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Sample records for cellular metabolic networks

  1. Optimal flux patterns in cellular metabolic networks

    SciTech Connect

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  2. Optimal flux patterns in cellular metabolic networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    2007-06-01

    The availability of whole-cell-level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate the metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30 000 random cellular environments. The distribution of reaction fluxes is heavy tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations has relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reactions are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central carbon metabolic pathways for the sample of random environments.

  3. C. elegans Metabolic Gene Regulatory Networks Govern the Cellular Economy

    PubMed Central

    Watson, Emma; Walhout, Albertha J.M.

    2014-01-01

    Diet greatly impacts metabolism in health and disease. In response to the presence or absence of specific nutrients, metabolic gene regulatory networks sense the metabolic state of the cell and regulate metabolic flux accordingly, for instance by the transcriptional control of metabolic enzymes. Here we discuss recent insights regarding metazoan metabolic regulatory networks using the nematode Caenorhabditis elegans as a model, including the modular organization of metabolic gene regulatory networks, the prominent impact of diet on the transcriptome and metabolome, specialized roles of nuclear hormone receptors in responding to dietary conditions, regulation of metabolic genes and metabolic regulators by microRNAs, and feedback between metabolic genes and their regulators. PMID:24731597

  4. Cellular Metabolic Network Analysis: Discovering Important Reactions in Treponema pallidum

    PubMed Central

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis. PMID:26495292

  5. Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

    PubMed

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis. PMID:26495292

  6. Engineering Cellular Metabolism.

    PubMed

    Nielsen, Jens; Keasling, Jay D

    2016-03-10

    Metabolic engineering is the science of rewiring the metabolism of cells to enhance production of native metabolites or to endow cells with the ability to produce new products. The potential applications of such efforts are wide ranging, including the generation of fuels, chemicals, foods, feeds, and pharmaceuticals. However, making cells into efficient factories is challenging because cells have evolved robust metabolic networks with hard-wired, tightly regulated lines of communication between molecular pathways that resist efforts to divert resources. Here, we will review the current status and challenges of metabolic engineering and will discuss how new technologies can enable metabolic engineering to be scaled up to the industrial level, either by cutting off the lines of control for endogenous metabolism or by infiltrating the system with disruptive, heterologous pathways that overcome cellular regulation. PMID:26967285

  7. Exact quantification of cellular robustness in genome-scale metabolic networks

    PubMed Central

    Gerstl, Matthias P.; Klamt, Steffen; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2016-01-01

    Motivation: Robustness, the ability of biological networks to uphold their functionality in spite of perturbations, is a key characteristic of all living systems. Although several theoretical approaches have been developed to formalize robustness, it still eludes an exact quantification. Here, we present a rigorous and quantitative approach for the structural robustness of metabolic networks by measuring their ability to tolerate random reaction (or gene) knockouts. Results: In analogy to reliability theory, based on an explicit consideration of all possible knockout sets, we exactly quantify the probability of failure for a given network function (e.g. growth). This measure can be computed if the network’s minimal cut sets (MSCs) are known. We show that even in genome-scale metabolic networks the probability of (network) failure can be reliably estimated from MSCs with lowest cardinalities. We demonstrate the applicability of our theory by analyzing the structural robustness of multiple Enterobacteriaceae and Blattibacteriaceae and show a dramatically low structural robustness for the latter. We find that structural robustness develops from the ability to proliferate in multiple growth environments consistent with experimentally found knowledge. Conclusion: The probability of (network) failure provides thus a reliable and easily computable measure of structural robustness and redundancy in (genome-scale) metabolic networks. Availability and implementation: Source code is available under the GNU General Public License at https://github.com/mpgerstl/networkRobustnessToolbox. Contact: juergen.zanghellini@boku.ac.at Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26543173

  8. Peroxisome Metabolism and Cellular Aging

    PubMed Central

    Titorenko, Vladimir I.; Terlecky, Stanley R.

    2010-01-01

    The essential role of peroxisomes in fatty acid oxidation, anaplerotic metabolism, and hydrogen peroxide turnover is well established. Recent findings suggest these and other related biochemical processes governed by the organelle may also play a critical role in regulating cellular aging. The goal of this review is to summarize and integrate into a model, the evidence that peroxisome metabolism actually helps define the replicative and chronological age of a eukaryotic cell. In this model, peroxisomal reactive oxygen species (ROS) are seen as altering organelle biogenesis and function, and eliciting changes in the dynamic communication networks that exist between peroxisomes and other cellular compartments. At low levels, peroxisomal ROS activate an anti-aging program in the cell; at concentrations beyond a specific threshold, a pro-aging course is triggered. PMID:21083858

  9. Cellular compartmentalization of secondary metabolism

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fungal secondary metabolism is often considered apart from the essential housekeeping functions of the cell. However, there are clear links between fundamental cellular metabolism and the biochemical pathways leading to secondary metabolite synthesis. Besides utilizing key biochemical precursors sh...

  10. Mathematical Modeling of Cellular Metabolism.

    PubMed

    Berndt, Nikolaus; Holzhütter, Hermann-Georg

    2016-01-01

    Cellular metabolism basically consists of the conversion of chemical compounds taken up from the extracellular environment into energy (conserved in energy-rich bonds of organic phosphates) and a wide array of organic molecules serving as catalysts (enzymes), information carriers (nucleic acids), and building blocks for cellular structures such as membranes or ribosomes. Metabolic modeling aims at the construction of mathematical representations of the cellular metabolism that can be used to calculate the concentration of cellular molecules and the rates of their mutual chemical interconversion in response to varying external conditions as, for example, hormonal stimuli or supply of essential nutrients. Based on such calculations, it is possible to quantify complex cellular functions as cellular growth, detoxification of drugs and xenobiotic compounds or synthesis of exported molecules. Depending on the specific questions to metabolism addressed, the methodological expertise of the researcher, and available experimental information, different conceptual frameworks have been established, allowing the usage of computational methods to condense experimental information from various layers of organization into (self-) consistent models. Here, we briefly outline the main conceptual frameworks that are currently exploited in metabolism research. PMID:27557541

  11. Elements of the cellular metabolic structure

    PubMed Central

    De la Fuente, Ildefonso M.

    2015-01-01

    A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

  12. Robustness of metabolic networks

    NASA Astrophysics Data System (ADS)

    Jeong, Hawoong

    2009-03-01

    We investigated the robustness of cellular metabolism by simulating the system-level computational models, and also performed the corresponding experiments to validate our predictions. We address the cellular robustness from the ``metabolite''-framework by using the novel concept of ``flux-sum,'' which is the sum of all incoming or outgoing fluxes (they are the same under the pseudo-steady state assumption). By estimating the changes of the flux-sum under various genetic and environmental perturbations, we were able to clearly decipher the metabolic robustness; the flux-sum around an essential metabolite does not change much under various perturbations. We also identified the list of the metabolites essential to cell survival, and then ``acclimator'' metabolites that can control the cell growth were discovered. Furthermore, this concept of ``metabolite essentiality'' should be useful in developing new metabolic engineering strategies for improved production of various bioproducts and designing new drugs that can fight against multi-antibiotic resistant superbacteria by knocking-down the enzyme activities around an essential metabolite. Finally, we combined a regulatory network with the metabolic network to investigate its effect on dynamic properties of cellular metabolism.

  13. Cellular energy metabolism

    SciTech Connect

    Glaser, M.

    1991-06-01

    Studies have been carried out on adenylate kinase which is an important enzyme in determining the concentrations of the adenine nucleotides. An efficient method has been developed to clone mutant adenylate kinase genes in E. coli. Site-specific mutagenesis of the wild type gene also has been used to obtain forms of adenylate kinase with altered amino acids. The wild type and mutant forms of adenylate kinase have been overexpressed and large quantities were readily isolated. The kinetic and fluorescence properties of the different forms of adenylate kinase were characterized. This has led to a new model for the location of the AMP and ATP bindings sites on the enzyme and a proposal for the mechanism of substrate inhibition. Crystals of the wild type enzyme were obtained that diffract to at least 2.3 {angstrom} resolution. Experiments were also initiated to determine the function of adenylate kinase in vivo. In one set of experiments, E. coli strains with mutations in adenylate kinase showed large changes in cellular nucleotides after reaching the stationary phase in a low phosphate medium. This was caused by selective proteolytic degradation of the mutant adenylate kinase caused by phosphate starvation.

  14. Cellular compartmentalization of secondary metabolism

    PubMed Central

    Kistler, H. Corby; Broz, Karen

    2015-01-01

    Fungal secondary metabolism is often considered apart from the essential housekeeping functions of the cell. However, there are clear links between fundamental cellular metabolism and the biochemical pathways leading to secondary metabolite synthesis. Besides utilizing key biochemical precursors shared with the most essential processes of the cell (e.g., amino acids, acetyl CoA, NADPH), enzymes for secondary metabolite synthesis are compartmentalized at conserved subcellular sites that position pathway enzymes to use these common biochemical precursors. Co-compartmentalization of secondary metabolism pathway enzymes also may function to channel precursors, promote pathway efficiency and sequester pathway intermediates and products from the rest of the cell. In this review we discuss the compartmentalization of three well-studied fungal secondary metabolite biosynthetic pathways for penicillin G, aflatoxin and deoxynivalenol, and summarize evidence used to infer subcellular localization. We also discuss how these metabolites potentially are trafficked within the cell and may be exported. PMID:25709603

  15. Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

    PubMed Central

    de la Fuente, Ildefonso Martínez

    2010-01-01

    One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

  16. Cellular metabolism and disease: what do metabolic outliers teach us?

    PubMed Central

    DeBerardinis, Ralph J.; Thompson, Craig B.

    2012-01-01

    An understanding of metabolic pathways based solely on biochemistry textbooks would underestimate the pervasive role of metabolism in essentially every aspect of biology. It is evident from recent work that many human diseases involve abnormal metabolic states – often genetically programmed – that perturb normal physiology and lead to severe tissue dysfunction. Understanding these metabolic outliers is now a crucial frontier in disease-oriented research. This review discusses the broad impact of metabolism in cellular function, how modern concepts of metabolism can inform our understanding of common diseases like cancer, and considers the prospects of developing new metabolic approaches to disease treatment. PMID:22424225

  17. MSAT and cellular hybrid networking

    NASA Technical Reports Server (NTRS)

    Baranowsky, Patrick W., II

    1993-01-01

    Westinghouse Electric Corporation is developing both the Communications Ground Segment and the Series 1000 Mobile Phone for American Mobile Satellite Corporation's (AMSC's) Mobile Satellite (MSAT) system. The success of the voice services portion of this system depends, to some extent, upon the interoperability of the cellular network and the satellite communication circuit switched communication channels. This paper will describe the set of user-selectable cellular interoperable modes (cellular first/satellite second, etc.) provided by the Mobile Phone and described how they are implemented with the ground segment. Topics including roaming registration and cellular-to-satellite 'seamless' call handoff will be discussed, along with the relevant Interim Standard IS-41 Revision B Cellular Radiotelecommunications Intersystem Operations and IOS-553 Mobile Station - Land Station Compatibility Specification.

  18. Immunometabolism: Cellular Metabolism Turns Immune Regulator.

    PubMed

    Loftus, Róisín M; Finlay, David K

    2016-01-01

    Immune cells are highly dynamic in terms of their growth, proliferation, and effector functions as they respond to immunological challenges. Different immune cells can adopt distinct metabolic configurations that allow the cell to balance its requirements for energy, molecular biosynthesis, and longevity. However, in addition to facilitating immune cell responses, it is now becoming clear that cellular metabolism has direct roles in regulating immune cell function. This review article describes the distinct metabolic signatures of key immune cells, explains how these metabolic setups facilitate immune function, and discusses the emerging evidence that intracellular metabolism has an integral role in controlling immune responses. PMID:26534957

  19. Control of fluxes in metabolic networks.

    PubMed

    Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

    2016-07-01

    Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

  20. Compartmentalization of the Edinburgh Human Metabolic Network

    PubMed Central

    2010-01-01

    Background Direct in vivo investigation of human metabolism is complicated by the distinct metabolic functions of various sub-cellular organelles. Diverse micro-environments in different organelles may lead to distinct functions of the same protein and the use of different enzymes for the same metabolic reaction. To better understand the complexity in the human metabolism, a compartmentalized human metabolic network with integrated sub-cellular location information is required. Results We extended the previously reconstructed Edinburgh Human Metabolic Network (EHMN) [Ma, et al. Molecular Systems Biology, 3:135, 2007] by integrating the sub-cellular location information for the reactions, adding transport reactions and refining the protein-reaction relationships based on the location information. Firstly, protein location information was obtained from Gene Ontology and complemented by a Swiss-Prot location keywords search. Then all the reactions in EHMN were assigned to a location based on the protein-reaction relationships to get a preliminary compartmentalized network. We investigated the localized sub-networks in each pathway to identify gaps and isolated reactions by connectivity analysis and refined the location information based on information from literature. As a result, location information for hundreds of reactions was revised and hundreds of incorrect protein-reaction relationships were corrected. Over 1400 transport reactions were added to link the location specific metabolic network. To validate the network, we have done pathway analysis to examine the capability of the network to synthesize or degrade certain key metabolites. Compared with a previously published human metabolic network (Human Recon 1), our network contains over 1000 more reactions assigned to clear cellular compartments. Conclusions By combining protein location information, network connectivity analysis and manual literature search, we have reconstructed a more complete

  1. Primitive control of cellular metabolism

    NASA Technical Reports Server (NTRS)

    Mitz, M. A.

    1974-01-01

    It is pointed out that control substances must have existed from the earliest times in the evolution of life and that the same control mechanisms must exist today. The investigation reported is concerned with the concept that carbon dioxide is a primitive regulator of cell function. The effects of carbon dioxide on cellular materials are examined, taking into account questions of solubilization, dissociation, changes of charge, stabilization, structural changes, wettability, the exclusion of other gases, the activation of compounds, changes in plasticity, and changes in membrane permeability.

  2. The challenges of cellular compartmentalization in plant metabolic engineering.

    PubMed

    Heinig, Uwe; Gutensohn, Michael; Dudareva, Natalia; Aharoni, Asaph

    2013-04-01

    The complex metabolic networks in plants are highly compartmentalized and biochemical steps of a single pathway can take place in multiple subcellular locations. Our knowledge regarding reactions and precursor compounds in the various cellular compartments has increased in recent years due to innovations in tracking the spatial distribution of proteins and metabolites. Nevertheless, to date only few studies have integrated subcellular localization criteria in metabolic engineering attempts. Here, we highlight the crucial factors for subcellular-localization-based strategies in plant metabolic engineering including substrate availability, enzyme targeting, the role of transporters, and multigene transfer approaches. The availability of compartmentalized metabolic network models for plants in the near future will greatly advance the integration of localization constraints in metabolic engineering experiments and aid in predicting their outcomes. PMID:23246154

  3. Predicting and Analyzing Cellular Networks

    NASA Astrophysics Data System (ADS)

    Singh, Mona

    High-throughput experimental technologies, along with computational predictions, have resulted in large-scale biological networks for numerous organisms. Global analyses of biological networks provide new opportunities for revealing protein functions and pathways, and for uncovering cellular organization principles. In my talk, I will discuss a number of approaches we have developed over the years for the complementary problems of predicting interactions and analyzing interaction networks. First, I will describe a genomic approach for uncovering high-confidence regulatory interactions, and show how it can be effectively combined with a framework for predicting regulatory interactions for proteins with known structural domains but unknown binding specificity. Next, I will describe algorithms for analyzing protein interaction networks in order to uncover protein function and functional modules, and demonstrate the importance of considering the topological structure of interaction networks in order to make high quality predictions. Finally, I will present a framework for explicitly incorporating known attributes of individual proteins into the analysis of biological networks, and utilize it to discover recurring network patterns underlying a range of biological processes.

  4. Complement-Mediated Regulation of Metabolism and Basic Cellular Processes.

    PubMed

    Hess, Christoph; Kemper, Claudia

    2016-08-16

    Complement is well appreciated as a critical arm of innate immunity. It is required for the removal of invading pathogens and works by directly destroying them through the activation of innate and adaptive immune cells. However, complement activation and function is not confined to the extracellular space but also occurs within cells. Recent work indicates that complement activation regulates key metabolic pathways and thus can impact fundamental cellular processes, such as survival, proliferation, and autophagy. Newly identified functions of complement include a key role in shaping metabolic reprogramming, which underlies T cell effector differentiation, and a role as a nexus for interactions with other effector systems, in particular the inflammasome and Notch transcription-factor networks. This review focuses on the contributions of complement to basic processes of the cell, in particular the integration of complement with cellular metabolism and the potential implications in infection and other disease settings. PMID:27533012

  5. Cellular metabolism of unnatural sialic acid precursors.

    PubMed

    Pham, Nam D; Fermaintt, Charles S; Rodriguez, Andrea C; McCombs, Janet E; Nischan, Nicole; Kohler, Jennifer J

    2015-10-01

    Carbohydrates, in addition to their metabolic functions, serve important roles as receptors, ligands, and structural molecules for diverse biological processes. Insight into carbohydrate biology and mechanisms has been aided by metabolic oligosaccharide engineering (MOE). In MOE, unnatural carbohydrate analogs with novel functional groups are incorporated into cellular glycoconjugates and used to probe biological systems. While MOE has expanded knowledge of carbohydrate biology, limited metabolism of unnatural carbohydrate analogs restricts its use. Here we assess metabolism of SiaDAz, a diazirine-modified analog of sialic acid, and its cell-permeable precursor, Ac4ManNDAz. We show that the efficiency of Ac4ManNDAz and SiaDAz metabolism depends on cell type. Our results indicate that different cell lines can have different metabolic roadblocks in the synthesis of cell surface SiaDAz. These findings point to roles for promiscuous intracellular esterases, kinases, and phosphatases during unnatural sugar metabolism and provide guidance for ways to improve MOE. PMID:25957566

  6. Global Self-Organization of the Cellular Metabolic Structure

    PubMed Central

    De La Fuente, Ildefonso M.; Martínez, Luis; Pérez-Samartín, Alberto L.; Ormaetxea, Leire; Amezaga, Cristian; Vera-López, Antonio

    2008-01-01

    Background Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using “metabolic networks models” are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used “dissipative metabolic networks” (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures. PMID:18769681

  7. Integrating Cellular Metabolism into a Multiscale Whole-Body Model

    PubMed Central

    Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

    2012-01-01

    Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

  8. Lipid Droplets And Cellular Lipid Metabolism

    PubMed Central

    Walther, Tobias C.; Farese, Robert V.

    2013-01-01

    Among organelles, lipid droplets (LDs) uniquely constitute a hydrophobic phase in the aqueous environment of the cytosol. Their hydrophobic core of neutral lipids stores metabolic energy and membrane components, making LDs hubs for lipid metabolism. In addition, LDs are implicated in a number of other cellular functions, ranging from protein storage and degradation to viral replication. These processes are functionally linked to many physiological and pathological conditions, including obesity and related metabolic diseases. Despite their important functions and nearly ubiquitous presence in cells, many aspects of LD biology are unknown. In the past few years, the pace of LD investigation has increased, providing new insights. Here, we review the current knowledge of LD cell biology and its translation to physiology. PMID:22524315

  9. Micromechanics of cellularized biopolymer networks

    PubMed Central

    Jones, Christopher A. R.; Cibula, Matthew; Feng, Jingchen; Krnacik, Emma A.; McIntyre, David H.; Levine, Herbert; Sun, Bo

    2015-01-01

    Collagen gels are widely used in experiments on cell mechanics because they mimic the extracellular matrix in physiological conditions. Collagen gels are often characterized by their bulk rheology; however, variations in the collagen fiber microstructure and cell adhesion forces cause the mechanical properties to be inhomogeneous at the cellular scale. We study the mechanics of type I collagen on the scale of tens to hundreds of microns by using holographic optical tweezers to apply pN forces to microparticles embedded in the collagen fiber network. We find that in response to optical forces, particle displacements are inhomogeneous, anisotropic, and asymmetric. Gels prepared at 21 °C and 37 °C show qualitative difference in their micromechanical characteristics. We also demonstrate that contracting cells remodel the micromechanics of their surrounding extracellular matrix in a strain- and distance-dependent manner. To further understand the micromechanics of cellularized extracellular matrix, we have constructed a computational model which reproduces the main experiment findings. PMID:26324923

  10. Approximating the stabilization of cellular metabolism by compartmentalization.

    PubMed

    Fürtauer, Lisa; Nägele, Thomas

    2016-06-01

    Biochemical regulation in compartmentalized metabolic networks is highly complex and non-intuitive. This is particularly true for cells of higher plants showing one of the most compartmentalized cellular structures across all kingdoms of life. The interpretation and testable hypothesis generation from experimental data on such complex systems is a challenging step in biological research and biotechnological applications. While it is known that subcellular compartments provide defined reaction spaces within a cell allowing for the tight coordination of complex biochemical reaction sequences, its role in the coordination of metabolic signals during metabolic reprogramming due to environmental fluctuations is less clear. In the present study, we numerically analysed the effects of environmental fluctuations in a subcellular metabolic network with regard to the stability of an experimentally observed steady state in the genetic model plant Arabidopsis thaliana. Applying a method for kinetic parameter normalization, several millions of probable enzyme kinetic parameter constellations were simulated and evaluated with regard to the stability information of the metabolic homeostasis. Information about the stability of the metabolic steady state was derived from real parts of eigenvalues of Jacobian matrices. Our results provide evidence for a differential stabilizing contribution of different subcellular compartments. We could identify stabilizing and destabilizing network components which we could classify according to their subcellular localization. The findings prove that a highly dynamic interplay between intracellular compartments is preliminary for an efficient stabilization of a metabolic homeostasis after environmental perturbation. Further, our results provide evidence that feedback-inhibition originating from the cytosol and plastid seem to stabilize the sucrose homeostasis more efficiently than vacuolar control. In summary, our results indicate stabilizing and

  11. Sesquiterpene antitumor agents: inhibitors of cellular metabolism.

    PubMed

    Lee, K H; Hall, I H; Mar, E C; Starnes, C O; ElGebaly, S A; Waddell, T G; HADGRAFT, R I; Ruffner, C G; Weidner, I

    1977-04-29

    Helenalin and tenulin injected into CF1 male mice bearing Ehrlich ascites tumors inhibit DNA synthesis and DNA polymerase enzymatic activity in the tumor cells. Helenalin inhibited protein synthesis. Both drugs increased the concentration of adenosine 3',5'-monophosphate, and interfered with glycolytic and mitochondrial energy processes. Cholesterol synthesis was also inhibited, resulting in lower serum cholesterol levels in tumor-bearing animals. Data obtained in vitro indicate that the cyclopentenone-bearing sesquiterpene lactone and related compounds do not alkylate puring bases of nucleic acids but rather undergo a Michael-type addition reaction with the sulfhydryl groups of reduced glutathione and l-cysteine. Thus, the inhibition of cellular enzyme activities and metabolism that has been observed with these drugs might be explained by the occurrence of a Michael-type teaction. PMID:191909

  12. Aging cellular networks: chaperones as major participants.

    PubMed

    Soti, C; Csermely, P

    2007-01-01

    We increasingly rely on the network approach to understand the complexity of cellular functions. Chaperones (heat shock proteins) are key "networkers", which sequester and repair damaged proteins. In order to link the network approach and chaperones with the aging process, we first summarize the properties of aging networks suggesting a "weak link theory of aging". This theory suggests that age-related random damage primarily affects the overwhelming majority of the low affinity, transient interactions (weak links) in cellular networks leading to increased noise, destabilization and diversity. These processes may be further amplified by age-specific network remodelling and by the sequestration of weakly linked cellular proteins to protein aggregates of aging cells. Chaperones are weakly linked hubs (i.e., network elements with a large number of connections) and inter-modular bridge elements of protein-protein interaction, signalling and mitochondrial networks. As aging proceeds, the increased overload of damaged proteins is an especially important element contributing to cellular disintegration and destabilization. Additionally, chaperone overload may contribute to the increase of "noise" in aging cells, which leads to an increased stochastic resonance resulting in a deficient discrimination between signals and noise. Chaperone- and other multi-target therapies, which restore the missing weak links in aging cellular networks, may emerge as important anti-aging interventions. PMID:16814508

  13. [Cellular metabolism of sodium and hypertension].

    PubMed

    Cusi, D; Colombo, R; Pozzoli, E; Bianchi, G

    1989-01-01

    Essential hypertension develops from interactions between genetic and environmental components. Studies on cell membrane ions (in particular the sodium ion) transport in essential hypertension were originally carried out in order to better understand the roles these two components play in a less complex system than the overall organ system or the single organs involved in blood pressure regulation. The theory supporting this experimental approach is based on the observation that cell membrane function affects all the phenomena involved in blood pressure regulation. Receptor function, hormonal secretion, cell volume regulation, ion transport and ion composition of the cell are all regulated at the cell membrane level. However the problem of the relevance of cellular sodium metabolism in the pathogenesis of essential hypertension and of the interpretation of the many conflicting results has grown in complexity with the growing mass of data published in the literature. At least part of this complexity seems related to methodological problems but part is surely due to real differences among the various populations or subpopulations studied. This review analyzes the main sources of the discrepancies, the different ion transport systems and the end point of the overall transport system as well as the steady state intracellular cation concentration in both genetic animal models of essential hypertension and in man. PMID:2702018

  14. The widespread role of non-enzymatic reactions in cellular metabolism

    PubMed Central

    Keller, Markus A; Piedrafita, Gabriel; Ralser, Markus

    2015-01-01

    Enzymes shape cellular metabolism, are regulated, fast, and for most cases specific. Enzymes do not however prevent the parallel occurrence of non-enzymatic reactions. Non-enzymatic reactions were important for the evolution of metabolic pathways, but are retained as part of the modern metabolic network. They divide into unspecific chemical reactivity and specific reactions that occur either exclusively non-enzymatically as part of the metabolic network, or in parallel to existing enzyme functions. Non-enzymatic reactions resemble catalytic mechanisms as found in all major enzyme classes and occur spontaneously, small molecule (e.g. metal-) catalyzed or light-induced. The frequent occurrence of non-enzymatic reactions impacts on stability and metabolic network structure, and has thus to be considered in the context of metabolic disease, network modeling, biotechnology and drug design. PMID:25617827

  15. Stability of Stochastic Neutral Cellular Neural Networks

    NASA Astrophysics Data System (ADS)

    Chen, Ling; Zhao, Hongyong

    In this paper, we study a class of stochastic neutral cellular neural networks. By constructing a suitable Lyapunov functional and employing the nonnegative semi-martingale convergence theorem we give some sufficient conditions ensuring the almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration. Finally, two examples are provided to show the correctness of our analysis.

  16. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    PubMed Central

    2011-01-01

    Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

  17. Inferring cellular networks – a review

    PubMed Central

    Markowetz, Florian; Spang, Rainer

    2007-01-01

    In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations. PMID:17903286

  18. Autophagy in cellular metabolism and cancer

    PubMed Central

    Jiang, Xuejun; Overholtzer, Michael; Thompson, Craig B.

    2015-01-01

    Autophagy is a catabolic process mediated by incorporation of cellular material into cytosolic membrane vesicles for lysosomal degradation. It is crucial for maintaining cell viability and homeostasis in response to numerous stressful conditions. In this Review, the role of autophagy in both normal biology and disease is discussed. Emphasis is given to the interplay of autophagy with nutrient signaling through the ULK1 autophagy pre-initiation complex. Furthermore, related cellular processes utilizing components of the canonical autophagy pathway are discussed due to their potential roles in nutrient scavenging. Finally, the role of autophagy in cancer and its potential as a cancer therapeutic target are considered. PMID:25654550

  19. Sestrins orchestrate cellular metabolism to attenuate aging

    PubMed Central

    Karin, Michael

    2013-01-01

    Summary The Sestrins constitute a family of evolutionarily-conserved stress-inducible proteins that suppress oxidative stress and regulate adenosine monophosphate-dependent protein kinase (AMPK)-mammalian target of rapamycin (mTOR) signaling. By virtue of these activities, the Sestrins serve as important regulators of metabolic homeostasis. Accordingly, inactivation of Sestrin genes in invertebrates resulted in diverse metabolic pathologies, including oxidative damage, fat accumulation, mitochondrial dysfunction and muscle degeneration that resemble accelerated tissue aging. Likewise, Sestrin deficiencies in mice led to accelerated diabetic progression upon obesity. Further investigation of Sestrin function and regulation should provide new insights into age-associated metabolic diseases, such as diabetes, myopathies and cancer. PMID:24055102

  20. Translation Factors Specify Cellular Metabolic State.

    PubMed

    Mata, Juan

    2016-08-16

    In this issue of Cell Reports, Shah et al. present evidence that a subcomplex of the eIF3 translation initiation factor regulates translation of mRNAs encoding components of the mitochondrial electron transport chain and glycolytic enzymes, thus linking translational control with energy metabolism. PMID:27533178

  1. MOLECULAR PROCESSES IN CELLULAR ARSENIC METABOLISM

    EPA Science Inventory

    Elucidating molecular processes that underlie accumulation, metabolism, and binding of iAs and its methylated metabolites provides a basis for understanding the modes of action by which iAs acts as a toxin and a carcinogen. One approach to this problem is to construct a conceptu...

  2. Is cancer a disease of abnormal cellular metabolism?

    PubMed Central

    DeBerardinis, Ralph J.

    2009-01-01

    In the 1920s, Otto Warburg observed that tumor cells consume a large amount of glucose, much more than normal cells, and convert most of it to lactic acid. This phenomenon, now known as the ‘Warburg effect,’ is the foundation of one of the earliest general concepts of cancer: that a fundamental disturbance of cellular metabolic activity is at the root of tumor formation and growth. In the ensuing decades, as it became apparent that abnormalities in chromosomes and eventually individual genes caused cancer, the ‘metabolic’ model of cancer lost a good deal of its appeal, even as emerging technologies were exploiting the Warburg effect clinically to detect tumors in vivo. We now know that tumor suppressors and proto-oncogenes influence metabolism, and that mutations in these genes can promote a metabolic phenotype supporting cell growth and proliferation. Thus, these advances have unified aspects of the metabolic and genetic models of cancer, and have stimulated a renewed interest in the role of cellular metabolism in tumorigenesis. This review reappraises the notion that dysregulated cellular metabolism is a key feature of cancer, and discusses some metabolic issues that have escaped scrutiny over the years and now deserve closer attention. PMID:18941420

  3. Using metabolomics approaches to understand the effects of changing nutrient availability on cellular metabolism

    NASA Astrophysics Data System (ADS)

    Higgins, M. B.; Rabinowitz, J. D.

    2010-12-01

    HPLC-MS-based metabolomics techniques allow for a holistic, quantitative understanding of the effects of changing environmental conditions on cellular metabolism. Here, we use HPLC-MS and HPLC-MS/MS to quantitatively analyze the dynamics of a suite of >100 intracellular metabolites in the model gram negative bacteria Escherichia coli under changing conditions of phosphorus availability. Using stable carbon isotope tracers, we examine the effects of phosphorus availability on central carbon metabolism on short (30s - 2h) timescales. This approach allows for enhanced understanding of nutrient-driven metabolic network regulation and how enzyme networks control fluxes and concentrations of metabolites. Such techniques have application for understanding the cellular control of carbon transformations in a variety of environmental settings.

  4. Heterogeneous Force Chains in Cellularized Biopolymer Network

    NASA Astrophysics Data System (ADS)

    Liang, Long; Jones, Christopher Allen Rucksack; Sun, Bo; Jiao, Yang

    Biopolymer Networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the mechanical response of a model biopolymer network due to the active contraction of embedded cells. Specifically, a graph (bond-node) model derived from confocal microscopy data is used to represent the network microstructure, and cell contraction is modeled by applying correlated displacements at specific nodes, representing the focal adhesion sites. A force-based stochastic relaxation method is employed to obtain force-balanced network under cell contraction. We find that the majority of the forces are carried by a small number of heterogeneous force chains emerged from the contracting cells. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to the reorientation induced by cell contraction. Large fluctuations of the forces along different force chains are observed. Importantly, the decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure could support long-range mechanical signaling between cells.

  5. Cellular automata modelling of biomolecular networks dynamics.

    PubMed

    Bonchev, D; Thomas, S; Apte, A; Kier, L B

    2010-01-01

    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  6. Torsins Are Essential Regulators of Cellular Lipid Metabolism.

    PubMed

    Grillet, Micheline; Dominguez Gonzalez, Beatriz; Sicart, Adria; Pöttler, Maria; Cascalho, Ana; Billion, Karolien; Hernandez Diaz, Sergio; Swerts, Jef; Naismith, Teresa V; Gounko, Natalia V; Verstreken, Patrik; Hanson, Phyllis I; Goodchild, Rose E

    2016-08-01

    Torsins are developmentally essential AAA+ proteins, and mutation of human torsinA causes the neurological disease DYT1 dystonia. They localize in the ER membranes, but their cellular function remains unclear. We now show that dTorsin is required in Drosophila adipose tissue, where it suppresses triglyceride levels, promotes cell growth, and elevates membrane lipid content. We also see that human torsinA at the inner nuclear membrane is associated with membrane expansion and elevated cellular lipid content. Furthermore, the key lipid metabolizing enzyme, lipin, is mislocalized in dTorsin-KO cells, and dTorsin increases levels of the lipin substrate, phosphatidate, and reduces the product, diacylglycerol. Finally, genetic suppression of dLipin rescues dTorsin-KO defects, including adipose cell size, animal growth, and survival. These findings identify that torsins are essential regulators of cellular lipid metabolism and implicate disturbed lipid biology in childhood-onset DYT1 dystonia. PMID:27453503

  7. Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

    PubMed Central

    Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R.; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

    2014-01-01

    Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates. PMID:25540776

  8. A Wireless Communications Laboratory on Cellular Network Planning

    ERIC Educational Resources Information Center

    Dawy, Z.; Husseini, A.; Yaacoub, E.; Al-Kanj, L.

    2010-01-01

    The field of radio network planning and optimization (RNPO) is central for wireless cellular network design, deployment, and enhancement. Wireless cellular operators invest huge sums of capital on deploying, launching, and maintaining their networks in order to ensure competitive performance and high user satisfaction. This work presents a lab…

  9. The Impact of Non-Enzymatic Reactions and Enzyme Promiscuity on Cellular Metabolism during (Oxidative) Stress Conditions

    PubMed Central

    Piedrafita, Gabriel; Keller, Markus A; Ralser, Markus

    2015-01-01

    Cellular metabolism assembles in a structurally highly conserved, but functionally dynamic system, known as the metabolic network. This network involves highly active, enzyme-catalyzed metabolic pathways that provide the building blocks for cell growth. In parallel, however, chemical reactivity of metabolites and unspecific enzyme function give rise to a number of side products that are not part of canonical metabolic pathways. It is increasingly acknowledged that these molecules are important for the evolution of metabolism, affect metabolic efficiency, and that they play a potential role in human disease—age-related disorders and cancer in particular. In this review we discuss the impact of oxidative and other cellular stressors on the formation of metabolic side products, which originate as a consequence of: (i) chemical reactivity or modification of regular metabolites; (ii) through modifications in substrate specificity of damaged enzymes; and (iii) through altered metabolic flux that protects cells in stress conditions. In particular, oxidative and heat stress conditions are causative of metabolite and enzymatic damage and thus promote the non-canonical metabolic activity of the cells through an increased repertoire of side products. On the basis of selected examples, we discuss the consequences of non-canonical metabolic reactivity on evolution, function and repair of the metabolic network. PMID:26378592

  10. [Construction and structural analysis of integrated cellular network of Corynebacterium glutamicum].

    PubMed

    Jiang, Jinguo; Song, Lifu; Zheng, Ping; Jia, Shiru; Sun, Jibin

    2012-05-01

    Corynebacterium glutamicum is one of the most important traditional industrial microorganisms and receiving more and more attention towards a novel cellular factory due to the recently rapid development in genomics and genetic operation toolboxes for Corynebacterium. However, compared to other model organisms such as Escherichia coli, there were few studies on its metabolic regulation, especially a genome-scale integrated cellular network model currently missing for Corynebacterium, which hindered the systematic study of Corynebacterium glutamicum and large-scale rational design and optimization for strains. Here, by gathering relevant information from a number of public databases, we successfully constructed an integrated cellular network, which was composed of 1384 reactions, 1276 metabolites, 88 transcriptional factors and 999 pairs of transcriptional regulatory relationships. The transcriptional regulatory sub-network could be arranged into five layers and the metabolic sub-network presented a clear bow-tie structure. We proposed a new method to extract complex metabolic and regulatory sub-network for product-orientated study taking lysine biosynthesis as an example. The metabolic and regulatory sub-network extracted by our method was more close to the real functional network than the simplex biochemical pathways. The results would be greatly helpful for understanding the high-yielding biomechanism for amino acids and the re-design of the industrial strains. PMID:22916496

  11. Metabolic Constraint-Based Refinement of Transcriptional Regulatory Networks

    PubMed Central

    Chandrasekaran, Sriram; Price, Nathan D.

