks and structures. PMID:26549015

  10. Neural Networks For Demodulation Of Phase-Modulated Signals

    NASA Technical Reports Server (NTRS)

    Altes, Richard A.

    1995-01-01

    Hopfield neural networks proposed for demodulating quadrature phase-shift-keyed (QPSK) signals carrying digital information. Networks solve nonlinear integral equations prior demodulation circuits cannot solve. Consists of set of N operational amplifiers connected in parallel, with weighted feedback from output terminal of each amplifier to input terminals of other amplifiers. Used to solve signal processing problems. Implemented as analog very-large-scale integrated circuit that achieves rapid convergence. Alternatively, implemented as digital simulation of such circuit. Also used to improve phase estimation performance over that of phase-locked loop.

  11. Distributed Estimation for Vector Signal in Linear Coherent Sensor Networks

    NASA Astrophysics Data System (ADS)

    Wu, Chien-Hsien; Lin, Ching-An

    We introduce the distributed estimation of a random vector signal in wireless sensor networks that follow coherent multiple access channel model. We adopt the linear minimum mean squared error fusion rule. The problem of interest is to design linear coding matrices for those sensors in the network so as to minimize mean squared error of the estimated vector signal under a total power constraint. We show that the problem can be formulated as a convex optimization problem and we obtain closed form expressions of the coding matrices. Numerical results are used to illustrate the performance of the proposed method.

  12. 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.

  13. 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

  14. Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks.

    PubMed

    Wang, Yan; Sun, Huiyan; Du, Wei; Blanzieri, Enrico; Viero, Gabriella; Xu, Ying; Liang, Yanchun

    2014-01-01

    Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges. PMID:25268881

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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

  20. The PHR proteins: intracellular signaling hubs in neuronal development and axon degeneration.

    PubMed

    Grill, Brock; Murphey, Rodney K; Borgen, Melissa A

    2016-01-01

    During development, a coordinated and integrated series of events must be accomplished in order to generate functional neural circuits. Axons must navigate toward target cells, build synaptic connections, and terminate outgrowth. The PHR proteins (consisting of mammalian Phr1/MYCBP2, Drosophila Highwire and C. elegans RPM-1) function in each of these events in development. Here, we review PHR function across species, as well as the myriad of signaling pathways PHR proteins regulate. These findings collectively suggest that the PHR proteins are intracellular signaling hubs, a concept we explore in depth. Consistent with prominent developmental functions, genetic links have begun to emerge between PHR signaling networks and neurodevelopmental disorders, such as autism, schizophrenia and intellectual disability. Finally, we discuss the recent and important finding that PHR proteins regulate axon degeneration, which has further heightened interest in this fascinating group of molecules. PMID:27008623

  1. 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

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

    PubMed Central

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

    2015-01-01

    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. PMID:25797237

  3. ERM proteins: from cellular architecture to cell signaling.

    PubMed

    Louvet-Vallée, S

    2000-08-01

    ERM (ezrin/radixin/moesin) proteins, concentrated in actin rich cell-surface structures, cross-link actin filaments with the plasma membrane. They are involved in the formation of microvilli, cell-cell adhesion, maintenance of cell shape, cell motility and membrane trafficking. Recent analyses reveal that they are not only involved in cytoskeleton organization but also in signaling pathway. They play an important role in the activation of members of the Rho family by recruiting their regulators. The functions of ERM proteins are regulated by their conformational charges: the intramolecular interaction between the N- and C-terminal domains of ERM proteins charges masks several binding sites, leading to a dormant protein. Different activation signals regulate ERM proteins functions by modulating these intramolecular interactions. The involvement of ERM proteins in many signaling pathways has led to study their role during development of different species. PMID:11071040

  4. 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

  5. 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

  6. Evolutionarily Conserved Herpesviral Protein Interaction Networks

    PubMed Central

    Fossum, Even; Friedel, Caroline C.; Rajagopala, Seesandra V.; Titz, Björn; Baiker, Armin; Schmidt, Tina; Kraus, Theo; Stellberger, Thorsten; Rutenberg, Christiane; Suthram, Silpa; Bandyopadhyay, Sourav; Rose, Dietlind; von Brunn, Albrecht; Uhlmann, Mareike; Zeretzke, Christine; Dong, Yu-An; Boulet, Hélène; Koegl, Manfred; Bailer, Susanne M.; Koszinowski, Ulrich; Ideker, Trey; Uetz, Peter; Zimmer, Ralf; Haas, Jürgen

    2009-01-01

    Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV) and Kaposi's sarcoma-associated herpesvirus (KSHV). In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1), murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H), and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species. PMID:19730696

  7. HKC: an algorithm to predict protein complexes in protein-protein interaction networks.

    PubMed

    Wang, Xiaomin; Wang, Zhengzhi; Ye, Jun

    2011-01-01

    With the availability of more and more genome-scale protein-protein interaction (PPI) networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods. PMID:22174556

  8. Modeling of cell signaling pathways in macrophages by semantic networks

    PubMed Central

    Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

    2004-01-01

    Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed

  9. Interaction prediction using conserved network motifs in protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2005-03-01

    High-throughput protein interaction detection methods are strongly affected by false positive and false negative results. Focused experiments are needed to complement the large-scale methods by validating previously detected interactions but it is often difficult to decide which proteins to probe as interaction partners. Developing reliable computational methods assisting this decision process is a pressing need in bioinformatics. This talk will describe the recent developments in analyzing and understanding protein interaction networks, then present a method that uses the conserved properties of the protein network to identify and validate interaction candidates. We apply a number of machine learning algorithms to the protein connectivity information and achieve a surprisingly good overall performance in predicting interacting proteins. Using a ``leave-one-ou approach we find average success rates between 20-50% for predicting the correct interaction partner of a protein. We demonstrate that the success of these methods is based on the presence of conserved interaction motifs within the network. A reference implementation and a table with candidate interacting partners for each yeast protein are available at http://www.protsuggest.org

  10. 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

  11. 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

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

    PubMed Central

    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

  13. Discrete dynamic modeling of T cell survival signaling networks

    NASA Astrophysics Data System (ADS)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  14. 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

  15. 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

  16. Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics.

    PubMed

    Pandini, Alessandro; Fornili, Arianna; Fraternali, Franca; Kleinjung, Jens

    2012-02-01

    Allostery offers a highly specific way to modulate protein function. Therefore, understanding this mechanism is of increasing interest for protein science and drug discovery. However, allosteric signal transmission is difficult to detect experimentally and to model because it is often mediated by local structural changes propagating along multiple pathways. To address this, we developed a method to identify communication pathways by an information-theoretical analysis of molecular dynamics simulations. Signal propagation was described as information exchange through a network of correlated local motions, modeled as transitions between canonical states of protein fragments. The method was used to describe allostery in two-component regulatory systems. In particular, the transmission from the allosteric site to the signaling surface of the receiver domain NtrC was shown to be mediated by a layer of hub residues. The location of hubs preferentially connected to the allosteric site was found in close agreement with key residues experimentally identified as involved in the signal transmission. The comparison with the networks of the homologues CheY and FixJ highlighted similarities in their dynamics. In particular, we showed that a preorganized network of fragment connections between the allosteric and functional sites exists already in the inactive state of all three proteins. PMID:22071506

  17. Signal-Response Modeling of Partial Hormone Feedback Networks

    PubMed Central

    Johnson, Michael L.; Veldhuis, Paula P.; Evans, William S.

    2009-01-01

    Background Endocrine feedback control networks are typically complex and contain multiple hormones, pools, and compartments. The hormones themselves commonly interact via multiple pathways and targets within the networks, and a complete description of such relationships may involve hundreds of parameters. In addition, it is often difficult, if not impossible, to collect experimental data pertaining to every component within the network. Therefore, the complete simultaneous analysis of such networks is challenging. Nevertheless, an understanding of these networks is critical for furthering our knowledge of hormonal regulation in both physiologic and pathophysiologic conditions. Methods We propose a novel approach for the analysis of dose-response relationships of subsets of hormonal feedback networks. The algorithm and signal-response quantification (SRQuant) software is based on convolution integrals, and tests whether several discretely measured input signals can be individually delayed, spread in time, transformed, combined, and discretely convolved with an elimination function to predict the time course of the concentration of an output hormone. Signal-response quantification is applied to examples from the endocrine literature to demonstrate its applicability to the analysis of the different endocrine networks. Results In one example, SRQuant determines the dose-response relationship by which one hormone regulates another, highlighting its advantages over other traditional methods. In a second example, for the first time (to the best of our knowledge), we show that the secretion of glucagon may be jointly controlled by the β and the δ cells. Conclusion We have developed a novel convolution integral-based approach, algorithm, and software (SRQuant) for the analysis of dose-response relationships within subsets of complex endocrine feedback control networks. PMID:20046649

  18. 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

  19. Choline-releasing glycerophosphodiesterase EDI3 links the tumor metabolome to signaling network activities.

    PubMed

    Marchan, Rosemarie; Lesjak, Michaela S; Stewart, Joanna D; Winter, Roland; Seeliger, Janine; Hengstler, Jan G

    2012-12-15

    Recently, EDI3 was identified as a key factor for choline metabolism that controls tumor cell migration and is associated with metastasis in endometrial carcinomas. EDI3 cleaves glycerophosphocholine (GPC) to form choline and glycerol-3-phosphate (G3P). Choline is then further metabolized to phosphatidylcholine (PtdC), the major lipid in membranes and a key player in membrane-mediated cell signaling. The second product, G3P, is a precursor molecule for several lipids with central roles in signaling, for example lysophosphatidic acid (LPA), phosphatidic acid (PA) and diacylglycerol (DAG). LPA activates intracellular signaling pathways by binding to specific LPA receptors, including membrane-bound G protein-coupled receptors and the intracellular nuclear receptor, PPARγ. Conversely, PA and DAG mediate signaling by acting as lipid anchors that bind and activate several signaling proteins. For example, binding of GTPases and PKC to PA and DAG, respectively, increases the activation of signaling networks, mediating processes such as migration, adhesion, proliferation or anti-apoptosis-all relevant for tumor development. We present a concept by which EDI3 either directly generates signaling molecules or provides "membrane anchors" for downstream signaling factors. As a result, EDI3 links choline metabolism to signaling activities resulting in a more malignant phenotype. PMID:23114620

  20. 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

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

    PubMed

    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. Signal bi-amplification in networks of unidirectionally coupled MEMS

    NASA Astrophysics Data System (ADS)

    Tchakui, Murielle Vanessa; Woafo, Paul; Colet, Pere

    2016-01-01

    The purpose of this paper is to analyze the propagation and the amplification of an input signal in networks of unidirectionally coupled micro-electro-mechanical systems (MEMS). Two types of external excitations are considered: sinusoidal and stochastic signals. We show that sinusoidal signals are amplified up to a saturation level which depends on the transmission rate and despite MEMS being nonlinear the sinusoidal shape is well preserved if the number of MEMS is not too large. However, increasing the number of MEMS, there is an instability that leads to chaotic behavior and which is triggered by the amplification of the harmonics generated by the nonlinearities. We also show that for stochastic input signals, the MEMS array acts as a band-pass filter and after just a few elements the signal has a narrow power spectra.

  3. SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

    PubMed

    Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

    2013-04-30

    The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube. PMID:23589857

  4. Profiles of Basal and stimulated receptor signaling networks predict drug response in breast cancer lines.

    PubMed

    Niepel, Mario; Hafner, Marc; Pace, Emily A; Chung, Mirra; Chai, Diana H; Zhou, Lili; Schoeberl, Birgit; Sorger, Peter K

    2013-09-24

    Identifying factors responsible for variation in drug response is essential for the effective use of targeted therapeutics. We profiled signaling pathway activity in a collection of breast cancer cell lines before and after stimulation with physiologically relevant ligands, which revealed the variability in network activity among cells of known genotype and molecular subtype. Despite the receptor-based classification of breast cancer subtypes, we found that the abundance and activity of signaling proteins in unstimulated cells (basal profile), as well as the activity of proteins in stimulated cells (signaling profile), varied within each subtype. Using a partial least-squares regression approach, we constructed models that significantly predicted sensitivity to 23 targeted therapeutics. For example, one model showed that the response to the growth factor receptor ligand heregulin effectively predicted the sensitivity of cells to drugs targeting the cell survival pathway mediated by PI3K (phosphoinositide 3-kinase) and Akt, whereas the abundance of Akt or the mutational status of the enzymes in the pathway did not. Thus, basal and signaling protein profiles may yield new biomarkers of drug sensitivity and enable the identification of appropriate therapies in cancers characterized by similar functional dysregulation of signaling networks. PMID:24065145

  5. Optogenetic pharmacology for control of native neuronal signaling proteins

    PubMed Central

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

    2016-01-01

    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

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. Model calibration and uncertainty analysis in signaling networks.

    PubMed

    Heinemann, Tim; Raue, Andreas

    2016-06-01

    For a long time the biggest challenges in modeling cellular signal transduction networks has been the inference of crucial pathway components and the qualitative description of their interactions. As a result of the emergence of powerful high-throughput experiments, it is now possible to measure data of high temporal and spatial resolution and to analyze signaling dynamics quantitatively. In addition, this increase of high-quality data is the basis for a better understanding of model limitations and their influence on the predictive power of models. We review established approaches in signal transduction network modeling with a focus on ordinary differential equation models as well as related developments in model calibration. As central aspects of the calibration process we discuss possibilities of model adaptation based on data-driven parameter optimization and the concomitant objective of reducing model uncertainties. PMID:27085224

  12. Hedgehog signaling: networking to nurture a promalignant tumor microenvironment.

    PubMed

    Harris, Lillianne G; Samant, Rajeev S; Shevde, Lalita A

    2011-09-01

    In addition to its role in embryonic development, the Hedgehog pathway has been shown to be an active participant in cancer development, progression, and metastasis. Although this pathway is activated by autocrine signaling by Hedgehog ligands, it can also initiate paracrine signaling with cells in the microenvironment. This creates a network of Hedgehog signaling that determines the malignant behavior of the tumor cells. As a result of paracrine signal transmission, the effects of Hedgehog signaling most profoundly influence the stromal cells that constitute the tumor microenvironment. The stromal cells in turn produce factors that nurture the tumor. Thus, such a resonating cross-talk can amplify Hedgehog signaling, resulting in molecular chatter that overall promotes tumor progression. Inhibitors of Hedgehog signaling have been the subject of intense research. Several of these inhibitors are currently being evaluated in clinical trials. Here, we review the role of the Hedgehog pathway in the signature characteristics of cancer cells that determine tumor development, progression, and metastasis. This review condenses the latest findings on the signaling pathways that are activated and/or regulated by molecules generated from Hedgehog signaling in cancer and cites promising clinical interventions. Finally, we discuss future directions for identifying the appropriate patients for therapy, developing reliable markers of efficacy of treatment, and combating resistance to Hedgehog pathway inhibitors. PMID:21775419

  13. 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

  14. 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

  15. The Intrinsic Geometric Structure of Protein-Protein Interaction Networks for Protein Interaction Prediction.

    PubMed

    Fang, Yi; Sun, Mengtian; Dai, Guoxian; Ramain, Karthik

    2016-01-01

    Recent developments in high-throughput technologies for measuring protein-protein interaction (PPI) have profoundly advanced our ability to systematically infer protein function and regulation. However, inherently high false positive and false negative rates in measurement have posed great challenges in computational approaches for the prediction of PPI. A good PPI predictor should be 1) resistant to high rate of missing and spurious PPIs, and 2) robust against incompleteness of observed PPI networks. To predict PPI in a network, we developed an intrinsic geometry structure (IGS) for network, which exploits the intrinsic and hidden relationship among proteins in network through a heat diffusion process. In this process, all explicit PPIs participate simultaneously to glue local infinitesimal and noisy experimental interaction data to generate a global macroscopic descriptions about relationships among proteins. The revealed implicit relationship can be interpreted as the probability of two proteins interacting with each other. The revealed relationship is intrinsic and robust against individual, local and explicit protein interactions in the original network. We apply our approach to publicly available PPI network data for the evaluation of the performance of PPI prediction. Experimental results indicate that, under different levels of the missing and spurious PPIs, IGS is able to robustly exploit the intrinsic and hidden relationship for PPI prediction with a higher sensitivity and specificity compared to that of recently proposed methods. PMID:26886733

  16. Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks

    PubMed Central

    Eddy, James A.; Papin, Jason A.

    2008-01-01

    Extracellular cues affect signaling, metabolic, and regulatory processes to elicit cellular responses. Although intracellular signaling, metabolic, and regulatory networks are highly integrated, previous analyses have largely focused on independent processes (e.g., metabolism) without considering the interplay that exists among them. However, there is evidence that many diseases arise from multifunctional components with roles throughout signaling, metabolic, and regulatory networks. Therefore, in this study, we propose a flux balance analysis (FBA)–based strategy, referred to as integrated dynamic FBA (idFBA), that dynamically simulates cellular phenotypes arising from integrated networks. The idFBA framework requires an integrated stoichiometric reconstruction of signaling, metabolic, and regulatory processes. It assumes quasi-steady-state conditions for “fast” reactions and incorporates “slow” reactions into the stoichiometric formalism in a time-delayed manner. To assess the efficacy of idFBA, we developed a prototypic integrated system comprising signaling, metabolic, and regulatory processes with network features characteristic of actual systems and incorporating kinetic parameters based on typical time scales observed in literature. idFBA was applied to the prototypic system, which was evaluated for different environments and gene regulatory rules. In addition, we applied the idFBA framework in a similar manner to a representative module of the single-cell eukaryotic organism Saccharomyces cerevisiae. Ultimately, idFBA facilitated quantitative, dynamic analysis of systemic effects of extracellular cues on cellular phenotypes and generated comparable time-course predictions when contrasted with an equivalent kinetic model. Since idFBA solves a linear programming problem and does not require an exhaustive list of detailed kinetic parameters, it may be efficiently scaled to integrated intracellular systems that incorporate signaling, metabolic, and

  17. Signalling Network Construction for Modelling Plant Defence Response

    PubMed Central

    Miljkovic, Dragana; Stare, Tjaša; Mozetič, Igor; Podpečan, Vid; Petek, Marko; Witek, Kamil; Dermastia, Marina; Lavrač, Nada; Gruden, Kristina

    2012-01-01

    Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for

  18. Signal peptides are allosteric activators of the protein translocase.

    PubMed

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

    2009-11-19

    Extra-cytoplasmic polypeptides are usually synthesized as 'preproteins' carrying amino-terminal, cleavable signal peptides and secreted across membranes by translocases. The main bacterial translocase comprises the SecYEG protein-conducting channel and the peripheral ATPase motor SecA. Most proteins destined for the periplasm and beyond are exported post-translationally by SecA. Preprotein targeting to SecA is thought to involve signal peptides and chaperones like SecB. Here we show that signal peptides have a new role beyond targeting: they are essential allosteric activators of the translocase. On 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; second, 'trapping' that engages non-native preprotein mature domains docked with high affinity on the secretion apparatus; and third, 'secretion' during which trapped mature domains undergo several turnovers of translocation in segments. 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

  19. 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

  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

    2016-01-01

    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. PMID:27485017

  1. 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

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

    PubMed

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

    2016-06-01

    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

  4. Collective prediction of protein functions from protein-protein interaction networks

    PubMed Central

    2014-01-01

    Background Automated assignment of functions to unknown proteins is one of the most important task in computational biology. The development of experimental methods for genome scale analysis of molecular interaction networks offers new ways to infer protein function from protein-protein interaction (PPI) network data. Existing techniques for collective classification (CC) usually increase accuracy for network data, wherein instances are interlinked with each other, using a large amount of labeled data for training. However, the labeled data are time-consuming and expensive to obtain. On the other hand, one can easily obtain large amount of unlabeled data. Thus, more sophisticated methods are needed to exploit the unlabeled data to increase prediction accuracy for protein function prediction. Results In this paper, we propose an effective Markov chain based CC algorithm (ICAM) to tackle the label deficiency problem in CC for interrelated proteins from PPI networks. Our idea is to model the problem using two distinct Markov chain classifiers to make separate predictions with regard to attribute features from protein data and relational features from relational information. The ICAM learning algorithm combines the results of the two classifiers to compute the ranks of labels to indicate the importance of a set of labels to an instance, and uses an ICA framework to iteratively refine the learning models for improving performance of protein function prediction from PPI networks in the paucity of labeled data. Conclusion Experimental results on the real-world Yeast protein-protein interaction datasets show that our proposed ICAM method is better than the other ICA-type methods given limited labeled training data. This approach can serve as a valuable tool for the study of protein function prediction from PPI networks. PMID:24564855

  5. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

    PubMed Central

    2010-01-01

    Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming) experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor) that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/. PMID:20684769

  6. Aberrant expression of signaling proteins in essential thrombocythemia.

    PubMed

    Hui, Wuhan; Ye, Fei; Zhang, Wei; Liu, Congyan; Cui, Miao; Li, Wei; Xu, Juan; Zhang, David Y

    2013-09-01

    Dysregulated expression of signaling proteins may contribute to the pathophysiology of essential thrombocythemia (ET). This study aimed to characterize protein expression in ET and to correlate the dysregulated proteins with phenotypes and prognosis of ET patients. The expression of 128 proteins in peripheral blood neutrophils from 74 ET patients was assessed and compared with those from 29 healthy subjects and 35 polycythemia vera (PV) patients using protein pathway array. Fifteen proteins were differentially expressed between ET patients and normal controls. These dysregulated proteins were involved in the signaling pathways related with apoptosis and inflammation. Our results showed a significant overlap in protein expression between ET patients with JAK2V617F mutation and PV patients. In addition, nine proteins were associated with JAK2V617F mutation status in ET patients. Furthermore, estrogen receptor beta (ERβ) and Stat3 were independent risk factors for subsequent thrombosis during follow-up on multivariable analysis. Our study shows a broad dysregulation of signaling protein in ET patients, suggesting their roles in ET pathogenesis. The expression levels of ERβ and Stat3 could be promising predictors of subsequent thrombosis in ET patients. PMID:23639951

  7. Signaling Network Triggers and Membrane Physical Properties Control the Actin Cytoskeleton-Driven Isotropic Phase of Cell Spreading

    PubMed Central

    Rangamani, Padmini; Fardin, Marc-Antoine; Xiong, Yuguang; Lipshtat, Azi; Rossier, Olivier; Sheetz, Michael P.; Iyengar, Ravi

    2011-01-01

    Cell spreading is regulated by signaling from the integrin receptors that activate intracellular signaling pathways to control actin filament regulatory proteins. We developed a hybrid model of whole-cell spreading in which we modeled the integrin signaling network as ordinary differential equations in multiple compartments, and cell spreading as a three-dimensional stochastic model. The computed activity of the signaling network, represented as time-dependent activity levels of the actin filament regulatory proteins, is used to drive the filament dynamics. We analyzed the hybrid model to understand the role of signaling during the isotropic phase of fibroblasts spreading on fibronectin-coated surfaces. Simulations showed that the isotropic phase of spreading depends on integrin signaling to initiate spreading but not to maintain the spreading dynamics. Simulations predicted that signal flow in the absence of Cdc42 or WASP would reduce the spreading rate but would not affect the shape evolution of the spreading cell. These predictions were verified experimentally. Computational analyses showed that the rate of spreading and the evolution of cell shape are largely controlled by the membrane surface load and membrane bending rigidity, and changing information flow through the integrin signaling network has little effect. Overall, the plasma membrane acts as a damper such that only ∼5% of the actin dynamics capability is needed for isotropic spreading. Thus, the biophysical properties of the plasma membrane can condense varying levels of signaling network activities into a single cohesive macroscopic cellular behavior. PMID:21320428

  8. Activators of G Protein Signaling in the Kidney

    PubMed Central

    2015-01-01

    Heterotrimeric G proteins play a crucial role in regulating signal processing to maintain normal cellular homeostasis, and subtle perturbations in its activity can potentially lead to the pathogenesis of renal disorders or diseases. Cell-surface receptors and accessory proteins, which normally modify and organize the coupling of individual G protein subunits, contribute to the regulation of heterotrimeric G protein activity and their convergence and/or divergence of downstream signaling initiated by effector systems. Activators of G protein signaling (AGS) are a family of accessory proteins that intervene at multiple distinct points during the activation–inactivation cycle of G proteins, even in the absence of receptor stimulation. Perturbations in the expression of individual AGS proteins have been reported to modulate signal transduction pathways in a wide array of diseases and disorders within the brain, heart, immune system, and more recently, the kidney. This review will provide an overview of the expression profile, localization, and putative biologic role of the AGS family in the context of normal and diseased states of the kidney. PMID:25628392

  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 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

  11. 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

  12. 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

  13. Mechanical stress and network structure drive protein dynamics during cytokinesis

    PubMed Central

    Srivastava, Vasudha; Robinson, Douglas N.

    2015-01-01

    Summary Cell shape changes associated with processes like cytokinesis and motility proceed on several second time-scales, but are derived from molecular events, including protein-protein interactions, filament assembly, and force generation by molecular motors, all of which occur much faster [1–4]. Therefore, defining the dynamics of such molecular machinery is critical for understanding cell shape regulation. In addition to signaling pathways, mechanical stresses also direct cytoskeletal protein accumulation [5–7]. A myosin II-based mechanosensory system controls cellular contractility and shape during cytokinesis and under applied stress [6, 8]. In Dictyostelium, this system tunes myosin II accumulation by feedback through the actin network, particularly through the crosslinker cortexillin I. Cortexillin-binding IQGAPs are major regulators of this system. Here, we defined the short time-scale dynamics of key cytoskeletal proteins during cytokinesis and under mechanical stress using fluorescence recovery after photobleaching and fluorescence correlation spectroscopy, to examine the dynamic interplay between these proteins. Equatorially enriched proteins including cortexillin I, IQGAP2, and myosin II recovered much more slowly than actin and polar crosslinkers. The mobility of equatorial proteins was greatly reduced at the furrow compared to the interphase cortex, suggesting their stabilization during cytokinesis. This mobility shift did not arise from a single biochemical event, but rather from a global inhibition of protein dynamics by mechanical stress-associated changes in the cytoskeletal structure. Mechanical tuning of contractile protein dynamics provides robustness to the cytoskeletal framework responsible for regulating cell shape and contributes to cytokinesis fidelity. PMID:25702575

  14. Protein import into plant mitochondria: signals, machinery, processing, and regulation.

    PubMed

    Murcha, Monika W; Kmiec, Beata; Kubiszewski-Jakubiak, Szymon; Teixeira, Pedro F; Glaser, Elzbieta; Whelan, James

    2014-12-01

    The majority of more than 1000 proteins present in mitochondria are imported from nuclear-encoded, cytosolically synthesized precursor proteins. This impressive feat of transport and sorting is achieved by the combined action of targeting signals on mitochondrial proteins and the mitochondrial protein import apparatus. The mitochondrial protein import apparatus is composed of a number of multi-subunit protein complexes that recognize, translocate, and assemble mitochondrial proteins into functional complexes. While the core subunits involved in mitochondrial protein import are well conserved across wide phylogenetic gaps, the accessory subunits of these complexes differ in identity and/or function when plants are compared with Saccharomyces cerevisiae (yeast), the model system for mitochondrial protein import. These differences include distinct protein import receptors in plants, different mechanistic operation of the intermembrane protein import system, the location and activity of peptidases, the function of inner-membrane translocases in linking the outer and inner membrane, and the association/regulation of mitochondrial protein import complexes with components of the respiratory chain. Additionally, plant mitochondria share proteins with plastids, i.e. dual-targeted proteins. Also, the developmental and cell-specific nature of mitochondrial biogenesis is an aspect not observed in single-celled systems that is readily apparent in studies in plants. This means that plants provide a valuable model system to study the various regulatory processes associated with protein import and mitochondrial biogenesis. PMID:25324401

  15. 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

  16. An Improved Network Strain Filter for Detecting Transient Deformation Signals

    NASA Astrophysics Data System (ADS)

    Ohtani, R.; McGuire, J.; Segall, P.

    2008-12-01

    We have developed a tool to detect transient signals such as aseismic fault slip and magmatic intrusion automatically from large-scale (principally GPS) geodetic arrays, referred to as a Network Strain Filter (NSF). The NSF is capable of detecting transient signals in large data sets which may be difficult to identify by visual inspection of individual time series. The underlying principle is to exploit the spatially coherent nature of tectonic signals. The NSF models GPS displacement time series as a sum of contributions from tectonic transients, steady motion due to secular deformation, site-specific local benchmark motion, reference frame errors, and white noise. Transient deformation is represented by a spatial wavelet basis with time varying coefficients estimated using Kalman filtering techniques. A "hyperparameter" is also estimated to constrain the amount of temporal smoothness of the tectonic deformation. As station distribution is irregular and wavelets have local support (non-zero only over a localized domain), the design matrix is generally ill-conditioned. We investigate two strategies for regularizing the problem. The first is explicit spatial smoothing of the transient deformation. The second is to simply exclude wavelet bases that don't span some minimum number of stations. In this case, the smallest wavelet scale is determined such that the residual variance is consistent with the a priori errors of the data. Similarly the degree of spatial smoothing is determined by a priori knowledge of the data errors. To test the performance of the NSF, we carried out numerical tests using the southern California Integrated GPS Network (SCIGN) station distribution with synthetic transients of variable signal to noise ratio. We tested a six-year-long time series with a slow slip event with a duration of three years. Due to the long duration of the transient event, the contributions from secular motion and benchmark wobble make it difficult to identify the

  17. 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. PMID:25850092

  18. An integrative C. elegans protein-protein interaction network with reliability assessment based on a probabilistic graphical model.

    PubMed

    Huang, Xiao-Tai; Zhu, Yuan; Chan, Leanne Lai Hang; Zhao, Zhongying; Yan, Hong

    2016-01-01

    In Caenorhabditis elegans, a large number of protein-protein interactions (PPIs) are identified by different experiments. However, a comprehensive weighted PPI network, which is essential for signaling pathway inference, is not yet available in this model organism. Therefore, we firstly construct an integrative PPI network in C. elegans with 12,951 interactions involving 5039 proteins from seven molecular interaction databases. Then, a reliability score based on a probabilistic graphical model (RSPGM) is proposed to assess PPIs. It assumes that the random number of interactions between two proteins comes from the Bernoulli distribution to avoid multi-links. The main parameter of the RSPGM score contains a few latent variables which can be considered as several common properties between two proteins. Validations on high-confidence yeast datasets show that RSPGM provides more accurate evaluation than other approaches, and the PPIs in the reconstructed PPI network have higher biological relevance than that in the original network in terms of gene ontology, gene expression, essentiality and the prediction of known protein complexes. Furthermore, this weighted integrative PPI network in C. elegans is employed on inferring interaction path of the canonical Wnt/β-catenin pathway as well. Most genes on the inferred interaction path have been validated to be Wnt pathway components. Therefore, RSPGM is essential and effective for evaluating PPIs and inferring interaction path. Finally, the PPI network with RSPGM scores can be queried and visualized on a user interactive website, which is freely available at . PMID:26555698

  19. 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

  20. 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

  1. 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

  2. Ribo-Proteomics Approach to Profile RNA-Protein and Protein-Protein Interaction Networks.

    PubMed

    Yeh, Hsin-Sung; Chang, Jae-Woong; Yong, Jeongsik

    2016-01-01

    Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses. PMID:26965265

  3. Chemical approaches for investigating phosphorylation in signal transduction networks.

    PubMed

    Rothman, Deborah M; Shults, Melissa D; Imperiali, Barbara

    2005-09-01

    The power and scope of chemical synthesis offer considerable opportunities to broaden the lexicon of chemical tools that can be implemented for the study of complex biological systems. To investigate individual signaling proteins and pathways, chemical tools provide a powerful complement to existing genetic, chemical genetic and immunologic methods. In particular, understanding phosphorylation-mediated signaling in real time yields important information about the regulation of cellular function and insights into the origin of disease. Recent advances in the development of photolabile caged analogs of bioactive species and fluorescence-based sensors of protein kinase activities are useful for investigating protein phosphorylation and the roles of phosphoproteins. Photolabile caged analogs allow spatial and temporal control over the release of a compound, while fluorescence-based sensors allow the real-time visualization of kinase activity. Here, we discuss recent advances that have increased the specificity and availability of these tools. PMID:16084095

  4. Heterotrimeric G protein signalling in the plant kingdom

    PubMed Central

    Urano, Daisuke; Chen, Jin-Gui; Botella, José Ramón; Jones, Alan M.

    2013-01-01

    In animals, heterotrimeric G proteins, comprising α-, β-and γ-subunits, perceive extracellular stimuli through cell surface receptors, and transmit signals to ion channels, enzymes and other effector proteins to affect numerous cellular behaviours. In plants, G proteins have structural similarities to the corresponding molecules in animals but transmit signals by atypical mechanisms and effector proteins to control growth, cell proliferation, defence, stomate movements, channel regulation, sugar sensing and some hormonal responses. In this review, we summarize the current knowledge on the molecular regulation of plant G proteins, their effectors and the physiological functions studied mainly in two model organisms: Arabidopsis thaliana and rice (Oryza sativa). We also look at recent progress on structural analyses, systems biology and evolutionary studies. PMID:23536550

  5. PRDM Proteins: Molecular Mechanisms in Signal Transduction and Transcriptional Regulation.

    PubMed

    Di Zazzo, Erika; De Rosa, Caterina; Abbondanza, Ciro; Moncharmont, Bruno

    2013-01-01

    PRDM (PRDI-BF1 and RIZ homology domain containing) protein family members are characterized by the presence of a PR domain and a variable number of Zn-finger repeats. Experimental evidence has shown that the PRDM proteins play an important role in gene expression regulation, modifying the chromatin structure either directly, through the intrinsic methyltransferase activity, or indirectly through the recruitment of chromatin remodeling complexes. PRDM proteins have a dual action: they mediate the effect induced by different cell signals like steroid hormones and control the expression of growth factors. PRDM proteins therefore have a pivotal role in the transduction of signals that control cell proliferation and differentiation and consequently neoplastic transformation. In this review, we describe pathways in which PRDM proteins are involved and the molecular mechanism of their transcriptional regulation. PMID:24832654

  6. PRDM Proteins: Molecular Mechanisms in Signal Transduction and Transcriptional Regulation

    PubMed Central

    Di Zazzo, Erika; De Rosa, Caterina; Abbondanza, Ciro; Moncharmont, Bruno

    2013-01-01

    PRDM (PRDI-BF1 and RIZ homology domain containing) protein family members are characterized by the presence of a PR domain and a variable number of Zn-finger repeats. Experimental evidence has shown that the PRDM proteins play an important role in gene expression regulation, modifying the chromatin structure either directly, through the intrinsic methyltransferase activity, or indirectly through the recruitment of chromatin remodeling complexes. PRDM proteins have a dual action: they mediate the effect induced by different cell signals like steroid hormones and control the expression of growth factors. PRDM proteins therefore have a pivotal role in the transduction of signals that control cell proliferation and differentiation and consequently neoplastic transformation. In this review, we describe pathways in which PRDM proteins are involved and the molecular mechanism of their transcriptional regulation. PMID:24832654

  7. 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

  8. Multitask Learning of Signaling and Regulatory Networks with Application to Studying Human Response to Flu

    PubMed Central

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

    2014-01-01

    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

  9. 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

  10. 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.