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10−172), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10−14) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework

  12. Metabolic constraint-based refinement of transcriptional regulatory networks.

    PubMed

    Chandrasekaran, Sriram; Price, Nathan D

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10(-172)), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10(-14)) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework to

  13. Metabolic modulation and cellular therapy of cardiac dysfunction and failure

    PubMed Central

    Revenco, Diana; Morgan, James P

    2009-01-01

    Abstract At present the prevalence of heart failure rises along with aging of the population. Current heart failure therapeutic options are directed towards disease prevention via neurohormonal antagonism (β-blockers, angiotensin converting enzyme inhibitors and/or angiotensin receptor blockers and aldosterone antagonists), symptomatic treatment with diuretics and digitalis and use of biventricular pacing and defibrillators in a special subset of patients. Despite these therapies and device interventions heart failure remains a progressive disease with high mortality and morbidity rates. The number of patients who survive to develop advanced heart failure is increasing. These patients require new therapeutic strategies. In this review two of emerging therapies in the treatment of heart failure are discussed: metabolic modulation and cellular therapy. Metabolic modulation aims to optimize the myocardial energy utilization via shifting the substrate utilization from free fatty acids to glucose. Cellular therapy on the other hand has the goal to achieve true cardiac regeneration. We review the experimental data that support these strategies as well as the available pharmacological agents for metabolic modulation and clinical application of cellular therapy. PMID:19382894

  14. 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

  15. An online system for metabolic network analysis

    PubMed Central

    Cicek, Abdullah Ercument; Qi, Xinjian; Cakmak, Ali; Johnson, Stephen R.; Han, Xu; Alshalwi, Sami; Ozsoyoglu, Zehra Meral; Ozsoyoglu, Gultekin

    2014-01-01

    Metabolic networks have become one of the centers of attention in life sciences research with the advancements in the metabolomics field. A vast array of studies analyzes metabolites and their interrelations to seek explanations for various biological questions, and numerous genome-scale metabolic networks have been assembled to serve for this purpose. The increasing focus on this topic comes with the need for software systems that store, query, browse, analyze and visualize metabolic networks. PathCase Metabolomics Analysis Workbench (PathCaseMAW) is built, released and runs on a manually created generic mammalian metabolic network. The PathCaseMAW system provides a database-enabled framework and Web-based computational tools for browsing, querying, analyzing and visualizing stored metabolic networks. PathCaseMAW editor, with its user-friendly interface, can be used to create a new metabolic network and/or update an existing metabolic network. The network can also be created from an existing genome-scale reconstructed network using the PathCaseMAW SBML parser. The metabolic network can be accessed through a Web interface or an iPad application. For metabolomics analysis, steady-state metabolic network dynamics analysis (SMDA) algorithm is implemented and integrated with the system. SMDA tool is accessible through both the Web-based interface and the iPad application for metabolomics analysis based on a metabolic profile. PathCaseMAW is a comprehensive system with various data input and data access subsystems. It is easy to work with by design, and is a promising tool for metabolomics research and for educational purposes. Database URL: http://nashua.case.edu/PathwaysMAW/Web PMID:25267793

  16. Metabolism and evolution: A comparative study of reconstructed genome-level metabolic networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    2008-03-01

    The availability of high-quality annotations of sequenced genomes has made it possible to generate organism-specific comprehensive maps of cellular metabolism. Currently, more than twenty such metabolic reconstructions are publicly available, with the majority focused on bacteria. A typical metabolic reconstruction for a bacterium results in a complex network containing hundreds of metabolites (nodes) and reactions (links), while some even contain more than a thousand. The constrain-based optimization approach of flux-balance analysis (FBA) is used to investigate the functional characteristics of such large-scale metabolic networks, making it possible to estimate an organism's growth behavior in a wide variety of nutrient environments, as well as its robustness to gene loss. We have recently completed the genome-level metabolic reconstruction of Yersinia pseudotuberculosis, as well as the three Yersinia pestis biovars Antiqua, Mediaevalis, and Orientalis. While Y. pseudotuberculosis typically only causes fever and abdominal pain that can mimic appendicitis, the evolutionary closely related Y. pestis strains are the aetiological agents of the bubonic plague. In this presentation, I will discuss our results and conclusions from a comparative study on the evolution of metabolic function in the four Yersiniae networks using FBA and related techniques, and I will give particular focus to the interplay between metabolic network topology and evolutionary flexibility.

  17. Signatures of arithmetic simplicity in metabolic network architecture.

    PubMed

    Riehl, William J; Krapivsky, Paul L; Redner, Sidney; Segrè, Daniel

    2010-04-01

    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity. PMID:20369010

  18. Signatures of Arithmetic Simplicity in Metabolic Network Architecture

    PubMed Central

    Riehl, William J.; Krapivsky, Paul L.; Redner, Sidney; Segrè, Daniel

    2010-01-01

    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity. PMID:20369010

  19. Cellular hallmarks reveal restricted aerobic metabolism at thermal limits

    PubMed Central

    Neves, Aitana; Busso, Coralie; Gönczy, Pierre

    2015-01-01

    All organisms live within a given thermal range, but little is known about the mechanisms setting the limits of this range. We uncovered cellular features exhibiting signature changes at thermal limits in Caenorhabditis elegans embryos. These included changes in embryo size and shape, which were also observed in Caenorhabditis briggsae, indicating evolutionary conservation. We hypothesized that such changes could reflect restricted aerobic capacity at thermal limits. Accordingly, we uncovered that relative respiration in C. elegans embryos decreases at the thermal limits as compared to within the thermal range. Furthermore, by compromising components of the respiratory chain, we demonstrated that the reliance on aerobic metabolism is reduced at thermal limits. Moreover, embryos thus compromised exhibited signature changes in size and shape already within the thermal range. We conclude that restricted aerobic metabolism at the thermal limits contributes to setting the thermal range in a metazoan organism. DOI: http://dx.doi.org/10.7554/eLife.04810.001 PMID:25929283

  20. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    PubMed

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934

  1. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning

    PubMed Central

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934

  2. Molecular and Cellular Bases of Iron Metabolism in Humans.

    PubMed

    Milto, I V; Suhodolo, I V; Prokopieva, V D; Klimenteva, T K

    2016-06-01

    Iron is a microelement with the most completely studied biological functions. Its wide dissemination in nature and involvement in key metabolic pathways determine the great importance of this metal for uni- and multicellular organisms. The biological role of iron is characterized by its indispensability in cell respiration and various biochemical processes providing normal functioning of cells and organs of the human body. Iron also plays an important role in the generation of free radicals, which under different conditions can be useful or damaging to biomolecules and cells. In the literature, there are many reviews devoted to iron metabolism and its regulation in pro- and eukaryotes. Significant progress has been achieved recently in understanding molecular bases of iron metabolism. The purpose of this review is to systematize available data on mechanisms of iron assimilation, distribution, and elimination from the human body, as well as on its biological importance and on the major iron-containing proteins. The review summarizes recent ideas about iron metabolism. Special attention is paid to mechanisms of iron absorption in the small intestine and to interrelationships of cellular and extracellular pools of this metal in the human body. PMID:27301283

  3. Tensegrity II. How structural networks influence cellular information processing networks

    NASA Technical Reports Server (NTRS)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  4. Evolutionary constraints permeate large metabolic networks

    PubMed Central

    Wagner, Andreas

    2009-01-01

    Background Metabolic networks show great evolutionary plasticity, because they can differ substantially even among closely related prokaryotes. Any one metabolic network can also effectively compensate for the blockage of individual reactions by rerouting metabolic flux through other pathways. These observations, together with the continual discovery of new microbial metabolic pathways and enzymes, raise the possibility that metabolic networks are only weakly constrained in changing their complement of enzymatic reactions. Results To ask whether this is the case, I characterized pairwise and higher-order associations in the co-occurrence of genes encoding metabolic enzymes in more than 200 completely sequenced representatives of prokaryotic genera. The majority of reactions show constrained evolution. Specifically, genes encoding most reactions tend to co-occur with genes encoding other reaction(s). Constrained reaction pairs occur in small sets whose number is substantially greater than expected by chance alone. Most such sets are associated with single biochemical pathways. The respective genes are not always tightly linked, which renders horizontal co-transfer of constrained reaction sets an unlikely sole cause for these patterns of association. Conclusion Even a limited number of available genomes suffices to show that metabolic network evolution is highly constrained by reaction combinations that are favored by natural selection. With increasing numbers of completely sequenced genomes, an evolutionary constraint-based approach may enable a detailed characterization of co-evolving metabolic modules. PMID:19747381

  5. Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction

    PubMed Central

    Heavner, Benjamin D.; Price, Nathan D.

    2015-01-01

    We have compared 12 genome-scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progress in reconstruction of the yeast metabolic network. We compared the genomic coverage, overlap of annotated metabolites, predictive ability for single gene essentiality with a selection of model parameters, and biomass production predictions in simulated nutrient-limited conditions. We have also compared pairwise gene knockout essentiality predictions for 10 of these models. We found that varying approaches to model scope and annotation reflected the involvement of multiple research groups in model development; that single-gene essentiality predictions were affected by simulated medium, objective function, and the reference list of essential genes; and that predictive ability for single-gene essentiality did not correlate well with predictive ability for our reference list of synthetic lethal gene interactions (R = 0.159). We conclude that the reconstruction of the yeast metabolic network is indeed gradually improving through the iterative process of model development, and there remains great opportunity for advancing our understanding of biology through continued efforts to reconstruct the full biochemical reaction network that constitutes yeast metabolism. Additionally, we suggest that there is opportunity for refining the process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanistic investigation and discovery. This comparative study lays the groundwork for developing improved tools and formalized methods to quantitatively assess metabolic network reconstructions independently of any particular model application, which will facilitate ongoing efforts to advance our understanding of the relationship between genotype and cellular phenotype. PMID:26566239

  6. Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction.

    PubMed

    Heavner, Benjamin D; Price, Nathan D

    2015-11-01

    We have compared 12 genome-scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progress in reconstruction of the yeast metabolic network. We compared the genomic coverage, overlap of annotated metabolites, predictive ability for single gene essentiality with a selection of model parameters, and biomass production predictions in simulated nutrient-limited conditions. We have also compared pairwise gene knockout essentiality predictions for 10 of these models. We found that varying approaches to model scope and annotation reflected the involvement of multiple research groups in model development; that single-gene essentiality predictions were affected by simulated medium, objective function, and the reference list of essential genes; and that predictive ability for single-gene essentiality did not correlate well with predictive ability for our reference list of synthetic lethal gene interactions (R = 0.159). We conclude that the reconstruction of the yeast metabolic network is indeed gradually improving through the iterative process of model development, and there remains great opportunity for advancing our understanding of biology through continued efforts to reconstruct the full biochemical reaction network that constitutes yeast metabolism. Additionally, we suggest that there is opportunity for refining the process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanistic investigation and discovery. This comparative study lays the groundwork for developing improved tools and formalized methods to quantitatively assess metabolic network reconstructions independently of any particular model application, which will facilitate ongoing efforts to advance our understanding of the relationship between genotype and cellular phenotype. PMID:26566239

  7. A Novel Mathematical Model Describing Adaptive Cellular Drug Metabolism and Toxicity in the Chemoimmune System

    PubMed Central

    Tóth, Attila; Brózik, Anna; Szakács, Gergely; Sarkadi, Balázs; Hegedüs, Tamás

    2015-01-01

    Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This “chemoimmune system” consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (ABC) membrane transporters, and nuclear receptors regulating these components. In order to provide a systems biology characterization of the chemoimmune network, we designed a reaction kinetic model based on differential equations describing Phase 0–III participants and regulatory elements, and characterized cellular fitness to evaluate toxicity. In spite of the simplifications, the model recapitulates changes associated with acquired drug resistance and allows toxicity predictions under variable protein expression and xenobiotic exposure conditions. Our simulations suggest that multidrug ABC transporters at Phase 0 significantly facilitate the defense function of successive network members by lowering intracellular drug concentrations. The model was extended with a novel toxicity framework which opened the possibility of performing in silico cytotoxicity assays. The alterations of the in silico cytotoxicity curves show good agreement with in vitro cell killing experiments. The behavior of the simplified kinetic model suggests that it can serve as a basis for more complex models to efficiently predict xenobiotic and drug metabolism for human medical applications. PMID:25699998

  8. Modelling chronotaxicity of cellular energy metabolism to facilitate the identification of altered metabolic states

    PubMed Central

    Lancaster, Gemma; Suprunenko, Yevhen F.; Jenkins, Kirsten; Stefanovska, Aneta

    2016-01-01

    Altered cellular energy metabolism is a hallmark of many diseases, one notable example being cancer. Here, we focus on the identification of the transition from healthy to abnormal metabolic states. To do this, we study the dynamics of energy production in a cell. Due to the thermodynamic openness of a living cell, the inability to instantaneously match fluctuating supply and demand in energy metabolism results in nonautonomous time-varying oscillatory dynamics. However, such oscillatory dynamics is often neglected and treated as stochastic. Based on experimental evidence of metabolic oscillations, we show that changes in metabolic state can be described robustly by alterations in the chronotaxicity of the corresponding metabolic oscillations, i.e. the ability of an oscillator to resist external perturbations. We also present a method for the identification of chronotaxicity, applicable to general oscillatory signals and, importantly, apply this to real experimental data. Evidence of chronotaxicity was found in glycolytic oscillations in real yeast cells, verifying that chronotaxicity could be used to study transitions between metabolic states. PMID:27483987

  9. Modelling chronotaxicity of cellular energy metabolism to facilitate the identification of altered metabolic states.

    PubMed

    Lancaster, Gemma; Suprunenko, Yevhen F; Jenkins, Kirsten; Stefanovska, Aneta

    2016-01-01

    Altered cellular energy metabolism is a hallmark of many diseases, one notable example being cancer. Here, we focus on the identification of the transition from healthy to abnormal metabolic states. To do this, we study the dynamics of energy production in a cell. Due to the thermodynamic openness of a living cell, the inability to instantaneously match fluctuating supply and demand in energy metabolism results in nonautonomous time-varying oscillatory dynamics. However, such oscillatory dynamics is often neglected and treated as stochastic. Based on experimental evidence of metabolic oscillations, we show that changes in metabolic state can be described robustly by alterations in the chronotaxicity of the corresponding metabolic oscillations, i.e. the ability of an oscillator to resist external perturbations. We also present a method for the identification of chronotaxicity, applicable to general oscillatory signals and, importantly, apply this to real experimental data. Evidence of chronotaxicity was found in glycolytic oscillations in real yeast cells, verifying that chronotaxicity could be used to study transitions between metabolic states. PMID:27483987

  10. Modeling cellular compartmentation in one-carbon metabolism

    PubMed Central

    Scotti, Marco; Stella, Lorenzo; Shearer, Emily J.; Stover, Patrick J.

    2015-01-01

    Folate-mediated one-carbon metabolism (FOCM) is associated with risk for numerous pathological states including birth defects, cancers, and chronic diseases. Although the enzymes that constitute the biological pathways have been well described and their interdependency through the shared use of folate cofactors appreciated, the biological mechanisms underlying disease etiologies remain elusive. The FOCM network is highly sensitive to nutritional status of several B-vitamins and numerous penetrant gene variants that alter network outputs, but current computational approaches do not fully capture the dynamics and stochastic noise of the system. Combining the stochastic approach with a rule-based representation will help model the intrinsic noise displayed by FOCM, address the limited flexibility of standard simulation methods for coarse-graining the FOCM-associated biochemical processes, and manage the combinatorial complexity emerging from reactions within FOCM that would otherwise be intractable. PMID:23408533

  11. [Caloric restriction: about its positive metabolic effects and cellular impact].

    PubMed

    Ortiz-Bautista, Raúl Julián; Aguilar-Salinas, Carlos Alberto; Monroy-Guzmán, Adriana

    2013-01-01

    Caloric restriction, as a 30 to 60% decrease of ad libitum balanced caloric intake, without malnutrition, is the non-genetic strategy that has consistently extended the average and maximum lifespan of most living beings, and it has been tested from unicellular organisms like yeast Saccharomyces cerevisiae to Rhesus primates. In addition, various genetic and pharmacological caloric restriction models have shown to protect against cancer, cardiovascular and neurodegenerative diseases. Primate studies suggest that this intervention delays the onset of age-related diseases; in humans, it has physiological, biochemical and metabolic effects decreasing diabetes and cardiovascular disease risk factor. Although currently the mechanism by which caloric restriction has its positive effects at the cellular level is unknown, it has been reported to decrease oxidative stress and increase in mitochondrial biogenesis. PMID:25125067

  12. Chemical Approaches to Probe Metabolic Networks

    PubMed Central

    Medina-Cleghorn, Daniel; Nomura, Daniel K.

    2013-01-01

    One of the more provocative realizations that have come out of the genome sequencing projects is that organisms possess a large number of uncharacterized or poorly characterized enzymes. This finding belies the commonly held notion that our knowledge of cell metabolism is nearly complete, underscoring the vast landscape of unannotated metabolic and signaling networks that operate under normal physiological conditions, let alone in disease states where metabolic networks may be rewired, dysregulated, or altered to drive disease progression. Consequently, the functional annotation of enzymatic pathways represents a grand challenge for researchers in the post-genomic era. This review will highlight the chemical technologies that have been successfully used to characterize metabolism, and put forth some of the challenges we face as we expand our map of metabolic pathways. PMID:23296751

  13. Reconstruction and applications of consensus yeast metabolic network based on RNA sequencing.

    PubMed

    Zhao, Yuqi; Wang, Yanjie; Zou, Lei; Huang, Jingfei

    2016-04-01

    One practical application of genome-scale metabolic reconstructions is to interrogate multispecies relationships. Here, we report a consensus metabolic model in four yeast species (Saccharomyces cerevisiae, S. paradoxus, S. mikatae, and S. bayanus) by integrating metabolic network simulations with RNA sequencing (RNA-seq) datasets. We generated high-resolution transcriptome maps of four yeast species through de novo assembly and genome-guided approaches. The transcriptomes were annotated and applied to build the consensus metabolic network, which was verified using independent RNA-seq experiments. The expression profiles reveal that the genes involved in amino acid and lipid metabolism are highly coexpressed. The diverse phenotypic characteristics, such as cellular growth and gene deletions, can be simulated using the metabolic model. We also explored the applications of the consensus model in metabolic engineering using yeast-specific reactions and biofuel production as examples. Similar strategies will benefit communities studying genome-scale metabolic networks of other organisms. PMID:27239440

  14. Extracting insight from noisy cellular networks.

    PubMed

    Landry, Christian R; Levy, Emmanuel D; Abd Rabbo, Diala; Tarassov, Kirill; Michnick, Stephen W

    2013-11-21

    Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched. PMID:24267884

  15. Energy efficiency analysis of relay-assisted cellular networks

    NASA Astrophysics Data System (ADS)

    Yu, Huan; Li, Yunzhou; Kountouris, Marios; Xu, Xibin; Wang, Jing

    2014-12-01

    To meet the demand for higher throughput, improved coverage and enhanced reliability, future wireless cellular networks face significant technical challenges. One promising solution is to place relay stations between transmitters and receivers in the cellular network. Meanwhile, as energy consumption reduction has been an important concern for the wireless industry, energy-efficient communications is of prime interest for future networks. In this paper, we study whether and how relays can improve the energy efficiency of cellular networks. Specifically, the energy efficiency of relay-assisted cellular networks is analyzed using tools of stochastic geometry. We first derive the coverage probability for the macro base station (MBS) to user (UE), the MBS to relay station (RS), and the RS to UE links, and then we model the power consumption at the MBS and RS. Based on the analytical model and expressions, the energy efficiency of relay-assisted cellular networks is then evaluated and is shown to be strictly quasi-concave on the transmit power for MBS to UE link or the RS to UE link. Numerical results show that the energy efficiency first improves while it hits a ceiling as the MBS density increases.

  16. A new small-world network created by Cellular Automata

    NASA Astrophysics Data System (ADS)

    Ruan, Yuhong; Li, Anwei

    2016-08-01

    In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.

  17. 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.

  18. Stochastic cellular automata model of neural networks.

    PubMed

    Goltsev, A V; de Abreu, F V; Dorogovtsev, S N; Mendes, J F F

    2010-06-01

    We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons. PMID:20866454

  19. Personal communication in traditional cellular networks

    NASA Astrophysics Data System (ADS)

    Neuer, Ellwood I.

    1996-01-01

    The purpose of this paper is to describe the flow of calls through the mobile network as it applies to the operation of Basic and Enhanced Services. Included in the discussion is the overall network layout, the physical connections between the network entities, and the signaling protocols which allow the entities to be integrated. The specific functionality of the applications and services are not detailed as the specific implementation varies from vendor to vendor and from service provider to service provider. The Enhanced Services Platform is installed in a service providers network in order to offer mobile subscribers services and applications which would otherwise not be available. The service providers' objective is to increase revenue/subscriber, increase subscriber loyalty/decrease churn, and build competitive advantages through differentiation. The services provided on the Enhanced Services platform can be viewed as either Basic or Enhanced. For the purpose of this paper, Basic Services refers to Numeric Paging, Call Answering, and Voice Messaging while Enhanced Services refers to FAX Messaging, One Number Service, Voice Dialing and other Voice Recognition applications, Information Services including FAX on Demand, and Automated Call Routing.

  20. Metabolic networks are almost nonfractal: A comprehensive evaluation

    NASA Astrophysics Data System (ADS)

    Takemoto, Kazuhiro

    2014-08-01

    Network self-similarity or fractality are widely accepted as an important topological property of metabolic networks; however, recent studies cast doubt on the reality of self-similarity in the networks. Therefore, we perform a comprehensive evaluation of metabolic network fractality using a box-covering method with an earlier version and the latest version of metabolic networks and demonstrate that the latest metabolic networks are almost self-dissimilar, while the earlier ones are fractal, as reported in a number of previous studies. This result may be because the networks were randomized because of an increase in network density due to database updates, suggesting that the previously observed network fractality was due to a lack of available data on metabolic reactions. This finding may not entirely discount the importance of self-similarity of metabolic networks. Rather, it highlights the need for a more suitable definition of network fractality and a more careful examination of self-similarity of metabolic networks.

  1. Increasing cellular coverage within integrated terrestrial/satellite mobile networks

    NASA Technical Reports Server (NTRS)

    Castro, Jonathan P.

    1995-01-01

    When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

  2. Optimising base station location for UMTS cellular networks

    NASA Astrophysics Data System (ADS)

    Kalata, G.; Pozniak-Koszalka, I.; Koszalka, L.; Kasprzak, A.

    2014-12-01

    Rapid development of universal mobile telecommunication systems put demands on tools for assisting planning of cellular network infrastructure. The tools need to focus on critical issues in modern cellular networks and techniques used for previous generation system no longer serve useful. In this paper, an algorithm based on Branch & Bound approach is proposed for solving base station location problem, covering interference levels, traffic demands and power control mechanism. The efficiency of the algorithm is evaluated with respect to existing approaches for solving this problem - using the designed and implemented experimentation system.

  3. MIRA: mutual information-based reporter algorithm for metabolic networks

    PubMed Central

    Cicek, A. Ercument; Roeder, Kathryn; Ozsoyoglu, Gultekin

    2014-01-01

    Motivation: Discovering the transcriptional regulatory architecture of the metabolism has been an important topic to understand the implications of transcriptional fluctuations on metabolism. The reporter algorithm (RA) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulation is focused owing to a disease or a genetic perturbation. Using a z-score-based scoring scheme, RA calculates the average statistical change in the expression levels of genes that are neighbors to a target metabolite in the metabolic network. The RA approach has been used in numerous studies to analyze cellular responses to the downstream genetic changes. In this article, we propose a mutual information-based multivariate reporter algorithm (MIRA) with the goal of eliminating the following problems in detecting reporter metabolites: (i) conventional statistical methods suffer from small sample sizes, (ii) as z-score ranges from minus to plus infinity, calculating average scores can lead to canceling out opposite effects and (iii) analyzing genes one by one, then aggregating results can lead to information loss. MIRA is a multivariate and combinatorial algorithm that calculates the aggregate transcriptional response around a metabolite using mutual information. We show that MIRA’s results are biologically sound, empirically significant and more reliable than RA. Results: We apply MIRA to gene expression analysis of six knockout strains of Escherichia coli and show that MIRA captures the underlying metabolic dynamics of the switch from aerobic to anaerobic respiration. We also apply MIRA to an Autism Spectrum Disorder gene expression dataset. Results indicate that MIRA reports metabolites that highly overlap with recently found metabolic biomarkers in the autism literature. Overall, MIRA is a promising algorithm for detecting metabolic drug targets and understanding the relation between gene expression and metabolic activity. Availability and

  4. Estimating the size of the solution space of metabolic networks

    PubMed Central

    Braunstein, Alfredo; Mulet, Roberto; Pagnani, Andrea

    2008-01-01

    Background Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network is quite well understood there is still a lack of comprehension regarding the global functional behavior of the system. In the last few years flux-balance analysis (FBA) has been the most successful and widely used technique for studying metabolism at system level. This method strongly relies on the hypothesis that the organism maximizes an objective function. However only under very specific biological conditions (e.g. maximization of biomass for E. coli in reach nutrient medium) the cell seems to obey such optimization law. A more refined analysis not assuming extremization remains an elusive task for large metabolic systems due to algorithmic limitations. Results In this work we propose a novel algorithmic strategy that provides an efficient characterization of the whole set of stable fluxes compatible with the metabolic constraints. Using a technique derived from the fields of statistical physics and information theory we designed a message-passing algorithm to estimate the size of the affine space containing all possible steady-state flux distributions of metabolic networks. The algorithm, based on the well known Bethe approximation, can be used to approximately compute the volume of a non full-dimensional convex polytope in high dimensions. We first compare the accuracy of the predictions with an exact algorithm on small random metabolic networks. We also verify that the predictions of the algorithm match closely those of Monte Carlo based methods in the case of the Red Blood Cell metabolic network. Then we test the effect of gene knock-outs on the size of the solution space in the case of E. coli central metabolism. Finally we analyze the statistical properties of the average fluxes of the reactions in the E. coli metabolic network. Conclusion We propose a novel efficient

  5. Molecular Biology, Biochemistry and Cellular Physiology of Cysteine Metabolism in Arabidopsis thaliana

    PubMed Central

    Hell, Rüdiger; Wirtz, Markus

    2011-01-01

    Cysteine is one of the most versatile molecules in biology, taking over such different functions as catalysis, structure, regulation and electron transport during evolution. Research on Arabidopsis has contributed decisively to the understanding of cysteine synthesis and its role in the assimilatory pathways of S, N and C in plants. The multimeric cysteine synthase complex is present in the cytosol, plastids and mitochondria and forms the centre of a unique metabolic sensing and signaling system. Its association is reversible, rendering the first enzyme of cysteine synthesis active and the second one inactive, and vice-versa. Complex formation is triggered by the reaction intermediates of cysteine synthesis in response to supply and demand and gives rise to regulation of genes of sulfur metabolism to adjust cellular sulfur homeostasis. Combinations of biochemistry, forward and reverse genetics, structural- and cell-biology approaches using Arabidopsis have revealed new enzyme functions and the unique pattern of spatial distribution of cysteine metabolism in plant cells. These findings place the synthesis of cysteine in the centre of the network of primary metabolism. PMID:22303278

  6. Network signatures of cellular immortalization in human lymphoblastoid cell lines

    SciTech Connect

    Shim, Sung-Mi; Jung, So-Young; Nam, Hye-Young; Kim, Hye-Ryun; Lee, Mee-Hee; Kim, Jun-Woo; Han, Bok-Ghee; Jeon, Jae-Pil

    2013-11-15

    Highlights: •We identified network signatures of LCL immortalization from transcriptomic profiles. •More than 41% of DEGs are possibly regulated by miRNAs in LCLs. •MicroRNA target genes in LCLs are involved in apoptosis and immune-related functions. •This approach is useful to find functional miRNA targets in specific cell conditions. -- Abstract: Human lymphoblastoid cell line (LCL) has been used as an in vitro cell model in genetic and pharmacogenomic studies, as well as a good model for studying gene expression regulatory machinery using integrated genomic analyses. In this study, we aimed to identify biological networks of LCL immortalization from transcriptomic profiles of microRNAs and their target genes in LCLs. We first selected differentially expressed genes (DEGs) and microRNAs (DEmiRs) between early passage LCLs (eLCLs) and terminally differentiated late passage LCLs (tLCLs). The in silico and correlation analysis of these DEGs and DEmiRs revealed that 1098 DEG–DEmiR pairs were found to be positively (n = 591 pairs) or negatively (n = 507 pairs) correlated with each other. More than 41% of DEGs are possibly regulated by miRNAs in LCL immortalizations. The target DEGs of DEmiRs were enriched for cellular functions associated with apoptosis, immune response, cell death, JAK–STAT cascade and lymphocyte activation while non-miRNA target DEGs were over-represented for basic cell metabolisms. The target DEGs correlated negatively with miR-548a-3p and miR-219-5p were significantly associated with protein kinase cascade, and the lymphocyte proliferation and apoptosis, respectively. In addition, the miR-106a and miR-424 clusters located in the X chromosome were enriched in DEmiR–mRNA pairs for LCL immortalization. In this study, the integrated transcriptomic analysis of LCLs could identify functional networks of biologically active microRNAs and their target genes involved in LCL immortalization.

  7. Natural Products as Tools for Defining How Cellular Metabolism Influences Cellular Immune and Inflammatory Function during Chronic Infection

    PubMed Central

    Lovelace, Erica S.; Polyak, Stephen J.

    2015-01-01

    Chronic viral infections like those caused by hepatitis C virus (HCV) and human immunodeficiency virus (HIV) cause disease that establishes an ongoing state of chronic inflammation. While there have been tremendous improvements towards curing HCV with directly acting antiviral agents (DAA) and keeping HIV viral loads below detection with antiretroviral therapy (ART), there is still a need to control inflammation in these diseases. Recent studies indicate that many natural products like curcumin, resveratrol and silymarin alter cellular metabolism and signal transduction pathways via enzymes such as adenosine monophosphate kinase (AMPK) and mechanistic target of rapamycin (mTOR), and these pathways directly influence cellular inflammatory status (such as NF-κB) and immune function. Natural products represent a vast toolkit to dissect and define how cellular metabolism controls cellular immune and inflammatory function. PMID:26633463

  8. Maize metabolic network construction and transcriptome analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A framework for understanding the synthesis and catalysis of metabolites and other biochemicals by proteins is crucial for unraveling the physiology of cells. To create such a framework for Zea mays ssp. mays (maize), we developed MaizeCyc a metabolic network of enzyme catalysts, proteins, carbohydr...

  9. Dissecting Germ Cell Metabolism through Network Modeling

    PubMed Central

    Whitmore, Leanne S.; Ye, Ping

    2015-01-01

    Metabolic pathways are increasingly postulated to be vital in programming cell fate, including stemness, differentiation, proliferation, and apoptosis. The commitment to meiosis is a critical fate decision for mammalian germ cells, and requires a metabolic derivative of vitamin A, retinoic acid (RA). Recent evidence showed that a pulse of RA is generated in the testis of male mice thereby triggering meiotic commitment. However, enzymes and reactions that regulate this RA pulse have yet to be identified. We developed a mouse germ cell-specific metabolic network with a curated vitamin A pathway. Using this network, we implemented flux balance analysis throughout the initial wave of spermatogenesis to elucidate important reactions and enzymes for the generation and degradation of RA. Our results indicate that primary RA sources in the germ cell include RA import from the extracellular region, release of RA from binding proteins, and metabolism of retinal to RA. Further, in silico knockouts of genes and reactions in the vitamin A pathway predict that deletion of Lipe, hormone-sensitive lipase, disrupts the RA pulse thereby causing spermatogenic defects. Examination of other metabolic pathways reveals that the citric acid cycle is the most active pathway. In addition, we discover that fatty acid synthesis/oxidation are the primary energy sources in the germ cell. In summary, this study predicts enzymes, reactions, and pathways important for germ cell commitment to meiosis. These findings enhance our understanding of the metabolic control of germ cell differentiation and will help guide future experiments to improve reproductive health. PMID:26367011

  10. Dissecting Germ Cell Metabolism through Network Modeling.

    PubMed

    Whitmore, Leanne S; Ye, Ping

    2015-01-01

    Metabolic pathways are increasingly postulated to be vital in programming cell fate, including stemness, differentiation, proliferation, and apoptosis. The commitment to meiosis is a critical fate decision for mammalian germ cells, and requires a metabolic derivative of vitamin A, retinoic acid (RA). Recent evidence showed that a pulse of RA is generated in the testis of male mice thereby triggering meiotic commitment. However, enzymes and reactions that regulate this RA pulse have yet to be identified. We developed a mouse germ cell-specific metabolic network with a curated vitamin A pathway. Using this network, we implemented flux balance analysis throughout the initial wave of spermatogenesis to elucidate important reactions and enzymes for the generation and degradation of RA. Our results indicate that primary RA sources in the germ cell include RA import from the extracellular region, release of RA from binding proteins, and metabolism of retinal to RA. Further, in silico knockouts of genes and reactions in the vitamin A pathway predict that deletion of Lipe, hormone-sensitive lipase, disrupts the RA pulse thereby causing spermatogenic defects. Examination of other metabolic pathways reveals that the citric acid cycle is the most active pathway. In addition, we discover that fatty acid synthesis/oxidation are the primary energy sources in the germ cell. In summary, this study predicts enzymes, reactions, and pathways important for germ cell commitment to meiosis. These findings enhance our understanding of the metabolic control of germ cell differentiation and will help guide future experiments to improve reproductive health. PMID:26367011

  11. Metabolic Network Modeling of Microbial Communities

    PubMed Central

    Biggs, Matthew B.; Medlock, Gregory L.; Kolling, Glynis L.

    2015-01-01

    Genome-scale metabolic network reconstructions and constraint-based analysis are powerful methods that have the potential to make functional predictions about microbial communities. Current use of genome-scale metabolic networks to characterize the metabolic functions of microbial communities includes species compartmentalization, separating species-level and community-level objectives, dynamic analysis, the “enzyme-soup” approach, multi-scale modeling, and others. There are many challenges inherent to the field, including a need for tools that accurately assign high-level omics signals to individual community members, new automated reconstruction methods that rival manual curation, and novel algorithms for integrating omics data and engineering communities. As technologies and modeling frameworks improve, we expect that there will be proportional advances in the fields of ecology, health science, and microbial community engineering. PMID:26109480

  12. Meta-ecosystem metabolism across fluvial networks

    NASA Astrophysics Data System (ADS)

    Ulseth, A. J.; Singer, G. A.; Battin, T. J.

    2013-12-01

    Freshwater ecosystems store, transform, and export terrestrial carbon and play an important role for regional and global carbon fluxes. Ecosystem metabolism is a measure of how and how much carbon is produced and transformed and - for streams and rivers - is typically estimated at the reach scale (typically tens to hundreds of meters). Due to methodological constraints we so far lack an understanding of metabolism of the fluvial meta-ecosystem continuum, i.e. at the scale of a fluvial network. To address this issue, we measured metabolism in multiple reaches across a 254 km2 catchment in Lower Austria, capturing both temporal dynamics and the spatial scale of the whole fluvial network. Stream metabolism was estimated from diel changes in oxygen and corrected for reaeration; continuously in 15 streams and during a short-term ';snap-shot' campaign across 42 streams. Across the network, the streams varied in catchment size (0.1 to 254 km2) and water chemistry (DOC: 1.0 to 2.7 mg L-1, NO3: 259 to 1277 μg L-1, NH4:<0.1 to 30 μg L-1, and PO4:<0.1 to 20 μg L-1) as a consequence of subcatchment landuse, elevation and geology. Gross primary production (GPP) and ecosystem respiration (ER) were suppressed across the network by high stream discharge events such as snow melt and heavy rains. Larger streams (catchment size > 35 km2) had higher GPP and tended to be more autotrophic than lower order streams. However, streams located above 1000 m elevation had higher GPP than streams of equivalent size found elsewhere in the stream network. During the winter months, all streams across the network were net heterotrophic, with GPP typically <1.0 g 02 m-2 d-1. The degree of autotrophy versus heterotrophy across the network was driven in part by light, which is contingent on location within the stream network. We will discuss scaling GPP and ER from the reach to the network scale in order to elucidate patterns of meta-ecosystem metabolism across fluvial networks.

  13. On functional module detection in metabolic networks.

    PubMed

    Koch, Ina; Ackermann, Jörg

    2013-01-01

    Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145

  14. On Functional Module Detection in Metabolic Networks

    PubMed Central

    Koch, Ina; Ackermann, Jörg

    2013-01-01

    Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145

  15. Kinetic analysis of complex metabolic networks

    SciTech Connect

    Stephanopoulos, G.