  11. RNAi screening reveals a large signaling network controlling the Golgi apparatus in human cells

    PubMed Central

    Chia, Joanne; Goh, Germaine; Racine, Victor; Ng, Susanne; Kumar, Pankaj; Bard, Frederic

    2012-01-01

    The Golgi apparatus has many important physiological functions, including sorting of secretory cargo and biosynthesis of complex glycans. These functions depend on the intricate and compartmentalized organization of the Golgi apparatus. To investigate the mechanisms that regulate Golgi architecture, we developed a quantitative morphological assay using three different Golgi compartment markers and quantitative image analysis, and performed a kinome- and phosphatome-wide RNAi screen in HeLa cells. Depletion of 159 signaling genes, nearly 20% of genes assayed, induced strong and varied perturbations in Golgi morphology. Using bioinformatics data, a large regulatory network could be constructed. Specific subnetworks are involved in phosphoinositides regulation, acto-myosin dynamics and mitogen activated protein kinase signaling. Most gene depletion also affected Golgi functions, in particular glycan biosynthesis, suggesting that signaling cascades can control glycosylation directly at the Golgi level. Our results provide a genetic overview of the signaling pathways that control the Golgi apparatus in human cells. PMID:23212246

  12. 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

  13. Giardia mitosomal protein import machinery differentially recognizes mitochondrial targeting signals.

    PubMed

    Nyindodo-Ogari, Lilian; Schwartzbach, Steven D; Estraño, Carlos E

    2014-01-01

    Giardia lamblia mitosomes are believed to be vestigial mitochondria which lack a genome. Similar to higher eukaryotes, mitosomal proteins possess either N-terminal or internal mitosomal targeting sequences. To date, some components of the higher eukaryote archetypal mitochondrial protein import apparatus have been identified and characterized in Giardia mitosomes; therefore, it is expected that mitochondrial signals will be recognized by the mitosomal protein import system. To further determine the level of conservation of the Giardia mitosome protein import apparatus, we expressed mitochondrial proteins from higher eukaryotes in Giardia. These recombinant proteins include Tom20 and Tom22; two components of the mitochondrial protein import machinery. Our results indicate that N-terminal mitochondrial targeting sequence is recognized by the mitosomal protein import machinery; however, interestingly the internal mitochondrial targeting sequences of higher eukaryotes are not recognized by the mitosome. Our results indicate that Giardia mitosome protein transport machinery shows differential recognition of higher eukaryotic mitochondria transfer signals, suggesting a divergence of the transport system in G. lamblia. Therefore, our data support the hypothesis that the protein import machinery in Giardia lamblia mitosome is an incomplete vestigial derivative of mitochondria components. PMID:25159305

  14. Network analysis of reverse phase protein expression data: Characterizing protein signatures in acute myeloid leukemia cytogenetic categories t(8;21) and inv(16)

    PubMed Central

    York, Heather; Kornblau, Steven M.; Qutub, Amina Ann

    2015-01-01

    Acute myeloid leukemia (AML) patients present with cancerous cells originating from bone marrow. Proteomic data on AML patient cells provides critical information on the key molecules associated with the disease. Here, we introduce a new computational approach to identify complex patterns in protein signaling from reverse phase protein array data. We analyzed the expression of 203 proteins in cells taken from AML patients. Dominant overlapping protein networks between subtypes of AML patients were characterized computationally, through a paired t-test approach looking at relative protein expression. In the first application of this method, we compared recurrent cytogenetic abnormalities inv(16) and t(8;21), both affecting core-binding factor (CBFβ), to normal CD34+ cells and to each other. Six hundred seventy-eight sets of proteins were identified as significantly different in both inv(16) and t(8;21) compared to controls, at the Bonferroni number, α < 2.44 × 10−6. We strengthened our predictions by comparing results to those obtained using lasso regression analysis. Signaling networks were constructed from the protein pairs that were significantly different in the t-test and lasso regression analysis. Predicted networks were also compared to known networks from public protein–protein interaction and signaling databases. By characterizing unique “protein signatures” through this rapid computational analysis, and placing them in the context of canonical biological networks, we identify signaling pathways distinct to subcategories of AML patients. PMID:22623292

  15. Systematic Analysis of Essential Genes Reveals New Regulators of G protein Signaling

    PubMed Central

    Cappell, Steven D.; Baker, Rachael; Skowyra, Dorota; Dohlman, Henrik G.

    2010-01-01

    SUMMARY The yeast pheromone pathway consists of a canonical heterotrimeric G protein and MAP kinase cascade. To identify new signaling components we systematically evaluated 870 essential genes using a library of repressible-promoter strains. Quantitative transcription-reporter and MAPK activity assays were used to identify strains that exhibit altered pheromone sensitivity. Of the 92 newly identified essential genes required for proper G protein signaling, those involved with protein degradation were most highly-represented. Included in this group are members of the SCF (Skp-Cullin-F-Box) ubiquitin ligase complex. Further genetic and biochemical analysis reveals that SCFCdc4 acts together with the Cdc34 ubiquitin conjugating enzyme at the level of the G protein, promotes degradation of the G protein α subunit, Gpa1, in vivo and catalyzes Gpa1 ubiquitination in vitro. These new insights to the G protein signaling network reveal the essential-genome as an untapped resource for identifying new components and regulators of signal transduction pathways. PMID:20542006

  16. 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

  17. Regulation of Bone Morphogenetic Protein Signaling by ADP-ribosylation.

    PubMed

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

    2016-06-10

    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

  18. Modeling of cortical signals using echo state networks

    NASA Astrophysics Data System (ADS)

    Zhou, Hanying; Wang, Yongji; Huang, Jiangshuai

    2009-10-01

    Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recordings collected from relevant regions of a monkey's brain while the outputs are the associated behavior which is typically the 2-D or 3-D hand position of a primate. Here our task is to set up a proper model in order to figure out the move trajectories by input the neural signals which are simultaneously collected in the experiment. In this paper, we propose to use Echo State Networks (ESN) to map the neural firing activities into hand positions. ESN is a newly developed recurrent neural network(RNN) model. Besides its dynamic property and short term memory just as other recurrent neural networks have, it has a special echo state property which endows it with the ability to model nonlinear dynamic systems powerfully. What distinguished it from transitional recurrent neural networks most significantly is its special learning method. In this paper we train this net with a refined version of its typical training method and get a better model.

  19. 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

  20. 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

  1. A Least Square Method Based Model for Identifying Protein Complexes in Protein-Protein Interaction Network

    PubMed Central

    Dai, Qiguo; Guo, Maozu; Guo, Yingjie; Liu, Xiaoyan; Liu, Yang; Teng, Zhixia

    2014-01-01

    Protein complex formed by a group of physical interacting proteins plays a crucial role in cell activities. Great effort has been made to computationally identify protein complexes from protein-protein interaction (PPI) network. However, the accuracy of the prediction is still far from being satisfactory, because the topological structures of protein complexes in the PPI network are too complicated. This paper proposes a novel optimization framework to detect complexes from PPI network, named PLSMC. The method is on the basis of the fact that if two proteins are in a common complex, they are likely to be interacting. PLSMC employs this relation to determine complexes by a penalized least squares method. PLSMC is applied to several public yeast PPI networks, and compared with several state-of-the-art methods. The results indicate that PLSMC outperforms other methods. In particular, complexes predicted by PLSMC can match known complexes with a higher accuracy than other methods. Furthermore, the predicted complexes have high functional homogeneity. PMID:25405206

  2. 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

  3. 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.

  4. Emerging Role of Protein-Protein Transnitrosylation in Cell Signaling Pathways

    PubMed Central

    2013-01-01

    Abstract Significance: Protein S-nitrosylation, a covalent reaction of a nitric oxide (NO) group with a critical protein thiol (or more properly thiolate anion), mediates an important form of redox-related signaling as well as aberrant signaling in disease states. Recent Advances: A growing literature suggests that over 3000 proteins are S-nitrosylated in cell systems. Our laboratory and several others have demonstrated that protein S-nitrosylation can regulate protein function by directly inhibiting catalytically active cysteines, by reacting with allosteric sites, or via influencing protein-protein interaction. For example, S-nitrosylation of critical cysteine thiols in protein-disulfide isomerase and in parkin alters their activity, thus contributing to protein misfolding in Parkinson's disease. Critical Issues: However, the mechanism by which specific protein S-nitrosylation occurs in cell signaling pathways is less well investigated. Interestingly, the recent discovery of protein-protein transnitrosylation reactions (transfer of an NO group from one protein to another) has revealed a unique mechanism whereby NO can S-nitrosylate a particular set of protein thiols, and represents a major class of nitrosylating/denitrosylating enzymes in mammalian systems. In this review, we will discuss recent evidence for transnitrosylation reactions between (i) hemoglobin/anion exchanger 1, (ii) thioredoxin/caspase-3, (iii) X-linked inhibitor of apoptosis/caspase-3, (iv) GAPDH-HDAC2/SIRT1/DNA-PK, and (v) Cdk5/dynamin related protein 1 (Drp1). This review also discusses experimental techniques useful in characterizing protein-protein transnitrosylations. Future Directions: Elucidation of additional transnitrosylation cascades will further our understanding of the enzymes that catalyze nitrosation, thereby contributing to NO-mediated signaling pathways. Antioxid. Redox Signal. 18, 239–249. PMID:22657837

  5. 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

  6. Spatiotemporal Control of Cell Signalling Using A Light-Switchable Protein Interaction

    PubMed Central

    Levskaya, Anselm; Weiner, Orion D.; Lim, Wendell A.; Voigt, Christopher A.

    2010-01-01

    Genetically-encodable optical reporters, such as Green Fluorescent Protein, have revolutionized the observation and measurement of cellular states. However, the inverse challenge of using light to precisely control cellular behavior has only recently begun to be addressed; semi-synthetic chromophore-tethered receptors1 and naturally-occurring channel rhodopsins have been used to directly perturb neuronal networks2,3. The difficulty of engineering light sensitive proteins remains a significant impediment to the optical control to most cell-biological processes. Here we demonstrate the use of a new genetically-encoded light-control system based on an optimized reversible protein-protein interaction from the phytochrome signaling network of Arabidopsis thaliana. Because protein-protein interactions are one of the most general currencies of cellular information, this system can in principal be generically used to control diverse functions. Here we show that this system can be used to precisely and reversibly translocate target proteins to the membrane with micrometer spatial resolution and second time resolution. We show that light-gated translocation of the upstream activators of rho-family GTPases, which control the actin cytoskeleton, can be used to precisely reshape and direct the cell morphology of mammalian cells. The light-gated protein-protein interaction that has been optimized in this work should be useful for the design of diverse light-programmable reagents, potentially enabling a new generation of perturbative, quantitative experiments in cell biology. PMID:19749742

  7. Spatiotemporal control of cell signalling using a light-switchable protein interaction.

    PubMed

    Levskaya, Anselm; Weiner, Orion D; Lim, Wendell A; Voigt, Christopher A

    2009-10-15

    Genetically encodable optical reporters, such as green fluorescent protein, have revolutionized the observation and measurement of cellular states. However, the inverse challenge of using light to control precisely cellular behaviour has only recently begun to be addressed; semi-synthetic chromophore-tethered receptors and naturally occurring channel rhodopsins have been used to perturb directly neuronal networks. The difficulty of engineering light-sensitive proteins remains a significant impediment to the optical control of most cell-biological processes. Here we demonstrate the use of a new genetically encoded light-control system based on an optimized, reversible protein-protein interaction from the phytochrome signalling network of Arabidopsis thaliana. Because protein-protein interactions are one of the most general currencies of cellular information, this system can, in principle, be generically used to control diverse functions. Here we show that this system can be used to translocate target proteins precisely and reversibly to the membrane with micrometre spatial resolution and at the second timescale. We show that light-gated translocation of the upstream activators of Rho-family GTPases, which control the actin cytoskeleton, can be used to precisely reshape and direct the cell morphology of mammalian cells. The light-gated protein-protein interaction that has been optimized here should be useful for the design of diverse light-programmable reagents, potentially enabling a new generation of perturbative, quantitative experiments in cell biology. PMID:19749742

  8. Identification of Protein Interactions Involved in Cellular Signaling

    PubMed Central

    Westermarck, Jukka; Ivaska, Johanna; Corthals, Garry L.

    2013-01-01

    Protein-protein interactions drive biological processes. They are critical for all intra- and extracellular functions, and the technologies to analyze them are widely applied throughout the various fields of biological sciences. This study takes an in-depth view of some common principles of cellular regulation and provides a detailed account of approaches required to comprehensively map signaling protein-protein interactions in any particular cellular system or condition. We provide a critical review of the benefits and disadvantages of the yeast two-hybrid method and affinity purification coupled with mass spectrometric procedures for identification of signaling protein-protein interactions. In particular, we emphasize the quantitative and qualitative differences between tandem affinity and one-step purification (such as FLAG and Strep tag) methods. Although applicable to all types of interaction studies, a special section is devoted in this review to aspects that should be considered when attempting to identify signaling protein interactions that often are transient and weak by nature. Finally, we discuss shotgun and quantitative information that can be gleaned by MS-coupled methods for analysis of multiprotein complexes. PMID:23481661

  9. 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

  10. 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

  11. Surface sensing and signaling networks in plant pathogenic fungi.

    PubMed

    Kou, Yanjun; Naqvi, Naweed I

    2016-09-01

    Pathogenic fungi have evolved highly varied and remarkable strategies to invade and infect their plant hosts. Typically, such fungal pathogens utilize highly specialized infection structures, morphologies or cell types produced from conidia or ascospores on the cognate host surfaces to gain entry therein. Such diverse infection strategies require intricate coordination in cell signaling and differentiation in phytopathogenic fungi. Here, we present an overview of our current understanding of cell signaling and infection-associated development that primes host penetration in the top ten plant pathogenic fungi, which utilize specific receptors to sense and respond to different surface cues, such as topographic features, hydrophobicity, hardness, plant lipids, phytohormones, and/or secreted enzymes. Subsequently, diverse signaling components such as G proteins, cyclic AMP/Protein Kinase A and MAP kinases are activated to enable the differentiation of infection structures. Recent studies have also provided fascinating insights into the spatio-temporal dynamics and specialized sequestration and trafficking of signaling moieties required for proper development of infection structures in phytopathogenic fungi. Molecular insight in such infection-related morphogenesis and cell signaling holds promise for identifying novel strategies for intervention of fungal diseases in plants. PMID:27133541

  12. Protein-protein-interaction Network Organization of the Hypusine Modification System*

    PubMed Central

    Sievert, Henning; Venz, Simone; Platas-Barradas, Oscar; Dhople, Vishnu M.; Schaletzky, Martin; Nagel, Claus-Henning; Braig, Melanie; Preukschas, Michael; Pällmann, Nora; Bokemeyer, Carsten; Brümmendorf, Tim H.; Pörtner, Ralf; Walther, Reinhard; Duncan, Kent E.; Hauber, Joachim; Balabanov, Stefan

    2012-01-01

    Hypusine modification of eukaryotic initiation factor 5A (eIF-5A) represents a unique and highly specific post-translational modification with regulatory functions in cancer, diabetes, and infectious diseases. However, the specific cellular pathways that are influenced by the hypusine modification remain largely unknown. To globally characterize eIF-5A and hypusine-dependent pathways, we used an approach that combines large-scale bioreactor cell culture with tandem affinity purification and mass spectrometry: “bioreactor-TAP-MS/MS.” By applying this approach systematically to all four components of the hypusine modification system (eIF-5A1, eIF-5A2, DHS, and DOHH), we identified 248 interacting proteins as components of the cellular hypusine network, with diverse functions including regulation of translation, mRNA processing, DNA replication, and cell cycle regulation. Network analysis of this data set enabled us to provide a comprehensive overview of the protein-protein interaction landscape of the hypusine modification system. In addition, we validated the interaction of eIF-5A with some of the newly identified associated proteins in more detail. Our analysis has revealed numerous novel interactions, and thus provides a valuable resource for understanding how this crucial homeostatic signaling pathway affects different cellular functions. PMID:22888148