    1996-12-31

    A new methodology is presented for the analysis of complex metabolic networks with the goal of metabolite overproduction. The objective is to locate a small number of reaction steps in a network that have maximum impact on network flux amplification and whose rate can also be increased without functional network derangement. This method extends the concepts of Metabolic Control Analysis to groups of reactions and offers the means for calculating group control coefficients as measures of the control exercised by groups of reactions on the overall network fluxes and intracellular metabolite pools. It is further demonstrated that the optimal strategy for the effective increase of network fluxes, while maintaining an uninterrupted supply of intermediate metabolites, is through the coordinated amplification of multiple (as opposed to a single) reaction steps. Satisfying this requirement invokes the concept of the concentration control to coefficient, which emerges as a critical parameter in the identification of feasible enzymatic modifications with maximal impact on the network flux. A case study of aromatic aminoacid production is provided to illustrate these concepts.

  16. Millimeter-Wave Evolution for 5G Cellular Networks

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Kei; Tran, Gia Khanh; Shimodaira, Hidekazu; Nanba, Shinobu; Sakurai, Toshiaki; Takinami, Koji; Siaud, Isabelle; Strinati, Emilio Calvanese; Capone, Antonio; Karls, Ingolf; Arefi, Reza; Haustein, Thomas

    Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

  17. Automatic analysis of the control of metabolic networks.

    PubMed

    Bayram, M

    1996-09-01

    In this paper we apply computer algebra techniques to analyze the control of metabolic networks. For this purpose, a computer program based on metabolic control theory was developed. When a stoichiometry matrix of the metabolic networks is given, the program calculates all the control coefficients (flux and metabolic control coefficients, summation and connectivity relationships) using elasticity coefficients. The program can be applied to any metabolic network which includes unlimited steps and intermediate metabolites. PMID:8889337

  18. Phylogenetic sequence of metabolic pathways in Precambrian cellular life

    NASA Technical Reports Server (NTRS)

    Barnabas, J.; Schwartz, R. M.; Dayhoff, M. O.

    1981-01-01

    A sequence of major metabolic events is presented as they may have appeared during prokaryote evolution. This is based on (1) the phylogenetic schema derived from sequences of bacterial ferredoxin, 2Fe-2S ferredoxin, 5S ribosomal RNA, and c-type cytochromes; (2) metabolic settings in which these macromolecules are found; and (3) metabolic capabilities of the prokaryotes that carry these molecules.

  19. Cellular neural networks for welding arc thermograms segmentation

    NASA Astrophysics Data System (ADS)

    Jamrozik, Wojciech

    2014-09-01

    Machine vision systems are used in many areas for monitoring of technological processes. Among this processes welding takes important place, where often infrared cameras are used. Besides reliable hardware, successful application of vision systems requires suitable software based on proper algorithms. One of most important group of image processing algorithms is connected to image segmentation. Obtainment of exact boundary of an object that changes shape in time, such as the welding arc, represented on a thermogram is not a trivial task. In the paper a segmentation method using supervised approach based on a cellular neural networks is presented. Simulated annealing and genetic algorithm were used for training of the network (template optimization). Comparison of proposed method to a well elaborated segmentation method based on region growing approach was made. Obtained results prove that the cellular neural network can be a valuable tool for infrared welding pool images segmentation.

  20. The topology of metabolic isotope labeling networks

    PubMed Central

    Weitzel, Michael; Wiechert, Wolfgang; Nöh, Katharina

    2007-01-01

    Background Metabolic Flux Analysis (MFA) based on isotope labeling experiments (ILEs) is a widely established tool for determining fluxes in metabolic pathways. Isotope labeling networks (ILNs) contain all essential information required to describe the flow of labeled material in an ILE. Whereas recent experimental progress paves the way for high-throughput MFA, large network investigations and exact statistical methods, these developments are still limited by the poor performance of computational routines used for the evaluation and design of ILEs. In this context, the global analysis of ILN topology turns out to be a clue for realizing large speedup factors in all required computational procedures. Results With a strong focus on the speedup of algorithms the topology of ILNs is investigated using graph theoretic concepts and algorithms. A rigorous determination of all cyclic and isomorphic subnetworks, accompanied by the global analysis of ILN connectivity is performed. Particularly, it is proven that ILNs always brake up into a large number of small strongly connected components (SCCs) and, moreover, there are natural isomorphisms between many of these SCCs. All presented techniques are universal, i.e. they do not require special assumptions on the network structure, bidirectionality of fluxes, measurement configuration, or label input. The general results are exemplified with a practically relevant metabolic network which describes the central metabolism of E. coli comprising 10390 isotopomer pools. Conclusion Exploiting the topological features of ILNs leads to a significant speedup of all universal algorithms for ILE evaluation. It is proven in theory and exemplified with the E. coli example that a speedup factor of about 1000 compared to standard algorithms is achieved. This widely opens the door for new high performance algorithms suitable for high throughput applications and large ILNs. Moreover, for the first time the global topological analysis of ILNs

  1. Conservation of Edge Essentiality Profiles in Metabolic Networks Across Species

    NASA Astrophysics Data System (ADS)

    Arodź, Tomasz

    Reactions involved in cellular metabolism form a complex network susceptible to targeted attacks. Recent experiments show that several descriptors of edge essentiality correlate well with lethality of silencing corresponding genes in a model organism, opening path to identifying targets for antimicrobial drugs that would disrupt network functioning in bacteria. However, correlation of high essentiality with experiment is necessary but not sufficient for a descriptor to be useful. Also, the essentialities of corresponding edges have to differ markedly between pathogens and hosts, to yield minimal effect on the latter. Here, we analyse similarity of profiles of several edge essentiality measures across multiple species. We show that local measures, based on degrees of a substrate and a product linked by the edge, or on the alternative paths connecting the two, are evolutionarily conserved within bacteria, archaea and eukaryotes, but also differ between these groups, leading to isolated clusters of species. Furthermore, comparison with a global topological measure, the relative decrease in network efficiency upon edge removal, shows that metabolic networks are more conserved locally than globally.

  2. The role of actin networks in cellular mechanosensing

    NASA Astrophysics Data System (ADS)

    Azatov, Mikheil

    Physical processes play an important role in many biological phenomena, such as wound healing, organ development, and tumor metastasis. During these processes, cells constantly interact with and adapt to their environment by exerting forces to mechanically probe the features of their surroundings and generating appropriate biochemical responses. The mechanisms underlying how cells sense the physical properties of their environment are not well understood. In this thesis, I present my studies to investigate cellular responses to the stiffness and topography of the environment. In order to sense the physical properties of their environment, cells dynamically reorganize the structure of their actin cytoskeleton, a dynamic network of biopolymers, altering the shape and spatial distribution of protein assemblies. Several observations suggest that proteins that crosslink actin filaments may play an important role in cellular mechanosensitivity. Palladin is an actin-crosslinking protein that is found in the lamellar actin network, stress fibers and focal adhesions, cellular structures that are critical for mechanosensing of the physical environment. By virtue of its close interactions with these structures in the cell, palladin may play an important role in cell mechanics. However, the role of actin crosslinkers in general, and palladin in particular, in cellular force generation and mechanosensing is not well known. I have investigated the role of palladin in regulating the plasticity of the actin cytoskeleton and cellular force generation in response to alterations in substrate stiffness. I have shown that the expression levels of palladin modulate the forces exerted by cells and their ability to sense substrate stiffness. Perturbation experiments also suggest that palladin levels in cells altered myosin motor activity. These results suggest that the actin crosslinkers, such as palladin, and myosin motors coordinate for optimal cell function and to prevent aberrant

  3. Tools and Models for Integrating Multiple Cellular Networks

    SciTech Connect

    Gerstein, Mark

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  4. Network-based analysis of the sphingolipid metabolism in hypertension

    PubMed Central

    Fenger, Mogens; Linneberg, Allan; Jeppesen, Jørgen

    2015-01-01

    Common diseases like essential hypertension or diabetes mellitus are complex as they are polygenic in nature, such that each genetic variation only has a small influence on the disease. Genes operates in integrated networks providing the blue-print for all biological processes and conditional of the complex genotype determines the state and dynamics of any trait, which may be modified to various extent by non-genetic factors. Thus, diseases are heterogenous ensembles of conditions with a common endpoint. Numerous studies have been performed to define genes of importance for a trait or disease, but only a few genes with small effect have been identified. The major reasons for this modest progress is the unresolved heterogeneity of the regulation of blood pressure and the shortcomings of the prevailing monogenic approach to capture genetic effects in a polygenic condition. Here, a two-step procedure is presented in which physiological heterogeneity is disentangled and genetic effects are analyzed by variance decomposition of genetic interactions and by an information theoretical approach including 162 single nucleotide polymorphisms (SNP) in 84 genes in the sphingolipid metabolism and related networks in blood pressure regulation. As expected, almost no genetic main effects were detected. In contrast, two-gene interactions established the entire sphingolipid metabolic and related genetic network to be highly involved in the regulation of blood pressure. The pattern of interaction clearly revealed that epistasis does not necessarily reflects the topology of the metabolic pathways i.e., the flow of metabolites. Rather, the enzymes and proteins are integrated in complex cellular substructures where communication flows between the components of the networks, which may be composite in structure. The heritabilities for diastolic and systolic blood pressure were estimated to be 0.63 and 0.01, which may in fact be the maximum heritabilities of these traits. This procedure

  5. Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803

    PubMed Central

    Knoop, Henning; Gründel, Marianne; Zilliges, Yvonne; Lehmann, Robert; Hoffmann, Sabrina; Lockau, Wolfgang; Steuer, Ralf

    2013-01-01

    Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism. PMID:23843751

  6. Mining metabolic networks for optimal drug targets.

    PubMed

    Sridhar, Padmavati; Song, Bin; Kahveci, Tamer; Ranka, Sanjay

    2008-01-01

    Recent advances in bioinformatics promote drug-design methods that aim to reduce side-effects. Efficient computational methods are required to identify the optimal enzyme-combination (i.e., drug targets) whose inhibition, will achieve the required effect of eliminating a given target set of compounds, while incurring minimal side-effects. We formulate the optimal enzyme-combination identification problem as an optimization problem on metabolic networks. We define a graph based computational damage model that encapsulates the impact of enzymes onto compounds in metabolic networks. We develop a branch-and-bound algorithm, named OPMET, to explore the search space dynamically. We also develop two filtering strategies to prune the search space while still guaranteeing an optimal solution. They compute an upper bound to the number of target compounds eliminated and a lower bound to the side-effect respectively. Our experiments on the human metabolic network demonstrate that the proposed algorithm can accurately identify the target enzymes for known successful drugs in the literature. Our experiments also show that OPMET can reduce the total search time by several orders of magnitude as compared to the exhaustive search. PMID:18229694

  7. THE CELLULAR METABOLISM AND SYSTEMIC TOXICITY OF ARSENIC

    EPA Science Inventory

    Abstract

    Toxic Consequences of the Metabolism of Arsenic. David J. Thomas, Miroslav Styblo, and Shan Lin. (2001). Toxicol. Appl. Pharmacol. 000, xxx-yyy.
    Although it has been known for decades that humans and many other species metabolize inorganic arsenic to methyl ...

  8. Using Cellular Communication Networks To Detect Air Pollution.

    PubMed

    David, Noam; Gao, H Oliver

    2016-09-01

    Accurate real time monitoring of atmospheric conditions at ground level is vital for hazard warning, meteorological forecasting, and various environmental applications required for public health and safety. However, conventional monitoring facilities are costly and often insufficient, for example, since they are not representative of the larger space and are not deployed densely enough in the field. There have been numerous scientific works showing the ability of commercial microwave links that comprise the data transmission infrastructure in cellular communication networks to monitor hydrometeors as a potential complementary solution. However, despite the large volume of research carried out in this emerging field during the past decade, no study has shown the ability of the system to provide critical information regarding air quality. Here we reveal the potential for identifying atmospheric conditions prone to air pollution by detecting temperature inversions that trap pollutants at ground level. The technique is based on utilizing standard signal measurements from an existing cellular network during routine operation. PMID:27490182

  9. Analysing Dynamical Behavior of Cellular Networks via Stochastic Bifurcations

    PubMed Central

    Zakharova, Anna; Kurths, Jürgen; Vadivasova, Tatyana; Koseska, Aneta

    2011-01-01

    The dynamical structure of genetic networks determines the occurrence of various biological mechanisms, such as cellular differentiation. However, the question of how cellular diversity evolves in relation to the inherent stochasticity and intercellular communication remains still to be understood. Here, we define a concept of stochastic bifurcations suitable to investigate the dynamical structure of genetic networks, and show that under stochastic influence, the expression of given proteins of interest is defined via the probability distribution of the phase variable, representing one of the genes constituting the system. Moreover, we show that under changing stochastic conditions, the probabilities of expressing certain concentration values are different, leading to different functionality of the cells, and thus to differentiation of the cells in the various types. PMID:21647432

  10. Performance evaluation of cellular phone network based portable ECG device.

    PubMed

    Hong, Joo-Hyun; Cha, Eun-Jong; Lee, Tae-Soo

    2008-01-01

    In this study, cellular phone network based portable ECG device was developed and three experiments were performed to evaluate the accuracy, reliability and operability, applicability during daily life of the developed device. First, ECG signals were measured using the developed device and Biopac device (reference device) during sitting and marking time and compared to verify the accuracy of R-R intervals. Second, the reliable data transmission to remote server was verified on two types of simulated emergency event using patient simulator. Third, during daily life with five types of motion, accuracy of data transmission to remote server was verified on two types of event occurring. By acquiring and comparing subject's biomedical signal and motion signal, the accuracy, reliability and operability, applicability during daily life of the developed device were verified. Therefore, cellular phone network based portable ECG device can monitor patient with inobtrusive manner. PMID:19162767

  11. Global insights into energetic and metabolic networks in Rhodobacter sphaeroides

    PubMed Central

    2013-01-01

    Background Improving our understanding of processes at the core of cellular lifestyles can be aided by combining information from genetic analyses, high-throughput experiments and computational predictions. Results We combined data and predictions derived from phenotypic, physiological, genetic and computational analyses to dissect the metabolic and energetic networks of the facultative photosynthetic bacterium Rhodobacter sphaeroides. We focused our analysis on pathways crucial to the production and recycling of pyridine nucleotides during aerobic respiratory and anaerobic photosynthetic growth in the presence of an organic electron donor. In particular, we assessed the requirement for NADH/NADPH transhydrogenase enzyme, PntAB during respiratory and photosynthetic growth. Using high-throughput phenotype microarrays (PMs), we found that PntAB is essential for photosynthetic growth in the presence of many organic electron donors, particularly those predicted to require its activity to produce NADPH. Utilizing the genome-scale metabolic model iRsp1095, we predicted alternative routes of NADPH synthesis and used gene expression analyses to show that transcripts from a subset of the corresponding genes were conditionally increased in a ΔpntAB mutant. We then used a combination of metabolic flux predictions and mutational analysis to identify flux redistribution patterns utilized in the ΔpntAB mutant to compensate for the loss of this enzyme. Data generated from metabolic and phenotypic analyses of wild type and mutant cells were used to develop iRsp1140, an expanded genome-scale metabolic reconstruction for R. sphaeroides with improved ability to analyze and predict pathways associated with photosynthesis and other metabolic processes. Conclusions These analyses increased our understanding of key aspects of the photosynthetic lifestyle, highlighting the added importance of NADPH production under these conditions. It also led to a significant improvement in the

  12. Cellular Automata with network incubation in information technology diffusion

    NASA Astrophysics Data System (ADS)

    Guseo, Renato; Guidolin, Mariangela

    2010-06-01

    Innovation diffusion of network goods determines direct network externalities that depress sales for long periods and delay full benefits. We model this effect through a multiplicative dynamic market potential driven by a latent individual threshold embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a collective threshold (critical mass). Weighted nonlinear least squares are the main inferential methodology. An application is analysed with reference to USA fax machine diffusion.

  13. Ion beam analysis based on cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Senger, V.; Tetzlaff, R.; Reichau, H.; Ratzinger, U.

    2011-07-01

    The development of a non- destructive measurement method for ion beam parameters has been treated in various projects. Although results are promising, the high complexity of beam dynamics has made it impossible to implement a real time process control up to now. In this paper we will propose analysing methods based on the dynamics of Cellular Nonlinear Networks (CNN) that can be implemented on pixel parallel CNN based architectures and yield satisfying results even at low resolutions.

  14. Network Medicine: From Cellular Networks to the Human Diseasome

    NASA Astrophysics Data System (ADS)

    Barabasi, Albert-Laszlo

    2014-03-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

  15. Hybrid Spectral Efficient Cellular Network Deployment to Reduce RF Pollution

    NASA Astrophysics Data System (ADS)

    Katiyar, Sumit; K. Jain, R.; K. Agrawal, N.

    2012-09-01

    As the mobile telecommunication systems are growing tremendously all over the world, the numbers of handheld and base stations are also rapidly growing and it became very popular to see these base stations distributed everywhere in the neighborhood and on roof tops which has caused a considerable amount of panic to the public in Palestine concerning wither the radiated electromagnetic fields from these base stations may cause any health effect or hazard. Recently UP High Court in India ordered for removal of BTS towers from residential area, it has created panic among cellular communication network designers too. Green cellular networks could be a solution for the above problem. This paper deals with green cellular networks with the help of multi-layer overlaid hierarchical structure (macro / micro / pico / femto cells). Macrocell for area coverage, micro for pedestrian and a slow moving traffic while pico for indoor use and femto for individual high capacity users. This could be the answer of the problem of energy conservation and enhancement of spectral density also.

  16. 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

  17. Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

    PubMed Central

    Hamilton, Joshua J.; Reed, Jennifer L.

    2012-01-01

    Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different

  18. Distinctive Behaviors of Druggable Proteins in Cellular Networks

    PubMed Central

    Workman, Paul; Al-Lazikani, Bissan

    2015-01-01

    The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. PMID:26699810

  19. Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

    PubMed

    Notebaart, Richard A; Teusink, Bas; Siezen, Roland J; Papp, Balázs

    2008-01-01

    To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools. PMID:18225949

  20. Bioenergetic Impairment in Animal and Cellular Models of Alzheimer's Disease: PARP-1 Inhibition Rescues Metabolic Dysfunctions.

    PubMed

    Martire, Sara; Fuso, Andrea; Mosca, Luciana; Forte, Elena; Correani, Virginia; Fontana, Mario; Scarpa, Sigfrido; Maras, Bruno; d'Erme, Maria

    2016-08-10

    Amyloid-beta peptide accumulation in the brain is one of the main hallmarks of Alzheimer's disease. The amyloid aggregation process is associated with the generation of free radical species responsible for mitochondrial impairment and DNA damage that in turn activates poly(ADP-ribose)polymerase 1 (PARP-1). PARP-1 catalyzes the poly(ADP-ribosylation), a post-translational modification of proteins, cleaving the substrate NAD+ and transferring the ADP-ribose moieties to the enzyme itself or to an acceptor protein to form branched polymers of ADP-ribose. In this paper, we demonstrate that a mitochondrial dysfunction occurs in Alzheimer's transgenic mice TgCRND8, in SH-SY5Y treated with amyloid-beta and in 7PA2 cells. Moreover, PARP-1 activation contributes to the functional energetic decline affecting cytochrome oxidase IV protein levels, oxygen consumption rates, and membrane potential, resulting in cellular bioenergetic deficit. We also observed, for the first time, an increase of pyruvate kinase 2 expression, suggesting a modulation of the glycolytic pathway by PARP-1. PARP-1 inhibitors are able to restore both mitochondrial impairment and pyruvate kinase 2 expression. The overall data here presented indicate a pivotal role for this enzyme in the bioenergetic network of neuronal cells and open new perspectives for investigating molecular mechanisms underlying energy charge decline in Alzheimer's disease. In this scenario, PARP-1 inhibitors might represent a novel therapeutic intervention to rescue cellular energetic metabolism. PMID:27567805

  1. Network Coordinated Opportunistic Beamforming in Downlink Cellular Networks

    NASA Astrophysics Data System (ADS)

    Shin, Won-Yong; Jung, Bang Chul

    We propose a network coordinated opportunistic beamforming (NC-OBF) protocol for downlink K-cell networks with M-antenna base stations (BSs). In the NC-OBF scheme, based on pseudo-randomly generated BF vectors, a user scheduling strategy is introduced, where each BS opportunistically selects a set of mobile stations (MSs) whose desired signals generate the minimum interference to the other MSs. Its performance is then analyzed in terms of degrees-of-freedom (DoFs). As our achievability result, it is shown that KM DoFs are achievable if the number N of MSs in a cell scales at least as SNRKM-1, where SNR denotes the received signal-to-noise ratio. Furthermore, by deriving the corresponding upper bound on the DoFs, it is shown that the NC-OBF scheme is DoF-optimal. Note that the proposed scheme does not require the global channel state information and dimension expansion, thereby resulting in easier implementation.

  2. Global reconstruction of the human metabolic network based on genomic and bibliomic data

    PubMed Central

    Duarte, Natalie C.; Becker, Scott A.; Jamshidi, Neema; Thiele, Ines; Mo, Monica L.; Vo, Thuy D.; Srivas, Rohith; Palsson, Bernhard Ø.

    2007-01-01

    Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype–phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology. PMID:17267599

  3. Impaired cellular energy metabolism contributes to bluetongue-virus-induced autophagy.

    PubMed

    Lv, Shuang; Xu, Qingyuan; Sun, Encheng; Zhang, Jikai; Wu, Donglai

    2016-10-01

    Bluetongue virus (BTV) has been found to trigger autophagy to favor its replication, but the underlying mechanisms have not been clarified. Here, we show that cellular energy metabolism is involved in BTV-induced autophagy. Cellular ATP synthesis was impaired by BTV1 infection, causing metabolic stress, which was responsible for activation of autophagy, since the conversion of LC3 and aggregation of GFP-LC3 (autophagy markers) were suppressed when infection-caused energy depletion was reversed via MP (metabolic substrate) treatment. The reduced virus yields with MP further supported this view. Overall, our findings suggest that BTV1-induced disruption of cellular energy metabolism contributes to autophagy, and this provides new insights into BTV-host interactions. PMID:27379971

  4. From Ancient Pathways to Aging Cells-Connecting Metabolism and Cellular Senescence.

    PubMed

    Wiley, Christopher D; Campisi, Judith

    2016-06-14

    Cellular senescence is a complex stress response that permanently arrests the proliferation of cells at risk for oncogenic transformation. However, senescent cells can also drive phenotypes associated with aging. Although the senescence-associated growth arrest prevents the development of cancer, and the metabolism of cancer cells has been studied in depth, the metabolic causes and consequences of cellular senescence were largely unexplored until recently. New findings reveal key roles for several aspects of cellular metabolism in the establishment and control of senescent phenotypes. These discoveries have important implications for both cancer and aging. In this review, we highlight some of the recent links between metabolism and phenotypes that are commonly associated with senescent cells. PMID:27304503

  5. Cellular iron metabolism in prognosis and therapy of breast cancer.

    PubMed

    Torti, Suzy V; Torti, Frank M

    2013-01-01

    Despite many recent advances, breast cancer remains a clinical challenge. Current issues include improving prognostic evaluation and increasing therapeutic options for women whose tumors are refractory to current frontline therapies. Iron metabolism is frequently disrupted in breast cancer, and may offer an opportunity to address these challenges. Iron enhances breast tumor initiation, growth and metastases. Iron may contribute to breast tumor initiation by promoting redox cycling of estrogen metabolites. Up-regulation of iron import and down-regulation of iron export may enable breast cancer cells to acquire and retain excess iron. Alterations in iron metabolism in macrophages and other cells of the tumor microenvironment may also foster breast tumor growth. Expression of iron metabolic genes in breast tumors is predictive of breast cancer prognosis. Iron chelators and other strategies designed to limit iron may have therapeutic value in breast cancer. The dependence of breast cancer on iron presents rich opportunities for improved prognostic evaluation and therapeutic intervention. PMID:23879588

  6. An association of metabolic syndrome constellation with cellular membrane caveolae

    PubMed Central

    Zhang, Wei-zheng

    2014-01-01

    Metabolic syndrome (MetS) is a cluster of metabolic abnormalities that can predispose an individual to a greater risk of developing type-2 diabetes and cardiovascular diseases. The cluster includes abdominal obesity, dyslipidemia, hypertension, and hyperglycemia – all of which are risk factors to public health. While searching for a link among the aforementioned malaises, clues have been focused on the cell membrane domain caveolae, wherein the MetS-associated active molecules are colocalized and interacted with to carry out designated biological activities. Caveola disarray could induce all of those individual metabolic abnormalities to be present in animal models and humans, providing a new target for therapeutic strategy in the management of MetS. PMID:24563731

  7. Mechanics of composite actin networks: in vitro and cellular perspectives

    NASA Astrophysics Data System (ADS)

    Upadhyaya, Arpita

    2014-03-01

    Actin filaments and associated actin binding proteins play an essential role in governing the mechanical properties of eukaryotic cells. Even though cells have multiple actin binding proteins (ABPs) that exist simultaneously to maintain the structural and mechanical integrity of the cellular cytoskeleton, how these proteins work together to determine the properties of actin networks is not well understood. The ABP, palladin, is essential for the integrity of cell morphology and movement during development. Palladin coexists with alpha-actinin in stress fibers and focal adhesions and binds to both actin and alpha-actinin. To obtain insight into how mutually interacting actin crosslinking proteins modulate the properties of actin networks, we have characterized the micro-structure and mechanics of actin networks crosslinked with palladin and alpha-actinin. Our studies on composite networks of alpha-actinin/palladin/actin show that palladin and alpha-actinin synergistically determine network viscoelasticity. We have further examined the role of palladin in cellular force generation and mechanosensing. Traction force microscopy revealed that TAFs are sensitive to substrate stiffness as they generate larger forces on substrates of increased stiffness. Contrary to expectations, knocking down palladin increased the forces generated by cells, and also inhibited the ability to sense substrate stiffness for very stiff gels. This was accompanied by significant differences in the actin organization and adhesion dynamics of palladin knock down cells. Perturbation experiments also suggest altered myosin activity in palladin KD cells. Our results suggest that the actin crosslinkers such as palladin and myosin motors coordinate for optimal cell function and to prevent aberrant behavior as in cancer metastasis.

  8. Study and Simulation of Traffic Behavior in Cellular Network

    NASA Astrophysics Data System (ADS)

    Madhup, D. K.; Shrestha, C. L.; Sharma, R. K.

    2007-07-01

    Cellular radio systems accommodate a large number of users with a limited radio spectrum. The concept of trunking allows a large number of users to share the relatively small number of channels in a cell by providing access to each user, on demand, from a pool of available channels. Traffic engineering deals with provisioning of communication circuits in a given area for a number of subscribers with a required grade of service. Traffic in any cell depends upon the number of users, the average request rate and average call duration. Certain number of channels is required for the required GOS. To design an optimum capacity cellular system, traffic behavior on that system is important. The number of channel required can be estimated by using Erlang formula and Erlang table. Erlang table is not always useful to calculate the probability of blocking in various complex scenarios such as channel borrowing strategies. When the total number of channel available in a given cell are divided to serve partly for newly generated calls and partly for handover calls, and if they use dynamic channel assignment strategies like channel borrowing, then the probability of blocking can't be calculated from Erlang table. Simulation model of the behavior help us to determine the blocking and the channel utilization while using various channel assignment strategies. The title "Study and Simulation of Traffic Behavior in Cellular Network" entail the study of the blocking probability of traffic in cellular network for static channel assignment strategies and dynamic channel borrowing strategies through MATLAB programming language and graphic user interface (GUI). The result shows that the dynamic scheme can perform better than static maximizing the overall utilization of the circuits and minimizing the overall blocking.

  9. Cutting the Wires: Modularization of Cellular Networks for Experimental Design

    PubMed Central

    Lang, Moritz; Summers, Sean; Stelling, Jörg

    2014-01-01

    Understanding naturally evolved cellular networks requires the consecutive identification and revision of the interactions between relevant molecular species. In this process, initially often simplified and incomplete networks are extended by integrating new reactions or whole subnetworks to increase consistency between model predictions and new measurement data. However, increased consistency with experimental data alone is not sufficient to show the existence of biomolecular interactions, because the interplay of different potential extensions might lead to overall similar dynamics. Here, we present a graph-based modularization approach to facilitate the design of experiments targeted at independently validating the existence of several potential network extensions. Our method is based on selecting the outputs to measure during an experiment, such that each potential network extension becomes virtually insulated from all others during data analysis. Each output defines a module that only depends on one hypothetical network extension, and all other outputs act as virtual inputs to achieve insulation. Given appropriate experimental time-series measurements of the outputs, our modules can be analyzed, simulated, and compared to the experimental data separately. Our approach exemplifies the close relationship between structural systems identification and modularization, an interplay that promises development of related approaches in the future. PMID:24411264

  10. Country-wide rainfall maps from cellular communication networks

    PubMed Central

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-01-01

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  11. Country-wide rainfall maps from cellular communication networks.

    PubMed

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-02-19

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km(2)), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  12. Application-Aware Dynamic Retransmission Control in Mobile Cellular Networks

    NASA Astrophysics Data System (ADS)

    Halima, Nadhir Ben; Kliazovich, Dzmitry; Granelli, Fabrizio

    This paper proposes an application-aware cross-layer approach between application/transport layers on the mobile terminal and link layer at the wireless base station to enable dynamic control on the strength of per-packet error protection for multimedia and data transfers. Specifically, in the context of cellular networks, the proposed scheme allows to control the desired level of Hybrid ARQ (HARQ) protection by using an in-band control feedback channel. Such protection is dynamically adapted on a per-packet basis and depends on the perceptual importance of different packets as well as on the reception history of the flow.

  13. Emulating fire propagation by using cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Buscarino, A.; Fortuna, L.; Frasca, M.; Xibilia, M. G.

    2012-09-01

    In this paper a new approach based on Cellular Nonlinear Networks (CNNs) for modeling the diffusion of forest fires is presented. Based on a model relying on an hyperbolic reaction-diffusion equation, the proposed approach exploits the peculiarity of CNNs allowing the investigation of different types of forest fires, also considering specific morphological characteristics of the terrain and the presence of external perturbations like wind flows. Results show the emergence of particular phenomena really observed in wildfires, allowing to assess the validity of the approach.

  14. 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

  15. The Effects of Cholera Toxin on Cellular Energy Metabolism

    PubMed Central

    Snider, Rachel M.; McKenzie, Jennifer R.; Kraft, Lewis; Kozlov, Eugene; Wikswo, John P.; Cliffel, David E.

    2010-01-01

    Multianalyte microphysiometry, a real-time instrument for simultaneous measurement of metabolic analytes in a microfluidic environment, was used to explore the effects of cholera toxin (CTx). Upon exposure of CTx to PC-12 cells, anaerobic respiration was triggered, measured as increases in acid and lactate production and a decrease in the oxygen uptake. We believe the responses observed are due to a CTx-induced activation of adenylate cyclase, increasing cAMP production and resulting in a switch to anaerobic respiration. Inhibitors (H-89, brefeldin A) and stimulators (forskolin) of cAMP were employed to modulate the CTx-induced cAMP responses. The results of this study show the utility of multianalyte microphysiometry to quantitatively determine the dynamic metabolic effects of toxins and affected pathways. PMID:22069603

  16. Exploring mitochondrial evolution and metabolism organization principles by comparative analysis of metabolic networks.

    PubMed

    Chang, Xiao; Wang, Zhuo; Hao, Pei; Li, Yuan-Yuan; Li, Yi-Xue

    2010-06-01

    The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level. PMID:20298776

  17. GPM ground validation via commercial cellular networks: an exploratory approach

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko

    2016-04-01

    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  18. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in The Netherlands.

  19. MicroRNAs Regulate Cellular ATP Levels by Targeting Mitochondrial Energy Metabolism Genes during C2C12 Myoblast Differentiation

    PubMed Central

    Siengdee, Puntita; Trakooljul, Nares; Murani, Eduard; Schwerin, Manfred; Wimmers, Klaus; Ponsuksili, Siriluck

    2015-01-01

    In our previous study, we identified an miRNA regulatory network involved in energy metabolism in porcine muscle. To better understand the involvement of miRNAs in cellular ATP production and energy metabolism, here we used C2C12 myoblasts, in which ATP levels increase during differentiation, to identify miRNAs modulating these processes. ATP level, miRNA and mRNA microarray expression profiles during C2C12 differentiation into myotubes were assessed. The results suggest 14 miRNAs (miR-423-3p, miR-17, miR-130b, miR-301a/b, miR-345, miR-15a, miR-16a, miR-128, miR-615, miR-1968, miR-1a/b, and miR-194) as cellular ATP regulators targeting genes involved in mitochondrial energy metabolism (Cox4i2, Cox6a2, Ndufb7, Ndufs4, Ndufs5, and Ndufv1) during C2C12 differentiation. Among these, miR-423-3p showed a high inverse correlation with increasing ATP levels. Besides having implications in promoting cell growth and cell cycle progression, its function in cellular ATP regulation is yet unknown. Therefore, miR-423-3p was selected and validated for the function together with its potential target, Cox6a2. Overexpression of miR-423-3p in C2C12 myogenic differentiation lead to decreased cellular ATP level and decreased expression of Cox6a2 compared to the negative control. These results suggest miR-423-3p as a novel regulator of ATP/energy metabolism by targeting Cox6a2. PMID:26010876

  20. Integration of metabolomics data into metabolic networks

    PubMed Central

    Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

    2015-01-01

    Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data. PMID:25741348

  1. Cellular telephone-based wide-area radiation detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  2. Cellular Metabolic Rate Is Influenced by Life-History Traits in Tropical and Temperate Birds

    PubMed Central

    Jimenez, Ana Gabriela; Van Brocklyn, James; Wortman, Matthew; Williams, Joseph B.

    2014-01-01

    In general, tropical birds have a “slow pace of life,” lower rates of whole-animal metabolism and higher survival rates, than temperate species. A fundamental challenge facing physiological ecologists is the understanding of how variation in life-history at the whole-organism level might be linked to cellular function. Because tropical birds have lower rates of whole-animal metabolism, we hypothesized that cells from tropical species would also have lower rates of cellular metabolism than cells from temperate species of similar body size and common phylogenetic history. We cultured primary dermal fibroblasts from 17 tropical and 17 temperate phylogenetically-paired species of birds in a common nutritive and thermal environment and then examined basal, uncoupled, and non-mitochondrial cellular O2 consumption (OCR), proton leak, and anaerobic glycolysis (extracellular acidification rates [ECAR]), using an XF24 Seahorse Analyzer. We found that multiple measures of metabolism in cells from tropical birds were significantly lower than their temperate counterparts. Basal and uncoupled cellular metabolism were 29% and 35% lower in cells from tropical birds, respectively, a decrease closely aligned with differences in whole-animal metabolism between tropical and temperate birds. Proton leak was significantly lower in cells from tropical birds compared with cells from temperate birds. Our results offer compelling evidence that whole-animal metabolism is linked to cellular respiration as a function of an animal’s life-history evolution. These findings are consistent with the idea that natural selection has uniquely fashioned cells of long-lived tropical bird species to have lower rates of metabolism than cells from shorter-lived temperate species. PMID:24498080

  3. Alkalizing Reactions Streamline Cellular Metabolism in Acidogenic Microorganisms

    PubMed Central

    Arioli, Stefania; Ragg, Enzio; Scaglioni, Leonardo; Fessas, Dimitrios; Signorelli, Marco; Karp, Matti; Daffonchio, Daniele; De Noni, Ivano; Mulas, Laura; Oggioni, Marco; Guglielmetti, Simone; Mora, Diego

    2010-01-01

    An understanding of the integrated relationships among the principal cellular functions that govern the bioenergetic reactions of an organism is necessary to determine how cells remain viable and optimise their fitness in the environment. Urease is a complex enzyme that catalyzes the hydrolysis of urea to ammonia and carbonic acid. While the induction of urease activity by several microorganisms has been predominantly considered a stress-response that is initiated to generate a nitrogen source in response to a low environmental pH, here we demonstrate a new role of urease in the optimisation of cellular bioenergetics. We show that urea hydrolysis increases the catabolic efficiency of Streptococcus thermophilus, a lactic acid bacterium that is widely used in the industrial manufacture of dairy products. By modulating the intracellular pH and thereby increasing the activity of β-galactosidase, glycolytic enzymes and lactate dehydrogenase, urease increases the overall change in enthalpy generated by the bioenergetic reactions. A cooperative altruistic behaviour of urease-positive microorganisms on the urease-negative microorganisms within the same environment was also observed. The physiological role of a single enzymatic activity demonstrates a novel and unexpected view of the non-transcriptional regulatory mechanisms that govern the bioenergetics of a bacterial cell, highlighting a new role for cytosol-alkalizing biochemical pathways in acidogenic microorganisms. PMID:21152088

  4. Assessing the weather monitoring capabilities of cellular microwave link networks

    NASA Astrophysics Data System (ADS)

    Fencl, Martin; Vrzba, Miroslav; Rieckermann, Jörg; Bareš, Vojtěch

    2016-04-01

    Using of microwave links for rainfall monitoring was suggested already by (Atlas and Ulbrich, 1977). However, this technique attracted broader attention of scientific community only in the recent decade, with the extensive growth of cellular microwave link (CML) networks, which form the backbone of today's cellular telecommunication infrastructure. Several studies have already shown that CMLs can be conveniently used as weather sensors and have potential to provide near-ground path-integrated observations of rainfall but also humidity or fog. However, although research is still focusing on algorithms to improve the weather sensing capabilities (Fencl et al., 2015), it is not clear how to convince cellular operators to provide the power levels of their network. One step in this direction is to show in which regions or municipalities the networks are sufficiently dense to provide/develop good services. In this contribution we suggest a standardized approach to evaluate CML networks in terms of rainfall observation and to identify suitable regions for CML rainfall monitoring. We estimate precision of single CML based on its sensitivity to rainfall, i.e. as a function of frequency, polarization and path length. Capability of a network to capture rainfall spatial patterns is estimated from the CML coverage and path lengths considering that single CML provides path-integrated rain rates. We also search for suitable predictors for regions where no network topologies are available. We test our approach on several European networks and discuss the results. Our results show that CMLs are very dense in urban areas (> 1 CML/km2), but less in rural areas (< 0.02 CML/km2). We found a strong correlation between a population and CML network density (e.g. R2 = 0.97 in Czech Republic), thus population could be a simple proxy to identify suitable regions for CML weather monitoring. To enable a simple and efficient assessment of the CML monitoring potential for any region worldwide

  5. Sigma-delta cellular neural network for 2D modulation.

    PubMed

    Aomori, Hisashi; Otake, Tsuyoshi; Takahashi, Nobuaki; Tanaka, Mamoru

    2008-01-01

    Although sigma-delta modulation is widely used for analog-to-digital (A/D) converters, sigma-delta concepts are only for 1D signals. Signal processing in the digital domain is extremely useful for 2D signals such as used in image processing, medical imaging, ultrasound imaging, and so on. The intricate task that provides true 2D sigma-delta modulation is feasible in the spatial domain sigma-delta modulation using the discrete-time cellular neural network (DT-CNN) with a C-template. In the proposed architecture, the A-template is used for a digital-to-analog converter (DAC), the C-template works as an integrator, and the nonlinear output function is used for the bilevel output. In addition, due to the cellular neural network (CNN) characteristics, each pixel of an image corresponds to a cell of a CNN, and each cell is connected spatially by the A-template. Therefore, the proposed system can be thought of as a very large-scale and super-parallel sigma-delta modulator. Moreover, the spatio-temporal dynamics is designed to obtain an optimal reconstruction signal. The experimental results show the excellent reconstruction performance and capabilities of the CNN as a sigma-delta modulator. PMID:18215502

  6. Thermodynamic-based computational profiling of cellular regulatory control in hepatocyte metabolism.

    PubMed

    Beard, Daniel A; Qian, Hong

    2005-03-01

    Thermodynamic-based constraints on biochemical fluxes and concentrations are applied in concert with mass balance of fluxes in glycogenesis and glycogenolysis in a model of hepatic cell metabolism. Constraint-based modeling methods that facilitate predictions of reactant concentrations, reaction potentials, and enzyme activities are introduced to identify putative regulatory and control sites in biological networks by computing the minimal control scheme necessary to switch between metabolic modes. Computational predictions of control sites in glycogenic and glycogenolytic operational modes in the hepatocyte network compare favorably with known regulatory mechanisms. The developed hepatic metabolic model is used to computationally analyze the impairment of glucose production in von Gierke's and Hers' diseases, two metabolic diseases impacting glycogen metabolism. The computational methodology introduced here can be generalized to identify downstream targets of agonists, to systematically probe possible drug targets, and to predict the effects of specific inhibitors (or activators) on integrated network function. PMID:15507536

  7. Steady states and stability in metabolic networks without regulation.

    PubMed

    Ivanov, Oleksandr; van der Schaft, Arjan; Weissing, Franz J

    2016-07-21

    Metabolic networks are often extremely complex. Despite intensive efforts many details of these networks, e.g., exact kinetic rates and parameters of metabolic reactions, are not known, making it difficult to derive their properties. Considerable effort has been made to develop theory about properties of steady states in metabolic networks that are valid for any values of parameters. General results on uniqueness of steady states and their stability have been derived with specific assumptions on reaction kinetics, stoichiometry and network topology. For example, deep results have been obtained under the assumptions of mass-action reaction kinetics, continuous flow stirred tank reactors (CFSTR), concordant reaction networks and others. Nevertheless, a general theory about properties of steady states in metabolic networks is still missing. Here we make a step further in the quest for such a theory. Specifically, we study properties of steady states in metabolic networks with monotonic kinetics in relation to their stoichiometry (simple and general) and the number of metabolites participating in every reaction (single or many). Our approach is based on the investigation of properties of the Jacobian matrix. We show that stoichiometry, network topology, and the number of metabolites that participate in every reaction have a large influence on the number of steady states and their stability in metabolic networks. Specifically, metabolic networks with single-substrate-single-product reactions have disconnected steady states, whereas in metabolic networks with multiple-substrates-multiple-product reactions manifolds of steady states arise. Metabolic networks with simple stoichiometry have either a unique globally asymptotically stable steady state or asymptotically stable manifolds of steady states. In metabolic networks with general stoichiometry the steady states are not always stable and we provide conditions for their stability. In order to demonstrate the biological

  8. Energetics of Glucose Metabolism: A Phenomenological Approach to Metabolic Network Modeling

    PubMed Central

    Diederichs, Frank

    2010-01-01

    A new formalism to describe metabolic fluxes as well as membrane transport processes was developed. The new flux equations are comparable to other phenomenological laws. Michaelis-Menten like expressions, as well as flux equations of nonequilibrium thermodynamics, can be regarded as special cases of these new equations. For metabolic network modeling, variable conductances and driving forces are required to enable pathway control and to allow a rapid response to perturbations. When applied to oxidative phosphorylation, results of simulations show that whole oxidative phosphorylation cannot be described as a two-flux-system according to nonequilibrium thermodynamics, although all coupled reactions per se fulfill the equations of this theory. Simulations show that activation of ATP-coupled load reactions plus glucose oxidation is brought about by an increase of only two different conductances: a [Ca2+] dependent increase of cytosolic load conductances, and an increase of phosphofructokinase conductance by [AMP], which in turn becomes increased through [ADP] generation by those load reactions. In ventricular myocytes, this feedback mechanism is sufficient to increase cellular power output and O2 consumption several fold, without any appreciable impairment of energetic parameters. Glucose oxidation proceeds near maximal power output, since transformed input and output conductances are nearly equal, yielding an efficiency of about 0.5. This conductance matching is fulfilled also by glucose oxidation of β-cells. But, as a price for the metabolic mechanism of glucose recognition, β-cells have only a limited capability to increase their power output. PMID:21152283

  9. Heat stress effects on livestock: molecular, cellular and metabolic aspects, a review.

    PubMed

    Belhadj Slimen, I; Najar, T; Ghram, A; Abdrrabba, M

    2016-06-01

    Elevated ambient temperatures affect animal production and welfare. Animal's reduced production performances during heat stress were traditionally thought to result from the decreased feed intake. However, it has recently been shown that heat stress disturbs the steady state concentrations of free radicals, resulting in both cellular and mitochondrial oxidative damage. Indeed, heat stress reorganizes the use of the body resources including fat, protein and energy. Heat stress reduces the metabolic rates and alters post-absorptive metabolism, regardless of the decreased feed intake. Consequently, growth, production, reproduction and health are not priorities any more in the metabolism of heat-stressed animals. The drastic effects of heat stress depend on its duration and severity. This review clearly describes about biochemical, cellular and metabolic changes that occur during thermal stress in farm animals. PMID:26250521

  10. Mitochondrial Mg2+ homeostasis decides cellular energy metabolism and vulnerability to stress

    PubMed Central

    Yamanaka, Ryu; Tabata, Sho; Shindo, Yutaka; Hotta, Kohji; Suzuki, Koji; Soga, Tomoyoshi; Oka, Kotaro

    2016-01-01

    Cellular energy production processes are composed of many Mg2+ dependent enzymatic reactions. In fact, dysregulation of Mg2+ homeostasis is involved in various cellular malfunctions and diseases. Recently, mitochondria, energy-producing organelles, have been known as major intracellular Mg2+ stores. Several biological stimuli alter mitochondrial Mg2+ concentration by intracellular redistribution. However, in living cells, whether mitochondrial Mg2+ alteration affect cellular energy metabolism remains unclear. Mg2+ transporter of mitochondrial inner membrane MRS2 is an essential component of mitochondrial Mg2+ uptake system. Here, we comprehensively analyzed intracellular Mg2+ levels and energy metabolism in Mrs2 knockdown (KD) cells using fluorescence imaging and metabolome analysis. Dysregulation of mitochondrial Mg2+ homeostasis disrupted ATP production via shift of mitochondrial energy metabolism and morphology. Moreover, Mrs2 KD sensitized cellular tolerance against cellular stress. These results indicate regulation of mitochondrial Mg2+ via MRS2 critically decides cellular energy status and cell vulnerability via regulation of mitochondrial Mg2+ level in response to physiological stimuli. PMID:27458051

  11. Mitochondrial Mg(2+) homeostasis decides cellular energy metabolism and vulnerability to stress.

    PubMed

    Yamanaka, Ryu; Tabata, Sho; Shindo, Yutaka; Hotta, Kohji; Suzuki, Koji; Soga, Tomoyoshi; Oka, Kotaro

    2016-01-01

    Cellular energy production processes are composed of many Mg(2+) dependent enzymatic reactions. In fact, dysregulation of Mg(2+) homeostasis is involved in various cellular malfunctions and diseases. Recently, mitochondria, energy-producing organelles, have been known as major intracellular Mg(2+) stores. Several biological stimuli alter mitochondrial Mg(2+) concentration by intracellular redistribution. However, in living cells, whether mitochondrial Mg(2+) alteration affect cellular energy metabolism remains unclear. Mg(2+) transporter of mitochondrial inner membrane MRS2 is an essential component of mitochondrial Mg(2+) uptake system. Here, we comprehensively analyzed intracellular Mg(2+) levels and energy metabolism in Mrs2 knockdown (KD) cells using fluorescence imaging and metabolome analysis. Dysregulation of mitochondrial Mg(2+) homeostasis disrupted ATP production via shift of mitochondrial energy metabolism and morphology. Moreover, Mrs2 KD sensitized cellular tolerance against cellular stress. These results indicate regulation of mitochondrial Mg(2+) via MRS2 critically decides cellular energy status and cell vulnerability via regulation of mitochondrial Mg(2+) level in response to physiological stimuli. PMID:27458051

  12. Accelerating the reconstruction of genome-scale metabolic networks

    PubMed Central

    Notebaart, Richard A; van Enckevort, Frank HJ; Francke, Christof; Siezen, Roland J; Teusink, Bas

    2006-01-01

    Background The genomic information of a species allows for the genome-scale reconstruction of its metabolic capacity. Such a metabolic reconstruction gives support to metabolic engineering, but also to integrative bioinformatics and visualization. Sequence-based automatic reconstructions require extensive manual curation, which can be very time-consuming. Therefore, we present a method to accelerate the time-consuming process of network reconstruction for a query species. The method exploits the availability of well-curated metabolic networks and uses high-resolution predictions of gene equivalency between species, allowing the transfer of gene-reaction associations from curated networks. Results We have evaluated the method using Lactococcus lactis IL1403, for which a genome-scale metabolic network was published recently. We recovered most of the gene-reaction associations (i.e. 74 – 85%) which are incorporated in the published network. Moreover, we predicted over 200 additional genes to be associated to reactions, including genes with unknown function, genes for transporters and genes with specific metabolic reactions, which are good candidates for an extension to the previously published network. In a comparison of our developed method with the well-established approach Pathologic, we predicted 186 additional genes to be associated to reactions. We also predicted a relatively high number of complete conserved protein complexes, which are derived from curated metabolic networks, illustrating the potential predictive power of our method for protein complexes. Conclusion We show that our methodology can be applied to accelerate the reconstruction of genome-scale metabolic networks by taking optimal advantage of existing, manually curated networks. As orthology detection is the first step in the method, only the translated open reading frames (ORFs) of a newly sequenced genome are necessary to reconstruct a metabolic network. When more manually curated metabolic

  13. GIM3E: Condition-specific Models of Cellular Metabolism Developed from Metabolomics and Expression Data

    SciTech Connect

    Schmidt, Brian; Ebrahim, Ali; Metz, Thomas O.; Adkins, Joshua N.; Palsson, Bernard O.; Hyduke, Daniel R.

    2013-11-15

    Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/

  14. Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

    NASA Astrophysics Data System (ADS)

    Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

    2008-12-01

    Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

  15. The Crossroads of Iron with Hypoxia and Cellular Metabolism. Implications in the Pathobiology of Pulmonary Hypertension

    PubMed Central

    Graham, Brian B.; Rouault, Tracey C.; Tuder, Rubin M.

    2014-01-01

    The pathologic hallmark of pulmonary arterial hypertension (PAH) is pulmonary vascular remodeling, characterized by endothelial cell proliferation, smooth muscle hypertrophy, and perivascular inflammation, ultimately contributing to increased pulmonary arterial pressures. Several recent studies have observed that iron deficiency in patients with various forms of PAH is associated with worsened clinical outcome. Iron plays a key role in many cellular processes regulating the response to hypoxia, oxidative stress, cellular proliferation, and cell metabolism. Given the potential importance of iron supplementation in patients with the disease and the broad cellular functions of iron, we review its role in processes that pertain to PAH. PMID:24988529

  16. AMPK: A cellular metabolic and redox sensor. A minireview

    PubMed Central

    Shirwany, Najeeb A; Zou, Ming-Hui

    2014-01-01

    AMPK is a serine/threonine kinase that is found in all eukaryotes and is ubiquitously expressed in all organ systems. Once activated, AMPK stimulates hepatic fatty acid oxidation and ketogenesis, inhibits cholesterol synthesis, lipogenesis, and triglyceride synthesis, inhibits adipocyte lipolysis and lipogenesis, stimulates skeletal muscle fatty acid oxidation and muscle glucose uptake, and modulates insulin secretion by the pancreas. Thus its importance in many critical cellular processes is well established. For cells it is critical that energy supply and demand are closely matched. AMPK is recognized as a critical integrator of this balance. It is known to be allosterically activated by an increased AMP:ATP ratio. Activation of the kinase switches on catabolic pathways while switching off anabolic ones. It also acts as a redox sensor in endothelial cells where oxidative stress can disturb NO signaling. Abnormal NO signaling leads to disturbed vasodilatory responses. By inhibiting the formation of reactive oxygen species in the endothelium, AMPK can optimize the redox balance in the vasculature. Here, we review the role of AMPK in the cell. PMID:24389195

  17. Structural analysis of metabolic networks based on flux centrality.

    PubMed

    Koschützki, Dirk; Junker, Björn H; Schwender, Jörg; Schreiber, Falk

    2010-08-01

    Metabolic reactions are fundamental to living organisms, and a large number of reactions simultaneously occur at a given time in living cells transforming diverse metabolites into each other. There has been an ongoing debate on how to classify metabolites with respect to their importance for metabolic performance, usually based on the analysis of topological properties of genome scale metabolic networks. However, none of these studies have accounted quantitatively for flux in metabolic networks, thus lacking an important component of a cell's biochemistry. We therefore analyzed a genome scale metabolic network of Escherichia coli by comparing growth under 19 different growth conditions, using flux balance analysis and weighted network centrality investigation. With this novel concept of flux centrality we generated metabolite rankings for each particular growth condition. In contrast to the results of conventional analysis of genome scale metabolic networks, different metabolites were top-ranking dependent on the growth condition. At the same time, several metabolites were consistently among the high ranking ones. Those are associated with pathways that have been described by biochemists as the most central part of metabolism, such as glycolysis, tricarboxylic acid cycle and pentose phosphate pathway. The values for the average path length of the analyzed metabolite networks were between 10.5 and 12.6, supporting recent findings that the metabolic network of E. coli is not a small-world network. PMID:20471988

  18. A computational model of skeletal muscle metabolism linking cellular adaptations induced by altered loading states to metabolic responses during exercise

    PubMed Central

    Dash, Ranjan K; DiBella, John A; Cabrera, Marco E

    2007-01-01

    Background The alterations in skeletal muscle structure and function after prolonged periods of unloading are initiated by the chronic lack of mechanical stimulus of sufficient intensity, which is the result of a series of biochemical and metabolic interactions spanning from cellular to tissue/organ level. Reduced activation of skeletal muscle alters the gene expression of myosin heavy chain isoforms to meet the functional demands of reduced mechanical load, which results in muscle atrophy and reduced capacity to process fatty acids. In contrast, chronic loading results in the opposite pattern of adaptations. Methods To quantify interactions among cellular and skeletal muscle metabolic adaptations, and to predict metabolic responses to exercise after periods of altered loading states, we develop a computational model of skeletal muscle metabolism. The governing model equations – with parameters characterizing chronic loading/unloading states- were solved numerically to simulate metabolic responses to moderate intensity exercise (WR ≤ 40% VO2 max). Results Model simulations showed that carbohydrate oxidation was 8.5% greater in chronically unloaded muscle compared with the loaded muscle (0.69 vs. 0.63 mmol/min), while fat oxidation was 7% higher in chronically loaded muscle (0.14 vs. 0.13 mmol/min), during exercise. Muscle oxygen uptake (VO2) and blood flow (Q) response times were 29% and 44% shorter in chronically loaded muscle (0.4 vs. 0.56 min for VO2 and 0.25 vs. 0.45 min for Q). Conclusion The present model can be applied to test complex hypotheses during exercise involving the integration and control of metabolic processes at various organizational levels (cellular to tissue) in individuals who have undergone periods of chronic loading or unloading. PMID:17448235

  19. Mesoscale assembly of chemically modified graphene into complex cellular networks

    NASA Astrophysics Data System (ADS)

    Barg, Suelen; Perez, Felipe Macul; Ni, Na; Do Vale Pereira, Paula; Maher, Robert C.; Garcia-Tuñon, Esther; Eslava, Salvador; Agnoli, Stefano; Mattevi, Cecilia; Saiz, Eduardo

    2014-07-01

    The widespread technological introduction of graphene beyond electronics rests on our ability to assemble this two-dimensional building block into three-dimensional structures for practical devices. To achieve this goal we need fabrication approaches that are able to provide an accurate control of chemistry and architecture from nano to macroscopic levels. Here, we describe a versatile technique to build ultralight (density ≥1 mg cm-3) cellular networks based on the use of soft templates and the controlled segregation of chemically modified graphene to liquid interfaces. These novel structures can be tuned for excellent conductivity; versatile mechanical response (elastic-brittle to elastomeric, reversible deformation, high energy absorption) and organic absorption capabilities (above 600 g per gram of material). The approach can be used to uncover the basic principles that will guide the design of practical devices that by combining unique mechanical and functional performance will generate new technological opportunities.

  20. Mesoscale assembly of chemically modified graphene into complex cellular networks

    PubMed Central

    Barg, Suelen; Perez, Felipe Macul; Ni, Na; do Vale Pereira, Paula; Maher, Robert C.; Garcia-Tuñon, Esther; Eslava, Salvador; Agnoli, Stefano; Mattevi, Cecilia; Saiz, Eduardo

    2014-01-01

    The widespread technological introduction of graphene beyond electronics rests on our ability to assemble this two-dimensional building block into three-dimensional structures for practical devices. To achieve this goal we need fabrication approaches that are able to provide an accurate control of chemistry and architecture from nano to macroscopic levels. Here, we describe a versatile technique to build ultralight (density ≥1 mg cm−3) cellular networks based on the use of soft templates and the controlled segregation of chemically modified graphene to liquid interfaces. These novel structures can be tuned for excellent conductivity; versatile mechanical response (elastic-brittle to elastomeric, reversible deformation, high energy absorption) and organic absorption capabilities (above 600 g per gram of material). The approach can be used to uncover the basic principles that will guide the design of practical devices that by combining unique mechanical and functional performance will generate new technological opportunities. PMID:24999766

  1. A 'bioproduction breadboard': programming, assembling, and actuating cellular networks.

    PubMed

    Zargar, Amin; Payne, Gregory F; Bentley, William E

    2015-12-01

    With advances in synthetic biology and biofabrication, cellular networks can be functionalized and connected with unprecedented sophistication. We describe a platform for the creation of a 'bioproduction breadboard'. This would consist of physically isolated product-producing cell populations, product capture devices, and other unit operations that function as programmed in place, using unique, orthogonal inputs. For product synthesis, customized cell populations would be connected through standardized, generic inputs allowing 'plug and play' functionality and primary, user-mediated regulation. In addition, through autonomous pathway redirection and balancing, the cells themselves would provide secondary, self-directed regulation to optimize bioproduction. By leveraging specialization and division of labor, we envision diverse cell populations linked to create new pathway designs. PMID:26342587

  2. Automatic generation of multipath algorithms in the cellular nonlinear network

    NASA Astrophysics Data System (ADS)

    Preciado, Victor M.; Guinea, Domingo; Montufar-Chaveznava, Rodrigo

    2001-04-01

    The objective of this work is to generate a learning machine capable of find solutions for complex image processing task by Cellular Neural Network (CNN's). First a general machine for automatic analog algorithm design independent of the problem to solve is created, this is accomplished through an evolutionary strategy that is an extension of genetic programming. Second, this work introduces a suite of sub- mechanisms that increase the power of genetic programming and contribute to reduce the enormous space search for producing a plentiful search. Some concepts in this section are related with AI theory, in such a way that in this work we are in the intersection field of AI and Image Processing by CNN.

  3. Edge detection of noisy images based on cellular neural networks

    NASA Astrophysics Data System (ADS)

    Li, Huaqing; Liao, Xiaofeng; Li, Chuandong; Huang, Hongyu; Li, Chaojie

    2011-09-01

    This paper studies a technique employing both cellular neural networks (CNNs) and linear matrix inequality (LMI) for edge detection of noisy images. Our main work focuses on training templates of noise reduction and edge detection CNNs. Based on the Lyapunov stability theorem, we derive a criterion for global asymptotical stability of a unique equilibrium of the noise reduction CNN. Then we design an approach to train edge detection templates, and this approach can detect the edge precisely and efficiently, i.e., by only one iteration. Finally, we illustrate performance of the proposed methodology from the aspect of peak signal to noise ratio (PSNR) through computer simulations. Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.

  4. Country-wide rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  5. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    PubMed Central

    2011-01-01

    Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a) using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b) with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our results suggest that this

  6. Inhibition of HIV by Legalon-SIL is independent of its effect on cellular metabolism

    SciTech Connect

    McClure, Janela; Margineantu, Daciana H.; Sweet, Ian R.; Polyak, Stephen J.

    2014-01-20

    In this report, we further characterized the effects of silibinin (SbN), derived from milk thistle extract, and Legalon-SIL (SIL), a water-soluble derivative of SbN, on T cell metabolism and HIV infection. We assessed the effects of SbN and SIL on peripheral blood mononuclear cells (PBMC) and CEM-T4 cells in terms of cellular growth, ATP content, metabolism, and HIV infection. SIL and SbN caused a rapid and reversible (upon removal) decrease in cellular ATP levels, which was associated with suppression of mitochondrial respiration and glycolysis. SbN, but not SIL inhibited glucose uptake. Exposure of T cells to SIL (but not SbN or metabolic inhibitors) during virus adsorption blocked HIV infection. Thus, both SbN and SIL rapidly perturb T cell metabolism in vitro, which may account for its anti-inflammatory and anti-proliferative effects that arise with prolonged exposure of cells. However, the metabolic effects are not involved in SIL's unique ability to block HIV entry. - Highlights: • Silibinin (SbN) and Legalon-SIL (SIL) are cytoprotective mixtures of natural products. • SbN and SIL reduce T cell oxidative phosphorylation and glycolysis in vitro. • SIL but not SbN blocks entry of multiple HIV isolates into T cells in vitro. • SIL's suppression of HIV appears independent of its effects on T cell metabolism. • Metabolic effects of SIL and SbN may be relevant in inflammatory diseases.

  7. Cellular uptake and metabolism of curcuminoids in monocytes/macrophages: regulatory effects on lipid accumulation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We previously showed that curcumin (CUR) may increase lipid accumulation in cultured THP-1 monocytes/macrophages, but tetrahydrocurcumin (THC), an in vivo metabolite of CUR, had no such effect. In the present study, we have hypothesized that different cellular uptake and/or metabolism of CUR and THC...

  8. The functions of cardiolipin in cellular metabolism-potential modifiers of the Barth syndrome phenotype.

    PubMed

    Raja, Vaishnavi; Greenberg, Miriam L

    2014-04-01

    The phospholipid cardiolipin (CL) plays a role in many cellular functions and signaling pathways both inside and outside of mitochondria. This review focuses on the role of CL in energy metabolism. Many reactions of electron transport and oxidative phosphorylation, the transport of metabolites required for these processes, and the stabilization of electron transport chain supercomplexes require CL. Recent studies indicate that CL is required for the synthesis of iron-sulfur (Fe-S) co-factors, which are essential for numerous metabolic pathways. Activation of carnitine shuttle enzymes that are required for fatty acid metabolism is CL dependent. The presence of substantial amounts of CL in the peroxisomal membrane suggests that CL may be required for peroxisomal functions. Understanding the role of CL in energy metabolism may identify physiological modifiers that exacerbate the loss of CL and underlie the variation in symptoms observed in Barth syndrome, a genetic disorder of CL metabolism. PMID:24445246

  9. Compartmentalization and molecular traffic in secondary metabolism: a new understanding of established cellular processes

    PubMed Central

    Roze, Ludmila V.; Chanda, Anindya; Linz, John E.

    2010-01-01

    Great progress has been made in understanding the regulation of expression of genes involved in secondary metabolism. Less is known about the mechanisms that govern the spatial distribution of the enzymes, cofactors, and substrates that mediate catalysis of secondary metabolites within the cell. Filamentous fungi in the genus Aspergillus synthesize an array of secondary metabolites and provide useful systems to analyze the mechanisms that mediate the temporal and spatial regulation of secondary metabolism in eukaryotes. For example, aflatoxin biosynthesis in A. parasiticus has been studied intensively because this mycotoxin is highly toxic, mutagenic, and carcinogenic in humans and animals. Using aflatoxin synthesis to illustrate key concepts, this review focuses on the mechanisms by which sub-cellular compartmentalization and intra-cellular molecular traffic contribute to the initiation and completion of secondary metabolism within the cell. We discuss the recent discovery of aflatoxisomes, specialized trafficking vesicles that participate in the compartmentalization of aflatoxin synthesis and export of the toxin to the cell exterior; this work provides a new and clearer understanding of how cells integrate secondary metabolism into basic cellular metabolism via the intracellular trafficking machinery. PMID:20519149

  10. The lysosome as a command-and-control center for cellular metabolism.

    PubMed

    Lim, Chun-Yan; Zoncu, Roberto

    2016-09-12

    Lysosomes are membrane-bound organelles found in every eukaryotic cell. They are widely known as terminal catabolic stations that rid cells of waste products and scavenge metabolic building blocks that sustain essential biosynthetic reactions during starvation. In recent years, this classical view has been dramatically expanded by the discovery of new roles of the lysosome in nutrient sensing, transcriptional regulation, and metabolic homeostasis. These discoveries have elevated the lysosome to a decision-making center involved in the control of cellular growth and survival. Here we review these recently discovered properties of the lysosome, with a focus on how lysosomal signaling pathways respond to external and internal cues and how they ultimately enable metabolic homeostasis and cellular adaptation. PMID:27621362

  11. TMEM55B is a Novel Regulator of Cellular Cholesterol Metabolism

    PubMed Central

    Medina, Marisa W.; Bauzon, Frederick; Naidoo, Devesh; Theusch, Elizabeth; Stevens, Kristen; Schilde, Jessica; Schubert, Christian; Mangravite, Lara M.; Rudel, Lawrence L.; Temel, Ryan E.; Runz, Heiko; Krauss, Ronald M.

    2014-01-01

    Objective Inter-individual variation in pathways impacting cellular cholesterol metabolism can influence levels of plasma cholesterol, a well-established risk factor for cardiovascular disease. Inherent variation among immortalized lymphoblastoid cell lines (LCLs) from different donors can be leveraged to discover novel genes that modulate cellular cholesterol metabolism. The objective of this study was to identify novel genes that regulate cholesterol metabolism by testing for evidence of correlated gene expression with cellular levels of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) mRNA, a marker for cellular cholesterol homeostasis, in a large panel of LCLs. Approach and Results Expression array profiling was performed on 480 LCLs established from participants of the Cholesterol and Pharmacogenetics statin clinical trial, and transcripts were tested for evidence of correlated expression with HMGCR as a marker of intracellular cholesterol homeostasis. Of these, transmembrane protein 55b (TMEM55B) showed the strongest correlation (r=0.29, p=4.0E-08) of all genes not previously implicated in cholesterol metabolism and was found to be sterol regulated. TMEM55B knock-down in human hepatoma cell lines promoted the decay rate of the low density lipoprotein receptor (LDLR), reduced cell surface LDLR protein, impaired LDL uptake, and reduced intracellular cholesterol. Conclusions Here we report identification of TMEM55B as a novel regulator of cellular cholesterol metabolism through the combination of gene expression profiling and functional studies. The findings highlight the value of an integrated genomic approach for identifying genes that influence cholesterol homeostasis. PMID:25035345

  12. Cellular computational networks--a scalable architecture for learning the dynamics of large networked systems.

    PubMed

    Luitel, Bipul; Venayagamoorthy, Ganesh Kumar

    2014-02-01

    Neural networks for implementing large networked systems such as smart electric power grids consist of multiple inputs and outputs. Many outputs lead to a greater number of parameters to be adapted. Each additional variable increases the dimensionality of the problem and hence learning becomes a challenge. Cellular computational networks (CCNs) are a class of sparsely connected dynamic recurrent networks (DRNs). By proper selection of a set of input elements for each output variable in a given application, a DRN can be modified into a CCN which significantly reduces the complexity of the neural network and allows use of simple training methods for independent learning in each cell thus making it scalable. This article demonstrates this concept of developing a CCN using dimensionality reduction in a DRN for scalability and better performance. The concept has been analytically explained and empirically verified through application. PMID:24300549

  13. Systems Analysis of Plant Functional, Transcriptional, Physical Interaction, and Metabolic Networks

    PubMed Central

    Bassel, George W.; Gaudinier, Allison; Brady, Siobhan M.; Hennig, Lars; Rhee, Seung Y.; De Smet, Ive

    2012-01-01

    Physiological responses, developmental programs, and cellular functions rely on complex networks of interactions at different levels and scales. Systems biology brings together high-throughput biochemical, genetic, and molecular approaches to generate omics data that can be analyzed and used in mathematical and computational models toward uncovering these networks on a global scale. Various approaches, including transcriptomics, proteomics, interactomics, and metabolomics, have been employed to obtain these data on the cellular, tissue, organ, and whole-plant level. We summarize progress on gene regulatory, cofunction, protein interaction, and metabolic networks. We also illustrate the main approaches that have been used to obtain these networks, with specific examples from Arabidopsis thaliana, and describe the pros and cons of each approach. PMID:23110892

  14. Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism

    PubMed Central

    Chang, Roger L; Ghamsari, Lila; Manichaikul, Ani; Hom, Erik F Y; Balaji, Santhanam; Fu, Weiqi; Shen, Yun; Hao, Tong; Palsson, Bernhard Ø; Salehi-Ashtiani, Kourosh; Papin, Jason A

    2011-01-01

    Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. PMID:21811229

  15. GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data

    PubMed Central

    Schmidt, Brian J.; Ebrahim, Ali; Metz, Thomas O.; Adkins, Joshua N.; Palsson, Bernhard Ø.; Hyduke, Daniel R.

    2013-01-01

    Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been developed. Results: GIM3E (Gene Inactivation Moderated by Metabolism, Metabolomics and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics and cellular metabolomics data. GIM3E establishes metabolite use requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions and provides calculations of the turnover (production/consumption) flux of metabolites. GIM3E was used to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIM3E has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/ Contacts: brianjamesschmidt@gmail.com or hyduke@usu.edu Supplementary information: Supplementary information is available at Bioinformatics online. PMID:23975765

  16. The Edinburgh human metabolic network reconstruction and its functional analysis

    PubMed Central

    Ma, Hongwu; Sorokin, Anatoly; Mazein, Alexander; Selkov, Alex; Selkov, Evgeni; Demin, Oleg; Goryanin, Igor

    2007-01-01

    A better understanding of human metabolism and its relationship with diseases is an important task in human systems biology studies. In this paper, we present a high-quality human metabolic network manually reconstructed by integrating genome annotation information from different databases and metabolic reaction information from literature. The network contains nearly 3000 metabolic reactions, which were reorganized into about 70 human-specific metabolic pathways according to their functional relationships. By analysis of the functional connectivity of the metabolites in the network, the bow-tie structure, which was found previously by structure analysis, is reconfirmed. Furthermore, the distribution of the disease related genes in the network suggests that the IN (substrates) subset of the bow-tie structure has more flexibility than other parts. PMID:17882155

  17. Sources of uncertainty in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-03-01

    ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands.

  18. Metabolic allometric scaling model: combining cellular transportation and heat dissipation constraints.

    PubMed

    Shestopaloff, Yuri K

    2016-08-15

    Living organisms need energy to be 'alive'. Energy is produced by the biochemical processing of nutrients, and the rate of energy production is called the metabolic rate. Metabolism is very important from evolutionary and ecological perspectives, and for organismal development and functioning. It depends on different parameters, of which organism mass is considered to be one of the most important. Simple relationships between the mass of organisms and their metabolic rates were empirically discovered by M. Kleiber in 1932. Such dependence is described by a power function, whose exponent is referred to as the allometric scaling coefficient. With the increase of mass, the metabolic rate usually increases more slowly; if mass increases by two times, the metabolic rate increases less than two times. This fact has far-reaching implications for the organization of life. The fundamental biological and biophysical mechanisms underlying this phenomenon are still not well understood. The present study shows that one such primary mechanism relates to transportation of substances, such as nutrients and waste, at a cellular level. Variations in cell size and associated cellular transportation costs explain the known variance of the allometric exponent. The introduced model also includes heat dissipation constraints. The model agrees with experimental observations and reconciles experimental results across different taxa. It ties metabolic scaling to organismal and environmental characteristics, helps to define perspective directions of future research and allows the prediction of allometric exponents based on characteristics of organisms and the environments they live in. PMID:27284070

  19. The Aryl Hydrocarbon Receptor Relays Metabolic Signals to Promote Cellular Regeneration.

    PubMed

    Casado, Fanny L

    2016-01-01

    While sensing the cell environment, the aryl hydrocarbon receptor (AHR) interacts with different pathways involved in cellular homeostasis. This review summarizes evidence suggesting that cellular regeneration in the context of aging and diseases can be modulated by AHR signaling on stem cells. New insights connect orphaned observations into AHR interactions with critical signaling pathways such as WNT to propose a role of this ligand-activated transcription factor in the modulation of cellular regeneration by altering pathways that nurture cellular expansion such as changes in the metabolic efficiency rather than by directly altering cell cycling, proliferation, or cell death. Targeting the AHR to promote regeneration might prove to be a useful strategy to avoid unbalanced disruptions of homeostasis that may promote disease and also provide biological rationale for potential regenerative medicine approaches. PMID:27563312

  20. The Aryl Hydrocarbon Receptor Relays Metabolic Signals to Promote Cellular Regeneration

    PubMed Central

    2016-01-01

    While sensing the cell environment, the aryl hydrocarbon receptor (AHR) interacts with different pathways involved in cellular homeostasis. This review summarizes evidence suggesting that cellular regeneration in the context of aging and diseases can be modulated by AHR signaling on stem cells. New insights connect orphaned observations into AHR interactions with critical signaling pathways such as WNT to propose a role of this ligand-activated transcription factor in the modulation of cellular regeneration by altering pathways that nurture cellular expansion such as changes in the metabolic efficiency rather than by directly altering cell cycling, proliferation, or cell death. Targeting the AHR to promote regeneration might prove to be a useful strategy to avoid unbalanced disruptions of homeostasis that may promote disease and also provide biological rationale for potential regenerative medicine approaches. PMID:27563312

  1. Protease-associated cellular networks in malaria parasite Plasmodium falciparum

    PubMed Central

    2011-01-01

    Background Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species [1-3], providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. Results We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database [4], and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system [5], blood stage microarray experiments [6-8], proteomics [9-12], literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle

  2. A kidney-specific genome-scale metabolic network model for analyzing focal segmental glomerulosclerosis.

    PubMed

    Sohrabi-Jahromi, Salma; Marashi, Sayed-Amir; Kalantari, Shiva

    2016-04-01

    Focal Segmental Glomerulosclerosis (FSGS) is a type of nephrotic syndrome which accounts for 20 and 40 % of such cases in children and adults, respectively. The high prevalence of FSGS makes it the most common primary glomerular disorder causing end-stage renal disease. Although the pathogenesis of this disorder has been widely investigated, the exact mechanism underlying this disease is still to be discovered. Current therapies seek to stop the progression of FSGS and often fail to cure the patients since progression to end-stage renal failure is usually inevitable. In the present work, we use a kidney-specific metabolic network model to study FSGS. The model was obtained by merging two previously published kidney-specific metabolic network models. The validity of the new model was checked by comparing the inactivating reaction genes identified in silico to the list of kidney disease implicated genes. To model the disease state, we used a complete list of FSGS metabolic biomarkers extracted from transcriptome and proteome profiling of patients as well as genetic deficiencies known to cause FSGS. We observed that some specific pathways including chondroitin sulfate degradation, eicosanoid metabolism, keratan sulfate biosynthesis, vitamin B6 metabolism, and amino acid metabolism tend to show variations in FSGS model compared to healthy kidney. Furthermore, we computationally searched for the potential drug targets that can revert the diseased metabolic state to the healthy state. Interestingly, only one drug target, N-acetylgalactosaminidase, was found whose inhibition could alter cellular metabolism towards healthy state. PMID:26923795

  3. FIH Regulates Cellular Metabolism through Hydroxylation of the Deubiquitinase OTUB1

    PubMed Central

    Scholz, Carsten C.; Rodriguez, Javier; Pickel, Christina; Burr, Stephen; Fabrizio, Jacqueline-alba; Nolan, Karen A.; Spielmann, Patrick; Cavadas, Miguel A. S.; Crifo, Bianca; Halligan, Doug N.; Nathan, James A.; Peet, Daniel J.; Wenger, Roland H.; Von Kriegsheim, Alex; Cummins, Eoin P.; Taylor, Cormac T.