  13. 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. PMID:24642838

  14. Detecting Overlapping Protein Complexes by Rough-Fuzzy Clustering in Protein-Protein Interaction Networks

    PubMed Central

    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. PMID:24642838

  15. Joint clustering of protein interaction networks through Markov random walk

    PubMed Central

    2014-01-01

    Biological networks obtained by high-throughput profiling or human curation are typically noisy. For functional module identification, single network clustering algorithms may not yield accurate and robust results. In order to borrow information across multiple sources to alleviate such problems due to data quality, we propose a new joint network clustering algorithm ASModel in this paper. We construct an integrated network to combine network topological information based on protein-protein interaction (PPI) datasets and homological information introduced by constituent similarity between proteins across networks. A novel random walk strategy on the integrated network is developed for joint network clustering and an optimization problem is formulated by searching for low conductance sets defined on the derived transition matrix of the random walk, which fuses both topology and homology information. The optimization problem of joint clustering is solved by a derived spectral clustering algorithm. Network clustering using several state-of-the-art algorithms has been implemented to both PPI networks within the same species (two yeast PPI networks and two human PPI networks) and those from different species (a yeast PPI network and a human PPI network). Experimental results demonstrate that ASModel outperforms the existing single network clustering algorithms as well as another recent joint clustering algorithm in terms of complex prediction and Gene Ontology (GO) enrichment analysis. PMID:24565376

  16. Joint clustering of protein interaction networks through Markov random walk.

    PubMed

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

    Biological networks obtained by high-throughput profiling or human curation are typically noisy. For functional module identification, single network clustering algorithms may not yield accurate and robust results. In order to borrow information across multiple sources to alleviate such problems due to data quality, we propose a new joint network clustering algorithm ASModel in this paper. We construct an integrated network to combine network topological information based on protein-protein interaction (PPI) datasets and homological information introduced by constituent similarity between proteins across networks. A novel random walk strategy on the integrated network is developed for joint network clustering and an optimization problem is formulated by searching for low conductance sets defined on the derived transition matrix of the random walk, which fuses both topology and homology information. The optimization problem of joint clustering is solved by a derived spectral clustering algorithm. Network clustering using several state-of-the-art algorithms has been implemented to both PPI networks within the same species (two yeast PPI networks and two human PPI networks) and those from different species (a yeast PPI network and a human PPI network). Experimental results demonstrate that ASModel outperforms the existing single network clustering algorithms as well as another recent joint clustering algorithm in terms of complex prediction and Gene Ontology (GO) enrichment analysis. PMID:24565376

  17. Spatial and functional organization of mitochondrial protein network

    PubMed Central

    Yang, Jae-Seong; Kim, Jinho; Park, Solip; Jeon, Jouhyun; Shin, Young-Eun; Kim, Sanguk

    2013-01-01

    Characterizing the spatial organization of the human mitochondrial proteome will enhance our understanding of mitochondrial functions at the molecular level and provide key insight into protein-disease associations. However, the sub-organellar location and possible association with mitochondrial diseases are not annotated for most mitochondrial proteins. Here, we characterized the functional and spatial organization of mitochondrial proteins by assessing their position in the Mitochondrial Protein Functional (MPF) network. Network position was assigned to the MPF network and facilitated the determination of sub-organellar location and functional organization of mitochondrial proteins. Moreover, network position successfully identified candidate disease genes of several mitochondrial disorders. Thus, our data support the use of network position as a novel method to explore the molecular function and pathogenesis of mitochondrial proteins. PMID:23466738

  18. Modularity in the evolution of yeast protein interaction network

    PubMed Central

    Ogishima, Soichi; Tanaka, Hiroshi; Nakaya, Jun

    2015-01-01

    Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution. PMID:25914446

  19. Decoding signals for membrane protein assembly using alkaline phosphatase fusions.

    PubMed Central

    McGovern, K; Ehrmann, M; Beckwith, J

    1991-01-01

    We have used genetic methods to investigate the role of the different domains of a bacterial cytoplasmic membrane protein, MalF, in determining its topology. This was done by analyzing the effects of MalF topology of deleting various domains of the protein using MalF-alkaline phosphatase fusion proteins. Our results show that the cytoplasmic domains of the protein are the pre-eminent topogenic signals. These domains contain information that determines their cytoplasmic location and, thus, the orientation of the membrane spanning segments surrounding them. Periplasmic domains do not appear to have equivalent information specifying their location and membrane spanning segments do not contain information defining their orientation in the membrane. The strength of cytoplasmic domains as topogenic signals varies, correlated with the density of positively charged amino acids within them. Images PMID:1915262

  20. Isoelectric focusing technology quantifies protein signaling in 25 cells

    PubMed Central

    O'Neill, Roger A.; Bhamidipati, Arunashree; Bi, Xiahui; Deb-Basu, Debabrita; Cahill, Linda; Ferrante, Jason; Gentalen, Erik; Glazer, Marc; Gossett, John; Hacker, Kevin; Kirby, Celeste; Knittle, James; Loder, Robert; Mastroieni, Catherine; MacLaren, Michael; Mills, Thomas; Nguyen, Uyen; Parker, Nineveh; Rice, Audie; Roach, David; Suich, Daniel; Voehringer, David; Voss, Karl; Yang, Jade; Yang, Tom; Vander Horn, Peter B.

    2006-01-01

    A previously undescribed isoelectric focusing technology allows cell signaling to be quantitatively assessed in <25 cells. High-resolution capillary isoelectric focusing allows isoforms and individual phosphorylation forms to be resolved, often to baseline, in a 400-nl capillary. Key to the method is photochemical capture of the resolved protein forms. Once immobilized, the proteins can be probed with specific antibodies flowed through the capillary. Antibodies bound to their targets are detected by chemiluminescence. Because chemiluminescent substrates are flowed through the capillary during detection, localized substrate depletion is overcome, giving excellent linearity of response across several orders of magnitude. By analyzing pan-specific antibody signals from individual resolved forms of a protein, each of these can be quantified, without the problems associated with using multiple antibodies with different binding avidities to detect individual protein forms. PMID:17053065

  1. 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

  2. Caffeic acid phenethyl ester suppresses the proliferation of human prostate cancer cells through inhibition of AMPK and Akt signaling networks

    PubMed Central

    Chuu, Chih-Pin; Lin, Hui-Ping; Ciaccio, Mark F.; Kokontis, John M.; Hause, Ronald J.; Hiipakka, Richard A.; Liao, Shutsung; Jones, Richard Baker

    2016-01-01

    Caffeic acid phenethyl ester (CAPE) is a bioactive component derived from honeybee hive propolis. CAPE has been shown to have anti-mitogenic, anti-carcinogenic, and other beneficial medicinal properties. Many of its effects have been shown to be mediated through its inhibition of NF-κB signaling pathways. We took a systematic approach to uncover CAPE’s effects from hours to days on the signaling networks in human prostate cancer cells. We observed that CAPE dosage-dependently suppressed the proliferation of LNCaP, DU-145, and PC-3 human prostate cancer cells. Administration of CAPE by gavage significantly inhibited the tumor growth of LNCaP xenografts in nude mice. Using LNCaP cells as a model system, we examined CAPE’s effect on gene expression, protein signaling, and transcriptional regulatory networks using Micro-Western Arrays and PCR arrays. We built a model of CAPE’s impact on cell signaling which suggested that it acted through inhibition of Akt-related protein signaling networks. Over-expression of Akt1 or cMyc, a downstream target of Akt signaling, significantly blocked the anti-proliferative effects of CAPE. In summary, our results suggest that CAPE administration may be useful as an adjuvant therapy for prostate and potentially other types of cancers that are driven by the AMPK and Akt signaling networks. PMID:22562408

  3. Science Signaling Podcast for 12 July 2016: Adaptor proteins limit signaling.

    PubMed

    Wiley, H Steven; VanHook, Annalisa M

    2016-01-01

    This Podcast features an interview with Steven Wiley, senior author of a Research Article that appears in the 12 July 2016 issue of Science Signaling, about how the abundance of adaptor proteins and feedback regulators affect the flow of information downstream of the epidermal growth factor receptor (EGFR). Information flows through a signaling pathway by sequential interactions between core components of the pathway, many of which have enzymatic activity. Adaptor proteins do not directly participate in relaying the signal and do not have enzymatic activity, but are important for signaling because they facilitate interactions between the core components. Using quantitative methods, Shi et al demonstrated that core components of the EGFR pathway were highly abundant in both normal cells and cancer cells. However, adaptor proteins were present in much lower abundance in both cell types, indicating that it is the abundance of these proteins that limit signaling downstream of EGFR. The authors also found that differences in EGFR signaling between different cell types likely resulted from the variable abundance of feedback regulators.Listen to Podcast. PMID:27405978

  4. A novel functional module detection algorithm for protein-protein interaction networks

    PubMed Central

    Hwang, Woochang; Cho, Young-Rae; Zhang, Aidong; Ramanathan, Murali

    2006-01-01

    Background The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clustering and detecting functional modules in protein-protein interaction networks, termed STM. Results STM selects representative proteins for each cluster and iteratively refines clusters based on a combination of the signal transduced and graph topology. STM is found to be effective at detecting clusters with a diverse range of interaction structures that are significant on measures of biological relevance. The STM approach is compared to six competing approaches including the maximum clique, quasi-clique, minimum cut, betweeness cut and Markov Clustering (MCL) algorithms. The clusters obtained by each technique are compared for enrichment of biological function. STM generates larger clusters and the clusters identified have p-values that are approximately 125-fold better than the other methods on biological function. An important strength of STM is that the percentage of proteins that are discarded to create clusters is much lower than the other approaches. Conclusion STM outperforms competing approaches and is capable of effectively detecting both densely and sparsely connected, biologically relevant functional modules with fewer discards. PMID:17147822

  5. 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.

  6. Regulation of Phagocyte Migration by Signal Regulatory Protein-Alpha Signaling

    PubMed Central

    Alvarez-Zarate, Julian; Matlung, Hanke L.; Matozaki, Takashi; Kuijpers, Taco W.; Maridonneau-Parini, Isabelle; van den Berg, Timo K.

    2015-01-01

    Signaling through the inhibitory receptor signal regulatory protein-alpha (SIRPα) controls effector functions in phagocytes. However, there are also indications that interactions between SIRPα and its ligand CD47 are involved in phagocyte transendothelial migration. We have investigated the involvement of SIRPα signaling in phagocyte migration in vitro and in vivo using mice that lack the SIRPα cytoplasmic tail. During thioglycolate-induced peritonitis in SIRPα mutant mice, both neutrophil and macrophage influx were found to occur, but to be significantly delayed. SIRPα signaling appeared to be essential for an optimal transendothelial migration and chemotaxis, and for the amoeboid type of phagocyte migration in 3-dimensional environments. These findings demonstrate, for the first time, that SIRPα signaling can directly control phagocyte migration, and this may contribute to the impaired inflammatory phenotype that has been observed in the absence of SIRPα signaling. PMID:26057870

  7. Exploring signal transduction in heteromultimeric protein based on energy dissipation model.

    PubMed

    Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

    2015-01-01

    Dynamic intersubunit interactions are key elements in the regulation of many biological systems. A better understanding of how subunits interact with each other and how their interactions are related to dynamic protein structure is a fundamental task in biology. In this paper, a heteromultimeric allosteric protein, Corynebacterium glutamicum aspartokinase, is used as a model system to explore the signal transduction involved in intersubunit interactions and allosteric communication with an emphasis on the intersubunit signaling process. For this purpose, energy dissipation simulation and network construction are conducted for each subunit and the whole protein. Comparison with experimental results shows that the new approach is able to predict all the mutation sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. Additionally, analysis revealed that the function of the effector threonine is to facilitate the binding of the two subunits without contributing to the allosteric communication. During the allosteric regulation upon the binding of the effector lysine, signals can be transferred from the β-subunit to the catalytic site of the α-subunit through both a direct way of intersubunit signal transduction, and an indirect way: first, to the regulatory region of the α-subunit by intersubunit signal transduction and then to the catalytic region by intramolecular signal transduction. Therefore, the new approach is able to illustrate the diversity of the underlying mechanisms when the strength of feedback inhibition by the effector(s) is modulated, providing useful information that has potential applications in engineering heteromultimeric allosteric regulation. PMID:24279729

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  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. 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

  15. Signalling design and architecture for a proposed mobile satellite network

    NASA Technical Reports Server (NTRS)

    Yan, T.-Y.; Cheng, U.; Wang, C.

    1990-01-01

    In a frequency-division/demand-assigned multiple-access (FD/DAMA) architecture, each mobile subscriber must make a connection request to the Network Management Center before transmission for either open-end or closed-end services. Open-end services are for voice calls and long file transfer and are processed on a blocked-call-cleared basis. Closed-end services are for transmitting burst data and are processed on a first-come first-served basis. This paper presents the signalling design and architecture for non-voice services of an FD/DAMA mobile satellite network. The connection requests are made through the recently proposed multiple channel collision resolution scheme which provides a significantly higher throughput than the traditional slotted ALOHA scheme. For non-voice services, it is well known that retransmissions are necessary to ensure the delivery of a message in its entirety from the source to destination. Retransmission protocols for open-end and closed-end data transfer are investigated. The signal structure for the proposed network is derived from X-25 standards with appropriate modifications. The packet types and their usages are described in this paper.

  16. Microglia Control Neuronal Network Excitability via BDNF Signalling

    PubMed Central

    2013-01-01

    Microglia-neuron interactions play a crucial role in several neurological disorders characterized by altered neural network excitability, such as epilepsy and neuropathic pain. While a series of potential messengers have been postulated as substrates of the communication between microglia and neurons, including cytokines, purines, prostaglandins, and nitric oxide, the specific links between messengers, microglia, neuronal networks, and diseases have remained elusive. Brain-derived neurotrophic factor (BDNF) released by microglia emerges as an exception in this riddle. Here, we review the current knowledge on the role played by microglial BDNF in controlling neuronal excitability by causing disinhibition. The efforts made by different laboratories during the last decade have collectively provided a robust mechanistic paradigm which elucidates the mechanisms involved in the synthesis and release of BDNF from microglia, the downstream TrkB-mediated signals in neurons, and the biophysical mechanism by which disinhibition occurs, via the downregulation of the K+-Cl− cotransporter KCC2, dysrupting Cl−homeostasis, and hence the strength of GABAA- and glycine receptor-mediated inhibition. The resulting altered network activity appears to explain several features of the associated pathologies. Targeting the molecular players involved in this canonical signaling pathway may lead to novel therapeutic approach for ameliorating a wide array of neural dysfunctions. PMID:24089642

  17. Investigation of Protein-Protein Interactions and Conformational Changes in Hedgehog Signaling Pathway by FRET.

    PubMed

    Fu, Lin; Lv, Xiangdong; Xiong, Yue; Zhao, Yun

    2015-01-01

    Protein-protein interactions and signal-induced protein conformational changes are fundamental molecular events that are considered as essential in modern life sciences. Among various techniques developed to study such phenomena, fluorescence resonance energy transfer (FRET) is a widely used method with many advantages in detecting these molecular events. Here, we describe the application of FRET in the mechanistic investigation of cell signal transduction, taking the example of the Hh signaling pathway, which plays a critical role in embryonic development and tissue homeostasis. A number of general guidelines as well as some key notes have been summarized as a protocol for reader's reference. PMID:26179039

  18. Structural Reconstruction of Protein-Protein Complexes Involved in Intracellular Signaling.

    PubMed

    Kirsch, Klára; Sok, Péter; Reményi, Attila

    2016-01-01

    Signaling complexes within the cell convert extracellular cues into physiological outcomes. Their assembly involves signaling enzymes, allosteric regulators and scaffold proteins that often contain long stretches of disordered protein regions, display multi-domain architectures, and binding affinity between individual components is low. These features are indispensable for their central roles as dynamic information processing hubs, on the other hand they also make reconstruction of structurally homogeneous complex samples highly challenging. In this present chapter we discuss protein machinery which influences extracellular signal reception, intracellular pathway activity, and cytoskeletal or transcriptional activity. PMID:27165334

  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. Exploiting the yeast stress-activated signaling network to inform on stress biology and disease signaling

    PubMed Central

    Ho, Yi-Hsuan

    2016-01-01

    Healthy cells utilize intricate systems to monitor their environment and mount robust responses in the event of cellular stress. Whether stress arises from external insults or defects due to mutation and disease, cells must be able to respond precisely to mount the appropriate defenses. Multi-faceted stress responses are generally coupled with arrest of growth and cell-cycle progression, which both limits the transmission of damaged materials and serves to reallocate limited cellular resources toward defense. Therefore, stress defense versus rapid growth represent competing interests in the cell. How eukaryotic cells set the balance between defense versus proliferation, and in particular knowledge of the regulatory networks that control this decision, are poorly understood. In this perspective, we expand upon our recent work inferring the stress-activated signaling network in budding yeast, which captures pathways controlling stress defense and regulators of growth and cell-cycle progression. We highlight similarities between the yeast and mammalian stress responses and explore how stress-activated signaling networks in yeast can inform on signaling defects in human cancers. PMID:25957506

  2. Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

    SciTech Connect

    Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

    2012-03-29

    To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

  3. Transcription factor and microRNA-regulated network motifs for cancer and signal transduction networks

    PubMed Central

    2015-01-01

    Abstract Background Molecular networks are the basis of biological processes. Such networks can be decomposed into smaller modules, also known as network motifs. These motifs show interesting dynamical behaviors, in which co-operativity effects between the motif components play a critical role in human diseases. We have developed a motif-searching algorithm, which is able to identify common motif types from the cancer networks and signal transduction networks (STNs). Some of the network motifs are interconnected which can be merged together and form more complex structures, the so-called coupled motif structures (CMS). These structures exhibit mixed dynamical behavior, which may lead biological organisms to perform specific functions. Results In this study, we integrate transcription factors (TFs), microRNAs (miRNAs), miRNA targets and network motifs information to build the cancer-related TF-miRNA-motif networks (TMMN). This allows us to examine the role of network motifs in cancer formation at different levels of regulation, i.e. transcription initiation (TF → miRNA), gene-gene interaction (CMS), and post-transcriptional regulation (miRNA → target genes). Among the cancer networks and STNs we considered, it is found that there is a substantial amount of crosstalking through motif interconnections, in particular, the crosstalk between prostate cancer network and PI3K-Akt STN. Conclusions To validate the role of network motifs in cancer formation, several examples are presented which demonstrated the effectiveness of the present approach. A web-based platform has been set up which can be accessed at: http://ppi.bioinfo.asia.edu.tw/pathway/. It is very likely that our results can supply very specific CMS missing information for certain cancer types, it is an indispensable tool for cancer biology research. PMID:25707690

  4. 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.