    2016-01-01

    The asparagine hydroxylase, factor inhibiting HIF (FIH), confers oxygen-dependence upon the hypoxia-inducible factor (HIF), a master regulator of the cellular adaptive response to hypoxia. Studies investigating whether asparagine hydroxylation is a general regulatory oxygen-dependent modification have identified multiple non-HIF targets for FIH. However, the functional consequences of this outside of the HIF pathway remain unclear. Here, we demonstrate that the deubiquitinase ovarian tumor domain containing ubiquitin aldehyde binding protein 1 (OTUB1) is a substrate for hydroxylation by FIH on N22. Mutation of N22 leads to a profound change in the interaction of OTUB1 with proteins important in cellular metabolism. Furthermore, in cultured cells, overexpression of N22A mutant OTUB1 impairs cellular metabolic processes when compared to wild type. Based on these data, we hypothesize that OTUB1 is a target for functional hydroxylation by FIH. Additionally, we propose that our results provide new insight into the regulation of cellular energy metabolism during hypoxic stress and the potential for targeting hydroxylases for therapeutic benefit. PMID:26752685

  4. Environmental Monitoring using Measurements from Cellular Network Infrastructure

    NASA Astrophysics Data System (ADS)

    David, N.; Gao, O. H.

    2015-12-01

    atmospheric phenomena using current and future planned frequencies of cellular network infrastructure will be introduced.

  5. Cellular and network mechanisms of genetically-determined absence seizures.

    PubMed

    Pinault, Didier; O'Brien, Terence J

    2005-01-01

    The absence epilepsies are characterized by recurrent episodes of loss of consciousness associated with generalized spike-and-wave discharges, with an abrupt onset and offset, in the thalamocortical system. In the absence of detailed neurophysiological studies in humans, many of the concepts regarding the pathophysiological basis of absence seizures are based on studies in animal models. Each of these models has its particular strengths and limitations, and the validity of findings from these models for the human condition cannot be assumed. Consequently, studies in different models have produced some conflicting findings and conclusions. A long-standing concept, based primarily from studies in vivo in cats and in vitro brain slices, is that these paroxysmal electrical events develop suddenly from sleep-related spindle oscillations. More specifically, it is proposed that the initial mechanisms that underlie absence-related spike-and-wave discharges are located in the thalamus, involving especially the thalamic reticular nucleus. By contrast, more recent studies in well-established, genetic models of absence epilepsy in rats demonstrate that spike-and-wave discharges originate in a cortical focus and develop from a wake-related natural corticothalamic sensorimotor rhythm. In this review we integrate recent findings showing that, in both the thalamus and the neocortex, genetically-determined, absence-related spike-and-wave discharges are the manifestation of hypersynchronized, cellular, rhythmic excitations and inhibitions that result from a combination of complex, intrinsic, synaptic mechanisms. Arguments are put forward supporting the hypothesis that layer VI corticothalamic neurons act as 'drivers' in the generation of spike-and-wave discharges in the somatosensory thalamocortical system that result in corticothalamic resonances particularly initially involving the thalamic reticular nucleus. However an important unresolved question is: what are the cellular and

  6. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks.

    PubMed

    Ruppin, Eytan; Papin, Jason A; de Figueiredo, Luis F; Schuster, Stefan

    2010-08-01

    With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. PMID:20692823

  7. Radio Resource Allocation on Complex 4G Wireless Cellular Networks

    NASA Astrophysics Data System (ADS)

    Psannis, Kostas E.

    2015-09-01

    In this article we consider the heuristic algorithm which improves step by step wireless data delivery over LTE cellular networks by using the total transmit power with the constraint on users’ data rates, and the total throughput with the constraints on the total transmit power as well as users’ data rates, which are jointly integrated into a hybrid-layer design framework to perform radio resource allocation for multiple users, and to effectively decide the optimal system parameter such as modulation and coding scheme (MCS) in order to adapt to the varying channel quality. We propose new heuristic algorithm which balances the accessible data rate, the initial data rates of each user allocated by LTE scheduler, the priority indicator which signals delay- throughput- packet loss awareness of the user, and the buffer fullness by achieving maximization of radio resource allocation for multiple users. It is noted that the overall performance is improved with the increase in the number of users, due to multiuser diversity. Experimental results illustrate and validate the accuracy of the proposed methodology.

  8. Cellular nonlinear networks for strike-point localization at JET

    NASA Astrophysics Data System (ADS)

    Arena, P.; Fortuna, L.; Bruno, M.; Vagliasindi, G.; Murari, A.; Andrew, P.; Mazzitelli, G.

    2005-11-01

    At JET, the potential of fast image processing for real-time purposes is thoroughly investigated. Particular attention is devoted to smart sensors based on system on chip technology. The data of the infrared cameras were processed with a chip implementing a cellular nonlinear network (CNN) structure so as to support and complement the magnetic diagnostics in the real-time localization of the strike-point position in the divertor. The circuit consists of two layers of complementary metal-oxide semiconductor components, the first being the sensor and the second implementing the actual CNN. This innovative hardware has made it possible to determine the position of the maximum thermal load with a time resolution of the order of 30 ms. Good congruency has been found with the measurement from the thermocouples in the divertor, proving the potential of the infrared data in locating the region of the maximum thermal load. The results are also confirmed by JET magnetic codes, both those used for the equilibrium reconstructions and those devoted to the identification of the plasma boundary.

  9. Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks.

    PubMed

    Castrillo, Juan I; Oliver, Stephen G

    2016-01-01

    sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease. PMID:26235058

  10. RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations

    PubMed Central

    2012-01-01

    Predicting cellular responses to perturbations is an important task in systems biology. We report a new approach, RELATCH, which uses flux and gene expression data from a reference state to predict metabolic responses in a genetically or environmentally perturbed state. Using the concept of relative optimality, which considers relative flux changes from a reference state, we hypothesize a relative metabolic flux pattern is maintained from one state to another, and that cells adapt to perturbations using metabolic and regulatory reprogramming to preserve this relative flux pattern. This constraint-based approach will have broad utility where predictions of metabolic responses are needed. PMID:23013597

  11. Distinct metabolic network states manifest in the gene expression profiles of pediatric inflammatory bowel disease patients and controls

    PubMed Central

    Knecht, Carolin; Fretter, Christoph; Rosenstiel, Philip; Krawczak, Michael; Hütt, Marc-Thorsten

    2016-01-01

    Information on biological networks can greatly facilitate the function-orientated interpretation of high-throughput molecular data. Genome-wide metabolic network models of human cells, in particular, can be employed to contextualize gene expression profiles of patients with the goal of both, a better understanding of individual etiologies and an educated reclassification of (clinically defined) phenotypes. We analyzed publicly available expression profiles of intestinal tissues from treatment-naive pediatric inflammatory bowel disease (IBD) patients and age-matched control individuals, using a reaction-centric metabolic network derived from the Recon2 model. By way of defining a measure of ‘coherence’, we quantified how well individual patterns of expression changes matched the metabolic network. We observed a bimodal distribution of metabolic network coherence in both patients and controls, albeit at notably different mixture probabilities. Multidimensional scaling analysis revealed a bisectional pattern as well that overlapped widely with the metabolic network-based results. Expression differences driving the observed bimodality were related to cellular transport of thiamine and bile acid metabolism, thereby highlighting the crosstalk between metabolism and other vital pathways. We demonstrated how classical data mining and network analysis can jointly identify biologically meaningful patterns in gene expression data. PMID:27585741

  12. Distinct metabolic network states manifest in the gene expression profiles of pediatric inflammatory bowel disease patients and controls.

    PubMed

    Knecht, Carolin; Fretter, Christoph; Rosenstiel, Philip; Krawczak, Michael; Hütt, Marc-Thorsten

    2016-01-01

    Information on biological networks can greatly facilitate the function-orientated interpretation of high-throughput molecular data. Genome-wide metabolic network models of human cells, in particular, can be employed to contextualize gene expression profiles of patients with the goal of both, a better understanding of individual etiologies and an educated reclassification of (clinically defined) phenotypes. We analyzed publicly available expression profiles of intestinal tissues from treatment-naive pediatric inflammatory bowel disease (IBD) patients and age-matched control individuals, using a reaction-centric metabolic network derived from the Recon2 model. By way of defining a measure of 'coherence', we quantified how well individual patterns of expression changes matched the metabolic network. We observed a bimodal distribution of metabolic network coherence in both patients and controls, albeit at notably different mixture probabilities. Multidimensional scaling analysis revealed a bisectional pattern as well that overlapped widely with the metabolic network-based results. Expression differences driving the observed bimodality were related to cellular transport of thiamine and bile acid metabolism, thereby highlighting the crosstalk between metabolism and other vital pathways. We demonstrated how classical data mining and network analysis can jointly identify biologically meaningful patterns in gene expression data. PMID:27585741

  13. When are two multi-layer cellular neural networks the same?

    PubMed

    Ban, Jung-Chao; Chang, Chih-Hung

    2016-07-01

    This paper aims to characterize whether a multi-layer cellular neural network is of deep architecture; namely, when can an n-layer cellular neural network be replaced by an m-layer cellular neural network for mnetwork is revealed. PMID:27085113

  14. Obesity and cancer: At the crossroads of cellular metabolism and proliferation

    PubMed Central

    O’Rourke, Robert W.

    2014-01-01

    Obesity is associated with an increased risk of cancer. The mechanisms underlying this association include but are not limited to increased systemic inflammation, an anabolic hormonal milieu, and adipocyte-cancer crosstalk, aberrant stimuli that conspire to promote neoplastic transformation. Cellular proliferation is uncoupled from nutrient availability in malignant cells, promoting tumor progression. Elucidation of the mechanisms underlying the obesity-cancer connection will lead to the development of novel metabolism-based agents for cancer prevention and treatment. PMID:25264328

  15. Alginate-Iron Speciation and Its Effect on In Vitro Cellular Iron Metabolism

    PubMed Central

    Horniblow, Richard D.; Dowle, Miriam; Iqbal, Tariq H.; Latunde-Dada, Gladys O.; Palmer, Richard E.

    2015-01-01

    Alginates are a class of biopolymers with known iron binding properties which are routinely used in the fabrication of iron-oxide nanoparticles. In addition, alginates have been implicated in influencing human iron absorption. However, the synthesis of iron oxide nanoparticles employs non-physiological pH conditions and whether nanoparticle formation in vivo is responsible for influencing cellular iron metabolism is unclear. Thus the aims of this study were to determine how alginate and iron interact at gastric-comparable pH conditions and how this influences iron metabolism. Employing a range of spectroscopic techniques under physiological conditions alginate-iron complexation was confirmed and, in conjunction with aberration corrected scanning transmission electron microscopy, nanoparticles were observed. The results infer a nucleation-type model of iron binding whereby alginate is templating the condensation of iron-hydroxide complexes to form iron oxide centred nanoparticles. The interaction of alginate and iron at a cellular level was found to decrease cellular iron acquisition by 37% (p < 0.05) and in combination with confocal microscopy the alginate inhibits cellular iron transport through extracellular iron chelation with the resulting complexes not internalised. These results infer alginate as being useful in the chelation of excess iron, especially in the context of inflammatory bowel disease and colorectal cancer where excess unabsorbed luminal iron is thought to be a driver of disease. PMID:26378798

  16. Redox modulation of cellular metabolism through targeted degradation of signaling proteins by the proteasome

    SciTech Connect

    Squier, Thomas C.

    2006-02-01

    Under conditions of oxidative stress, the 20S proteasome plays a critical role in maintaining cellular homeostasis through the selective degradation of oxidized and damaged proteins. This adaptive stress response is distinct from ubiquitin-dependent pathways in that oxidized proteins are recognized and degraded in an ATP-independent mechanism, which can involve the molecular chaperone Hsp90. Like the regulatory complexes 19S and 11S REG, Hsp90 tightly associates with the 20S proteasome to mediate the recognition of aberrant proteins for degradation. In the case of the calcium signaling protein calmodulin, proteasomal degradation results from the oxidation of a single surface exposed methionine (i.e., Met145); oxidation of the other eight methionines has a minimal effect on the recognition and degradation of calmodulin by the proteasome. Since cellular concentrations of calmodulin are limiting, the targeted degradation of this critical signaling protein under conditions of oxidative stress will result in the downregulation of cellular metabolism, serving as a feedback regulation to diminish the generation of reactive oxygen species. The targeted degradation of critical signaling proteins, such as calmodulin, can function as sensors of oxidative stress to downregulate global rates of metabolism and enhance cellular survival.

  17. Multiphoton microscopy for skin wound healing study in terms of cellular metabolism and collagen regeneration

    NASA Astrophysics Data System (ADS)

    Deka, Gitanjal; Okano, Kazunori; Wu, Wei-Wen; Kao, Fu-Jen

    2014-02-01

    Multiphoton microscopy was employed to study normal skin wound healing in live rats noninvasively. Wound healing is a process involving series of biochemical events. This study evaluates the regeneration of collagen and change in cellular metabolic activity during wound healing in rats, with second harmonic generation (SHG) and fluorescence lifetime imaging microscopy (FLIM), respectively. In eukaryotic cells ATP is the molecule that holds the energy for cellular functioning. Whereas NADH is an electron donor in the metabolic pathways, required to generate ATP. Fluorescence lifetime of NADH free to protein bound ratio was evaluated to determine the relative metabolic activity. The FLIM data were acquired by a TCSPC system using SPCM software and analyzed by SPCImage software. Additionally, polarization resolved SHG signals were also collected to observe the changes in optical birefringence and hence the anisotropy of regenerated collagens from rat wound biopsy samples. Mat lab programming was used to process the data to construct the anisotropy images. Results indicated that, cells involved in healing had higher metabolic activity during the first week of healing, which decreases gradually and become equivalent to normal skin upon healing completes. A net degradation of collagen during the inflammatory phase and net regeneration starting from day 5 were observed in terms of SHG signal intensity change. Polarization resolved SHG imaging of the wound biopsy sample indicates higher value of anisotropy in proliferative phase, from day 4th to 8th, of wound formation; however the anisotropy decreases upon healing.

  18. Mitochondrial DNA Replication Defects Disturb Cellular dNTP Pools and Remodel One-Carbon Metabolism.

    PubMed

    Nikkanen, Joni; Forsström, Saara; Euro, Liliya; Paetau, Ilse; Kohnz, Rebecca A; Wang, Liya; Chilov, Dmitri; Viinamäki, Jenni; Roivainen, Anne; Marjamäki, Päivi; Liljenbäck, Heidi; Ahola, Sofia; Buzkova, Jana; Terzioglu, Mügen; Khan, Nahid A; Pirnes-Karhu, Sini; Paetau, Anders; Lönnqvist, Tuula; Sajantila, Antti; Isohanni, Pirjo; Tyynismaa, Henna; Nomura, Daniel K; Battersby, Brendan J; Velagapudi, Vidya; Carroll, Christopher J; Suomalainen, Anu

    2016-04-12

    Mitochondrial dysfunction affects cellular energy metabolism, but less is known about the consequences for cytoplasmic biosynthetic reactions. We report that mtDNA replication disorders caused by TWINKLE mutations-mitochondrial myopathy (MM) and infantile onset spinocerebellar ataxia (IOSCA)-remodel cellular dNTP pools in mice. MM muscle shows tissue-specific induction of the mitochondrial folate cycle, purine metabolism, and imbalanced and increased dNTP pools, consistent with progressive mtDNA mutagenesis. IOSCA-TWINKLE is predicted to hydrolyze dNTPs, consistent with low dNTP pools and mtDNA depletion in the disease. MM muscle also modifies the cytoplasmic one-carbon cycle, transsulfuration, and methylation, as well as increases glucose uptake and its utilization for de novo serine and glutathione biosynthesis. Our evidence indicates that the mitochondrial replication machinery communicates with cytoplasmic dNTP pools and that upregulation of glutathione synthesis through glucose-driven de novo serine biosynthesis contributes to the metabolic stress response. These results are important for disorders with primary or secondary mtDNA instability and offer targets for metabolic therapy. PMID:26924217

  19. Short- and medium-chain fatty acids in energy metabolism: the cellular perspective.

    PubMed

    Schönfeld, Peter; Wojtczak, Lech

    2016-06-01

    Short- and medium-chain fatty acids (SCFAs and MCFAs), independently of their cellular signaling functions, are important substrates of the energy metabolism and anabolic processes in mammals. SCFAs are mostly generated by colonic bacteria and are predominantly metabolized by enterocytes and liver, whereas MCFAs arise mostly from dietary triglycerides, among them milk and dairy products. A common feature of SCFAs and MCFAs is their carnitine-independent uptake and intramitochondrial activation to acyl-CoA thioesters. Contrary to long-chain fatty acids, the cellular metabolism of SCFAs and MCFAs depends to a lesser extent on fatty acid-binding proteins. SCFAs and MCFAs modulate tissue metabolism of carbohydrates and lipids, as manifested by a mostly inhibitory effect on glycolysis and stimulation of lipogenesis or gluconeogenesis. SCFAs and MCFAs exert no or only weak protonophoric and lytic activities in mitochondria and do not significantly impair the electron transport in the respiratory chain. SCFAs and MCFAs modulate mitochondrial energy production by two mechanisms: they provide reducing equivalents to the respiratory chain and partly decrease efficacy of oxidative ATP synthesis. PMID:27080715

  20. Predict drug-protein interaction in cellular networking.

    PubMed

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-01-01

    Involved with many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, GPCRs (G-protein-coupled receptors) are the most frequent targets for drug development: over 50% of all prescription drugs currently on the market are actually acting by targeting GPCRs directly or indirectly. Found in every living thing and nearly all cells, ion channels play crucial roles for many vital functions in life, such as heartbeat, sensory transduction, and central nervous system response. Their dysfunction may have significant impact to human health, and hence ion channels are deemed as "the next GPCRs". To develop GPCR-targeting or ion-channel-targeting drugs, the first important step is to identify the interactions between potential drug compounds with the two kinds of protein receptors in the cellular networking. In this minireview, we are to introduce two predictors. One is called iGPCR-Drug accessible at http://www.jci-bioinfo.cn/iGPCR-Drug/; the other called iCDI-PseFpt at http://www.jci-bioinfo.cn/iCDI-PseFpt. The former is for identifying the interactions of drug compounds with GPCRs; while the latter for that with ion channels. In both predictors, the drug compound was formulated by the two-dimensional molecular fingerprint, and the protein receptor by the pseudo amino acid composition generated with the grey model theory, while the operation engine was the fuzzy K-nearest neighbor algorithm. For the convenience of most experimental pharmaceutical and medical scientists, a step-bystep guide is provided on how to use each of the two web-servers to get the desired results without the need to follow the complicated mathematics involved originally for their establishment. PMID:23889048

  1. Green pathways: Metabolic network analysis of plant systems.

    PubMed

    Dersch, Lisa Maria; Beckers, Veronique; Wittmann, Christoph

    2016-03-01

    Metabolic engineering of plants with enhanced crop yield and value-added compositional traits is particularly challenging as they probably exhibit the highest metabolic network complexity of all living organisms. Therefore, approaches of plant metabolic network analysis, which can provide systems-level understanding of plant physiology, appear valuable as guidance for plant metabolic engineers. Strongly supported by the sequencing of plant genomes, a number of different experimental and computational methods have emerged in recent years to study plant systems at various levels: from heterotrophic cell cultures to autotrophic entire plants. The present review presents a state-of-the-art toolbox for plant metabolic network analysis. Among the described approaches are different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes. The fundamental principles of these techniques, the required data input and the obtained flux information are enriched by technical advices, specific to plants. In addition, pioneering and high-impacting findings of plant metabolic network analysis highlight the potential of the field. PMID:26704307

  2. Computational model of cellular metabolic dynamics: effect of insulin on glucose disposal in human skeletal muscle

    PubMed Central

    Li, Yanjun; Solomon, Thomas P. J.; Haus, Jacob M.; Saidel, Gerald M.; Cabrera, Marco E.

    2010-01-01

    Identifying the mechanisms by which insulin regulates glucose metabolism in skeletal muscle is critical to understanding the etiology of insulin resistance and type 2 diabetes. Our knowledge of these mechanisms is limited by the difficulty of obtaining in vivo intracellular data. To quantitatively distinguish significant transport and metabolic mechanisms from limited experimental data, we developed a physiologically based, multiscale mathematical model of cellular metabolic dynamics in skeletal muscle. The model describes mass transport and metabolic processes including distinctive processes of the cytosol and mitochondria. The model simulated skeletal muscle metabolic responses to insulin corresponding to human hyperinsulinemic-euglycemic clamp studies. Insulin-mediated rate of glucose disposal was the primary model input. For model validation, simulations were compared with experimental data: intracellular metabolite concentrations and patterns of glucose disposal. Model variations were simulated to investigate three alternative mechanisms to explain insulin enhancements: Model 1 (M.1), simple mass action; M.2, insulin-mediated activation of key metabolic enzymes (i.e., hexokinase, glycogen synthase, pyruvate dehydrogenase); or M.3, parallel activation by a phenomenological insulin-mediated intracellular signal that modifies reaction rate coefficients. These simulations indicated that models M.1 and M.2 were not sufficient to explain the experimentally measured metabolic responses. However, by application of mechanism M.3, the model predicts metabolite concentration changes and glucose partitioning patterns consistent with experimental data. The reaction rate fluxes quantified by this detailed model of insulin/glucose metabolism provide information that can be used to evaluate the development of type 2 diabetes. PMID:20332360

  3. Design mobile satellite system architecture as an integral part of the cellular access digital network

    NASA Technical Reports Server (NTRS)

    Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

    1988-01-01

    The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

  4. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    PubMed Central

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  5. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    PubMed

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  6. MicroRNAs and oncogenic transcriptional regulatory networks controlling metabolic reprogramming in cancers.

    PubMed

    Pinweha, Pannapa; Rattanapornsompong, Khanti; Charoensawan, Varodom; Jitrapakdee, Sarawut

    2016-01-01

    Altered cellular metabolism is a fundamental adaptation of cancer during rapid proliferation as a result of growth factor overstimulation. We review different pathways involving metabolic alterations in cancers including aerobic glycolysis, pentose phosphate pathway, de novo fatty acid synthesis, and serine and glycine metabolism. Although oncoproteins, c-MYC, HIF1α and p53 are the major drivers of this metabolic reprogramming, post-transcriptional regulation by microRNAs (miR) also plays an important role in finely adjusting the requirement of the key metabolic enzymes underlying this metabolic reprogramming. We also combine the literature data on the miRNAs that potentially regulate 40 metabolic enzymes responsible for metabolic reprogramming in cancers, with additional miRs from computational prediction. Our analyses show that: (1) a metabolic enzyme is frequently regulated by multiple miRs, (2) confidence scores from prediction algorithms might be useful to help narrow down functional miR-mRNA interaction, which might be worth further experimental validation. By combining known and predicted interactions of oncogenic transcription factors (TFs) (c-MYC, HIF1α and p53), sterol regulatory element binding protein 1 (SREBP1), 40 metabolic enzymes, and regulatory miRs we have established one of the first reference maps for miRs and oncogenic TFs that regulate metabolic reprogramming in cancers. The combined network shows that glycolytic enzymes are linked to miRs via p53, c-MYC, HIF1α, whereas the genes in serine, glycine and one carbon metabolism are regulated via the c-MYC, as well as other regulatory organization that cannot be observed by investigating individual miRs, TFs, and target genes. PMID:27358718

  7. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii.

    PubMed

    Gargouri, Mahmoud; Park, Jeong-Jin; Holguin, F Omar; Kim, Min-Jeong; Wang, Hongxia; Deshpande, Rahul R; Shachar-Hill, Yair; Hicks, Leslie M; Gang, David R

    2015-08-01

    Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism. PMID:26022256

  8. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii

    PubMed Central

    Gargouri, Mahmoud; Park, Jeong-Jin; Holguin, F. Omar; Kim, Min-Jeong; Wang, Hongxia; Deshpande, Rahul R.; Shachar-Hill, Yair; Hicks, Leslie M.; Gang, David R.

    2015-01-01

    Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism. PMID:26022256

  9. Metabolic Network Constrains Gene Regulation of C4 Photosynthesis: The Case of Maize

    PubMed Central

    Robaina-Estévez, Semidán; Nikoloski, Zoran

    2016-01-01

    Engineering C3 plants to increase their efficiency of carbon fixation as well as of nitrogen and water use simultaneously may be facilitated by understanding the mechanisms that underpin the C4 syndrome. Existing experimental studies have indicated that the emergence of the C4 syndrome requires co-ordination between several levels of cellular organization, from gene regulation to metabolism, across two co-operating cell systems—mesophyll and bundle sheath cells. Yet, determining the extent to which the structure of the C4 plant metabolic network may constrain gene expression remains unclear, although it will provide an important consideration in engineering C4 photosynthesis in C3 plants. Here, we utilize flux coupling analysis with the second-generation maize metabolic models to investigate the correspondence between metabolic network structure and transcriptomic phenotypes along the maize leaf gradient. The examined scenarios with publically available data from independent experiments indicate that the transcriptomic programs of the two cell types are co-ordinated, quantitatively and qualitatively, due to the presence of coupled metabolic reactions in specific metabolic pathways. Taken together, our study demonstrates that precise quantitative coupling will have to be achieved in order to ensure a successfully engineered transition from C3 to C4 crops. PMID:26903529

  10. Metabolic Network Constrains Gene Regulation of C4 Photosynthesis: The Case of Maize.

    PubMed

    Robaina-Estévez, Semidán; Nikoloski, Zoran

    2016-05-01

    Engineering C3 plants to increase their efficiency of carbon fixation as well as of nitrogen and water use simultaneously may be facilitated by understanding the mechanisms that underpin the C4 syndrome. Existing experimental studies have indicated that the emergence of the C4 syndrome requires co-ordination between several levels of cellular organization, from gene regulation to metabolism, across two co-operating cell systems-mesophyll and bundle sheath cells. Yet, determining the extent to which the structure of the C4 plant metabolic network may constrain gene expression remains unclear, although it will provide an important consideration in engineering C4 photosynthesis in C3 plants. Here, we utilize flux coupling analysis with the second-generation maize metabolic models to investigate the correspondence between metabolic network structure and transcriptomic phenotypes along the maize leaf gradient. The examined scenarios with publically available data from independent experiments indicate that the transcriptomic programs of the two cell types are co-ordinated, quantitatively and qualitatively, due to the presence of coupled metabolic reactions in specific metabolic pathways. Taken together, our study demonstrates that precise quantitative coupling will have to be achieved in order to ensure a successfully engineered transition from C3 to C4 crops. PMID:26903529

  11. Maintenance of mouse hematopoietic stem cells ex vivo by reprogramming cellular metabolism.

    PubMed

    Liu, Xia; Zheng, Hong; Yu, Wen-Mei; Cooper, Todd M; Bunting, Kevin D; Qu, Cheng-Kui

    2015-03-01

    The difficulty in maintaining the reconstituting capabilities of hematopoietic stem cells (HSCs) in culture outside of the bone marrow microenvironment has severely limited their utilization for clinical therapy. This hurdle is largely due to the differentiation of long-term stem cells. Emerging evidence suggests that energy metabolism plays an important role in coordinating HSC self-renewal and differentiation. Here, we show that treatment with alexidine dihydrochloride, an antibiotic and a selective inhibitor of the mitochondrial phosphatase Ptpmt1, which is crucial for the differentiation of HSCs, reprogrammed cellular metabolism from mitochondrial aerobic metabolism to glycolysis, resulting in a remarkable preservation of long-term HSCs ex vivo in part through hyperactivation of adenosine 5'-monophosphate-activated protein kinase (AMPK). In addition, inhibition of mitochondrial metabolism and activation of AMPK by metformin, a diabetes drug, also decreased differentiation and helped maintain stem cells in culture. Thus, manipulating metabolic pathways represents an effective new strategy for ex vivo maintenance of HSCs. PMID:25593337

  12. Mitochondrial proteomics on human fibroblasts for identification of metabolic imbalance and cellular stress

    PubMed Central

    Palmfeldt, Johan; Vang, Søren; Stenbroen, Vibeke; Pedersen, Christina B; Christensen, Jane H; Bross, Peter; Gregersen, Niels

    2009-01-01

    Background Mitochondrial proteins are central to various metabolic activities and are key regulators of apoptosis. Disturbance of mitochondrial proteins is therefore often associated with disease. Large scale protein data are required to capture the mitochondrial protein levels and mass spectrometry based proteomics is suitable for generating such data. To study the relative quantities of mitochondrial proteins in cells from cultivated human skin fibroblasts we applied a proteomic method based on nanoLC-MS/MS analysis of iTRAQ-labeled peptides. Results When fibroblast cultures were exposed to mild metabolic stress – by cultivation in galactose medium- the amount of mitochondria appeared to be maintained whereas the levels of individual proteins were altered. Proteins of respiratory chain complex I and IV were increased together with NAD+-dependent isocitrate dehydrogenase of the citric acid cycle illustrating cellular strategies to cope with altered energy metabolism. Furthermore, quantitative protein data, with a median standard error below 6%, were obtained for the following mitochondrial pathways: fatty acid oxidation, citric acid cycle, respiratory chain, antioxidant systems, amino acid metabolism, mitochondrial translation, protein quality control, mitochondrial morphology and apoptosis. Conclusion The robust analytical platform in combination with a well-defined compendium of mitochondrial proteins allowed quantification of single proteins as well as mapping of entire pathways. This enabled characterization of the interplay between metabolism and stress response in human cells exposed to mild stress. PMID:19476632

  13. [EFFECT OF LIPOPOLYSACCHARIDE ON NEUTRAL LIPID METABOLISM AND CELLULAR ENERGETICS IN FROG URINARY BLADDER EPITHELIAL CELLS].

    PubMed

    Fedorova, E V; Fock, E M; Braylovskaya, I V; Bachteeva, V T; Lavrova, E A; Zabelinskiĭ, S A; Parnova, R G

    2015-09-01

    It was shown previously that colonization of the frog urinary bladder by gram-negative bacteria leads to decreased ability of antidiuretic hormone to reabsorb water from the urinary bladder (Fock et al. J. Exp. Zool., 2013, 319A: 487-494). In the present work performed on epithelial cells isolated from the frog urinary bladder the influence of E. coli lipopolysaccharide (LPS) on neutral lipid metabolism and cellular energetics was studied. It was shown that incubation of cells with LPS led to decrease of fatty acids oxidation and to retention of triacylglycerols (TAG) followed by an increase of the cytoplasmic lipid droplets content and cellular amount of TAG. Fatty acid composition of TAG was not changed under LPS. LPS did not alter mitochondrial membrane potential, however, LPS decreased oxygen consumption rate both in basal and uncoupling conditions. Cellular ATP production was also reduced in the presence of LPS. The data obtained indicate that a decreased ability of antidiuretic hormone to reabsorb water from the urinary bladder induced by bacterial pathogens could be related to inhibition of fatty acids oxidation and impaired energy metabolism. PMID:26672162

  14. A novel alkyne cholesterol to trace cellular cholesterol metabolism and localization.

    PubMed

    Hofmann, Kristina; Thiele, Christoph; Schött, Hans-Frieder; Gaebler, Anne; Schoene, Mario; Kiver, Yuriy; Friedrichs, Silvia; Lütjohann, Dieter; Kuerschner, Lars

    2014-03-01

    Cholesterol is an important lipid of mammalian cells and plays a fundamental role in many biological processes. Its concentration in the various cellular membranes differs and is tightly regulated. Here, we present a novel alkyne cholesterol analog suitable for tracing both cholesterol metabolism and localization. This probe can be detected by click chemistry employing various reporter azides. Alkyne cholesterol is accepted by cellular enzymes from different biological species (Brevibacterium, yeast, rat, human) and these enzymes include cholesterol oxidases, hydroxylases, and acyl transferases that generate the expected metabolites in in vitro and in vivo assays. Using fluorescence microscopy, we studied the distribution of cholesterol at subcellular resolution, detecting the lipid in the Golgi and at the plasma membrane, but also in the endoplasmic reticulum and mitochondria. In summary, alkyne cholesterol represents a versatile, sensitive, and easy-to-use tool for tracking cellular cholesterol metabolism and localization as it allows for manifold detection methods including mass spectrometry, thin-layer chromatography/fluorography, and fluorescence microscopy. PMID:24334219

  15. Co-evolutionary networks of genes and cellular processes across fungal species

    PubMed Central

    Tuller, Tamir; Kupiec, Martin; Ruppin, Eytan

    2009-01-01

    Background The introduction of measures such as evolutionary rate and propensity for gene loss have significantly advanced our knowledge of the evolutionary history and selection forces acting upon individual genes and cellular processes. Results We present two new measures, the 'relative evolutionary rate pattern' (rERP), which records the relative evolutionary rates of conserved genes across the different branches of a species' phylogenetic tree, and the 'copy number pattern' (CNP), which quantifies the rate of gene loss of less conserved genes. Together, these measures yield a high-resolution study of the co-evolution of genes in 9 fungal species, spanning 3,540 sets of orthologs. We find that the evolutionary tempo of conserved genes varies in different evolutionary periods. The co-evolution of genes' Gene Ontology categories exhibits a significant correlation with their functional distance in the Gene Ontology hierarchy, but not with their location on chromosomes, showing that cellular functions are a more important driving force in gene co-evolution than their chromosomal proximity. Two fundamental patterns of co-evolution of conserved genes, cooperative and reciprocal, are identified; only genes co-evolving cooperatively functionally back each other up. The co-evolution of conserved and less conserved genes exhibits both commonalities and differences; DNA metabolism is positively correlated with nuclear traffic, transcription processes and vacuolar biology in both analyses. Conclusions Overall, this study charts the first global network view of gene co-evolution in fungi. The future application of the approach presented here to other phylogenetic trees holds much promise in characterizing the forces that shape cellular co-evolution. PMID:19416514

  16. An integrated text mining framework for metabolic interaction network reconstruction.

    PubMed

    Patumcharoenpol, Preecha; Doungpan, Narumol; Meechai, Asawin; Shen, Bairong; Chan, Jonathan H; Vongsangnak, Wanwipa

    2016-01-01

    Text mining (TM) in the field of biology is fast becoming a routine analysis for the extraction and curation of biological entities (e.g., genes, proteins, simple chemicals) as well as their relationships. Due to the wide applicability of TM in situations involving complex relationships, it is valuable to apply TM to the extraction of metabolic interactions (i.e., enzyme and metabolite interactions) through metabolic events. Here we present an integrated TM framework containing two modules for the extraction of metabolic events (Metabolic Event Extraction module-MEE) and for the construction of a metabolic interaction network (Metabolic Interaction Network Reconstruction module-MINR). The proposed integrated TM framework performed well based on standard measures of recall, precision and F-score. Evaluation of the MEE module using the constructed Metabolic Entities (ME) corpus yielded F-scores of 59.15% and 48.59% for the detection of metabolic events for production and consumption, respectively. As for the testing of the entity tagger for Gene and Protein (GP) and metabolite with the test corpus, the obtained F-score was greater than 80% for the Superpathway of leucine, valine, and isoleucine biosynthesis. Mapping of enzyme and metabolite interactions through network reconstruction showed a fair performance for the MINR module on the test corpus with F-score >70%. Finally, an application of our integrated TM framework on a big-scale data (i.e., EcoCyc extraction data) for reconstructing a metabolic interaction network showed reasonable precisions at 69.93%, 70.63% and 46.71% for enzyme, metabolite and enzyme-metabolite interaction, respectively. This study presents the first open-source integrated TM framework for reconstructing a metabolic interaction network. This framework can be a powerful tool that helps biologists to extract metabolic events for further reconstruction of a metabolic interaction network. The ME corpus, test corpus, source code, and virtual

  17. An integrated text mining framework for metabolic interaction network reconstruction

    PubMed Central

    Doungpan, Narumol; Meechai, Asawin; Shen, Bairong

    2016-01-01

    Text mining (TM) in the field of biology is fast becoming a routine analysis for the extraction and curation of biological entities (e.g., genes, proteins, simple chemicals) as well as their relationships. Due to the wide applicability of TM in situations involving complex relationships, it is valuable to apply TM to the extraction of metabolic interactions (i.e., enzyme and metabolite interactions) through metabolic events. Here we present an integrated TM framework containing two modules for the extraction of metabolic events (Metabolic Event Extraction module—MEE) and for the construction of a metabolic interaction network (Metabolic Interaction Network Reconstruction module—MINR). The proposed integrated TM framework performed well based on standard measures of recall, precision and F-score. Evaluation of the MEE module using the constructed Metabolic Entities (ME) corpus yielded F-scores of 59.15% and 48.59% for the detection of metabolic events for production and consumption, respectively. As for the testing of the entity tagger for Gene and Protein (GP) and metabolite with the test corpus, the obtained F-score was greater than 80% for the Superpathway of leucine, valine, and isoleucine biosynthesis. Mapping of enzyme and metabolite interactions through network reconstruction showed a fair performance for the MINR module on the test corpus with F-score >70%. Finally, an application of our integrated TM framework on a big-scale data (i.e., EcoCyc extraction data) for reconstructing a metabolic interaction network showed reasonable precisions at 69.93%, 70.63% and 46.71% for enzyme, metabolite and enzyme–metabolite interaction, respectively. This study presents the first open-source integrated TM framework for reconstructing a metabolic interaction network. This framework can be a powerful tool that helps biologists to extract metabolic events for further reconstruction of a metabolic interaction network. The ME corpus, test corpus, source code, and

  18. Creatine transporter deficiency leads to increased whole body and cellular metabolism.

    PubMed

    Perna, Marla K; Kokenge, Amanda N; Miles, Keila N; Udobi, Kenea C; Clark, Joseph F; Pyne-Geithman, Gail J; Khuchua, Zaza; Skelton, Matthew R

    2016-08-01

    Creatine (Cr) is a guanidino compound required for rapid replenishment of ATP in cells with a high-energy demand. In humans, mutations in the Cr transporter (CRT;SLC6A8) prevent Cr entry into tissue and result in a significant intellectual impairment, epilepsy, and aphasia. The lack of Cr on both the whole body and cellular metabolism was evaluated in Crt knockout (Crt (-/y) ) mice, a high-fidelity model of human CRT deficiency. Crt (-/y) mice have reduced body mass and, however, show a twofold increase in body fat. There was increased energy expenditure in a home cage environment and during treadmill running in Crt (-/y) mice. Consistent with the increases in the whole-body metabolic function, Crt (-/y) mice show increased cellular metabolism as well. Mitochondrial respiration increased in skeletal muscle fibers and hippocampal lysates from Crt (-/y) mice. In addition, Crt (-/y) mice had increased citrate synthase activity, suggesting a higher number of mitochondria instead of an increase in mitochondrial activity. To determine if the increase in respiration was due to increased mitochondrial numbers, we measured oxygen consumption in an equal number of mitochondria from Crt (+/y) and Crt (-/y) mice. There were no changes in mitochondrial respiration when normalized to mitochondrial number, suggesting that the increase in respiration observed could be to higher mitochondrial content in Crt (-/y) mice. PMID:27401086

  19. Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance

    NASA Astrophysics Data System (ADS)

    Thomas, Alex; Rahmanian, Sorena; Bordbar, Aarash; Palsson, Bernhard Ø.; Jamshidi, Neema

    2014-01-01

    Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies.