  5. Regulation of bone and cartilage development by network between BMP signalling and transcription factors.

    PubMed

    Nishimura, Riko; Hata, Kenji; Matsubara, Takuma; Wakabayashi, Makoto; Yoneda, Toshiyuki

    2012-03-01

    Bone morphogenetic protein(s) (BMP) are very powerful cytokines that induce bone and cartilage formation. BMP also stimulate osteoblast and chondrocyte differentiation. During bone and cartilage development, BMP regulates the expression and/or the function of several transcription factors through activation of Smad signalling. Genetic studies revealed that Runx2, Osterix and Sox9, all of which function downstream of BMP, play essential roles in bone and/or cartilage development. In addition, two other transcription factors, Msx2 and Dlx5, which interact with BMP signalling, are involved in bone and cartilage development. The importance of these transcription factors in bone and cartilage development has been supported by biochemical and cell biological studies. Interestingly, BMP is regulated by several negative feedback systems that appear necessary for fine-tuning of bone and cartilage development induced by BMP. Thus, BMP harmoniously regulates bone and cartilage development by forming network with several transcription factors. PMID:22253449

  6. NSP-Cas protein structures reveal a promiscuous interaction module in cell signaling

    SciTech Connect

    Mace, P.D.; Robinson, H.; Wallez, Y.; Dobaczewska, M. K.; Lee, J. J.; Pasquale, E. B.; Riedl, S. J.

    2011-12-01

    Members of the novel SH2-containing protein (NSP) and Crk-associated substrate (Cas) protein families form multidomain signaling platforms that mediate cell migration and invasion through a collection of distinct signaling motifs. Members of each family interact via their respective C-terminal domains, but the mechanism of this association has remained enigmatic. Here we present the crystal structures of the C-terminal domain from the NSP protein BCAR3 and the complex of NSP3 with p130Cas. BCAR3 adopts the Cdc25-homology fold of Ras GTPase exchange factors, but it has a 'closed' conformation incapable of enzymatic activity. The structure of the NSP3-p130Cas complex reveals that this closed conformation is instrumental for interaction of NSP proteins with a focal adhesion-targeting domain present in Cas proteins. This enzyme-to-adaptor conversion enables high-affinity, yet promiscuous, interactions between NSP and Cas proteins and represents an unprecedented mechanistic paradigm linking cellular signaling networks.

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

    PubMed Central

    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

  8. 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

  9. Proteins move! Protein dynamics and long-range allostery in cell signaling.

    PubMed

    Bu, Zimei; Callaway, David J E

    2011-01-01

    An emerging point of view in protein chemistry is that proteins are not the static objects that are displayed in textbooks but are instead dynamic actors. Protein dynamics plays a fundamental role in many diseases, and spans a large hierarchy of timescales, from picoseconds to milliseconds or even longer. Nanoscale protein domain motion on length scales comparable to protein dimensions is key to understanding how signals are relayed through multiple protein-protein interactions. A canonical example is how the scaffolding proteins NHERF1 and ezrin work in coordination to assemble crucial membrane complexes. As membrane-cytoskeleton scaffolding proteins, these provide excellent prototypes for understanding how regulatory signals are relayed through protein-protein interactions between the membrane and the cytoskeleton. Here, we review recent progress in understanding the structure and dynamics of the interaction. We describe recent novel applications of neutron spin echo spectroscopy to reveal the dynamic propagation of allosteric signals by nanoscale protein motion, and present a guide to the future study of dynamics and its application to the cure of disease. PMID:21570668

  10. 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

  11. 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. PMID:26462035

  12. Model for a neural network structure and signal transmission

    NASA Astrophysics Data System (ADS)

    Kotsavasiloglou, C.; Kalampokis, A.; Argyrakis, P.; Baloyannis, S.

    1997-10-01

    We present a model of a neural network that is based on the diffusion-limited-aggregation (DLA) structure from fractal physics. A single neuron is one DLA cluster, while a large number of clusters, in an interconnected fashion, make up the neural network. Using simulation techniques, a signal is randomly generated and traced through its transmission inside the neuron and from neuron to neuron through the synapses. The activity of the entire neural network is monitored as a function of time. The characteristics included in the model contain, among others, the threshold for firing, the excitatory or inhibitory character of the synapse, the synaptic delay, and the refractory period. The system activity results in ``noisy'' time series that exhibit an oscillatory character. Standard power spectra are evaluated and fractal analyses performed, showing that the system is not chaotic, but the varying parameters can be associated with specific values of fractal dimensions. It is found that the network activity is not linear with the system parameters, e.g., with the numbers of active synapses. The details of this behavior may have interesting repercussions from the neurological point of view.

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

    PubMed

    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

  14. 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.

  15. 14-3-3 Proteins in Guard Cell Signaling

    PubMed Central

    Cotelle, Valérie; Leonhardt, Nathalie

    2016-01-01

    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. PMID:26858725

  16. Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

    PubMed

    Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

    2016-07-01

    Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences. PMID:27267620

  17. Structural basis of a rationally rewired protein-protein interface critical to bacterial signaling

    PubMed Central

    Podgornaia, Anna I.; Casino, Patricia; Marina, Alberto; Laub, Michael T.

    2013-01-01

    Summary Two-component signal transduction systems typically involve a sensor histidine kinase that specifically phosphorylates a single, cognate response regulator. This protein-protein interaction relies on molecular recognition via a small set of residues in each protein. To better understand how these residues determine the specificity of kinase-substrate interactions, we rationally rewired the interaction interface of a Thermotoga maritima two-component system, HK853-RR468, to match that found in a different two-component system, E. coli PhoR-PhoB. The rewired proteins interacted robustly with each other, but no longer interacted with the parent proteins. Analysis of the crystal structures of the wild-type and mutant protein complexes, along with a systematic mutagenesis study, reveals how individual mutations contribute to the rewiring of interaction specificity. Our approach and conclusions have implications for studies of other protein-protein interactions, protein evolution, and the design of novel protein interfaces. PMID:23954504

  18. Structural basis of a rationally rewired protein-protein interface critical to bacterial signaling.

    PubMed

    Podgornaia, Anna I; Casino, Patricia; Marina, Alberto; Laub, Michael T

    2013-09-01

    Two-component signal transduction systems typically involve a sensor histidine kinase that specifically phosphorylates a single, cognate response regulator. This protein-protein interaction relies on molecular recognition via a small set of residues in each protein. To better understand how these residues determine the specificity of kinase-substrate interactions, we rationally rewired the interaction interface of a Thermotoga maritima two-component system, HK853-RR468, to match that found in a different two-component system, Escherichia coli PhoR-PhoB. The rewired proteins interacted robustly with each other, but no longer interacted with the parent proteins. Analysis of the crystal structures of the wild-type and mutant protein complexes and a systematic mutagenesis study reveal how individual mutations contribute to the rewiring of interaction specificity. Our approach and conclusions have implications for studies of other protein-protein interactions and protein evolution and for the design of novel protein interfaces. PMID:23954504

  19. Wnt signalling: the case of the 'missing' G-protein.

    PubMed

    Malbon, Craig C

    2011-02-01

    Wnt signalling remains a hot topic for cell signalling sleuthhounds. The trail of signalling downstream of the seven-transmembrane segment Frizzleds, which bind Wnt ligands, is replete of clues [e.g. LPR5/6 (lipoprotein receptor-related protein 5/6), G-proteins or Dishevelled] and yet remains the 'final problem'. Although the heptahelical nature of Frizzleds places them well within a populous family of G-protein-coupled receptors, resistance to this theme has waxed and waned amid increasing demands for 'proof'. The Wnt Homepage (http://www.stanford.edu/group/nusselab/cgi-bin/wnt/) has acted as a dynamic real-time arbiter of the controversy, highlighted by the appearance and later the disappearance of the G-protein from its central diagramming and tabulations. A recent publication in this issue of the Biochemical Journal offers a solution to the 'final problem', demonstrating under native conditions that Frizzleds expressed in mammalian brain preparations act functionally to catalyse guanine-nucleotide exchange in response to stimulation with Wnt3a. Lensed from the fictional character of Sherlock Holmes, The Case of the Missing G-Protein is investigated. PMID:21235522

  20. 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.

  1. Redox and zinc signalling pathways converging on protein tyrosine phosphatases.

    PubMed

    Bellomo, Elisa; Hogstrand, Christer; Maret, Wolfgang

    2014-10-01

    Zinc ions, though redox-inert, have either pro-antioxidant or pro-oxidant functions at critical junctures in redox metabolism and redox signalling. They are released from cells and in cells, e.g. from metallothionein, a protein that transduces redox signals into zinc signals (1). The released zinc ions inhibit enzymes such as protein tyrosine phosphatases (PTPs), key regulatory enzymes of cellular phosphorylation signalling. The Ki(Zn) value for inhibition of receptor PTPB is 21pM (2). The binding is about as tight as the binding of zinc to zinc metalloenzymes and suggests tonic zinc inhibition. PTP1-B (PTPN1), an enzyme regulating the insulin and leptin receptors and involved in cancer and diabetes pathobiochemistry, has a Ki(Zn) value of about 5nM (3). Zinc ions bind to the enzyme in the closed conformation when additional metal-binding ligands are brought into the vicinity of the active site. In contrast, redox reactions target cysteines in the active sites of PTPs in the open conformation. This work provides a molecular basis how hydrogen peroxide and free zinc ions generated by growth factor signalling stimulate phosphorylation signalling differentially. (Supported by the Biotechnology and Biological Sciences Research Council UK, grant BB/K001442/1.). PMID:26461422

  2. 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.

  3. Antigen receptor signaling: integration of protein tyrosine kinase functions.

    PubMed

    Tamir, I; Cambier, J C

    1998-09-17

    Antigen receptors on T and B cells function to transduce signals leading to a variety of biologic responses minimally including antigen receptor editing, apoptotic death, developmental progression, cell activation, proliferation and survival. The response to antigen depends upon antigen affinity and valence, involvement of coreceptors in signaling and differentiative stage of the responding cell. The requirement that these receptors integrate signals that drive an array of responses may explain their evolved structural complexity. Antigen receptors are composed of multiple subunits compartmentalized to provide antigen recognition and signal transduction function. In lieu of on-board enzymatic activity these receptors rely on associated Protein Tyrosine Kinases (PTKs) for their signaling function. By aggregating the receptors, and hence their appended PTKs, antigens induce PTK transphosphorylation, activating them to phosphorylate the receptor within conserved motifs termed Immunoreceptor Tyrosine-based Activation Motifs (ITAMs) found in transducer subunits. The tyrosyl phosphorylated ITAMs then interact with Src Homology 2 (SH2) domains within the PTKs leading to their further activation. As receptor phosphorylation is amplified, other effectors, such as Shc, dock by virtue of SH2 binding, and serve, in-turn, as substrates for these PTKs. This sequence of events not only provides a signal amplification mechanism by combining multiple consecutive steps with positive feedback, but also allows for signal diversification by differential recruitment of effectors that provide access to distinct parallel downstream signaling pathways. The subject of antigen receptor signaling has been recently reviewed in depth (DeFranco, 1997; Kurosaki, 1997). Here we discuss the biochemical basis of antigen receptor signal transduction, using the B cell receptor (BCR) as a paradigm, with specific emphasis on the involved PTKs. We review several specific mechanisms by which responses

  4. 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

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

    PubMed

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

    2016-02-01

    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

  6. The TLR and IL-1 signalling network at a glance.

    PubMed

    Cohen, Philip

    2014-06-01

    Toll-like receptors (TLRs) and the receptors for interleukin (IL)-1, IL-18 and IL-33 are required for defence against microbial pathogens but, if hyper-activated or not switched off efficiently, can cause tissue damage and inflammatory and autoimmune diseases. Understanding how the checks and balances in the system are integrated to fight infection without the network operating out of control will be crucial for the development of improved drugs to treat these diseases in the future. In this Cell Science at a Glance article and the accompanying poster, I provide a brief overview of how one of these intricate networks is controlled by the interplay of protein phosphorylation and protein ubiquitylation events, and the mechanisms in myeloid cells that restrict and terminate its activation to prevent inflammatory and autoimmune diseases. Finally, I suggest a few protein kinases that have been neglected as drug targets, but whose therapeutic potential should be explored in the light of recent advances in our understanding of their roles in the innate immune system. PMID:24829146

  7. 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

  8. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling

    PubMed Central

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors. PMID:26571415

  9. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

    PubMed

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors. PMID:26571415

  10. Retinoic acid signaling regulates sonic hedgehog and bone morphogenetic protein signalings during genital tubercle development.

    PubMed

    Liu, Liqing; Suzuki, Kentaro; Nakagata, Naomi; Mihara, Kenichiro; Matsumaru, Daisuke; Ogino, Yukiko; Yashiro, Kenta; Hamada, Hiroshi; Liu, Zhonghua; Evans, Sylvia M; Mendelsohn, Cathy; Yamada, Gen

    2012-02-01

    Retinoic acid (RA) plays pivotal roles in organogenesis, and both excessive and reduced amounts of RA cause developmental abnormalities. Reproductive organs are susceptible to teratogen toxigenicity, and the genital tubercle (GT) is one such representative organ. The physiological function of endogenous RA signaling and the mechanisms of RA-induced teratogenicity are poorly understood during the GT development. The objective of this study is to understand the developmental and teratogenic roles of RA during GT development by analyzing genetically modified mouse models. We found dynamic patterns of gene expression for the RA-synthesizing enzyme, Raldh2, and for the RA-catabolizing enzyme, Cyp26b1, during GT development. Rarb, an indicator gene for RA signaling, starts its expression in the prospective corpus cavernosum penis and in the urethral plate epithelium (UE), which plays central roles during GT development. Excessive RA signaling in Cyp26b1(-/-) mutants leads to abnormal extents of cell proliferation and differentiation during GT development, and also upregulates expression of growth factor signalings. They include Sonic hedgehog (Shh) signaling and Bone morphogenetic protein (Bmp) signaling, which are expressed in the UE and its bilateral mesenchyme. RA signaling positively regulatesShh and Bmp4 expression during GT development as testified also by the experiment of RA administration and analyses of loss-of-function of RA signaling mutants. Thus, RA signaling is involved in the developmental cascade necessary for UE formation and GT development. PMID:22127979

  11. 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

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

    PubMed Central

    2012-01-01

    Background Cell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses. Results We observe bimodal distributions of extracellular signal-regulated kinase (ERK) responses to epidermal growth factor (EGF) stimulation, which are generally thought to indicate bistable or ultrasensitive signaling behavior in single cells. Surprisingly, we find that a simple MAPK/ERK-cascade model with negative feedback that displays graded, analog ERK responses at a single cell level can explain the experimentally observed bimodality at the cell population level. Model analysis suggests that a conversion of graded input–output responses in single cells to digital responses at the population level is caused by a broad distribution of ERK pathway activation thresholds brought about by cell-to-cell variability in protein expression. Conclusions Our results show that bimodal signaling response distributions do not necessarily imply digital (ultrasensitive or bistable) single cell signaling, and the interplay between protein expression noise and network topologies can bring about digital population responses from analog single cell dose responses. Thus, cells can retain the benefits of robustness arising from negative feedback, while simultaneously generating population-level on/off responses that are thought to be critical for regulating cell fate decisions. PMID:22920937

  13. Hemojuvelin and bone morphogenetic protein (BMP) signaling in iron homeostasis.

    PubMed

    Core, Amanda B; Canali, Susanna; Babitt, Jodie L

    2014-01-01

    Mutations in hemojuvelin (HJV) are the most common cause of the juvenile-onset form of the iron overload disorder hereditary hemochromatosis. The discovery that HJV functions as a co-receptor for the bone morphogenetic protein (BMP) family of signaling molecules helped to identify this signaling pathway as a central regulator of the key iron hormone hepcidin in the control of systemic iron homeostasis. This review highlights recent work uncovering the mechanism of action of HJV and the BMP-SMAD signaling pathway in regulating hepcidin expression in the liver, as well as additional studies investigating possible extra-hepatic functions of HJV. This review also explores the interaction between HJV, the BMP-SMAD signaling pathway and other regulators of hepcidin expression in systemic iron balance. PMID:24860505

  14. A draft network of ligand–receptor-mediated multicellular signalling in human

    PubMed Central

    Ramilowski, Jordan A.; Goldberg, Tatyana; Harshbarger, Jayson; Kloppman, Edda; Lizio, Marina; Satagopam, Venkata P.; Itoh, Masayoshi; Kawaji, Hideya; Carninci, Piero; Rost, Burkhard; Forrest, Alistair R. R.