  20. Computational identification of obligatorily autocatalytic replicators embedded in metabolic networks

    PubMed Central

    Kun, Ádám; Papp, Balázs; Szathmáry, Eörs

    2008-01-01

    Background If chemical A is necessary for the synthesis of more chemical A, then A has the power of replication (such systems are known as autocatalytic systems). We provide the first systems-level analysis searching for small-molecular autocatalytic components in the metabolisms of diverse organisms, including an inferred minimal metabolism. Results We find that intermediary metabolism is invariably autocatalytic for ATP. Furthermore, we provide evidence for the existence of additional, organism-specific autocatalytic metabolites in the forms of coenzymes (NAD+, coenzyme A, tetrahydrofolate, quinones) and sugars. Although the enzymatic reactions of a number of autocatalytic cycles are present in most of the studied organisms, they display obligatorily autocatalytic behavior in a few networks only, hence demonstrating the need for a systems-level approach to identify metabolic replicators embedded in large networks. Conclusion Metabolic replicators are apparently common and potentially both universal and ancestral: without their presence, kick-starting metabolic networks is impossible, even if all enzymes and genes are present in the same cell. Identification of metabolic replicators is also important for attempts to create synthetic cells, as some of these autocatalytic molecules will presumably be needed to be added to the system as, by definition, the system cannot synthesize them without their initial presence. PMID:18331628

  1. Metabolic networks evolve towards states of maximum entropy production.

    PubMed

    Unrean, Pornkamol; Srienc, Friedrich

    2011-11-01

    A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. PMID:21903175

  2. Traffic Driven Analysis of Cellular and WiFi Networks

    ERIC Educational Resources Information Center

    Paul, Utpal Kumar

    2012-01-01

    Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

  3. Current concepts in chronic inflammatory diseases: Interactions between microbes, cellular metabolism, and inflammation.

    PubMed

    Garn, Holger; Bahn, Sabine; Baune, Bernhard T; Binder, Elisabeth B; Bisgaard, Hans; Chatila, Talal A; Chavakis, Triantafyllos; Culmsee, Carsten; Dannlowski, Udo; Gay, Steffen; Gern, James; Haahtela, Tari; Kircher, Tilo; Müller-Ladner, Ulf; Neurath, Markus F; Preissner, Klaus T; Reinhardt, Christoph; Rook, Graham; Russell, Shannon; Schmeck, Bernd; Stappenbeck, Thaddeus; Steinhoff, Ulrich; van Os, Jim; Weiss, Scott; Zemlin, Michael; Renz, Harald

    2016-07-01

    Recent research indicates that chronic inflammatory diseases, including allergies and autoimmune and neuropsychiatric diseases, share common pathways of cellular and molecular dysregulation. It was the aim of the International von-Behring-Röntgen Symposium (October 16-18, 2014, in Marburg, Germany) to discuss recent developments in this field. These include a concept of biodiversity; the contribution of urbanization, lifestyle factors, and nutrition (eg, vitamin D); and new mechanisms of metabolic and immune dysregulation, such as extracellular and intracellular RNAs and cellular and mitochondrial stress. Epigenetic mechanisms contribute further to altered gene expression and therefore to the development of chronic inflammation. These novel findings provide the foundation for further development of preventive and therapeutic strategies. PMID:27373325

  4. Mammalian Mss51 is a skeletal muscle-specific gene modulating cellular metabolism

    PubMed Central

    Moyer, Adam L.; Wagner, Kathryn R.

    2015-01-01

    Background The transforming growth factor β (TGF-β) signaling pathways modulate skeletal muscle growth, regeneration, and cellular metabolism. Several recent gene expression studies have shown that inhibition of myostatin and TGF-β1 signaling consistently leads to a significant reduction in expression of Mss51, also named Zmynd17. The function of mammalian Mss51 is unknown although a putative homolog in yeast is a mitochondrial translational activator. Objective The objective of this work was to characterize mammalian Mss51. Methods Quantitative RT-PCR and immunoblot of subcellular fractionation were used to determine expression patterns and localization of Mss51. The CRISPR/Cas9 system was used to reduce expression of Mss51 in C2C12 myoblasts and the function of Mss51 was evaluated in assays of proliferation, differentiation and cellular metabolism. Results Mss51 was predominantly expressed in skeletal muscle and in those muscles dominated by fast-twitch fibers. In vitro, its expression was upregulated upon differentiation of C2C12 myoblasts into myotubes. Expression of Mss51 was modulated in response to altered TGF-β family signaling. In human muscle, Mss51 localized to the mitochondria. Its genetic disruption resulted in increased levels of cellular ATP, β-oxidation, glycolysis, and oxidative phosphorylation. Conclusions Mss51 is a novel, skeletal muscle-specific gene and a key target of myostatin and TGF-β1 signaling. Unlike myostatin, TGF-β1 and IGF-1, Mss51 does not regulate myoblast proliferation or differentiation. Rather, Mss51 appears to be one of the effectors of these growth factors on metabolic processes including fatty acid oxidation, glycolysis and oxidative phosphorylation. PMID:26634192

  5. Fast Reconstruction of Compact Context-Specific Metabolic Network Models

    PubMed Central

    Sauter, Thomas

    2014-01-01

    Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present fastcore, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. fastcore takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and fastcore iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a rival method. Given its simplicity and its excellent performance, fastcore can form the backbone of many future metabolic network reconstruction algorithms. PMID:24453953

  6. Fast reconstruction of compact context-specific metabolic network models.

    PubMed

    Vlassis, Nikos; Pacheco, Maria Pires; Sauter, Thomas

    2014-01-01

    Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present fastcore, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. fastcore takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and fastcore iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a rival method. Given its simplicity and its excellent performance, fastcore can form the backbone of many future metabolic network reconstruction algorithms. PMID:24453953

  7. Phylogeny of metabolic networks: a spectral graph theoretical approach.

    PubMed

    Deyasi, Krishanu; Banerjee, Anirban; Deb, Bony

    2015-10-01

    Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms. PMID:26564980

  8. 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

  9. 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.

  10. Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli.

    PubMed

    Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem; O'Brien, Edward J; Szubin, Richard; Palsson, Bernhard O

    2014-01-01

    The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response to iron availability using genome-wide measurements. Integrative data analysis reveals that a total of 81 genes in 42 transcription units are directly regulated by three different modes of Fur regulation, including apo- and holo-Fur activation and holo-Fur repression. We show that Fur connects iron transport and utilization enzymes with negative-feedback loop pairs for iron homeostasis. In addition, direct involvement of Fur in the regulation of DNA synthesis, energy metabolism and biofilm development is found. These results show how Fur exhibits a comprehensive regulatory role affecting many fundamental cellular processes linked to iron metabolism in order to coordinate the overall response of E. coli to iron availability. PMID:25222563

  11. Effects of cellular homeostatic intrinsic plasticity on dynamical and computational properties of biological recurrent neural networks.

    PubMed

    Naudé, Jérémie; Cessac, Bruno; Berry, Hugues; Delord, Bruno

    2013-09-18

    Homeostatic intrinsic plasticity (HIP) is a ubiquitous cellular mechanism regulating neuronal activity, cardinal for the proper functioning of nervous systems. In invertebrates, HIP is critical for orchestrating stereotyped activity patterns. The functional impact of HIP remains more obscure in vertebrate networks, where higher order cognitive processes rely on complex neural dynamics. The hypothesis has emerged that HIP might control the complexity of activity dynamics in recurrent networks, with important computational consequences. However, conflicting results about the causal relationships between cellular HIP, network dynamics, and computational performance have arisen from machine-learning studies. Here, we assess how cellular HIP effects translate into collective dynamics and computational properties in biological recurrent networks. We develop a realistic multiscale model including a generic HIP rule regulating the neuronal threshold with actual molecular signaling pathways kinetics, Dale's principle, sparse connectivity, synaptic balance, and Hebbian synaptic plasticity (SP). Dynamic mean-field analysis and simulations unravel that HIP sets a working point at which inputs are transduced by large derivative ranges of the transfer function. This cellular mechanism ensures increased network dynamics complexity, robust balance with SP at the edge of chaos, and improved input separability. Although critically dependent upon balanced excitatory and inhibitory drives, these effects display striking robustness to changes in network architecture, learning rates, and input features. Thus, the mechanism we unveil might represent a ubiquitous cellular basis for complex dynamics in neural networks. Understanding this robustness is an important challenge to unraveling principles underlying self-organization around criticality in biological recurrent neural networks. PMID:24048833

  12. A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

    PubMed Central

    2011-01-01

    Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191

  13. Metabolic Network Prediction of Drug Side Effects.

    PubMed

    Shaked, Itay; Oberhardt, Matthew A; Atias, Nir; Sharan, Roded; Ruppin, Eytan

    2016-03-23

    Drug side effects levy a massive cost on society through drug failures, morbidity, and mortality cases every year, and their early detection is critically important. Here, we describe the array of model-based phenotype predictors (AMPP), an approach that leverages medical informatics resources and a human genome-scale metabolic model (GSMM) to predict drug side effects. AMPP is substantially predictive (AUC > 0.7) for >70 drug side effects, including very serious ones such as interstitial nephritis and extrapyramidal disorders. We evaluate AMPP's predictive signal through cross-validation, comparison across multiple versions of a side effects database, and co-occurrence analysis of drug side effect associations in scientific abstracts (hypergeometric p value = 2.2e-40). AMPP outperforms a previous biochemical structure-based method in predicting metabolically based side effects (aggregate AUC = 0.65 versus 0.59). Importantly, AMPP enables the identification of key metabolic reactions and biomarkers that are predictive of specific side effects. Taken together, this work lays a foundation for future detection of metabolically grounded side effects during early stages of drug development. PMID:27135366

  14. MaizeCyc: Metabolic networks in maize

    Technology Transfer Automated Retrieval System (TEKTRAN)

    MaizeCyc is a catalog of known and predicted metabolic and transport pathways that enables plant researchers to graphically represent the metabolome of maize (Zea mays), thereby supporting integrated systems-biology analysis. Supported analyses include molecular and genetic/phenotypic profiling (e.g...

  15. Efficient Reconstruction of Predictive Consensus Metabolic Network Models

    PubMed Central

    Martins dos Santos, Vitor A. P.; Stelling, Joerg

    2016-01-01

    Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions. PMID:27563720

  16. Efficient Reconstruction of Predictive Consensus Metabolic Network Models.

    PubMed

    van Heck, Ruben G A; Ganter, Mathias; Martins Dos Santos, Vitor A P; Stelling, Joerg

    2016-08-01

    Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions. PMID:27563720

  17. Cellular lead toxicity and metabolism in primary and clonal osteoblastic bone cells

    SciTech Connect

    Long, G.J.; Rosen, J.F.; Pounds, J.G. )

    1990-02-01

    A knowledge of bone lead metabolism is critical for understanding the toxicological importance of bone lead, as a toxicant both to bone cells and to soft tissues of the body, as lead is mobilized from large reservoirs in hard tissues. To further understand the processes that mediate metabolism of lead in bone, it is necessary to determine lead metabolism at the cellular level. Experiments were conducted to determine the intracellular steady-state {sup 210}Pb kinetics in cultures of primary and clonal osteoblastic bone cells. Osteoblastic bone cells obtained by sequential collagenase digestion of mouse calvaria or rat osteosarcoma (ROS 17/2.8) cells were labeled with {sup 210}Pb as 5 microM lead acetate for 20 hr, and kinetic parameters were determined by measuring the efflux of {sup 210}Pb from the cells over a {sup 210}-min period. The intracellular metabolism of {sup 210}Pb was characterized by three kinetic pools of {sup 210}Pb in both cell types. Although the values of these parameters differed between the primary osteoblastic cells and ROS cells, the profile of {sup 210}Pb was remarkably similar in both cell types. Both types exhibited one large, slowly exchanging pool (S3), indicative of mitochondrial lead. These data show that primary osteoblastic bone cells and ROS cells exhibit similar steady-state lead kinetics, and intracellular lead distribution. These data also establish a working model of lead kinetics in osteoblastic bone cells and now permit an integrated view of lead kinetics in bone.

  18. Cellular Metabolic Activity and the Oxygen and Hydrogen Stable Isotope Composition of Intracellular Water and Metabolites

    NASA Astrophysics Data System (ADS)

    Kreuzer-Martin, H. W.; Hegg, E. L.

    2008-12-01

    Intracellular water is an important pool of oxygen and hydrogen atoms for biosynthesis. Intracellular water is usually assumed to be isotopically identical to extracellular water, but an unexpected experimental result caused us to question this assumption. Heme O isolated from Escherichia coli cells grown in 95% H218O contained only a fraction of the theoretical value of labeled oxygen at a position where the O atom was known to be derived from water. In fact, fewer than half of the oxygen atoms were labeled. In an effort to explain this surprising result, we developed a method to determine the isotope ratios of intracellular water in cultured cells. The results of our experiments showed that during active growth, up to 70% of the oxygen atoms and 50% of the hydrogen atoms in the intracellular water of E. coli are generated during metabolism and can be isotopically distinct from extracellular water. The fraction of isotopically distinct atoms was substantially less in stationary phase and chilled cells, consistent with our hypothesis that less metabolically-generated water would be present in cells with lower metabolic activity. Our results were consistent with and explained the result of the heme O labeling experiment. Only about 40% of the O atoms on the heme O molecule were labeled because, presumably, only about 40% of the water inside the cells was 18O water that had diffused in from the culture medium. The rest of the intracellular water contained 16O atoms derived from either nutrients or atmospheric oxygen. To test whether we could also detect metabolically-derived hydrogen atoms in cellular constituents, we isolated fatty acids from log-phase and stationary phase E. coli and determined the H isotope ratios of individual fatty acids. The results of these experiments showed that environmental water contributed more H atoms to fatty acids isolated in stationary phase than to the same fatty acids isolated from log-phase cells. Stable isotope analyses of

  19. Cues for cellular assembly of vascular elastin networks

    NASA Astrophysics Data System (ADS)

    Kothapalli, Chandrasekhar R.

    Elastin, a structural protein distributed in the extracellular matrix of vascular tissues is critical to the maintenance of vascular mechanics, besides regulation of cell-signaling pathways involved in injury response and morphogenesis. Thus, congenital absence or disease-mediated degradation of vascular elastin and its malformation within native vessels due to innately poor elastin synthesis by adult vascular cells compromise vascular homeostasis. Current elastin regenerative strategies using tissue engineering principles are limited by the progressive destabilization of tropoelastin mRNA expression in adult vascular cells and the unavailability of scaffolds that can provide cellular cues necessary to up-regulate elastin synthesis and regenerate faithful mimics of native elastin. Since our earlier studies demonstrated the elastogenic utility of hyaluronan (HA)-based cues, we have currently sought to identify a unique set of culture conditions based on HA fragments (0.756-2000 kDa), growth factors (TGF-beta1, IGF-1) and other biomolecules (Cu2+ ions, LOX), which will together enhance synthesis, crosslinking, maturation and fibrous elastin matrix formation by adult SMCs, under both healthy and inflammatory conditions. It was observed that TGF-beta1 (1 ng/mL) together with HA oligomers (0.2 microg/mL) synergistically suppressed SMC proliferation, enhanced tropoelastin (8-fold) and matrix elastin synthesis (5.5-fold), besides improving matrix yield (4.5-fold), possibly by increasing production and activity of lysyl oxidase (LOX). Though addition of IGF-1 alone did not offer any advantage, HA fragments (20-200 kDa) in the presence of IGF-1 stimulated tropoelastin and soluble elastin synthesis more than 2.2-fold, with HMW HA contributing for ˜5-fold increase in crosslinked matrix elastin synthesis. Similarly, 0.1 M of Cu2+ ions, alone or together with HA fragments stimulated synthesis of tropoelastin (4-fold) and crosslinked matrix elastin (4.5-fold), via increases in

  20. Participatory sensing as an enabler for self-organisation in future cellular networks

    NASA Astrophysics Data System (ADS)

    Imran, Muhammad Ali; Imran, Ali; Onireti, Oluwakayode

    2013-12-01

    In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells.

  1. Performance evaluation of power control algorithms in wireless cellular networks

    NASA Astrophysics Data System (ADS)

    Temaneh-Nyah, C.; Iita, V.

    2014-10-01

    Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

  2. Embryonic MicroRNA-369 Controls Metabolic Splicing Factors and Urges Cellular Reprograming

    PubMed Central

    Konno, Masamitsu; Koseki, Jun; Kawamoto, Koichi; Nishida, Naohiro; Matsui, Hidetoshi; Dewi, Dyah Laksmi; Ozaki, Miyuki; Noguchi, Yuko; Mimori, Koshi; Gotoh, Noriko; Tanuma, Nobuhiro; Shima, Hiroshi; Doki, Yuichiro

    2015-01-01

    Noncoding microRNAs inhibit translation and lower the transcript stability of coding mRNA, however miR-369 s, in aberrant silencing genomic regions, stabilizes target proteins under cellular stress. We found that in vitro differentiation of embryonic stem cells led to chromatin methylation of histone H3K4 at the miR-369 region on chromosome 12qF in mice, which is expressed in embryonic cells and is critical for pluripotency. Proteomic analyses revealed that miR-369 stabilized translation of pyruvate kinase (Pkm2) splicing factors such as HNRNPA2B1. Overexpression of miR-369 stimulated Pkm2 splicing and enhanced induction of cellular reprogramming by induced pluripotent stem cell factors, whereas miR-369 knockdown resulted in suppression. Furthermore, immunoprecipitation analysis showed that the Argonaute complex contained the fragile X mental retardation-related protein 1 and HNRNPA2B1 in a miR-369-depedent manner. Our findings demonstrate a unique role of the embryonic miR-369-HNRNPA2B1 axis in controlling metabolic enzyme function, and suggest a novel pathway linking epigenetic, transcriptional, and metabolic control in cell reprogramming. PMID:26176628

  3. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks.

    PubMed

    Schuster, S; Fell, D A; Dandekar, T

    2000-03-01

    A set of linear pathways often does not capture the full range of behaviors of a metabolic network. The concept of 'elementary flux modes' provides a mathematical tool to define and comprehensively describe all metabolic routes that are both stoichiometrically and thermodynamically feasible for a group of enzymes. We have used this concept to analyze the interplay between the pentose phosphate pathway (PPP) and glycolysis. The set of elementary modes for this system involves conventional glycolysis, a futile cycle, all the modes of PPP function described in biochemistry textbooks, and additional modes that are a priori equally entitled to pathway status. Applications include maximizing product yield in amino acid and antibiotic synthesis, reconstruction and consistency checks of metabolism from genome data, analysis of enzyme deficiencies, and drug target identification in metabolic networks. PMID:10700151

  4. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    EPA Science Inventory

    With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

  5. 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

  6. 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

  7. Comparative analysis of Salmonella susceptibility and tolerance to the biocide chlorhexidine identifies a complex cellular defense network.

    PubMed

    Condell, Orla; Power, Karen A; Händler, Kristian; Finn, Sarah; Sheridan, Aine; Sergeant, Kjell; Renaut, Jenny; Burgess, Catherine M; Hinton, Jay C D; Nally, Jarlath E; Fanning, Séamus

    2014-01-01

    Chlorhexidine is one of the most widely used biocides in health and agricultural settings as well as in the modern food industry. It is a cationic biocide of the biguanide class. Details of its mechanism of action are largely unknown. The frequent use of chlorhexidine has been questioned recently, amidst concerns that an overuse of this compound may select for bacteria displaying an altered susceptibility to antimicrobials, including clinically important anti-bacterial agents. We generated a Salmonella enterica serovar Typhimurium isolate (ST24(CHX)) that exhibited a high-level tolerant phenotype to chlorhexidine, following several rounds of in vitro selection, using sub-lethal concentrations of the biocide. This mutant showed altered suceptibility to a panel of clinically important antimicrobial compounds. Here we describe a genomic, transcriptomic, proteomic, and phenotypic analysis of the chlorhexidine tolerant S. Typhimurium compared with its isogenic sensitive progenitor. Results from this study describe a chlorhexidine defense network that functions in both the reference chlorhexidine sensitive isolate and the tolerant mutant. The defense network involved multiple cell targets including those associated with the synthesis and modification of the cell wall, the SOS response, virulence, and a shift in cellular metabolism toward anoxic pathways, some of which were regulated by CreB and Fur. In addition, results indicated that chlorhexidine tolerance was associated with more extensive modifications of the same cellular processes involved in this proposed network, as well as a divergent defense response involving the up-regulation of additional targets such as the flagellar apparatus and an altered cellular phosphate metabolism. These data show that sub-lethal concentrations of chlorhexidine induce distinct changes in exposed Salmonella, and our findings provide insights into the mechanisms of action and tolerance to this biocidal agent. PMID:25136333

  8. Comparative analysis of Salmonella susceptibility and tolerance to the biocide chlorhexidine identifies a complex cellular defense network

    PubMed Central

    Condell, Orla; Power, Karen A.; Händler, Kristian; Finn, Sarah; Sheridan, Aine; Sergeant, Kjell; Renaut, Jenny; Burgess, Catherine M.; Hinton, Jay C. D.; Nally, Jarlath E.; Fanning, Séamus

    2014-01-01

    Chlorhexidine is one of the most widely used biocides in health and agricultural settings as well as in the modern food industry. It is a cationic biocide of the biguanide class. Details of its mechanism of action are largely unknown. The frequent use of chlorhexidine has been questioned recently, amidst concerns that an overuse of this compound may select for bacteria displaying an altered susceptibility to antimicrobials, including clinically important anti-bacterial agents. We generated a Salmonella enterica serovar Typhimurium isolate (ST24CHX) that exhibited a high-level tolerant phenotype to chlorhexidine, following several rounds of in vitro selection, using sub-lethal concentrations of the biocide. This mutant showed altered suceptibility to a panel of clinically important antimicrobial compounds. Here we describe a genomic, transcriptomic, proteomic, and phenotypic analysis of the chlorhexidine tolerant S. Typhimurium compared with its isogenic sensitive progenitor. Results from this study describe a chlorhexidine defense network that functions in both the reference chlorhexidine sensitive isolate and the tolerant mutant. The defense network involved multiple cell targets including those associated with the synthesis and modification of the cell wall, the SOS response, virulence, and a shift in cellular metabolism toward anoxic pathways, some of which were regulated by CreB and Fur. In addition, results indicated that chlorhexidine tolerance was associated with more extensive modifications of the same cellular processes involved in this proposed network, as well as a divergent defense response involving the up-regulation of additional targets such as the flagellar apparatus and an altered cellular phosphate metabolism. These data show that sub-lethal concentrations of chlorhexidine induce distinct changes in exposed Salmonella, and our findings provide insights into the mechanisms of action and tolerance to this biocidal agent. PMID:25136333

  9. Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for (13)C metabolic flux analysis.

    PubMed

    Au, Jennifer; Choi, Jungik; Jones, Shawn W; Venkataramanan, Keerthi P; Antoniewicz, Maciek R

    2014-11-01

    In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and (13)C-metabolic flux analysis ((13)C-MFA). Here, cells were grown in parallel cultures with [1-(13)C]glucose and [U-(13)C]glucose as tracers and (13)C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of (13)C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for (13)C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased (13)C-flux measurements in C. acetobutylicum. PMID:25183671

  10. Accelerated Cellular Uptake and Metabolism of L-Thyroxine during Acute Salmonella typhimurium Sepsis

    PubMed Central

    DeRubertis, Frederick R.; Woeber, Kenneth A.

    1973-01-01

    The effects of acute Salmonella typhimurium sepsis on the kinetics of peripheral L-thyroxine (T4) distribution and metabolism and on serum total and free T4 concentrations were studied in rhesus monkeys inoculated i.v. with either heat-killed or viable organisms. The rate of disappearance of labeled T4 from serum was increased within 8 h after inoculation of monkeys with either heat-killed or viable Salmonella. The effects of the heat-killed organisms were transient and no longer evident by 16 h postinoculation. The monkeys inoculated with the viable Salmonella experienced a 2-3 day febrile, septic illness that was accompanied by an increase in the absolute rate of T4 disposal. In the infected monkeys, serum total T4 and endogenously labeled protein-bound iodine concentrations fell significantly during the period of acute sepsis and then rose during convalescence to values that exceeded the preinoculation values, suggesting that thyroidal secretion of hormone had increased in response to a primary depletion of the peripheral hormonal pool. Total cellular and hepatic uptakes of T4 were enhanced by 4 h after inoculation of monkeys with either heat-killed or viable Salmonella, but the increase in total cellular uptake persisted for 24 h only in the monkeys inoculated with the viable organisms. These alterations in T4 kinetics could neither be correlated with changes in the binding of T4 in plasma nor attributed to an increase in vascular permeability. Moreover, they could not be ascribed to an in vitro product of bacterial growth, suggesting that the presence of the organisms themselves was required. An acceleration of T4 disappearance was also observed during Escherichia coli and Diplococcus pucumoniae bacteremias. Our findings are consistent with a primary increase in the cellular uptake and metabolism of T4 during bacterial sepsis, possibly related to phagocytic cell function in the host. PMID:4629910

  11. Arctigenin preferentially induces tumor cell death under glucose deprivation by inhibiting cellular energy metabolism.

    PubMed

    Gu, Yuan; Qi, Chunting; Sun, Xiaoxiao; Ma, Xiuquan; Zhang, Haohao; Hu, Lihong; Yuan, Junying; Yu, Qiang

    2012-08-15

    Selectively eradicating cancer cells with minimum adverse effects on normal cells is a major challenge in the development of anticancer therapy. We hypothesize that nutrient-limiting conditions frequently encountered by cancer cells in poorly vascularized solid tumors might provide an opportunity for developing selective therapy. In this study, we investigated the function and molecular mechanisms of a natural compound, arctigenin, in regulating tumor cell growth. We demonstrated that arctigenin selectively promoted glucose-starved A549 tumor cells to undergo necrosis by inhibiting mitochondrial respiration. In doing so, arctigenin elevated cellular level of reactive oxygen species (ROS) and blocked cellular energy metabolism in the glucose-starved tumor cells. We also demonstrated that cellular ROS generation was caused by intracellular ATP depletion and played an essential role in the arctigenin-induced tumor cell death under the glucose-limiting condition. Furthermore, we combined arctigenin with the glucose analogue 2-deoxyglucose (2DG) and examined their effects on tumor cell growth. Interestingly, this combination displayed preferential cell-death inducing activity against tumor cells compared to normal cells. Hence, we propose that the combination of arctigenin and 2DG may represent a promising new cancer therapy with minimal normal tissue toxicity. PMID:22687625

  12. Linking Pulmonary Oxygen Uptake, Muscle Oxygen Utilization and Cellular Metabolism during Exercise

    PubMed Central

    Lai, Nicola; Camesasca, Marco; Saidel, Gerald M.; Dash, Ranjan K.; Cabrera, Marco E.

    2014-01-01

    The energy demand imposed by physical exercise on the components of the oxygen transport and utilization system requires a close link between cellular and external respiration in order to maintain ATP homeostasis. Invasive and non-invasive experimental approaches have been used to elucidate mechanisms regulating the balance between oxygen supply and consumption during exercise. Such approaches suggest that the mechanism controlling the various subsystems coupling internal to external respiration are part of a highly redundant and hierarchical multi-scale system. In this work, we present a “systems biology” framework that integrates experimental and theoretical approaches able to provide simultaneously reliable information on the oxygen transport and utilization processes occurring at the various steps in the pathway of oxygen from air to mitochondria, particularly at the onset of exercise. This multi-disciplinary framework provides insights into the relationship between cellular oxygen consumption derived from measurements of muscle oxygenation during exercise and pulmonary oxygen uptake by indirect calorimetry. With a validated model, muscle oxygen dynamic responses is simulated and quantitatively related to cellular metabolism under a variety of conditions. PMID:17380394

  13. Defective Ca2+ metabolism in Duchenne muscular dystrophy: effects on cellular and viral growth.

    PubMed Central

    Fingerman, E; Campisi, J; Pardee, A B

    1984-01-01

    Normal fibroblasts in medium containing 0.02 mM CaCl2 arrested growth within 24 hr, whereas Duchenne muscular dystrophy fibroblasts continued to grow for 5 days, albeit at 40% of their rate in standard medium (1.8 mM CaCl2). Moreover, Duchenne cells in calcium-deficient medium showed an enhanced rate of protein synthesis (60% over the rate in standard medium), whereas normal cells were unaffected. Previously we described a general assay for detection of mutant cells by using herpes simplex virus I replication as a probe of cellular function. By altering the growth medium, one can elicit changes in viral DNA replication that depend upon cellular differences. Duchenne fibroblasts in calcium-deficient low-serum (0.5%) medium supported viral replication at a rate 7- to 10-fold greater than did normal cells infected under the same conditions. Using this viral assay, we have successfully identified all 10 samples of a blind coded set of Duchenne muscular dystrophy, normal, and heterozygote cells. In addition, differences of a lower magnitude were found between these cell strains as measured by cellular growth or protein synthesis. Therefore, a cell's ability to grow and support viral replication in calcium-deficient medium can be used to readily distinguish Duchenne muscular dystrophy fibroblasts from normal ones. These results suggest that the viral assay could be used as a prenatal diagnostic test. A defect related to calcium metabolism may be fundamental to this disease. PMID:6095311

  14. Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma.