    2015-01-01

    Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand–receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1–CSF1R interacting pair. PMID:26198319

  15. 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

  16. Control of protein trafficking by reversible masking of transport signals.

    PubMed

    Abraham, Omer; Gotliv, Karnit; Parnis, Anna; Boncompain, Gaelle; Perez, Franck; Cassel, Dan

    2016-04-15

    Systems that allow the control of protein traffic between subcellular compartments have been valuable in elucidating trafficking mechanisms. Most current approaches rely on ligand or light-controlled dimerization, which results in either retardation or enhancement of the transport of a reporter. We developed an alternative approach for trafficking regulation that we term "controlled unmasking of targeting elements" (CUTE). Regulated trafficking is achieved by reversible masking of the signal that directs the reporter to its target organelle, relying on the streptavidin-biotin system. The targeting signal is generated within or immediately after a 38-amino acid streptavidin-binding peptide (SBP) that is appended to the reporter. The binding of coexpressed streptavidin to SBP causes signal masking, whereas addition of biotin causes complex dissociation and triggers protein transport to the target organelle. We demonstrate the application of this approach to the control of nuclear and peroxisomal protein import and the generation of biotin-dependent trafficking through the endocytic and COPI systems. By simultaneous masking of COPI and endocytic signals, we were able to generate a synthetic pathway for efficient transport of a reporter from the plasma membrane to the endoplasmic reticulum. PMID:26941332

  17. RANK-mediated signaling network and cancer metastasis

    PubMed Central

    Chu, Chia-Yi Gina; Chung, Leland W. K.

    2014-01-01

    Cancer metastasis is highly inefficient and complex. Common features of metastatic cancer cells have been observed using cancer cell lines and genetically reconstituted mouse and human tumor xenograft models. These include cancer cell interaction with the tumor microenvironment, and the ability of cancer cells to sense extracellular stimuli and adapt to adverse growth conditions. This review summarizes the coordinated response of cancer cells to soluble growth factors, such as RANKL, by a unique forward feedback mechanism employing coordinated upregulation of RANKL and c-Met with downregulation of androgen receptor. The RANK-mediated signal network was found to drive epithelial to mesenchymal transition in prostate cancer cells, promote osteomimicry and the ability of prostate cancer cells to assume stem cell and neuroendocrine phenotypes, and confer the ability of prostate cancer cells to home to bone. Prostate cancer cells with activated RANK-mediated signal network were observed to recruit and even transform the non-tumorigenic prostate cancer cells to participate in bone and soft tissue colonization. The coordinated regulation of cancer cell invasion and metastasis by the forward feedback mechanism involving RANKL, c-Met, transcription factors and VEGF-neuropilin could offer new therapeutic opportunities to target prostate cancer bone and soft tissue metastases. PMID:24398859

  18. 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

  19. 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

  20. Oxidative Modification of Proteins: An Emerging Mechanism of Cell Signaling

    PubMed Central

    Wall, Stephanie B.; Oh, Joo-Yeun; Diers, Anne R.; Landar, Aimee

    2012-01-01

    There are a wide variety of reactive species which can affect cell function, including reactive oxygen, nitrogen, and lipid species. Some are formed endogenously through enzymatic or non-enzymatic pathways, and others are introduced through diet or environmental exposure. Many of these reactive species can interact with biomolecules and can result in oxidative post-translational modification of proteins. It is well documented that some oxidative modifications cause macromolecular damage and cell death. However, a growing body of evidence suggests that certain classes of reactive species initiate cell signaling by reacting with specific side chains of peptide residues without causing cell death. This process is generally termed “redox signaling,” and its role in physiological and pathological processes is a subject of active investigation. This review will give an overview of oxidative protein modification as a mechanism of redox signaling, including types of reactive species and how they modify proteins, examples of modified proteins, and a discussion about the current concepts in this area. PMID:23049513

  1. 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

  2. FGF21 is an endocrine signal of protein restriction.

    PubMed

    Laeger, Thomas; Henagan, Tara M; Albarado, Diana C; Redman, Leanne M; Bray, George A; Noland, Robert C; Münzberg, Heike; Hutson, Susan M; Gettys, Thomas W; Schwartz, Michael W; Morrison, Christopher D

    2014-09-01

    Enhanced fibroblast growth factor 21 (FGF21) production and circulation has been linked to the metabolic adaptation to starvation. Here, we demonstrated that hepatic FGF21 expression is induced by dietary protein restriction, but not energy restriction. Circulating FGF21 was increased 10-fold in mice and rats fed a low-protein (LP) diet. In these animals, liver Fgf21 expression was increased within 24 hours of reduced protein intake. In humans, circulating FGF21 levels increased dramatically following 28 days on a LP diet. LP-induced increases in FGF21 were associated with increased phosphorylation of eukaryotic initiation factor 2α (eIF2α) in the liver, and both baseline and LP-induced serum FGF21 levels were reduced in mice lacking the eIF2α kinase general control nonderepressible 2 (GCN2). Finally, while protein restriction altered food intake, energy expenditure, and body weight gain in WT mice, FGF21-deficient animals did not exhibit these changes in response to a LP diet. These and other data demonstrate that reduced protein intake underlies the increase in circulating FGF21 in response to starvation and a ketogenic diet and that FGF21 is required for behavioral and metabolic responses to protein restriction. FGF21 therefore represents an endocrine signal of protein restriction, which acts to coordinate metabolism and growth during periods of reduced protein intake. PMID:25133427

  3. Post-translational modification of PII signal transduction proteins

    PubMed Central

    Merrick, Mike

    2015-01-01

    The PII proteins constitute one of the most widely distributed families of signal transduction proteins in nature. They are pivotal players in the control of nitrogen metabolism in bacteria and archaea, and are also found in the plastids of plants. Quite remarkably PII proteins control the activities of a diverse range of enzymes, transcription factors and membrane transport proteins, and in all known cases they achieve their regulatory effect by direct interaction with their target. PII proteins in the Proteobacteria and the Actinobacteria are subject to post-translational modification by uridylylation or adenylylation respectively, whilst in some Cyanobacteria they can be modified by phosphorylation. In all these cases the protein’s modification state is influenced by the cellular nitrogen status and is thought to regulate its activity. However, in many organisms there is no evidence for modification of PII proteins and indeed the ability of these proteins to respond to the cellular nitrogen status is fundamentally independent of post-translational modification. In this review we explore the role of post-translational modification in PII proteins in the light of recent studies. PMID:25610437

  4. Identifying protein complexes in protein-protein interaction networks by using clique seeds and graph entropy.

    PubMed

    Chen, Bolin; Shi, Jinhong; Zhang, Shenggui; Wu, Fang-Xiang

    2013-01-01

    The identification of protein complexes plays a key role in understanding major cellular processes and biological functions. Various computational algorithms have been proposed to identify protein complexes from protein-protein interaction (PPI) networks. In this paper, we first introduce a new seed-selection strategy for seed-growth style algorithms. Cliques rather than individual vertices are employed as initial seeds. After that, a result-modification approach is proposed based on this seed-selection strategy. Predictions generated by higher order clique seeds are employed to modify results that are generated by lower order ones. The performance of this seed-selection strategy and the result-modification approach are tested by using the entropy-based algorithm, which is currently the best seed-growth style algorithm to detect protein complexes from PPI networks. In addition, we investigate four pairs of strategies for this algorithm in order to improve its accuracy. The numerical experiments are conducted on a Saccharomyces cerevisiae PPI network. The group of best predictions consists of 1711 clusters, with the average f-score at 0.68 after removing all similar and redundant clusters. We conclude that higher order clique seeds can generate predictions with higher accuracy and that our improved entropy-based algorithm outputs more reasonable predictions than the original one. PMID:23112006

  5. 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

  6. Conformational transition in signal transduction: metastable states and transition pathways in the activation of a signaling protein.

    PubMed

    Banerjee, Rahul; Yan, Honggao; Cukier, Robert I

    2015-06-01

    Signal transduction is of vital importance to the growth and adaptation of living organisms. The key to understand mechanisms of biological signal transduction is elucidation of the conformational dynamics of its signaling proteins, as the activation of a signaling protein is fundamentally a process of conformational transition from an inactive to an active state. A predominant form of signal transduction for bacterial sensing of environmental changes in the wild or inside their hosts is a variety of two-component systems, in which the conformational transition of a response regulator (RR) from an inactive to an active state initiates responses to the environmental changes. Here, RR activation has been investigated using RR468 as a model system by extensive unbiased all-atom molecular dynamics (MD) simulations in explicit solvent, starting from snapshots along a targeted MD trajectory that covers the conformational transition. Markov state modeling, transition path theory, and geometric analyses of the wealth of the MD data have provided a comprehensive description of the RR activation. It involves a network of metastable states, with one metastable state essentially the same as the inactive state and another very similar to the active state that are connected via a small set of intermediates. Five major pathways account for >75% of the fluxes of the conformational transition from the inactive to the active-like state. The thermodynamic stability of the states and the activation barriers between states are found, to identify rate-limiting steps. The conformal transition is initiated predominantly by movements of the β3α3 loop, followed by movements of the β4α4-loop and neighboring α4 helix region, and capped by additional movements of the β3α3 loop. A number of transient hydrophobic and hydrogen bond interactions are revealed, and they may be important for the conformational transition. PMID:25945797

  7. 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

  8. 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.

  9. 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.

  10. 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

  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. PMID:25030903

  12. 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

  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. Transduction of Redox Signaling by Electrophile-Protein Reactions

    PubMed Central

    Rudolph, Tanja K.; Freeman, Bruce A.

    2014-01-01

    Over the last 50 years, the posttranslational modification (PTM) of proteins has emerged as a central mechanism for cells to regulate metabolism, growth, differentiation, cell-cell interactions, and immune responses. By influencing protein structure and function, PTM leads to a multiplication of proteome diversity. Redox-dependent PTMs, mediated by environmental and endogenously generated reactive species, induce cell signaling responses and can have toxic effects in organisms. PTMs induced by the electrophilic by-products of redox reactions most frequently occur at protein thiols; other nucleophilic amino acids serve as less favorable targets. Advances in mass spectrometry and affinity-chemistry strategies have improved the detection of electrophile-induced protein modifications both in vitro and in vivo and have revealed a high degree of amino acid and protein selectivity of electrophilic PTM. The identification of biological targets of electrophiles has motivated further study of the functional impact of various PTM reactions on specific signaling pathways and how this might affect organisms. PMID:19797270

  15. Pulmonary Proteome and Protein Networks in Response to the Herbicide Paraquat in Rats

    PubMed Central

    Cho, Il Kyu; Jeong, Mihye; You, Are-Sun; Park, Kyung Hun; Li, Qing X.

    2015-01-01

    Paraquat (PQ) has been one of the most widely used herbicides in the world. PQ, when ingested, is toxic to humans and may cause acute respiratory distress syndrome. To investigate molecular perturbation in lung tissues caused by PQ, Sprague Dawley male rats were fed with PQ at a dose of 25 mg/kg body weight for 20 times in four weeks. The effects of PQ on cellular processes and biological pathways were investigated by analyzing proteome in the lung tissues in comparison with the control. Among the detected proteins, 321 and 254 proteins were over-represented and under-represented, respectively, in the PQ-exposed rat lung tissues in comparison with the no PQ control. All over- and under-represented proteins were subjected to Ingenuity Pathway Analysis to create 25 biological networks and 38 pathways of interacting protein clusters. Over-represented proteins were involved in the C-jun-amino-terminal kinase pathway, caveolae-mediated endocytosis signaling, cardiovascular-cancer-respiratory pathway, regulation of clathrin-mediated endocytosis, non-small cell lung cancer signaling, pulmonary hypertension, glutamate receptor, immune response and angiogenesis. Under-represented proteins occurred in the p53 signaling pathway, mitogen-activated protein kinase signaling pathway, cartilage development and angiogenesis inhibition in the PQ-treated lungs. The results suggest that PQ may generate reactive oxygen species, impair the MAPK/p53 signaling pathway, activate angiogenesis and depress apoptosis in the lungs. PMID:26538867

  16. Integration of G Protein α (Gα) Signaling by the Regulator of G Protein Signaling 14 (RGS14)*

    PubMed Central

    Brown, Nicole E.; Goswami, Devrishi; Branch, Mary Rose; Ramineni, Suneela; Ortlund, Eric A.; Griffin, Patrick R.; Hepler, John R.

    2015-01-01

    RGS14 contains distinct binding sites for both active (GTP-bound) and inactive (GDP-bound) forms of Gα subunits. The N-terminal regulator of G protein signaling (RGS) domain binds active Gαi/o-GTP, whereas the C-terminal G protein regulatory (GPR) motif binds inactive Gαi1/3-GDP. The molecular basis for how RGS14 binds different activation states of Gα proteins to integrate G protein signaling is unknown. Here we explored the intramolecular communication between the GPR motif and the RGS domain upon G protein binding and examined whether RGS14 can functionally interact with two distinct forms of Gα subunits simultaneously. Using complementary cellular and biochemical approaches, we demonstrate that RGS14 forms a stable complex with inactive Gαi1-GDP at the plasma membrane and that free cytosolic RGS14 is recruited to the plasma membrane by activated Gαo-AlF4−. Bioluminescence resonance energy transfer studies showed that RGS14 adopts different conformations in live cells when bound to Gα in different activation states. Hydrogen/deuterium exchange mass spectrometry revealed that RGS14 is a very dynamic protein that undergoes allosteric conformational changes when inactive Gαi1-GDP binds the GPR motif. Pure RGS14 forms a ternary complex with Gαo-AlF4− and an AlF4−-insensitive mutant (G42R) of Gαi1-GDP, as observed by size exclusion chromatography and differential hydrogen/deuterium exchange. Finally, a preformed RGS14·Gαi1-GDP complex exhibits full capacity to stimulate the GTPase activity of Gαo-GTP, demonstrating that RGS14 can functionally engage two distinct forms of Gα subunits simultaneously. Based on these findings, we propose a working model for how RGS14 integrates multiple G protein signals in host CA2 hippocampal neurons to modulate synaptic plasticity. PMID:25666614

  17. The eFIP system for text mining of protein interaction networks of phosphorylated proteins

    PubMed Central

    Wu, Cathy H.; Vijay-Shanker, K.

    2012-01-01

    Protein phosphorylation is a central regulatory mechanism in signal transduction involved in most biological processes. Phosphorylation of a protein may lead to activation or repression of its activity, alternative subcellular location and interaction with different binding partners. Extracting this type of information from scientific literature is critical for connecting phosphorylated proteins with kinases and interaction partners, along with their functional outcomes, for knowledge discovery from phosphorylation protein networks. We have developed the Extracting Functional Impact of Phosphorylation (eFIP) text mining system, which combines several natural language processing techniques to find relevant abstracts mentioning phosphorylation of a given protein together with indications of protein–protein interactions (PPIs) and potential evidences for impact of phosphorylation on the PPIs. eFIP integrates our previously developed tools, Extracting Gene Related ABstracts (eGRAB) for document retrieval and name disambiguation, Rule-based LIterature Mining System (RLIMS-P) for Protein Phosphorylation for extraction of phosphorylation information, a PPI module to detect PPIs involving phosphorylated proteins and an impact module for relation extraction. The text mining system has been integrated into the curation workflow of the Protein Ontology (PRO) to capture knowledge about phosphorylated proteins. The eFIP web interface accepts gene/protein names or identifiers, or PubMed identifiers as input, and displays results as a ranked list of abstracts with sentence evidence and summary table, which can be exported in a spreadsheet upon result validation. As a participant in the BioCreative-2012 Interactive Text Mining track, the performance of eFIP was evaluated on document retrieval (F-measures of 78–100%), sentence-level information extraction (F-measures of 70–80%) and document ranking (normalized discounted cumulative gain measures of 93–100% and mean average

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

    PubMed Central

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

    2014-01-01

    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

  19. Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling

    PubMed Central

    Lees, Jon G.; Reid, Adam J.; Yeats, Corin; Clegg, Andrew B.; Sanchez-Jimenez, Francisca; Orengo, Christine

    2010-01-01

    Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or “dark matter” of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case

  20. Finding the "dark matter" in human and yeast protein network prediction and modelling.

    PubMed

    Ranea, Juan A G; Morilla, Ian; Lees, Jon G; Reid, Adam J; Yeats, Corin; Clegg, Andrew B; Sanchez-Jimenez, Francisca; Orengo, Christine

    2010-01-01

    Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or "dark matter" of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case

  1. SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction

    SciTech Connect

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. Hayes; Pelletier, Dale A.; Schmoyer, Denise D.; Cannon, William R.