    PubMed

    Özcan, Emrah; Çakır, Tunahan

    2016-01-01

    Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM. PMID:27147948

  15. Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma

    PubMed Central

    Özcan, Emrah; Çakır, Tunahan

    2016-01-01

    Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM. PMID:27147948

  16. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    PubMed

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. PMID:26097169

  17. Predicting metabolic pathways by sub-network extraction.

    PubMed

    Faust, Karoline; van Helden, Jacques

    2012-01-01

    Various methods result in groups of functionally related genes obtained from genomes (operons, regulons, syntheny groups, and phylogenetic profiles), transcriptomes (co-expression groups) and proteomes (modules of interacting proteins). When such groups contain two or more enzyme-coding genes, graph analysis methods can be applied to extract a metabolic pathway that interconnects them. We describe here the way to use the Pathway extraction tool available on the NeAT Web server ( http://rsat.ulb.ac.be/neat/ ) to piece together the metabolic pathway from a group of associated, enzyme-coding genes. The tool identifies the reactions that can be catalyzed by the products of the query genes (seed reactions), and applies sub-graph extraction algorithms to extract from a metabolic network a sub-network that connects the seed reactions. This sub-network represents the predicted metabolic pathway. We describe here the pathway prediction process in a step-by-step way, give hints about the main parametric choices, and illustrate how this tool can be used to extract metabolic pathways from bacterial genomes, on the basis of two study cases: the isoleucine-valine operon in Escherichia coli and a predicted operon in Cupriavidus (Ralstonia) metallidurans. PMID:22144151

  18. A Caenorhabditis elegans Genome-Scale Metabolic Network Model.

    PubMed

    Yilmaz, L Safak; Walhout, Albertha J M

    2016-05-25

    Caenorhabditis elegans is a powerful model to study metabolism and how it relates to nutrition, gene expression, and life history traits. However, while numerous experimental techniques that enable perturbation of its diet and gene function are available, a high-quality metabolic network model has been lacking. Here, we reconstruct an initial version of the C. elegans metabolic network. This network model contains 1,273 genes, 623 enzymes, and 1,985 metabolic reactions and is referred to as iCEL1273. Using flux balance analysis, we show that iCEL1273 is capable of representing the conversion of bacterial biomass into C. elegans biomass during growth and enables the predictions of gene essentiality and other phenotypes. In addition, we demonstrate that gene expression data can be integrated with the model by comparing metabolic rewiring in dauer animals versus growing larvae. iCEL1273 is available at a dedicated website (wormflux.umassmed.edu) and will enable the unraveling of the mechanisms by which different macro- and micronutrients contribute to the animal's physiology. PMID:27211857

  19. Thioflavin T as a fluorescence probe for monitoring RNA metabolism at molecular and cellular levels.

    PubMed

    Sugimoto, Shinya; Arita-Morioka, Ken-ichi; Mizunoe, Yoshimitsu; Yamanaka, Kunitoshi; Ogura, Teru

    2015-08-18

    The intrinsically stochastic dynamics of mRNA metabolism have important consequences on gene regulation and non-genetic cell-to-cell variability; however, no generally applicable methods exist for studying such stochastic processes quantitatively. Here, we describe the use of the amyloid-binding probe Thioflavin T (ThT) for monitoring RNA metabolism in vitro and in vivo. ThT fluoresced strongly in complex with bacterial total RNA than with genomic DNA. ThT bound purine oligoribonucleotides preferentially over pyrimidine oligoribonucleotides and oligodeoxyribonucleotides. This property enabled quantitative real-time monitoring of poly(A) synthesis and phosphorolysis by polyribonucleotide phosphorylase in vitro. Cellular analyses, in combination with genetic approaches and the transcription-inhibitor rifampicin treatment, demonstrated that ThT mainly stained mRNA in actively dividing Escherichia coli cells. ThT also facilitated mRNA metabolism profiling at the single-cell level in diverse bacteria. Furthermore, ThT can also be used to visualise transitions between non-persister and persister cell states, a phenomenon of isogenic subpopulations of antibiotic-sensitive bacteria that acquire tolerance to multiple antibiotics due to stochastically induced dormant states. Collectively, these results suggest that probing mRNA dynamics with ThT is a broadly applicable approach ranging from the molecular level to the single-cell level. PMID:25883145

  20. Genome-scale metabolic network reconstruction and in silico flux analysis of the thermophilic bacterium Thermus thermophilus HB27

    PubMed Central

    2014-01-01

    Background Thermus thermophilus, an extremely thermophilic bacterium, has been widely recognized as a model organism for studying how microbes can survive and adapt under high temperature environment. However, the thermotolerant mechanisms and cellular metabolism still remains mostly unravelled. Thus, it is highly required to consider systems biological approaches where T. thermophilus metabolic network model can be employed together with high throughput experimental data for elucidating its physiological characteristics under such harsh conditions. Results We reconstructed a genome-scale metabolic model of T. thermophilus, iTT548, the first ever large-scale network of a thermophilic bacterium, accounting for 548 unique genes, 796 reactions and 635 unique metabolites. Our initial comparative analysis of the model with Escherichia coli has revealed several distinctive metabolic reactions, mainly in amino acid metabolism and carotenoid biosynthesis, producing relevant compounds to retain the cellular membrane for withstanding high temperature. Constraints-based flux analysis was, then, applied to simulate the metabolic state in glucose minimal and amino acid rich media. Remarkably, resulting growth predictions were highly consistent with the experimental observations. The subsequent comparative flux analysis under different environmental conditions highlighted that the cells consumed branched chain amino acids preferably and utilized them directly in the relevant anabolic pathways for the fatty acid synthesis. Finally, gene essentiality study was also conducted via single gene deletion analysis, to identify the conditional essential genes in glucose minimal and complex media. Conclusions The reconstructed genome-scale metabolic model elucidates the phenotypes of T. thermophilus, thus allowing us to gain valuable insights into its cellular metabolism through in silico simulations. The information obtained from such analysis would not only shed light on the

  1. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  2. Global probabilistic annotation of metabolic networks enables enzyme discovery

    PubMed Central

    Plata, Germán; Fuhrer, Tobias; Hsiao, Tzu-Lin; Sauer, Uwe; Vitkup, Dennis

    2013-01-01

    Annotation of organism-specific metabolic networks is one of the main challenges of systems biology. Importantly, due to inherent uncertainty of computational annotations, predictions of biochemical function need to be treated probabilistically. We present a global probabilistic approach to annotate genome-scale metabolic networks that integrates sequence homology and context-based correlations under a single principled framework. The developed method for Global Biochemical reconstruction Using Sampling (GLOBUS) not only provides annotation probabilities for each functional assignment, but also suggests likely alternative functions. GLOBUS is based on statistical Gibbs sampling of probable metabolic annotations and is able to make accurate functional assignments even in cases of remote sequence identity to known enzymes. We apply GLOBUS to genomes of Bacillus subtilis and Staphylococcus aureus, and validate the method predictions by experimentally demonstrating the 6-phosphogluconolactonase activity of ykgB and the role of the sps pathway for rhamnose biosynthesis in B. subtilis. PMID:22960854

  3. Simple topological properties predict functional misannotations in a metabolic network

    PubMed Central

    Liberal, Rodrigo; Pinney, John W.

    2013-01-01

    Motivation: Misannotation in sequence databases is an important obstacle for automated tools for gene function annotation, which rely extensively on comparison with sequences with known function. To improve current annotations and prevent future propagation of errors, sequence-independent tools are, therefore, needed to assist in the identification of misannotated gene products. In the case of enzymatic functions, each functional assignment implies the existence of a reaction within the organism’s metabolic network; a first approximation to a genome-scale metabolic model can be obtained directly from an automated genome annotation. Any obvious problems in the network, such as dead end or disconnected reactions, can, therefore, be strong indications of misannotation. Results: We demonstrate that a machine-learning approach using only network topological features can successfully predict the validity of enzyme annotations. The predictions are tested at three different levels. A random forest using topological features of the metabolic network and trained on curated sets of correct and incorrect enzyme assignments was found to have an accuracy of up to 86% in 5-fold cross-validation experiments. Further cross-validation against unseen enzyme superfamilies indicates that this classifier can successfully extrapolate beyond the classes of enzyme present in the training data. The random forest model was applied to several automated genome annotations, achieving an accuracy of in most cases when validated against recent genome-scale metabolic models. We also observe that when applied to draft metabolic networks for multiple species, a clear negative correlation is observed between predicted annotation quality and phylogenetic distance to the major model organism for biochemistry (Escherichia coli for prokaryotes and Homo sapiens for eukaryotes). Contact: j.pinney@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID

  4. Environmental and genetic perturbations reveal different networks of metabolic regulation

    PubMed Central

    Greenberg, Anthony J; Hackett, Sean R; Harshman, Lawrence G; Clark, Andrew G

    2011-01-01

    Progress in systems biology depends on accurate descriptions of biological networks. Connections in a regulatory network are identified as correlations of gene expression across a set of environmental or genetic perturbations. To use this information to predict system behavior, we must test how the nature of perturbations affects topologies of networks they reveal. To probe this question, we focused on metabolism of Drosophila melanogaster. Our source of perturbations is a set of crosses among 92 wild-derived lines from five populations, replicated in a manner permitting separate assessment of the effects of genetic variation and environmental fluctuation. We directly assayed activities of enzymes and levels of metabolites. Using a multivariate Bayesian model, we estimated covariance among metabolic parameters and built fine-grained probabilistic models of network topology. The environmental and genetic co-regulation networks are substantially the same among five populations. However, genetic and environmental perturbations reveal qualitative differences in metabolic regulation, suggesting that environmental shifts, such as diet modifications, produce different systemic effects than genetic changes, even if the primary targets are the same. PMID:22186737

  5. Early Cellular Changes in the Ascending Aorta and Myocardium in a Swine Model of Metabolic Syndrome

    PubMed Central

    Mahmood, Feroze; Owais, Khurram; Bardia, Amit; Khabbaz, Kamal R.; Liu, David; Senthilnathan, Venkatachalam; Lassaletta, Antonio D.; Sellke, Frank; Matyal, Robina

    2016-01-01

    Background Metabolic syndrome is associated with pathological remodeling of the heart and adjacent vessels. The early biochemical and cellular changes underlying the vascular damage are not fully understood. In this study, we sought to establish the nature, extent, and initial timeline of cytochemical derangements underlying reduced ventriculo-arterial compliance in a swine model of metabolic syndrome. Methods Yorkshire swine (n = 8 per group) were fed a normal diet (ND) or a high-cholesterol (HCD) for 12 weeks. Myocardial function and blood flow was assessed before harvesting the heart. Immuno-blotting and immuno-histochemical staining were used to assess the cellular changes in the myocardium, ascending aorta and left anterior descending artery (LAD). Results There was significant increase in body mass index, blood glucose and mean arterial pressures (p = 0.002, p = 0.001 and p = 0.024 respectively) in HCD group. At the cellular level there was significant increase in anti-apoptotic factors p-Akt (p = 0.007 and p = 0.002) and Bcl-xL (p = 0.05 and p = 0.01) in the HCD aorta and myocardium, respectively. Pro-fibrotic markers TGF-β (p = 0.01), pSmad1/5 (p = 0.03) and MMP-9 (p = 0.005) were significantly increased in the HCD aorta. The levels of pro-apoptotic p38MAPK, Apaf-1 and cleaved Caspase3 were significantly increased in aorta of HCD (p = 0.03, p = 0.04 and p = 0.007 respectively). Similar changes in coronary arteries were not observed in either group. Functionally, the high cholesterol diet resulted in significant increase in ventricular end systolic pressure and–dp/dt (p = 0.05 and p = 0.007 respectively) in the HCD group. Conclusion Preclinical metabolic syndrome initiates pro-apoptosis and pro-fibrosis pathways in the heart and ascending aorta, while sparing coronary arteries at this early stage of dietary modification. PMID:26766185

  6. Quantifying Uncertainties in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Rios Gaona, M. F.; Overeem, A.; Leijnse, H.

    2014-12-01

    The core idea behind rainfall retrievals from commercial microwave link networks is to measure the decrease in power due to attenuation of the electromagnetic signal by raindrops along the link path. Accurate rainfall measurements are of vital importance in hydrological applications, for instance, flash-flood early-warning systems, agriculture, and climate modeling. Hence, such an alternative technique fulfills the need for measurements with higher resolution in time and space, especially in places where standard rain gauge-networks are scarce or poorly maintained. Rainfall estimation via commercial microwave link networks, at country-wide scales, has recently been demonstrated. Despite their potential applicability in rainfall estimation at higher spatiotemporal resolutions, the uncertainties present in link-based rainfall maps are not yet fully comprehended. Now we attempt to quantify the inherent sources of uncertainty present in interpolated maps computed from commercial microwave link rainfall retrievals. In order to disentangle these sources of uncertainty we identified four main sources of error: 1) microwave link measurements, 2) availability of microwave link measurements, 3) spatial distribution of the network, and 4) interpolation methodology. We computed more than 1000 rainfall fields, for The Netherlands, from real and simulated microwave link data. These rainfall fields were compared to quality-controlled gauge-adjusted radar rainfall maps considered as ground-truth. Thus we were able to quantify the contribution of errors in microwave link measurements to the overall uncertainty. The actual performance of the commercial microwave link network is affected by the intermittent availability of the links, not only in time but also in space. We simulated a fully-operational network in time and space, and thus we quantified the role of the availability of microwave link measurements to the overall uncertainty. This research showed that the largest source of

  7. The anticancer plant triterpenoid, avicin D, regulates glucocorticoid receptor signaling: implications for cellular metabolism.

    PubMed

    Haridas, Valsala; Xu, Zhi-Xiang; Kitchen, Doug; Jiang, Anna; Michels, Peter; Gutterman, Jordan U

    2011-01-01

    Avicins, a family of apoptotic triterpene electrophiles, are known to regulate cellular metabolism and energy homeostasis, by targeting the mitochondria. Having evolved from "ancient hopanoids," avicins bear a structural resemblance with glucocorticoids (GCs), which are the endogenous regulators of metabolism and energy balance. These structural and functional similarities prompted us to compare the mode of action of avicin D with dexamethasone (Dex), a prototypical GC. Using cold competition assay, we show that Avicin D competes with Dex for binding to the GC receptor (GR), leading to its nuclear translocation. In contrast to Dex, avicin-induced nuclear translocation of GR does not result in transcriptional activation of GC-dependent genes. Instead we observe a decrease in the expression of GC-dependent metabolic proteins such as PEPCK and FASN. However, like Dex, avicin D treatment does induce a transrepressive effect on the pro-inflammatory transcription factor NF-κB. While avicin's ability to inhibit NF-κB and its downstream targets appear to be GR-dependent, its pro-apoptotic effects were independent of GR expression. Using various deletion mutants of GR, we demonstrate the requirement of both the DNA and ligand binding domains of GR in mediating avicin D's transrepressive effects. Modeling of avicin-GR interaction revealed that avicin molecule binds only to the antagonist confirmation of GR. These findings suggest that avicin D has properties of being a selective GR modulator that separates transactivation from transrepression. Since the gene-activating properties of GR are mainly linked to its metabolic effects, and the negative interference with the activity of transcription factors to its anti-inflammatory and immune suppressive effects, the identification of such a dissociated GR ligand could have great potential for therapeutic use. PMID:22132201

  8. Multi-scale modularity and motif distributional effect in metabolic networks.

    PubMed

    Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

    2016-01-01

    Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks. PMID:26412791

  9. Resource Management in QoS-Aware Wireless Cellular Networks

    ERIC Educational Resources Information Center

    Zhang, Zhi

    2011-01-01

    Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study…

  10. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    NASA Astrophysics Data System (ADS)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  11. Application of Cellular Automata to Detection of Malicious Network Packets

    ERIC Educational Resources Information Center

    Brown, Robert L.

    2014-01-01

    A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…

  12. Preservation, induction or incorporation of metabolism into the in vitro cellular system - views to current opportunities and limitations.

    PubMed

    Pelkonen, Olavi; Turpeinen, Miia; Hakkola, Jukka; Abass, Khaled; Pasanen, Markku; Raunio, Hannu; Vähäkangas, Kirsi

    2013-08-01

    Metabolism plays a major role in the toxicokinetics of a vast majority of substances, although other dispositional processes have to be considered as well. There are currently a large repertoire of primary or permanent cells/cell lines with variable metabolic capacities and a number of experimental approaches to preserve, induce or incorporate biotransformation enzymes for the development of metabolically competent cells. Many of these cell lines possess also other important dispositional characteristics mimicking the in vivo situation. Such cell models can be employed in studies targeted for estimating metabolic disposition of a substance or the production of active metabolites and ensuing toxic end points. There are also ways to collect metabolic information by using a large number of non-cellular systems and build a coherent view on metabolism, although not really replacing the actual cellular system. Early consideration of metabolic competence is a necessary prerequisite for the validation and use of cellular systems for toxicity studies and in vitro-in vivo extrapolation. PMID:22728233

  13. Parameter estimation for metabolic networks with two stage Bregman regularization homotopy inversion algorithm.

    PubMed

    Wang, Hong; Wang, Xi-cheng

    2014-02-21

    Metabolism is a very important cellular process and its malfunction contributes to human disease. Therefore, building dynamic models for metabolic networks with experimental data in order to analyze biological process rationally has attracted a lot of attention. Owing to the technical limitations, some unknown parameters contained in models need to be estimated effectively by means of the computational method. Generally, problems of parameter estimation of nonlinear biological network are known to be ill condition and multimodal. In particular, with the increasing amount and enlarging the scope of parameters, many optimization algorithms often fail to find a global solution. In this paper, two-stage variable factor Bregman regularization homotopy method is proposed. Discrete homotopy is used to identify the possible extreme region and continuous homotopy is executed for the purpose of stability of path tracing in the special region. Meanwhile, Latin hypercube sampling is introduced to get the good initial guess value and a perturbation strategy is developed to jump out of the local optimum. Three metabolic network inverse problems are investigated to demonstrate the effectiveness of the proposed method. PMID:24060619

  14. Frequency-dependent micromechanics of cellularized biopolymer networks

    NASA Astrophysics Data System (ADS)

    Jones, Chris; Kim, Jihan; McIntyre, David; Sun, Bo

    Mechanical interactions between cells and the extracellular matrix (ECM) influence many cellular behaviors such as growth, differentiation, and migration. These are dynamic processes in which the cells actively remodel the ECM. Reconstituted collagen gel is a common model ECM for studying cell-ECM interactions in vitro because collagen is the most abundant component of mammalian ECM and gives the ECM its material stiffness. We embed micron-sized particles in collagen and use holographic optical tweezers to apply forces to the particles in multiple directions and over a range of frequencies up to 10 Hz. We calculate the local compliance and show that it is dependent on both the direction and frequency of the applied force. Performing the same measurement on many particles allows us to characterize the spatial inhomogeneity of the mechanical properties and shows that the compliance decreases at higher frequencies. Performing these measurements on cell-populated collagen gels shows that cellular remodeling of the ECM changes the mechanical properties of the collagen and we investigate whether this change is dependent on the local strain and distance from nearby cells.

  15. Experimental determination of group flux control coefficients in metabolic networks

    SciTech Connect

    Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G.

    1998-04-20

    Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmental perturbations are used to determine the group flux control coefficients for three reaction groups formed around the phosphoenolpyruvate/pyruvate branch point. The consistency of the obtained group flux control coefficient estimates is systematically analyzed to ensure that all necessary conditions are satisfied. The magnitudes of the determined control coefficients suggest that the control of lysine production flux in Corynebacterium glutamicum cells at a growth base state resides within the lysine biosynthetic pathway that begins with the PEP/PYR carboxylation anaplorotic pathway.

  16. Out of fuzzy chemistry: from prebiotic chemistry to metabolic networks.

    PubMed

    Peretó, Juli

    2012-08-21

    The origin of life on Earth was a chemical affair. So how did primitive biochemical systems originate from geochemical and cosmochemical processes on the young planet? Contemporary research into the origins of life subscribes to the Darwinian principle of material causes operating in an evolutionary context, as advocated by A. I. Oparin and J. B. S. Haldane in the 1920s. In its simplest form (e.g., a bacterial cell) extant biological complexity relies on the functional integration of metabolic networks and replicative genomes inside a lipid boundary. Different research programmes have explored the prebiotic plausibility of each of these autocatalytic subsystems and combinations thereof: self-maintained networks of small molecules, template chemistry, and self-reproductive vesicles. This tutorial review focuses on the debates surrounding the origin of metabolism and offers a brief overview of current studies on the evolution of metabolic networks. I suggest that a leitmotif in the origin and evolution of metabolism is the role played by catalysers' substrate ambiguity and multifunctionality. PMID:22508108

  17. Differential contribution of key metabolic substrates and cellular oxygen in HIF signalling

    SciTech Connect

    Zhdanov, Alexander V.; Waters, Alicia H.C.; Golubeva, Anna V.; Papkovsky, Dmitri B.

    2015-01-01

    Changes in availability and utilisation of O{sub 2} and metabolic substrates are common in ischemia and cancer. We examined effects of substrate deprivation on HIF signalling in PC12 cells exposed to different atmospheric O{sub 2}. Upon 2–4 h moderate hypoxia, HIF-α protein levels were dictated by the availability of glutamine and glucose, essential for deep cell deoxygenation and glycolytic ATP flux. Nuclear accumulation of HIF-1α dramatically decreased upon inhibition of glutaminolysis or glutamine deprivation. Elevation of HIF-2α levels was transcription-independent and associated with the activation of Akt and Erk1/2. Upon 2 h anoxia, HIF-2α levels strongly correlated with cellular ATP, produced exclusively via glycolysis. Without glucose, HIF signalling was suppressed, giving way to other regulators of cell adaptation to energy crisis, e.g. AMPK. Consequently, viability of cells deprived of O{sub 2} and glucose decreased upon inhibition of AMPK with dorsomorphin. The capacity of cells to accumulate HIF-2α decreased after 24 h glucose deprivation. This effect, associated with increased AMPKα phosphorylation, was sensitive to dorsomorphin. In chronically hypoxic cells, glutamine played no major role in HIF-2α accumulation, which became mainly glucose-dependent. Overall, the availability of O{sub 2} and metabolic substrates intricately regulates HIF signalling by affecting cell oxygenation, ATP levels and pathways involved in production of HIF-α. - Highlights: • Gln and Glc regulate HIF levels in hypoxic cells by maintaining low O{sub 2} and high ATP. • HIF-α levels under anoxia correlate with cellular ATP and critically depend on Glc. • Gln and Glc modulate activity of Akt, Erk and AMPK, regulating HIF production. • HIF signalling is differentially inhibited by prolonged Glc and Gln deprivation. • Unlike Glc, Gln plays no major role in HIF signalling in chronically hypoxic cells.

  18. Changes in Transcription and Metabolism During the Early Stage of Replicative Cellular Senescence in Budding Yeast*

    PubMed Central

    Kamei, Yuka; Tamada, Yoshihiro; Nakayama, Yasumune; Fukusaki, Eiichiro; Mukai, Yukio

    2014-01-01

    Age-related damage accumulates and a variety of biological activities and functions deteriorate in senescent cells. However, little is known about when cellular aging behaviors begin and what cellular aging processes change. Previous research demonstrated age-related mRNA changes in budding yeast by the 18th to 20th generation, which is the average replicative lifespan of yeast (i.e. about half of the population is dead by this time point). Here, we performed transcriptional and metabolic profiling for yeast at early stages of senescence (4th, 7th, and 11th generation), that is, for populations in which most cells are still alive. Transcriptional profiles showed up- and down-regulation for ∼20% of the genes profiled after the first four generations, few further changes by the 7th generation, and an additional 12% of the genes were up- and down-regulated after 11 generations. Pathway analysis revealed that these 11th generation cells had accumulated transcripts coding for enzymes involved in sugar metabolism, the TCA cycle, and amino acid degradation and showed decreased levels of mRNAs coding for enzymes involved in amino acid biosynthetic pathways. These observations were consistent with the metabolomic profiles of aging cells: an accumulation of pyruvic acid and TCA cycle intermediates and depletion of most amino acids, especially branched-chain amino acids. Stationary phase-induced genes were highly expressed after 11 generations even though the growth medium contained adequate levels of nutrients, indicating deterioration of the nutrient sensing and/or signaling pathways by the 11th generation. These changes are presumably early indications of replicative senescence. PMID:25294875

  19. Cellular network entropy as the energy potential in Waddington's differentiation landscape

    NASA Astrophysics Data System (ADS)

    Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

    2013-10-01

    Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape.

  20. Logical Modeling and Dynamical Analysis of Cellular Networks

    PubMed Central

    Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T.; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle. PMID:27303434

  1. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  2. Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks

    PubMed Central

    Chokkathukalam, Achuthanunni; Kim, Dong-Hyun; Barrett, Michael P; Breitling, Rainer; Creek, Darren J

    2014-01-01

    The rapid emergence of metabolomics has enabled system-wide measurements of metabolites in various organisms. However, advances in the mechanistic understanding of metabolic networks remain limited, as most metabolomics studies cannot routinely provide accurate metabolite identification, absolute quantification and flux measurement. Stable isotope labeling offers opportunities to overcome these limitations. Here we describe some current approaches to stable isotope-labeled metabolomics and provide examples of the significant impact that these studies have had on our understanding of cellular metabolism. Furthermore, we discuss recently developed software solutions for the analysis of stable isotope-labeled metabolomics data and propose the bioinformatics solutions that will pave the way for the broader application and optimal interpretation of system-scale labeling studies in metabolomics. PMID:24568354

  3. Multiperiod cellular network design via price-influenced simulated annealing (PISA).

    PubMed

    Menon, Syam; Amiri, Ali

    2006-06-01

    Cellular telecommunications systems tend to be more flexible than traditional ones. As a result, traditional approaches to telecommunications network design are often inappropriate for the design of cellular networks, and approaches that explicitly incorporate the increased flexibility into the design process need to be developed. This paper presents one such multiperiod cellular network design problem and solves it via a hybrid heuristic that incorporates ideas from linear programming (LP) and simulated annealing (SA). Extensive computational results comparing the performance of the heuristic with the lower bound obtained from the LP relaxation are presented. These results indicate that this price-influenced simulated annealing (PISA) procedure is extremely efficient, consistently providing solutions with average gaps of 0.30% or less in fewer than 30 s. PMID:16761813

  4. Mechanisms in photodynamic therapy: part two—cellular signaling, cell metabolism and modes of cell death

    PubMed Central

    Castano, Ana P.; Demidova, Tatiana N.; Hamblin, Michael R.

    2013-01-01

    Summary Photodynamic therapy (PDT) has been known for over a hundred years, but is only now becoming widely used. Originally developed as a tumor therapy, some of its most successful applications are for non-malignant disease. In the second of a series of three reviews, we will discuss the mechanisms that operate in PDT on a cellular level. In Part I [Castano AP, Demidova TN, Hamblin MR. Mechanism in photodynamic therapy: part one—photosensitizers, photochemistry and cellular localization. Photodiagn Photodyn Ther 2004;1:279–93] it was shown that one of the most important factors governing the outcome of PDT, is how the photosensitizer (PS) interacts with cells in the target tissue or tumor, and the key aspect of this interaction is the subcellular localization of the PS. PS can localize in mitochondria, lysosomes, endoplasmic reticulum, Golgi apparatus and plasma membranes. An explosion of investigation and explorations in the field of cell biology have elucidated many of the pathways that mammalian cells undergo when PS are delivered in tissue culture and subsequently illuminated. There is an acute stress response leading to changes in calcium and lipid metabolism and production of cytokines and stress proteins. Enzymes particularly, protein kinases, are activated and transcription factors are expressed. Many of the cellular responses are centered on mitochondria. These effects frequently lead to induction of apoptosis either by the mitochondrial pathway involving caspases and release of cytochrome c, or by pathways involving ceramide or death receptors. However, under certain circumstances cells subjected to PDT die by necrosis. Although there have been many reports of DNA damage caused by PDT, this is not thought to be an important cell-death pathway. This mechanistic research is expected to lead to optimization of PDT as a tumor treatment, and to rational selection of combination therapies that include PDT as a component. PMID:25048553

  5. Quantitative Mass Spectrometry Reveals Plasticity of Metabolic Networks in Mycobacterium smegmatis *

    PubMed Central

    Chopra, Tarun; Hamelin, Romain; Armand, Florence; Chiappe, Diego; Moniatte, Marc; McKinney, John D.

    2014-01-01

    Mycobacterium tuberculosis has a remarkable ability to persist within the human host as a clinically inapparent or chronically active infection. Fatty acids are thought to be an important carbon source used by the bacteria during long term infection. Catabolism of fatty acids requires reprogramming of metabolic networks, and enzymes central to this reprogramming have been targeted for drug discovery. Mycobacterium smegmatis, a nonpathogenic relative of M. tuberculosis, is often used as a model system because of the similarity of basic cellular processes in these two species. Here, we take a quantitative proteomics-based approach to achieve a global view of how the M. smegmatis metabolic network adjusts to utilization of fatty acids as a carbon source. Two-dimensional liquid chromatography and mass spectrometry of isotopically labeled proteins identified a total of 3,067 proteins with high confidence. This number corresponds to 44% of the predicted M. smegmatis proteome and includes most of the predicted metabolic enzymes. Compared with glucose-grown cells, 162 proteins showed differential abundance in acetate- or propionate-grown cells. Among these, acetate-grown cells showed a higher abundance of proteins that could constitute a functional glycerate pathway. Gene inactivation experiments confirmed that both the glyoxylate shunt and the glycerate pathway are operational in M. smegmatis. In addition to proteins with annotated functions, we demonstrate carbon source-dependent differential abundance of proteins that have not been functionally characterized. These proteins might play as-yet-unidentified roles in mycobacterial carbon metabolism. This study reveals several novel features of carbon assimilation in M. smegmatis, which suggests significant functional plasticity of metabolic networks in this organism. PMID:24997995

  6. Metabolism of platelet activating factor at the whole organ and cellular level

    SciTech Connect

    Haroldsen, P.E.

    1987-01-01

    Platelet activating factor (PAF, 1-O-alkyl-2-acetyl-sn-3-glycerophosphocholine) has been characterized as a phospholipid possessing a myriad of effects from the cellular to whole organism levels. Analytical methods and procedures were developed in order to measure and identify PAF precursors and metabolites. Two quantitative physicochemical methods based on isotope dilution mass spectrometry (MS) were developed to measure lyso-PAF and applied to the calcium ionophore stimulated human neutrophil. Levels of lyso-PAF were found to be significantly increased, 2-3 fold, upon cell activation with a stimulus that concomitantly elicits the production of PAF. Investigation into the metabolism of PAF by the isolated perfused rat lung by intratracheal instillation revealed (/sup 3/H)-PAF to be extensively metabolized over a 15 minute time course. Greater than 96% of the administered dose was retained by the lung and was distributed as: lyso-PAF (3.3%), phosphatidylcholine (GPC, 82.3%), phosphatidylethanolamine (2.5%), and neutral lipid (2.5%), the remainder was intact PAF.

  7. Poly(ADP-ribose) metabolism in young and old cells: response to cellular stresses

    SciTech Connect

    Gracy, R.W.; Sims, J.L.; Cini, J.

    1986-05-01

    The authors have examined the effect of several cellular stresses on poly(ADP-ribose) metabolism in human fibroblasts of low passage number derived from young and old donors. Poly(ADP-ribose) was synthesized in response to alkylation of DNA caused by N-methyl-N'-nitro-N-nitroguanidine and by hyperthermic treatment at 43 /sup 0/C or 45 /sup 0/C. Ethanol is able to potentiate poly(ADP-ribose) accumulation following these treatments. There was little if any difference in the response of young and old cells to these stresses. Amino acid analogs are thought to induce a response in mammalian cells similar to that caused by hyperthermia and ethanol. However, amino acid analogs such as L-azetidine did not produce effects on poly(ADP-ribose) metabolism like those produced by ethanol or hyperthermia. The authors have also examined the poly(ADP-ribose) content of bovine eye lens. Each eye lens contains populations of young and old cells that are distributed in a fixed graduated manner. Thus, the eye lens allows the study of aging cells with identical genetic backgrounds without the complications of serial passage of young cultures in in vitro aging systems.

  8. Differential contribution of key metabolic substrates and cellular oxygen in HIF signalling.

    PubMed

    Zhdanov, Alexander V; Waters, Alicia H C; Golubeva, Anna V; Papkovsky, Dmitri B

    2015-01-01

    Changes in availability and utilisation of O2 and metabolic substrates are common in ischemia and cancer. We examined effects of substrate deprivation on HIF signalling in PC12 cells exposed to different atmospheric O2. Upon 2-4h moderate hypoxia, HIF-α protein levels were dictated by the availability of glutamine and glucose, essential for deep cell deoxygenation and glycolytic ATP flux. Nuclear accumulation of HIF-1α dramatically decreased upon inhibition of glutaminolysis or glutamine deprivation. Elevation of HIF-2α levels was transcription-independent and associated with the activation of Akt and Erk1/2. Upon 2h anoxia, HIF-2α levels strongly correlated with cellular ATP, produced exclusively via glycolysis. Without glucose, HIF signalling was suppressed, giving way to other regulators of cell adaptation to energy crisis, e.g. AMPK. Consequently, viability of cells deprived of O2 and glucose decreased upon inhibition of AMPK with dorsomorphin. The capacity of cells to accumulate HIF-2α decreased after 24h glucose deprivation. This effect, associated with increased AMPKα phosphorylation, was sensitive to dorsomorphin. In chronically hypoxic cells, glutamine played no major role in HIF-2α accumulation, which became mainly glucose-dependent. Overall, the availability of O2 and metabolic substrates intricately regulates HIF signalling by affecting cell oxygenation, ATP levels and pathways involved in production of HIF-α. PMID:25447307

  9. Monitoring intra-cellular lipid metabolism in macrophages by Raman- and CARS-microscopy

    NASA Astrophysics Data System (ADS)

    Matthäus, Christian; Bergner, Gero; Krafft, Christoph; Dietzek, Benjamin; Lorkowski, Stefan; Popp, Jürgen

    2010-04-01

    Monocyte-derived macrophages play a key role in lipid metabolism in vessel wall tissues. Macrophages can take up lipids by various mechanisms. As phagocytes, macrophages are important for the decomposition of lipid plaques within arterial walls that contribute to arteriosclerosis. Of special interest are uptake dynamics and intra-cellular fate of different individual types of lipids as, for example, fatty acids, triglycerides or free and esterified cholesterol. Here we utilize Raman microscopy to image the metabolism of such lipids and follow subsequent storage or degradation patterns. The combination of optical microscopy with Raman spectroscopy allows visualization at the diffraction limit of the employed laser light and biochemical characterization through the associated spectral information. Relatively long measuring times, due to the weakness of Raman scattering can be overcome by non-linear effects such as coherent anti-Stokes Raman scattering (CARS). With this contribution we introduce first results to monitor the incorporation of lipid components into individual cells employing Raman and CARS microscopy.

  10. Alterations in cellular metabolism modulate CD1d-mediated NKT-cell responses.

    PubMed

    Webb, Tonya J; Carey, Gregory B; East, James E; Sun, Wenji; Bollino, Dominique R; Kimball, Amy S; Brutkiewicz, Randy R

    2016-08-01

    Natural killer T (NKT) cells play a critical role in the host's innate immune response. CD1d-mediated presentation of glycolipid antigens to NKT cells has been established; however, the mechanisms by which NKT cells recognize infected or cancerous cells remain unclear. 5(')-AMP activated protein kinase (AMPK) is a master regulator of lipogenic pathways. We hypothesized that activation of AMPK during infection and malignancy could alter the repertoire of antigens presented by CD1d and serve as a danger signal to NKT cells. In this study, we examined the effect of alterations in metabolism on CD1d-mediated antigen presentation to NKT cells and found that an infection with lymphocytic choriomeningitis virus rapidly increased CD1d-mediated antigen presentation. Hypoxia inducible factors (HIF) enhance T-cell effector functions during infection, therefore antigen presenting cells pretreated with pharmacological agents that inhibit glycolysis, induce HIF and activate AMPK were assessed for their ability to induce NKT-cell responses. Pretreatment with 2-deoxyglucose, cobalt chloride, AICAR and metformin significantly enhanced CD1d-mediated NKT-cell activation. In addition, NKT cells preferentially respond to malignant B cells and B-cell lymphomas express HIF-1α. These data suggest that targeting cellular metabolism may serve as a novel means of inducing innate immune responses. PMID:27297969

  11. Systematic quantification of complex metabolic flux networks using stable isotopes and mass spectrometry.

    PubMed

    Klapa, Maria I; Aon, Juan-Carlos; Stephanopoulos, Gregory

    2003-09-01

    Metabolic fluxes provide a detailed metric of the cellular metabolic phenotype. Fluxes are estimated indirectly from available measurements and various methods have been developed for this purpose. Of particular interest are methods making use of stable isotopic tracers as they enable the estimation of fluxes at a high resolution. In this paper, we present data validating the use of mass spectrometry (MS) for the quantification of complex metabolic flux networks. In the context of the lysine biosynthesis flux network of Corynebacterium glutamicum (ATCC 21799) under glucose limitation in continuous culture, operating at 0.1 x h(-1) after the introduction of 50% [1-13C]glucose, we deploy a bioreaction network analysis methodology for flux determination from mass isotopomer measurements of biomass hydrolysates, while thoroughly addressing the issues of measurement accuracy, flux observability and data reconciliation. The analysis enabled the resolution of the involved anaplerotic activity of the microorganism using only one labeled substrate, the determination of the range of most of the exchange fluxes and the validation of the flux estimates through satisfaction of redundancies. Specifically, we determined that phosphoenolpyruvate carboxykinase and synthase do not carry flux at these experimental conditions and identified a high futile cycle between oxaloacetate and pyruvate, indicating a highly active in vivo oxaloacetate decarboxylase. Both results validated previous in vitro activity measurements. The flux estimates obtained passed the chi2 statistical test. This is a very important result considering that prior flux analyses of extensive metabolic networks from isotopic measurements have failed criteria of statistical consistency. PMID:12919317

  12. Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors

    PubMed Central

    PETERSON, CHRISTINE; VANNUCCI, MARINA; KARAKAS, CEMAL; CHOI, WILLIAM; MA, LIHUA; MALETIĆ-SAVATIĆ, MIRJANA

    2014-01-01

    Metabolic processes are essential for cellular function and survival. We are interested in inferring a metabolic network in activated microglia, a major neuroimmune cell in the brain responsible for the neuroinflammation associated with neurological diseases, based on a set of quantified metabolites. To achieve this, we apply the Bayesian adaptive graphical lasso with informative priors that incorporate known relationships between covariates. To encourage sparsity, the Bayesian graphical lasso places double exponential priors on the off-diagonal entries of the precision matrix. The Bayesian adaptive graphical lasso allows each double exponential prior to have a unique shrinkage parameter. These shrinkage parameters share a common gamma hyperprior. We extend this model to create an informative prior structure by formulating tailored hyperpriors on the shrinkage parameters. By choosing parameter values for each hyperprior that shift probability mass toward zero for nodes that are close together in a reference network, we encourage edges between covariates with known relationships. This approach can improve the reliability of network inference when the sample size is small relative to the number of parameters to be estimated. When applied to the data on activated microglia, the inferred network includes both known relationships and associations of potential interest for further investigation. PMID:24533172

  13. MIRAGE: a functional genomics-based approach for metabolic network model reconstruction and its application to cyanobacteria networks.