    2007-12-01

    One of the core tasks of the emerging discipline of systems biology is the reconstruction of the various biological networks in an organism. The importance of understanding such regulatory, interaction, and signaling networks has fueled the development by bioinformatics researchers of many inference algorithms for determining their structure. The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment, testing, and improvement of algorithms used to reconstruct the structures of regulatory and interaction networks from high-throughput expression data. Networks inferred from the SEBINI software platform can be further analyzed using the Collective Analysis of Biological Interaction Networks (CABIN) tool, a software package for exploratory data analysis that allows basic integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources. Thus, the combined SEBINI–CABIN platform aids in the more accurate determination of biological networks, in less time, with less effort. In this paper, we present a case study demonstrating the use of the SEBINI and CABIN tools for protein-protein interaction network reconstruction. Incorporating the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro) algorithm into the SEBINI toolkit, we have created a pipeline for structural inference and supplemental analysis of protein-protein interaction networks from sets of mass spectrometry bait-prey experiment data. To the best of our knowledge the pipeline so designed is the first to be publicly available for such use. A demonstration web site for SEBINI can be accessed from https://www.emsl.pnl.gov/NIT/NIT.html. Source code and PostgreSQL database schema are available under open source license. Contact: ronald.taylor@pnl.gov. For commercial use, some algorithms included in SEBINI require licensing from the original developers. The

  2. 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

  3. Directed disassembly of an interfacial rubisco protein network.

    PubMed

    Onaizi, Sagheer A; Malcolm, Andrew S; He, Lizhong; Middelberg, Anton P J

    2007-05-22

    We present the first study of the directed disassembly of a protein network at the air-water interface by the synergistic action of a surfactant and an enzyme. We seek to understand the fundamentals of protein network disassembly by using rubisco adsorbed at the air-water interface as a model. We propose that rubisco adsorption at the air-water interface results in the formation of a fishnet-like network of interconnected protein molecules, capable of transmitting lateral force. The mechanical properties of the rubisco network during assembly and disassembly at the air-water interface were characterized by direct measurement of laterally transmitted force through the protein network using the Cambridge interfacial tensiometer. We have shown that, when used individually, either 2 ppm of the surfactant, sodium dodecyl benzyl sulfonate (SDOBS), or 2 ppm of the enzyme, subtilisin A (SA), were insufficient to completely disassemble the rubisco network within 1 h of treatment. However, a combination of 2 ppm SDOBS and 2 ppm SA led to almost complete disassembly within 1 h. Increasing the concentration of SA in the mixture from 2 to 10 ppm, while keeping the SDOBS concentration constant, significantly decreased the time required to completely disassemble the rubisco network. Furthermore, the initial rate of network disassembly using formulations containing SDOBS was surprisingly insensitive to this increase in SA concentration. This study gives insight into the role of lateral interactions between protein molecules at interfaces in stabilizing interfacial protein networks and shows that surfactant and enzyme working in combination proves more effective at disrupting and mobilizing the interfacial protein network than the action of either agent alone. PMID:17447802

  4. Knr4: a disordered hub protein at the heart of fungal cell wall signalling.

    PubMed

    Martin-Yken, Hélène; François, Jean Marie; Zerbib, Didier

    2016-09-01

    The most highly connected proteins in protein-protein interactions networks are called hubs; they generally connect signalling pathways. In Saccharomyces cerevisiae, Knr4 constitutes a connecting node between the two main signal transmission pathways involved in cell wall maintenance upon stress: the cell wall integrity and the calcium-calcineurin pathway. Knr4 is required to enable the cells to resist many cell wall-affecting stresses, and KNR4 gene deletion is synthetic lethal with the simultaneous deletion of numerous other genes involved in morphogenesis and cell wall biogenesis. Knr4 has been shown to engage in multiple physical interactions, an ability conferred by the intrinsic structural adaptability of major disordered regions present in the N-terminal and C-terminal parts of the protein. Taking all together, Knr4 is an intrinsically disordered hub protein. Available data from other fungi indicate the conservation of Knr4 homologs cellular function and localization at sites of polarized growth among fungal species, including pathogenic species. Because of their particular role in morphogenesis control and of their fungal specificity, these proteins could constitute interesting new pharmaceutical drug targets for antifungal combination therapy. PMID:27199081

  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. 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

  7. 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

  8. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically i ntegrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet. PMID:26800544

  9. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Such networks are typically constructed using high throughput techniques (e.g., Yeast-2-Hybrid experiments). Of particular interest are hub proteins that can interact wit...

  10. Protein-Protein Interaction Network could reveal the relationship between the breast and colon cancer

    PubMed Central

    Zamanian-Azodi, Mona; Rezaei-Tavirani, Mostafa; Rahmati-Rad, Sara; Hasanzadeh, Hadi; Rezaei Tavirani, Majid; Seyyedi, Samaneh Sadat

    2015-01-01

    Aim: This study is aimed to elicit the possible correlation between breast and colon cancer from molecular prospective by analyzing and comparing pathway-based biomarkers. Background: Breast and colon cancer are known to be frequent causes of morbidity and mortality in men and women around the world. There is some evidence that while the incident of breast cancer in young women is high, it is reported lower in the aged women. In fact, aged women are more prone to colorectal cancer than older men. . In addition, many studies showed that several biomarkers are common among these malignancies. Patients and methods: The genes were retrieved and compared from KEGG database and WikiPathway, and subsequently, protein-protein interaction (PPI) network was constructed and analyzed using Cytoscape v:3.2.1 software and related algorithms. Results: More than forty common genes were identified among these malignancies; however, by pathways comparison, twenty genes are related to both breast and colon cancer. Centrality and cluster screening identified hub genes, including SMAD2, SMAD3, (SMAD4, MYC), JUN, BAD, TP53. These seven genes are enriched in regulation of transforming growth factor beta receptor signaling pathway, positive regulation of Rac protein signal transduction, positive regulation of mitochondrial outer membrane permeabilization involved in apoptotic signaling pathway, and positive regulation of mitotic metaphase/anaphase transition respectively. Conclusion: As there are numerous genes frequent between colorectal cancer and breast cancer, there may be a common molecular origin for these malignancies occurrences. It seems that breast cancer in females interferes with the rate of colorectal cancer incidence. PMID:26328044

  11. Keeping the Balance Right: Regulator of G Protein Signaling 5 in Vascular Physiology and Pathology.

    PubMed

    Ganss, Ruth

    2015-01-01

    The cardiovascular system including the heart and intricate network of arteries, veins, and capillaries is essential for normal organ homeostasis and tightly controlled by G protein-coupled receptor (GPCR) signaling cascades. Imbalances of these signaling systems can manifest in cardiovascular disease. There has been a recent surge in studies on modulators of GPCR activity, so-called regulator of G protein signaling (RGS) molecules, due to their potential as pharmacological targets. Among RGS proteins, RGS5 is prominently expressed in arterial vascular smooth muscle cells (vSMC) suggesting an important role in vascular function. Although apparently dispensable for embryonic development, RGS5 has now emerged as a crucial regulator of adaptive cardiovascular processes, including remodeling of the vascular wall under stress. RGS5 has been shown to regulate signaling pathways which shape vSMC differentiation, migration, contraction, as well as tissue inflammation and fibrosis. Indeed, studies in RGS5 mutant mice have confirmed a crucial and nonredundant role as regulator of cardiac function, blood pressure homeostasis, and adult neovascularization such as angiogenesis and arteriogenesis. In response to environmental cues, RGS5 is dynamically controlled at both mRNA and protein levels. This enables direct, precise, and rapid modulation of Gαq- and Gαi-coupled GPCR signaling which also integrates receptor tyrosine kinases (RTK) and Gαs/Gα12/13-mediated GPCR signal transduction. Although RGS5's endogenous role in a spatiotemporal context is still largely unknown, its prominence in vascular tissue makes it an important molecule to study and a prime candidate for therapeutic intervention. PMID:26123304

  12. 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

  13. A sterol binding protein integrates endosomal lipid metabolism with TOR signaling and nitrogen sensing

    PubMed Central

    Mousley, Carl J.; Yuan, Peihua; Gaur, Naseem A.; Trettin, Kyle D.; Nile, Aaron H.; Deminoff, Stephen J.; Dewar, Brian J.; Wolpert, Max; Macdonald, Jeffrey M.; Herman, Paul K.; Hinnebusch, Alan G.; Bankaitis, Vytas A.

    2012-01-01

    SUMMARY Kes1, and other oxysterol binding protein (OSBP) superfamily members, are involved in membrane and lipid trafficking through trans-Golgi network (TGN) and endosomal systems. We demonstrate that Kes1 represents a sterol-regulated antagonist of TGN/endosomal phosphatidylinositol-4-phosphate signaling. This regulation modulates TOR activation by amino acids, and dampens gene expression driven by Gcn4; the primary transcriptional activator of the general amino acid control regulon. Kes1-mediated repression of Gcn4 transcription factor activity is characterized by nonproductive Gcn4 binding to its target sequences, involves TGN/endosome-derived sphingolipid signaling, and requires activity of the cyclin-dependent kinase 8 (CDK8) module of the enigmatic ‘large Mediator’ complex. These data describe a pathway by which Kes1 integrates lipid metabolism with TORC1 signaling and nitrogen sensing. PMID:22341443

  14. 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

  15. Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks

    PubMed Central

    Shen, Ru; Wang, Xiaosheng; Guda, Chittibabu

    2015-01-01

    Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological network analysis. Results. In this study, we developed a new graph theory based method to identify distinct functional modules from nine different cancer protein-protein interaction networks. The method is composed of three major steps: (i) extracting modules from protein-protein interaction networks using network clustering algorithms; (ii) identifying distinct subgraphs from the derived modules; and (iii) identifying distinct subgraph patterns from distinct subgraphs. The subgraph patterns were evaluated using experimentally determined cancer-specific protein-protein interaction data from the Ingenuity knowledgebase, to identify distinct functional modules that are specific to each cancer type. Conclusion. We identified cancer-type specific subgraph patterns that may represent the functional modules involved in the molecular pathogenesis of different cancer types. Our method can serve as an effective tool to discover cancer-type specific functional modules from large protein-protein interaction networks. PMID:26495282

  16. Hipk proteins dually regulate Wnt/Wingless signal transduction.

    PubMed

    Verheyen, Esther M; Swarup, Sharan; Lee, Wendy

    2012-01-01

    The Wnt/Wingless (Wg) pathway is an evolutionarily conserved signaling system that is used reiteratively, both spatially and temporally, to control the development of multicellular animals. The stability of cytoplasmic β-catenin/Armadillo, the transcriptional effector of the pathway, is controlled by sequential N-terminal phosphorylation and ubiquitination that targets it for proteasome-mediated degradation. Orthologous members of the Homeodomain-interacting protein kinase family from Drosophila to vertebrates have been implicated in the regulation of Wnt/Wingless signaling. In Drosophila, as a consequence of Hipk activity, cells accumulate stabilized Armadillo that directs the expression of Wg-specific target genes. Hipk promotes the stabilization of Armadillo by inhibiting its ubiquitination (and hence subsequent degradation) by the SCF(Slimb) E3 ubiquitin ligase complex. Vertebrate Hipk2 impedes β-catenin ubiquitination to promote its stability and the Wnt signal in a mechanism that is functionally conserved. Moreover, we describe here that Hipk proteins have a role independent of their effect on β-catenin/Armadillo stability to enhance Wnt/Wingless signaling. PMID:22634475

  17. 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

  18. 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

  19. 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, Adriann M C H; Soethoudt, Marjolein; van der Wel, Tom; Zhou, Juan; Overkleeft, Herman S; Sanchez-Alavez, Manuel; 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. PMID:26668358

  20. 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.

  1. Systematic identification of signal integration by protein kinase A

    PubMed Central

    Filteau, Marie; Diss, Guillaume; Dubé, Alexandre K.; Schraffl, Andrea; Bachmann, Verena A.; Gagnon-Arsenault, Isabelle; Chrétien, Andrée-Ève; Steunou, Anne-Lise; Dionne, Ugo; Bisson, Nicolas; Stefan, Eduard; Landry, Christian R.

    2015-01-01

    Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein–protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA. PMID:25831502

  2. The ATM signaling network in development and disease

    PubMed Central

    Stracker, Travis H.; Roig, Ignasi; Knobel, Philip A.; Marjanović, Marko

    2013-01-01

    The DNA damage response (DDR) rapidly recognizes DNA lesions and initiates the appropriate cellular programs to maintain genome integrity. This includes the coordination of cell cycle checkpoints, transcription, translation, DNA repair, metabolism, and cell fate decisions, such as apoptosis or senescence (Jackson and Bartek, 2009). DNA double-strand breaks (DSBs) represent one of the most cytotoxic DNA lesions and defects in their metabolism underlie many human hereditary diseases characterized by genomic instability (Stracker and Petrini, 2011; McKinnon, 2012). Patients with hereditary defects in the DDR display defects in development, particularly affecting the central nervous system, the immune system and the germline, as well as aberrant metabolic regulation and cancer predisposition. Central to the DDR to DSBs is the ataxia-telangiectasia mutated (ATM) kinase, a master controller of signal transduction. Understanding how ATM signaling regulates various aspects of the DDR and its roles in vivo is critical for our understanding of human disease, its diagnosis and its treatment. This review will describe the general roles of ATM signaling and highlight some recent advances that have shed light on the diverse roles of ATM and related proteins in human disease. PMID:23532176

  3. 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. PMID:26157115

  4. Seismic Signal Classification with Offshore/Amphibious Networks Using an Artificial Neural Network

    NASA Astrophysics Data System (ADS)

    Williams, M. C.; Trehu, A. M.

    2011-12-01

    The amphibious Central Oregon Locked Zone Array (COLZA) of seismic stations was deployed from 2007-2009 to record earthquakes occurring in the seismogenic zone offshore central Oregon. This array included two year-long deployments of ocean bottom seismometers (OBS's) from the NSF OBSIP. In addition to local and distant earthquakes, the OBS array recorded thousands of impulsive local signals, which are not easily filtered out by a standard STA/LTA detection algorithm. Many of these signals are likely of biological origin (informally referred to as "bio-bumps"). These signals have a wide range of amplitudes, can mask local earthquake phase arrivals, and make automatic detection more difficult. We show that signal characteristics derived from 3-component seismic data at each station can be used to filter out event detections that are unlikely to be earthquake-generated. A decision-making algorithm is run using a joint set of signal characteristics to identify possible local events and classify detections that are likely to be "bumps". We present results on the effectiveness of this classification technique using various combinations of input parameters applied to the onshore/offshore COLZA array dataset. The classification algorithm is a multilayer perceptron (MLP) artificial neural network, trained through backpropagation using human-identified examples of both earthquake phases and impulsive "bumps". The effectiveness of a neural network is highly dependent on the data space consisting of the inputs calculated for each signal, which represent its main characteristics and differentiate it from other events. As inputs to the neural network, for each event detection, in addition to the STA/LTA value, we determine three signal characteristics from 3-component waveform data: the variance of the power cepstrum calculated from a portion of the signal spectrum, the rectilinearity of particle motion, and the ratio of particle motion orthogonal to the principle direction of

  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. 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

  7. 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

  8. 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

    2016-01-01

    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

  9. 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

  10. 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.

  11. Heparan sulfate is required for bone morphogenetic protein-7 signaling.

    PubMed

    Irie, Atsushi; Habuchi, Hiroko; Kimata, Koji; Sanai, Yutaka

    2003-09-01

    Although genetic studies have suggested that heparan sulfate (HS) is involved in bone morphogenetic protein (BMP)-mediated embryonic morphogenesis, it is unclear whether HS is directly involved in BMP-mediated signaling. Here, we investigate the involvement of HS in BMP-7 signaling. We show that HS and heparin chains specifically bind to BMP-7. Digestion of cell-surface HS with heparitinase interferes with BMP-7-mediated Smad phosphorylation in ROS 17/2.8 osteoblastic cells. Inhibiting sulfation of cell-surface HS with chlorate also causes interruption of Smad phosphorylation. Addition of exogenous heparin to ROS 17/2.8 cells prevents BMP-7-mediated Smad phosphorylation rather than enhances the BMP-7 signal, suggesting that HS should be anchored on the plasma membrane for BMP signaling. Moreover, BMP-7 binding to ROS 17/2.8 cells is inhibited by chlorate treatment and exogenous application of heparin. These results demonstrate that BMP-7 specifically binds to cell-surface HS and the BMP-7-HS interaction is required for BMP-7 signaling. PMID:12927798

  12. Intercellular calcium signaling in a gap junction-coupled cell network establishes asymmetric neuronal fates in C. elegans

    PubMed Central

    Schumacher, Jennifer A.; Hsieh, Yi-Wen; Chen, Shiuhwei; Pirri, Jennifer K.; Alkema, Mark J.; Li, Wen-Hong; Chang, Chieh; Chuang, Chiou-Fen

    2012-01-01

    The C. elegans left and right AWC olfactory neurons specify asymmetric subtypes, one default AWCOFF and one induced AWCON, through a stochastic, coordinated cell signaling event. Intercellular communication between AWCs and non-AWC neurons via a NSY-5 gap junction network coordinates AWC asymmetry. However, the nature of intercellular signaling across the network and how individual non-AWC cells in the network influence AWC asymmetry is not known. Here, we demonstrate that intercellular calcium signaling through the NSY-5 gap junction neural network coordinates a precise 1AWCON/1AWCOFF decision. We show that NSY-5 gap junctions in C. elegans cells mediate small molecule passage. We expressed vertebrate calcium-buffer proteins in groups of cells in the network to reduce intracellular calcium levels, thereby disrupting intercellular communication. We find that calcium in non-AWC cells of the network promotes the AWCON fate, in contrast to the autonomous role of calcium in AWCs to promote the AWCOFF fate. In addition, calcium in specific non-AWCs promotes AWCON side biases through NSY-5 gap junctions. Our results suggest a novel model in which calcium has dual roles within the NSY-5 network: autonomously promoting AWCOFF and non-autonomously promoting AWCON. PMID:23093425

  13. 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

  14. Established and emerging fluorescence-based assays for G-protein function: heterotrimeric G-protein alpha subunits and regulator of G-protein signaling (RGS) proteins.

    PubMed

    Kimple, Randall J; Jones, Miller B; Shutes, Adam; Yerxa, Benjamin R; Siderovski, David P; Willard, Francis S

    2003-06-01

    Heterotrimeric G-proteins are molecular switches that couple serpentine receptors to intracellular effector pathways and the regulation of cell physiology. Ligand-bound receptors cause G-protein alpha subunits to bind guanosine 5'-triphosphate (GTP) and activate effector pathways. Signal termination is facilitated by the intrinsic GTPase activity of G-protein alpha subunits. Regulators of G-protein signaling (RGS) proteins accelerate the GTPase activity of the G-protein alpha subunit, and thus negatively regulate G-protein-mediated signal transduction. In vitro biochemical assays of heterotrimeric G-proteins commonly include measurements of nucleotide binding, GTPase activity, and interaction with RGS proteins. However, the conventional assays for most of these processes involve radiolabeled guanine nucleotide analogues and scintillation counting. In this article, we focus on fluorescence-based methodologies to study heterotrimeric G-protein alpha subunit regulation in vitro. Furthermore, we consider the potential of such techniques in high-throughput screening and drug discovery. PMID:12769684

  15. 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

  16. Pattern Discovery in Breast Cancer Specific Protein Interaction Network

    PubMed Central

    Wu, Xiaogang; Harrison, Scott H.; Chen, Jake Yue

    2009-01-01

    The interest in indentifying novel biomarkers for early stage breast cancer (BRCA) detection has become grown significantly in recent years. From a view of network biology, one of the emerging themes today is to re-characterize a protein’s biological functions in its molecular network. Although many methods have been presented, including network-based gene ranking for molecular biomarker discovery, and graph clustering for functional module discovery, it is still hard to find systems-level properties hidden in disease specific molecular networks. We reconstructed BRCA-related protein interaction network by using BRCA-associated genes/proteins as seeds, and expanding them in an integrated protein interaction database. We further developed a computational framework based on Ant Colony Optimization to rank network nodes. The task of ranking nodes is represented as the problem of finding optimal density distributions of “ant colonies” on all nodes of the network. Our results revealed some interesting systems-level pattern in BRCA-related protein interaction network. PMID:21347162

  17. PADPIN: protein-protein interaction networks of angiogenesis, arteriogenesis, and inflammation in peripheral arterial disease

    PubMed Central

    Vijay, Chaitanya G.; Annex, Brian H.; Bader, Joel S.; Popel, Aleksander S.

    2015-01-01

    Peripheral arterial disease (PAD) results from an obstruction of blood flow in the arteries other than the heart, most commonly the arteries that supply the legs. The complexity of the known signaling pathways involved in PAD, including various growth factor pathways and their cross talks, suggests that analyses of high-throughput experimental data could lead to a new level of understanding of the disease as well as novel and heretofore unanticipated potential targets. Such bioinformatic analyses have not been systematically performed for PAD. We constructed global protein-protein interaction networks of angiogenesis (Angiome), immune response (Immunome), and arteriogenesis (Arteriome) using our previously developed algorithm GeneHits. The term “PADPIN” refers to the angiome, immunome, and arteriome in PAD. Here we analyze four microarray gene expression datasets from ischemic and nonischemic gastrocnemius muscles at day 3 posthindlimb ischemia (HLI) in two genetically different C57BL/6 and BALB/c mouse strains that display differential susceptibility to HLI to identify potential targets and signaling pathways in angiogenesis, immune, and arteriogenesis networks. We hypothesize that identification of the differentially expressed genes in ischemic and nonischemic muscles between the strains that recovers better (C57BL/6) vs. the strain that recovers more poorly (BALB/c) will help for the prediction of target genes in PAD. Our bioinformatics analysis identified several genes that are differentially expressed between the two mouse strains with known functions in PAD including TLR4, THBS1, and PRKAA2 and several genes with unknown functions in PAD including EphA4, TSPAN7, SLC22A4, and EIF2a. PMID:26058837

  18. 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

  19. Protein domain networks: Scale-free mixing of positive and negative exponents

    NASA Astrophysics Data System (ADS)

    Nacher, J. C.; Hayashida, M.; Akutsu, T.

    2006-07-01

    Many biological studies have been focused on the study of proteins, since proteins are essential for most cell functions. Although proteins are unique, they share certain common properties. For example, well-defined regions within a protein can fold independently from the rest of the protein and have their own function. They are called protein domains, and served as protein building blocks. In this article, we present a theoretical model for studying the protein domain networks, where one node of the network corresponds to one protein and two proteins are connected if they contain the same domain. The resulting distribution of nodes with a given degree, k, shows not only a power-law with negative exponent γ=-1, but it resembles the superposition of two power-law functions, one with a negative exponent and another with a positive exponent β=1. We call this distribution pattern “ scale-free mixing”. To explain the emergence of this superposition of power-laws, we propose a basic model with two main components: (1) mutation and (2) duplication of domains. Precisely, duplication gives rise to complete subgraphs (i.e., cliques) on the network, thus for several values of k a large number of nodes with degree k is produced, which explains the positive power-law branch of the degree distribution. In order to compare our model with experimental data, we generate protein domain networks with data from the UniProt Knowledgebase-Swissprot database for protein sequences and using InterPro, Pfam and Smart for domain databases. Our results indicate that the signal of this scale-free mixing pattern is also observed in the experimental data and it is conserved among organisms as Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, Drosophila melanogaster, Mus musculus, and Homo sapiens.

  20. Differential ligand-signaling network of CCL19/CCL21-CCR7 system

    PubMed Central

    Raju, Rajesh; Gadakh, Sachin; Gopal, Priyanka; George, Bijesh; Advani, Jayshree; Soman, Sowmya; Prasad, T. S. K.; Girijadevi, Reshmi

    2015-01-01

    Chemokine (C-C motif) receptor 7 (CCR7), a class A subtype G-Protein Coupled Receptor (GPCR), is involved in the migration, activation and survival of multiple cell types including dendritic cells, T cells, eosinophils, B cells, endothelial cells and different cancer cells. Together, CCR7 signaling system has been implicated in diverse biological processes such as lymph node homeostasis, T cell activation, immune tolerance, inflammatory response and cancer metastasis. CCL19 and CCL21, the two well-characterized CCR7 ligands, have been established to be differential in their signaling through CCR7 in multiple cell types. Although the differential ligand signaling through single receptor have been suggested for many receptors including GPCRs, there exists no resource or platform to analyse them globally. Here, first of its kind, we present the cell-type-specific differential signaling network of CCL19/CCL21-CCR7 system for effective visualization and differential analysis of chemokine/GPCR signaling. Database URL: http:// www. netpath. org/ pathways? path_ id= NetPath_ 46. PMID:26504105

  1. Induction of the Unfolded Protein Response by Constitutive G-protein Signaling in Rod Photoreceptor Cells*

    PubMed Central

    Wang, Tian; Chen, Jeannie

    2014-01-01

    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. PMID:25183010

  2. 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

  3. 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

  4. Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

    PubMed Central

    Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

    2014-01-01

    The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

  5. Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

    PubMed

    Li, Xiu-Qing; Xing, Tim; Du, Donglei

    2016-01-01

    Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity. PMID:26637164

  6. Retrograde signalling at the synapse: a role for Wnt proteins.

    PubMed

    Salinas, P C

    2005-12-01

    The formation of functional synapses requires a proper dialogue between incoming axons and their future synaptic targets. As axons approach their target, they are instructed to slow down and remodel to form proper presynaptic terminals. Although significant progress has been made in the identification of the mechanisms that control axon guidance, little is known about the mechanisms that regulate the conversion of actively growing axon into a presynaptic terminal. We found that Wnt secreted proteins are retrograde signals that regulate the terminal arborization of axons and synaptic differentiation. Wnts released from postsynaptic neurons induce extensive remodelling on incoming axons. This remodelling is manifested by a decrease in axon extension with a concomitant increase in growth-cone size. This morphological change is correlated with changes in the dynamics and organization of microtubules. Studies of a vertebrate synapse and the Drosophila neuromuscular junction suggest that a conserved Wnt signalling pathway modulates presynaptic microtubules as axons remodel during synapse formation. In this paper I discuss the role of the Wnt-Dvl (Dishevelled protein)-GSK-3beta (glycogen synthase kinase-3beta) signalling pathway in axon remodelling during synapse formation in the central nervous system. PMID:16246102

  7. 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

  8. 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

  9. Nerve ending "signal" proteins GAP-43, MARCKS, and BASP1.

    PubMed

    Mosevitsky, Mark I

    2005-01-01

    Mechanisms of growth cone pathfinding in the course of neuronal net formation as well as mechanisms of learning and memory have been under intense investigation for the past 20 years, but many aspects of these phenomena remain unresolved and even mysterious. "Signal" proteins accumulated mainly in the axon endings (growth cones and the presynaptic area of synapses) participate in the main brain processes. These proteins are similar in several essential structural and functional properties. The most prominent similarities are N-terminal fatty acylation and the presence of an "effector domain" (ED) that dynamically binds to the plasma membrane, to calmodulin, and to actin fibrils. Reversible phosphorylation of ED by protein kinase C modulates these interactions. However, together with similarities, there are significant differences among the proteins, such as different conditions (Ca2+ contents) for calmodulin binding and different modes of interaction with the actin cytoskeleton. In light of these facts, we consider GAP-43, MARCKS, and BASP1 both separately and in conjunction. Special attention is devoted to a discussion of apparent inconsistencies in results and opinions of different authors concerning specific questions about the structure of proteins and their interactions. PMID:16125549

  10. Regulator of G-Protein Signaling – 5 (RGS5) Is a Novel Repressor of Hedgehog Signaling

    PubMed Central

    Mahoney, William M.; Gunaje, Jagadambika; Daum, Guenter; Dong, Xiu Rong; Majesky, Mark W.

    2013-01-01

    Hedgehog (Hh) signaling plays fundamental roles in morphogenesis, tissue repair, and human disease. Initiation of Hh signaling is controlled by the interaction of two multipass membrane proteins, patched (Ptc) and smoothened (Smo). Recent studies identify Smo as a G-protein coupled receptor (GPCR)-like protein that signals through large G-protein complexes which contain the Gαi subunit. We hypothesize Regulator of G-Protein Signaling (RGS) proteins, and specifically RGS5, are endogenous repressors of Hh signaling via their ability to act as GTPase activating proteins (GAPs) for GTP-bound Gαi, downstream of Smo. In support of this hypothesis, we demonstrate that RGS5 over-expression inhibits sonic hedgehog (Shh)-mediated signaling and osteogenesis in C3H10T1/2 cells. Conversely, signaling is potentiated by siRNA-mediated knock-down of RGS5 expression, but not RGS4 expression. Furthermore, using immuohistochemical analysis and co-immunoprecipitation (Co-IP), we demonstrate that RGS5 is present with Smo in primary cilia. This organelle is required for canonical Hh signaling in mammalian cells, and RGS5 is found in a physical complex with Smo in these cells. We therefore conclude that RGS5 is an endogenous regulator of Hh-mediated signaling and that RGS proteins are potential targets for novel therapeutics in Hh-mediated diseases. PMID:23637832

  11. 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 6-12h 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 33h 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 differentiation

  12. Prolactin receptor and signal transduction to milk protein genes

    SciTech Connect

    Djiane, J.; Daniel, N.; Bignon, C.

    1994-06-01

    After cloning of the mammary gland prolactin (PRL) receptor cDNA, a functional assay was established using co-transfection of PRL receptor cDNA together with a milk protein promoter/chloramphenicol acetyl transferase (CAT) construct in Chinese hamster ovary (CHO) cells. Different mutants of the PRL receptor were tested in this CAT assay to delimit the domains in the receptor necessary for signal transduction to milk protein genes. In CHO cells stably transfected with PRL receptor cDNA, high numbers of PRL receptor are expressed. By metabolic labeling and immunoprecipitation, expressed PRL receptor was identified as a single species of 100 kDa. Using these cells, we analyzed the effects of PRL on intracellular free Ca{sup ++} concentration. PRL stimulates Ca{sup ++} entry and induces secondary Ca{sup ++} mobilization. The entry of Ca{sup ++} is a result of an increase in K{sup +} conductance that hyperpolarizes the membranes. We have also analyzed tyrosine phosphorylation induced by PRL. In CHO cells stably transfected with PRL receptor cDNA, PRL induced a very rapid and transient tyrosine phosphorylation of a 100-kDa protein which is most probably the PRL receptor. The same finding was obtained in mammary membranes after PRL injection to lactating rabbits. Whereas tyrosine kinase inhibitors genistein and lavendustin were without effect, PRL stimulation of milk protein gene promoters was partially inhibited by 2 {mu}M herbimycin in CHO cells co-transfected with PRL receptor cDNA and the {Beta} lactoglobulin CAT construct. Taken together these observations indicate that the cytoplasmic domain of the PRL receptor interacts with one or several tyrosine kinases, which may represent early postreceptor events necessary for PRL signal transduction to milk protein genes. 14 refs., 4 figs.

  13. 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

  14. G Protein Activation Stimulates Phospholipase D Signaling in Plants.

    PubMed Central

    Munnik, T.; Arisz, S. A.; De Vrije, T.; Musgrave, A.

    1995-01-01

    We provide direct evidence for phospholipase D (PLD) signaling in plants by showing that this enzyme is stimulated by the G protein activators mastoparan, ethanol, and cholera toxin. An in vivo assay for PLD activity in plant cells was developed based on the use of a "reporter alcohol" rather than water as a transphosphatidylation substrate. The product was a phosphatidyl alcohol, which, in contrast to the normal product phosphatidic acid, is a specific measure of PLD activity. When 32P-labeled cells were treated with 0.1% n-butanol, 32P-phosphatidyl butanol (32P-PtdBut) was formed in a time-dependent manner. In cells treated with any of the three G protein activators, the production of 32P-PtdBut was increased in a dose-dependent manner. The G protein involved was pertussis toxin insensitive. Ethanol could activate PLD but was itself consumed by PLD as transphosphatidylation substrate. In contrast, secondary alcohols (e.g., sec-butyl alcohol) activated PLD but did not function as substrate, whereas tertiary alcohols did neither. Although most of the experiments were performed with the green alga Chlamydomonas eugametos, the relevance for higher plants was demonstrated by showing that PLD in carnation petals could also be activated by mastoparan. The results indicate that PLD activation must be considered as a potential signal transduction mechanism in plants, just as in animals. PMID:12242371

  15. 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.

  16. 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

  17. Intrinsic noise, dissipation cost, and robustness of cellular networks: The underlying energy landscape of MAPK signal transduction

    PubMed Central

    Lapidus, Saul; Han, Bo; Wang, Jin

    2008-01-01

    We develop a probabilistic method for analyzing global features of a cellular network under intrinsic statistical fluctuations, which is important when there are finite numbers of molecules. By making a self-consistent mean field approximation of splitting the variables in order to reduce the large number of degrees of freedom, which is reasonable for a not very strongly interacting network, we discovered that the underlying energy landscape of the mitogen-activated protein kinases (MAPKs) signal transduction network (with experimentally measured or inferred parameters such as chemical reaction rate coefficients in the network) is funneled toward a global minimum characterized by the nonequilibrium steady-state fixed point of the system at the end of the signal transduction process. For this system, we also show that the energy landscape is robust against intrinsic fluctuations and random perturbation to the inherent chemical reaction rates. The ratio of the slope versus the roughness of the energy landscape becomes a quantitative measure of robustness and stability of the network. Furthermore, we quantify the dissipation cost of this nonequilibrium system through entropy production, caused by the nonequilibrium flux in the system. We found that a lower dissipation cost corresponds to a more robust network. This least dissipation property might provide a design principle for robust and functional networks. Finally, we find the possibility of bistable and oscillatory-like solutions, which are important for cell fate decisions, upon perturbations. The method described here can be used in a variety of biological networks. PMID:18420822

  18. Two R7 regulator of G-protein signaling proteins shape retinal bipolar cell signaling.

    PubMed

    Mojumder, Deb Kumar; Qian, Yan; Wensel, Theodore G

    2009-06-17

    RGS7, RGS11, and their binding partner Gbeta5 are localized to the dendritic tips of retinal ON bipolar cells (ON-BPC), where mGluR6 responds to glutamate released from photoreceptor terminals by activation of the RGS7/RGS11 substrate, Galphao. To determine their functions in retinal signaling, we investigated cell-specific expression patterns of RGS7 and RGS11 by immunostaining, and measured light responses by electroretinography in mice with targeted disruptions of the genes encoding them. RGS7 staining is present in dendritic tips of all rod ON-BPC, but missing in those for subsets of cone ON-BPC, whereas the converse was true for RGS11 staining. Genetic disruption of either RGS7 or RGS11 produced delays in the ON-BPC-derived electroretinogram b-wave, but no changes in the photoreceptor-derived a-wave. Homozygous RGS7 mutant mice had delays in rod-driven b-waves, whereas RGS11 mutant mice had delays in rod-driven, and especially in cone-driven b-waves. The b-wave delays were further enhanced in mice homozygous for both RGS7 and RGS11 gene disruptions. Thus, RGS7 and RGS11 act in parallel to regulate the kinetics of ON bipolar cell responses, with differential impacts on the rod and cone pathways. PMID:19535587

  19. 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

  20. 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

    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