    PubMed

    Vitkin, Edward; Shlomi, Tomer

    2012-01-01

    Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for these species. Then, it is applied to reconstruct genome-scale metabolic network models for 36 sequenced cyanobacteria amenable for constraint-based modeling analysis and specifically for metabolic engineering. The reconstructed network models are supplied via standard SBML files. PMID:23194418

  14. Synaptoproteomic Analysis of a Rat Gene-Environment Model of Depression Reveals Involvement of Energy Metabolism and Cellular Remodeling Pathways

    PubMed Central

    Failler, Marion; Corna, Stefano; Racagni, Giorgio; Mathé, Aleksander A.; Popoli, Maurizio

    2015-01-01

    Background: Major depression is a severe mental illness that causes heavy social and economic burdens worldwide. A number of studies have shown that interaction between individual genetic vulnerability and environmental risk factors, such as stress, is crucial in psychiatric pathophysiology. In particular, the experience of stressful events in childhood, such as neglect, abuse, or parental loss, was found to increase the risk for development of depression in adult life. Here, to reproduce the gene x environment interaction, we employed an animal model that combines genetic vulnerability with early-life stress. Methods: The Flinders Sensitive Line rats (FSL), a validated genetic animal model of depression, and the Flinders Resistant Line (FRL) rats, their controls, were subjected to a standard protocol of maternal separation (MS) from postnatal days 2 to 14. A basal comparison between the two lines for the outcome of the environmental manipulation was performed at postnatal day 73, when the rats were into adulthood. We carried out a global proteomic analysis of purified synaptic terminals (synaptosomes), in order to study a subcellular compartment enriched in proteins involved in synaptic function. Two-dimensional gel electrophoresis (2-DE), mass spectrometry, and bioinformatic analysis were used to analyze proteins and related functional networks that were modulated by genetic susceptibility (FSL vs. FRL) or by exposure to early-life stress (FRL + MS vs. FRL and FSL + MS vs. FSL). Results: We found that, at a synaptic level, mainly proteins and molecular pathways related to energy metabolism and cellular remodeling were dysregulated. Conclusions: The present results, in line with previous works, suggest that dysfunction of energy metabolism and cytoskeleton dynamics at a synaptic level could be features of stress-related pathologies, in particular major depression. PMID:25522407

  15. The evolution of metabolic networks of E. coli

    PubMed Central

    2011-01-01

    Background Despite the availability of numerous complete genome sequences from E. coli strains, published genome-scale metabolic models exist only for two commensal E. coli strains. These models have proven useful for many applications, such as engineering strains for desired product formation, and we sought to explore how constructing and evaluating additional metabolic models for E. coli strains could enhance these efforts. Results We used the genomic information from 16 E. coli strains to generate an E. coli pangenome metabolic network by evaluating their collective 76,990 ORFs. Each of these ORFs was assigned to one of 17,647 ortholog groups including ORFs associated with reactions in the most recent metabolic model for E. coli K-12. For orthologous groups that contain an ORF already represented in the MG1655 model, the gene to protein to reaction associations represented in this model could then be easily propagated to other E. coli strain models. All remaining orthologous groups were evaluated to see if new metabolic reactions could be added to generate a pangenome-scale metabolic model (iEco1712_pan). The pangenome model included reactions from a metabolic model update for E. coli K-12 MG1655 (iEco1339_MG1655) and enabled development of five additional strain-specific genome-scale metabolic models. These additional models include a second K-12 strain (iEco1335_W3110) and four pathogenic strains (two enterohemorrhagic E. coli O157:H7 and two uropathogens). When compared to the E. coli K-12 models, the metabolic models for the enterohemorrhagic (iEco1344_EDL933 and iEco1345_Sakai) and uropathogenic strains (iEco1288_CFT073 and iEco1301_UTI89) contained numerous lineage-specific gene and reaction differences. All six E. coli models were evaluated by comparing model predictions to carbon source utilization measurements under aerobic and anaerobic conditions, and to batch growth profiles in minimal media with 0.2% (w/v) glucose. An ancestral genome

  16. A malignant cellular network in gliomas: potential clinical implications.

    PubMed

    Osswald, Matthias; Solecki, Gergely; Wick, Wolfgang; Winkler, Frank

    2016-04-01

    The recent discovery of distinct, ultra-long, and highly functional membrane protrusions in gliomas, particularly in astrocytomas, extends our understanding of how these tumors progress in the brain and how they resist therapies. In this article, we will focus on ideas on how to target these membrane protrusions, for which we have suggested the term "tumor microtubes" (TMs), and the malignant multicellular network they form. First, we discuss TM-specific features and their differential biological functions known so far. Second, the connection between 1p/19q codeletion and the inability to form functional TMs via certain neurodevelopmental pathways is presented; this could provide an explanation for the distinct clinical features of oligodendrogliomas. Third, the role of TMs for primary and potentially also adaptive resistance to cytotoxic therapies is highlighted. Fourth, avenues for therapeutic approaches to inhibit TM formation and/or function are discussed, with a focus on disruption (or exploitation) of network functionality. Finally, we propose ideas on how to use TMs as a biomarker in glioma patients. An increasing understanding of TMs in clinical and preclinical settings will show us whether they really are a long-sought-after Achilles' heel of treatment-resistant gliomas. PMID:26995789

  17. Metabolomics integrated elementary flux mode analysis in large metabolic networks

    PubMed Central

    Gerstl, Matthias P.; Ruckerbauer, David E.; Mattanovich, Diethard; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2015-01-01

    Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size. However, many topologically feasible EFMs are biologically irrelevant. We present thermodynamic EFMA (tEFMA), which calculates only the small(er) subset of thermodynamically feasible EFMs. We integrate network embedded thermodynamics into EFMA and show that we can use the metabolome to identify and remove thermodynamically infeasible EFMs during an EFMA without losing biologically relevant EFMs. Calculating only the thermodynamically feasible EFMs strongly reduces memory consumption and program runtime, allowing the analysis of larger networks. We apply tEFMA to study the central carbon metabolism of E. coli and find that up to 80% of its EFMs are thermodynamically infeasible. Moreover, we identify glutamate dehydrogenase as a bottleneck, when E. coli is grown on glucose and explain its inactivity as a consequence of network embedded thermodynamics. We implemented tEFMA as a Java package which is available for download at https://github.com/mpgerstl/tEFMA. PMID:25754258

  18. Cellular Origins of Type IV Collagen Networks in Developing Glomeruli

    PubMed Central

    Abrahamson, Dale R.; Hudson, Billy G.; Stroganova, Larysa; Borza, Dorin-Bogdan; St. John, Patricia L.

    2009-01-01

    Laminin and type IV collagen composition of the glomerular basement membrane changes during glomerular development and maturation. Although it is known that both glomerular endothelial cells and podocytes produce different laminin isoforms at the appropriate stages of development, the cellular origins for the different type IV collagen heterotrimers that appear during development are unknown. Here, immunoelectron microscopy demonstrated that endothelial cells, mesangial cells, and podocytes of immature glomeruli synthesize collagen α1α2α1(IV). However, intracellular labeling revealed that podocytes, but not endothelial or mesangial cells, contain collagen α3α4α5(IV). To evaluate the origins of collagen IV further, we transplanted embryonic kidneys from Col4a3-null mutants (Alport mice) into kidneys of newborn, wildtype mice. Hybrid glomeruli within grafts containing numerous host-derived, wildtype endothelial cells never expressed collagen α3α4α5(IV). Finally, confocal microscopy of glomeruli from infant Alport mice that had been dually labeled with anti-collagen α5(IV) and the podocyte marker anti-GLEPP1 showed immunolabeling exclusively within podocytes. Together, these results indicate that collagen α3α4α5(IV) originates solely from podocytes; therefore, glomerular Alport disease is a genetic defect that manifests specifically within this cell type. PMID:19423686

  19. Cellular origins of type IV collagen networks in developing glomeruli.

    PubMed

    Abrahamson, Dale R; Hudson, Billy G; Stroganova, Larysa; Borza, Dorin-Bogdan; St John, Patricia L

    2009-07-01

    Laminin and type IV collagen composition of the glomerular basement membrane changes during glomerular development and maturation. Although it is known that both glomerular endothelial cells and podocytes produce different laminin isoforms at the appropriate stages of development, the cellular origins for the different type IV collagen heterotrimers that appear during development are unknown. Here, immunoelectron microscopy demonstrated that endothelial cells, mesangial cells, and podocytes of immature glomeruli synthesize collagen alpha 1 alpha 2 alpha1(IV). However, intracellular labeling revealed that podocytes, but not endothelial or mesangial cells, contain collagen alpha 3 alpha 4 alpha 5(IV). To evaluate the origins of collagen IV further, we transplanted embryonic kidneys from Col4a3-null mutants (Alport mice) into kidneys of newborn, wildtype mice. Hybrid glomeruli within grafts containing numerous host-derived, wildtype endothelial cells never expressed collagen alpha 3 alpha 4 alpha 5(IV). Finally, confocal microscopy of glomeruli from infant Alport mice that had been dually labeled with anti-collagen alpha 5(IV) and the podocyte marker anti-GLEPP1 showed immunolabeling exclusively within podocytes. Together, these results indicate that collagen alpha 3 alpha 4 alpha 5(IV) originates solely from podocytes; therefore, glomerular Alport disease is a genetic defect that manifests specifically within this cell type. PMID:19423686

  20. Estimating Metabolic Fluxes Using a Maximum Network Flexibility Paradigm

    PubMed Central

    Megchelenbrink, Wout; Rossell, Sergio; Huynen, Martijn A.

    2015-01-01

    Motivation Genome-scale metabolic networks can be modeled in a constraint-based fashion. Reaction stoichiometry combined with flux capacity constraints determine the space of allowable reaction rates. This space is often large and a central challenge in metabolic modeling is finding the biologically most relevant flux distributions. A widely used method is flux balance analysis (FBA), which optimizes a biologically relevant objective such as growth or ATP production. Although FBA has proven to be highly useful for predicting growth and byproduct secretion, it cannot predict the intracellular fluxes under all environmental conditions. Therefore, alternative strategies have been developed to select flux distributions that are in agreement with experimental “omics” data, or by incorporating experimental flux measurements. The latter, unfortunately can only be applied to a limited set of reactions and is currently not feasible at the genome-scale. On the other hand, it has been observed that micro-organisms favor a suboptimal growth rate, possibly in exchange for a more “flexible” metabolic network. Instead of dedicating the internal network state to an optimal growth rate in one condition, a suboptimal growth rate is used, that allows for an easier switch to other nutrient sources. A small decrease in growth rate is exchanged for a relatively large gain in metabolic capability to adapt to changing environmental conditions. Results Here, we propose Maximum Metabolic Flexibility (MMF) a computational method that utilizes this observation to find the most probable intracellular flux distributions. By mapping measured flux data from central metabolism to the genome-scale models of Escherichia coli and Saccharomyces cerevisiae we show that i) indeed, most of the measured fluxes agree with a high adaptability of the network, ii) this result can be used to further reduce the space of feasible solutions iii) this reduced space improves the quantitative predictions

  1. Characterizing the Network of Drugs and Their Affected Metabolic Subpathways

    PubMed Central

    Li, Jing; Han, Junwei; Wang, Shuyuan; Yao, Qianlan; Wang, Yingying; Zhang, Yunpeng; Zhang, Chunlong; Xu, Yanjun; Jiang, Wei; Li, Xia

    2012-01-01

    A fundamental issue in biology and medicine is illustration of the overall drug impact which is always the consequence of changes in local regions of metabolic pathways (subpathways). To gain insights into the global relationship between drugs and their affected metabolic subpathways, we constructed a drug–metabolic subpathway network (DRSN). This network included 3925 significant drug–metabolic subpathway associations representing drug dual effects. Through analyses based on network biology, we found that if drugs were linked to the same subpathways in the DRSN, they tended to share the same indications and side effects. Furthermore, if drugs shared more subpathways, they tended to share more side effects. We then calculated the association score by integrating drug-affected subpathways and disease-related subpathways to quantify the extent of the associations between each drug class and disease class. The results showed some close drug–disease associations such as sex hormone drugs and cancer suggesting drug dual effects. Surprisingly, most drugs displayed close associations with their side effects rather than their indications. To further investigate the mechanism of drug dual effects, we classified all the subpathways in the DRSN into therapeutic and non-therapeutic subpathways representing drug therapeutic effects and side effects. Compared to drug side effects, the therapeutic effects tended to work through tissue-specific genes and these genes tend to be expressed in the adrenal gland, liver and kidney; while drug side effects always occurred in the liver, bone marrow and trachea. Taken together, the DRSN could provide great insights into understanding the global relationship between drugs and metabolic subpathways. PMID:23112813

  2. The role of topological features of intercellular communication networks by the synchronization of cellular oscillators

    NASA Astrophysics Data System (ADS)

    Markovič, R.; Gosak, M.; Marhl, M.

    2012-08-01

    Because of the complexity of processes that govern the regulatory mechanisms which control the cellular functions and dynamic behavior, mathematical models and numerical simulations are needed to fully grasp the mechanisms and functions of biological rhythms. In the last decade the theory of complex networks is frequently applied to address those issues. In the present paper we investigate theoretically the role of the intercellular communication network structure by synchronization of cellular oscillators. Motivated by the fact that in biological systems the interplay between the network structure and the dynamics taking place on it is closely interrelated, we develop a spatial network representation of an ensemble of cells in which we can tune the network organization between a scale-free network with dominating long-range connections and a homogeneous network with mostly adjacent neurons connected. Our results reveal that for noise-induced oscillations in excitable cells and for chaotic bursting oscillations the most synchronized response is obtained for the intermediate regime where long-as well as short-range connections constitute the intercellular network. On the other hand, for periodic oscillations it is found than the scale-free network topology ensures the greatest collective response. We argue that those findings are related to flexibility properties of individual cells.

  3. Second Law of Thermodynamics Applied to Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Nigam, R.; Liang, S.

    2003-01-01

    We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

  4. Redox Modulation of Cellular Signaling and Metabolism Through Reversible Oxidation of Methionine Sensors in Calcium Regulatory Proteins

    SciTech Connect

    Bigelow, Diana J.; Squier, Thomas C.

    2005-01-17

    Adaptive responses associated with environmental stressors are critical to cell survival. These involve the modulation of central signaling protein functions through site-specific and enzymatically reversible oxidative modifications of methionines to coordinate cellular metabolism, energy utilization, and calcium signaling. Under conditions when cellular redox and antioxidant defenses are overwhelmed, the selective oxidation of critical methionines within selected protein sensors functions to down-regulate energy metabolism and the further generation of reactive oxygen species (ROS). Mechanistically, these functional changes within protein sensors take advantage of the helix-breaking character of methionine sulfoxide. Thus, depending on either the ecological niche of the organism or the cellular milieu of different organ systems, cellular metabolism can be fine-tuned to maintain optimal function in the face of variable amounts of collateral oxidative damage. The sensitivity of several calcium regulatory proteins to oxidative modification provides cellular sensors that link oxidative stress to cellular response and recovery. Calmodulin (CaM) is one such critical calcium regulatory protein, which is functionally sensitive to methionine oxidation. Helix destabilization resulting from the oxidation of either Met{sup 144} or Met{sup 145} results in the nonproductive association between CaM and target proteins. The ability of oxidized CaM to stabilize its target proteins in an inhibited state with an affinity similar to that of native (unoxidized) CaM permits this central regulatory protein to function as a cellular rheostat that down-regulates energy metabolism in response to oxidative stress. Likewise, oxidation of a methionine within a critical switch region of the regulatory protein phospholamban is expected to destabilize the phosphorylationdependent helix formation necessary for the release of enzyme inhibition, resulting in a down-regulation of the Ca-ATPase in

  5. Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory

    PubMed Central

    Takemoto, Kazuhiro

    2012-01-01

    Formation and adaptation of metabolic networks has been a long-standing question in biology. With recent developments in biotechnology and bioinformatics, the understanding of metabolism is progressively becoming clearer from a network perspective. This review introduces the comprehensive metabolic world that has been revealed by a wide range of data analyses and theoretical studies; in particular, it illustrates the role of evolutionary events, such as gene duplication and horizontal gene transfer, and environmental factors, such as nutrient availability and growth conditions, in evolution of the metabolic network. Furthermore, the mathematical models for the formation and adaptation of metabolic networks have also been described, according to the current understanding from a perspective of metabolic networks. These recent findings are helpful in not only understanding the formation of metabolic networks and their adaptation, but also metabolic engineering. PMID:24957641

  6. Beta Cell Formation in vivo Through Cellular Networking, Integration and Processing (CNIP) in Wild Type Adult Mice.

    PubMed

    Doiron, Bruno; Hu, Wenchao; DeFronzo, Ralph A

    2016-01-01

    Insulin replacement therapy is essential in type 1 diabetic individuals and is required in ~40- 50% of type 2 diabetics during their lifetime. Prior attempts at beta cell regeneration have relied upon pancreatic injury to induce beta cell proliferation, dedifferentiation and activation of the embryonic pathway, or stem cell replacement. We report an alternative method to transform adult non-stem (somatic) cells into pancreatic beta cells. The Cellular Networking, Integration and Processing (CNIP) approach targets cellular mechanisms involved in pancreatic function in the organ's adult state and utilizes a synergistic mechanism that integrates three important levels of cellular regulation to induce beta cell formation: (i) glucose metabolism, (ii) membrane receptor function, and (iii) gene transcription. The aim of the present study was to induce pancreatic beta cell formation in vivo in adult animals without stem cells and without dedifferentiating cells to recapitulate the embryonic pathway as previously published (1-3). Our results employing CNIP demonstrate that: (i) insulin secreting cells can be generated in adult pancreatic tissue in vivo and circumvent the problem of generating endocrine (glucagon and somatostatin) cells that exert deleterious effects on glucose homeostasis, and (ii) longterm normalization of glucose tolerance and insulin secretion can be achieved in a wild type diabetic mouse model. The CNIP cocktail has the potential to be used as a preventative or therapeutic treatment or cure for both type 1 and type 2 diabetes. PMID:26696016

  7. A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

    PubMed Central

    Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

    2013-01-01

    Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

  8. Cross-talk between circadian clocks, sleep-wake cycles, and metabolic networks: Dispelling the darkness.

    PubMed

    Ray, Sandipan; Reddy, Akhilesh B

    2016-04-01

    Integration of knowledge concerning circadian rhythms, metabolic networks, and sleep-wake cycles is imperative for unraveling the mysteries of biological cycles and their underlying mechanisms. During the last decade, enormous progress in circadian biology research has provided a plethora of new insights into the molecular architecture of circadian clocks. However, the recent identification of autonomous redox oscillations in cells has expanded our view of the clockwork beyond conventional transcription/translation feedback loop models, which have been dominant since the first circadian period mutants were identified in fruit fly. Consequently, non-transcriptional timekeeping mechanisms have been proposed, and the antioxidant peroxiredoxin proteins have been identified as conserved markers for 24-hour rhythms. Here, we review recent advances in our understanding of interdependencies amongst circadian rhythms, sleep homeostasis, redox cycles, and other cellular metabolic networks. We speculate that systems-level investigations implementing integrated multi-omics approaches could provide novel mechanistic insights into the connectivity between daily cycles and metabolic systems. PMID:26866932

  9. Cross‐talk between circadian clocks, sleep‐wake cycles, and metabolic networks: Dispelling the darkness

    PubMed Central

    Ray, Sandipan

    2016-01-01

    Integration of knowledge concerning circadian rhythms, metabolic networks, and sleep‐wake cycles is imperative for unraveling the mysteries of biological cycles and their underlying mechanisms. During the last decade, enormous progress in circadian biology research has provided a plethora of new insights into the molecular architecture of circadian clocks. However, the recent identification of autonomous redox oscillations in cells has expanded our view of the clockwork beyond conventional transcription/translation feedback loop models, which have been dominant since the first circadian period mutants were identified in fruit fly. Consequently, non‐transcriptional timekeeping mechanisms have been proposed, and the antioxidant peroxiredoxin proteins have been identified as conserved markers for 24‐hour rhythms. Here, we review recent advances in our understanding of interdependencies amongst circadian rhythms, sleep homeostasis, redox cycles, and other cellular metabolic networks. We speculate that systems‐level investigations implementing integrated multi‐omics approaches could provide novel mechanistic insights into the connectivity between daily cycles and metabolic systems. PMID:26866932

  10. Developmental changes in the metabolic network of snapdragon flowers.

    PubMed

    Muhlemann, Joëlle K; Maeda, Hiroshi; Chang, Ching-Yun; San Miguel, Phillip; Baxter, Ivan; Cooper, Bruce; Perera, M Ann; Nikolau, Basil J; Vitek, Olga; Morgan, John A; Dudareva, Natalia

    2012-01-01

    Evolutionary and reproductive success of angiosperms, the most diverse group of land plants, relies on visual and olfactory cues for pollinator attraction. Previous work has focused on elucidating the developmental regulation of pathways leading to the formation of pollinator-attracting secondary metabolites such as scent compounds and flower pigments. However, to date little is known about how flowers control their entire metabolic network to achieve the highly regulated production of metabolites attracting pollinators. Integrative analysis of transcripts and metabolites in snapdragon sepals and petals over flower development performed in this study revealed a profound developmental remodeling of gene expression and metabolite profiles in petals, but not in sepals. Genes up-regulated during petal development were enriched in functions related to secondary metabolism, fatty acid catabolism, and amino acid transport, whereas down-regulated genes were enriched in processes involved in cell growth, cell wall formation, and fatty acid biosynthesis. The levels of transcripts and metabolites in pathways leading to scent formation were coordinately up-regulated during petal development, implying transcriptional induction of metabolic pathways preceding scent formation. Developmental gene expression patterns in the pathways involved in scent production were different from those of glycolysis and the pentose phosphate pathway, highlighting distinct developmental regulation of secondary metabolism and primary metabolic pathways feeding into it. PMID:22808147

  11. Dengue Virus NS1 Protein Modulates Cellular Energy Metabolism by Increasing Glyceraldehyde-3-Phosphate Dehydrogenase Activity

    PubMed Central

    Allonso, Diego; Andrade, Iamara S.; Conde, Jonas N.; Coelho, Diego R.; Rocha, Daniele C. P.; da Silva, Manuela L.; Ventura, Gustavo T.

    2015-01-01

    ABSTRACT Dengue is one of the main public health concerns worldwide. Recent estimates indicate that over 390 million people are infected annually with the dengue virus (DENV), resulting in thousands of deaths. Among the DENV nonstructural proteins, the NS1 protein is the only one whose function during replication is still unknown. NS1 is a 46- to 55-kDa glycoprotein commonly found as both a membrane-associated homodimer and a soluble hexameric barrel-shaped lipoprotein. Despite its role in the pathogenic process, NS1 is essential for proper RNA accumulation and virus production. In the present study, we identified that glyceraldehyde-3-phosphate dehydrogenase (GAPDH) interacts with intracellular NS1. Molecular docking revealed that this interaction occurs through the hydrophobic protrusion of NS1 and the hydrophobic residues located at the opposite side of the catalytic site. Moreover, addition of purified recombinant NS1 enhanced the glycolytic activity of GAPDH in vitro. Interestingly, we observed that DENV infection promoted the relocalization of GAPDH to the perinuclear region, where NS1 is commonly found. Both DENV infection and expression of NS1 itself resulted in increased GAPDH activity. Our findings indicate that the NS1 protein acts to increase glycolytic flux and, consequently, energy production, which is consistent with the recent finding that DENV induces and requires glycolysis for proper replication. This is the first report to propose that NS1 is an important modulator of cellular energy metabolism. The data presented here provide new insights that may be useful for further drug design and the development of alternative antiviral therapies against DENV. IMPORTANCE Dengue represents a serious public health problem worldwide and is caused by infection with dengue virus (DENV). Estimates indicate that half of the global population is at risk of infection, with almost 400 million cases occurring per year. The NS1 glycoprotein is found in both the

  12. Sequence-based Network Completion Reveals the Integrality of Missing Reactions in Metabolic Networks*

    PubMed Central

    Krumholz, Elias W.; Libourel, Igor G. L.

    2015-01-01

    Genome-scale metabolic models are central in connecting genotypes to metabolic phenotypes. However, even for well studied organisms, such as Escherichia coli, draft networks do not contain a complete biochemical network. Missing reactions are referred to as gaps. These gaps need to be filled to enable functional analysis, and gap-filling choices influence model predictions. To investigate whether functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes. Quadratic programming revealed that the number of reactions that could partake in a gap-filling solution was vast: 3,270 in the case of E. coli, where 72% of the metabolites in the draft network could connect a gap-filling solution. Nonetheless, no network could be completed without the inclusion of orphaned enzymes, suggesting that parts of the biochemistry integral to biomass precursor formation are uncharacterized. However, many gap-filling reactions were well determined, and the resulting networks showed improved prediction of gene essentiality compared with networks generated through canonical gap filling. In addition, gene essentiality predictions that were sensitive to poorly determined gap-filling reactions were of poor quality, suggesting that damage to the network structure resulting from the inclusion of erroneous gap-filling reactions may be predictable. PMID:26041773

  13. Flexible Sheet-Type Sensor for Noninvasive Measurement of Cellular Oxygen Metabolism on a Culture Dish.

    PubMed

    Kojima, Mari; Takehara, Hiroaki; Akagi, Takanori; Shiono, Hirofumi; Ichiki, Takanori

    2015-01-01

    A novel flexible sensor was developed for the noninvasive oxygen metabolism measurement of cultivated cells and tissues. This device is composed of a transparent double-layered polymer sheet of ethylene-vinyl alcohol (EVOH) and poly(dimethylsiloxane) (PDMS) having an array of microhole structures of 90 μm diameter and 50 μm depth on its surface. All the microhole structures were equipped with a 1-μm-thick optical chemical sensing layer of platinum porphyrin-fluoropolymer on their bottom. The three-dimensional microstructures of the sensor were fabricated by a newly developed simple and low-cost production method named self-aligned hot embossing. The device was designed to be attached slightly above the cells cultivated on a dish to form a temporarily closed microspace over the target cells during measurement. Since the change in oxygen concentration is relatively fast in the microcompartmentalized culture medium, a rapid evaluation of the oxygen consumption rate is possible by measuring the phosphorescence lifetime of the platinum porphyrin-fluoropolymer. The combined use of the device and an automated optical measurement system enabled the high-throughput sensing of cellular oxygen consumption (100 points/min). We monitored the oxygen metabolism of the human breast cancer cell line MCF7 on a Petri dish and evaluated the oxygen consumption rate to be 0.72 ± 0.12 fmol/min/cell. Furthermore, to demonstrate the utility of the developed sensing system, we demonstrated the mapping of the oxygen consumption rate of rat brain slices and succeeded in visualizing a clear difference among the layer structures of the hippocampus, i.e., the cornu ammonis (CA1 and CA3) and dentate gyrus (DG). PMID:26624889

  14. Flexible Sheet-Type Sensor for Noninvasive Measurement of Cellular Oxygen Metabolism on a Culture Dish

    PubMed Central

    Akagi, Takanori; Shiono, Hirofumi; Ichiki, Takanori

    2015-01-01

    A novel flexible sensor was developed for the noninvasive oxygen metabolism measurement of cultivated cells and tissues. This device is composed of a transparent double-layered polymer sheet of ethylene-vinyl alcohol (EVOH) and poly(dimethylsiloxane) (PDMS) having an array of microhole structures of 90 μm diameter and 50 μm depth on its surface. All the microhole structures were equipped with a 1-μm-thick optical chemical sensing layer of platinum porphyrin-fluoropolymer on their bottom. The three-dimensional microstructures of the sensor were fabricated by a newly developed simple and low-cost production method named self-aligned hot embossing. The device was designed to be attached slightly above the cells cultivated on a dish to form a temporarily closed microspace over the target cells during measurement. Since the change in oxygen concentration is relatively fast in the microcompartmentalized culture medium, a rapid evaluation of the oxygen consumption rate is possible by measuring the phosphorescence lifetime of the platinum porphyrin-fluoropolymer. The combined use of the device and an automated optical measurement system enabled the high-throughput sensing of cellular oxygen consumption (100 points/min). We monitored the oxygen metabolism of the human breast cancer cell line MCF7 on a Petri dish and evaluated the oxygen consumption rate to be 0.72 ± 0.12 fmol/min/cell. Furthermore, to demonstrate the utility of the developed sensing system, we demonstrated the mapping of the oxygen consumption rate of rat brain slices and succeeded in visualizing a clear difference among the layer structures of the hippocampus, i.e., the cornu ammonis (CA1 and CA3) and dentate gyrus (DG). PMID:26624889

  15. Ocean warming alters cellular metabolism and induces mortality in fish early life stages: A proteomic approach.

    PubMed

    Madeira, D; Araújo, J E; Vitorino, R; Capelo, J L; Vinagre, C; Diniz, M S

    2016-07-01

    Climate change has pervasive effects on marine ecosystems, altering biodiversity patterns, abundance and distribution of species, biological interactions, phenology, and organisms' physiology, performance and fitness. Fish early life stages have narrow thermal windows and are thus more vulnerable to further changes in water temperature. The aim of this study was to address the sensitivity and underlying molecular changes of larvae of a key fisheries species, the sea bream Sparus aurata, towards ocean warming. Larvae were exposed to three temperatures: 18°C (control), 24°C (warm) and 30°C (heat wave) for seven days. At the end of the assay, i) survival curves were plotted for each temperature treatment and ii) entire larvae were collected for proteomic analysis via 2D gel electrophoresis, image analysis and mass spectrometry. Survival decreased with increasing temperature, with no larvae surviving at 30°C. Therefore, proteomic analysis was only carried out for 18°C and 24°C. Larvae up-regulated protein folding and degradation, cytoskeletal re-organization, transcriptional regulation and the growth hormone while mostly down-regulating cargo transporting and porphyrin metabolism upon exposure to heat stress. No changes were detected in proteins related to energetic metabolism suggesting that larval fish may not have the energetic plasticity needed to sustain cellular protection in the long-term. These results indicate that despite proteome modulation, S. aurata larvae do not seem able to fully acclimate to higher temperatures as shown by the low survival rates. Consequently, elevated temperatures seem to have bottleneck effects during fish early life stages, and future ocean warming can potentially compromise recruitment's success of key fisheries species. PMID:27062348

  16. An Organic Anion Transporter 1 (OAT1)-centered Metabolic Network.

    PubMed

    Liu, Henry C; Jamshidi, Neema; Chen, Yuchen; Eraly, Satish A; Cho, Sai Yee; Bhatnagar, Vibha; Wu, Wei; Bush, Kevin T; Abagyan, Ruben; Palsson, Bernhard O; Nigam, Sanjay K

    2016-09-01

    There has been a recent interest in the broader physiological importance of multispecific "drug" transporters of the SLC and ABC transporter families. Here, a novel multi-tiered systems biology approach was used to predict metabolites and signaling molecules potentially affected by the in vivo deletion of organic anion transporter 1 (Oat1, Slc22a6, originally NKT), a major kidney-expressed drug transporter. Validation of some predictions in wet-lab assays, together with re-evaluation of existing transport and knock-out metabolomics data, generated an experimentally validated, confidence ranked set of OAT1-interacting endogenous compounds enabling construction of an "OAT1-centered metabolic interaction network." Pathway and enrichment analysis indicated an important role for OAT1 in metabolism involving: the TCA cycle, tryptophan and other amino acids, fatty acids, prostaglandins, cyclic nucleotides, odorants, polyamines, and vitamins. The partly validated reconstructed network is also consistent with a major role for OAT1 in modulating metabolic and signaling pathways involving uric acid, gut microbiome products, and so-called uremic toxins accumulating in chronic kidney disease. Together, the findings are compatible with the hypothesized role of drug transporters in remote inter-organ and inter-organismal communication: The Remote Sensing and Signaling Hypothesis (Nigam, S. K. (2015) Nat. Rev. Drug Disc. 14, 29). The fact that OAT1 can affect many systemic biological pathways suggests that drug-metabolite interactions need to be considered beyond simple competition for the drug transporter itself and may explain aspects of drug-induced metabolic syndrome. Our approach should provide novel mechanistic insights into the role of OAT1 and other drug transporters implicated in metabolic diseases like gout, diabetes, and chronic kidney disease. PMID:27440044

  17. Systematic analysis of transcription-level effects of neurodegenerative diseases on human brain metabolism by a newly reconstructed brain-specific metabolic network

    PubMed Central

    Sertbaş, Mustafa; Ülgen, Kutlu; Çakır, Tunahan

    2014-01-01

    Network-oriented analysis is essential to identify those parts of a cell affected by a given perturbation. The effect of neurodegenerative perturbations in the form of diseases of brain metabolism was investigated by using a newly reconstructed brain-specific metabolic network. The developed stoichiometric model correctly represents healthy brain metabolism, and includes 630 metabolic reactions in and between astrocytes and neurons, which are controlled by 570 genes. The integration of transcriptome data of six neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, multiple sclerosis, schizophrenia) with the model was performed to identify reporter features specific and common for these diseases, which revealed metabolites and pathways around which the most significant changes occur. The identified metabolites are potential biomarkers for the pathology of the related diseases. Our model indicated perturbations in oxidative stress, energy metabolism including TCA cycle and lipid metabolism as well as several amino acid related pathways, in agreement with the role of these pathways in the studied diseases. The computational prediction of transcription factors that commonly regulate the reporter metabolites was achieved through binding-site analysis. Literature support for the identified transcription factors such as USF1, SP1 and those from FOX families are known from the literature to have regulatory roles in the identified reporter metabolic pathways as well as in the neurodegenerative diseases. In essence, the reconstructed brain model enables the elucidation of effects of a perturbation on brain metabolism and the illumination of possible machineries in which a specific metabolite or pathway acts as a regulatory spot for cellular reorganization. PMID:25061554

  18. Identification of driving network of cellular differentiation from single sample time course gene expression data

    NASA Astrophysics Data System (ADS)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  19. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  20. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-06-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  1. A self-learning call admission control scheme for CDMA cellular networks.

    PubMed

    Liu, Derong; Zhang, Yi; Zhang, Huaguang

    2005-09-01

    In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call admission controller can perform learning in real-time as well as in offline environments and the controller improves its performance as it gains more experience. Another important contribution in the present work is the choice of utility function for the present self-learning control approach which makes the present learning process much more efficient than existing learning control methods. The performance of our algorithm will be shown through computer simulation and compared with existing algorithms. PMID:16252828

  2. The Electrophysiological MEMS Device with Micro Channel Array for Cellular Network Analysis

    NASA Astrophysics Data System (ADS)

    Tonomura, Wataru; Kurashima, Toshiaki; Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

    This paper describes a new type of MCA (Micro Channel Array) for simultaneous multipoint measurement of cellular network. Presented MCA employing the measurement principles of the patch-clamp technique is designed for advanced neural network analysis which has been studied by co-authors using 64ch MEA (Micro Electrode Arrays) system. First of all, sucking and clamping of cells through channels of developed MCA is expected to improve electrophysiological signal detections. Electrophysiological sensing electrodes integrated around individual channels of MCA by using MEMS (Micro Electro Mechanical System) technologies are electrically isolated for simultaneous multipoint measurement. In this study, we tested the developed MCA using the non-cultured rat's cerebral cortical slice and the hippocampal neurons. We could measure the spontaneous action potential of the slice simultaneously at multiple points and culture the neurons on developed MCA. Herein, we describe the experimental results together with the design and fabrication of the electrophysiological MEMS device with MCA for cellular network analysis.

  3. Alteration of heme metabolism in a cellular model of Diamond-Blackfan anemia.

    PubMed

    Mercurio, Sonia; Aspesi, Anna; Silengo, Lorenzo; Altruda, Fiorella; Dianzani, Irma; Chiabrando, Deborah

    2016-04-01

    Diamond-Blackfan anemia (DBA) is a congenital pure red cell aplasia often associated with skeletal malformations. Mutations in ribosomal protein coding genes, mainly in RPS19, account for the majority of DBA cases. The molecular mechanisms underlying DBA pathogenesis are still not completely understood. Alternative spliced isoforms of FLVCR1 (feline leukemia virus subgroup C receptor 1) transcript coding for non-functional proteins have been reported in some DBA patients. Consistently, a phenotype very close to DBA has been described in animal models of FLVCR1 deficiency. FLVCR1 gene codes for two proteins: the plasma membrane heme exporter FLVCR1a and the mitochondrial heme exporter FLVCR1b. The coordinated expression of both FLVCR1 isoforms regulates an intracellular heme pool, necessary for proper expansion and differentiation of erythroid precursors. Here, we investigate the role of FLVCR1 isoforms in a cellular model of DBA. RPS19-downregulated TF1 cells show reduced FLVCR1a and FLVCR1b mRNA levels associated with heme overload. The downregulation of FLVCR1 isoforms affects cell cycle progression and apoptosis in differentiating K562 cells, a phenotype similar to DBA. Taken together, these data suggest that alteration of heme metabolism could play a role in the pathogenesis of DBA. PMID:26058344

  4. Neurophysiological, metabolic and cellular compartments that drive neurovascular coupling and neuroimaging signals.

    PubMed

    Moreno, Andrea; Jego, Pierrick; de la Cruz, Feliberto; Canals, Santiago

    2013-01-01

    Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals. PMID:23543907

  5. Neurophysiological, metabolic and cellular compartments that drive neurovascular coupling and neuroimaging signals

    PubMed Central

    Moreno, Andrea; Jego, Pierrick; de la Cruz, Feliberto; Canals, Santiago

    2013-01-01

    Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals. PMID:23543907

  6. Multi-objective optimization of enzyme manipulations in metabolic networks considering resilience effects

    PubMed Central

    2011-01-01

    Background Improving the synthesis rate of desired metabolites in metabolic systems is one of the main tasks in metabolic engineering. In the last decade, metabolic engineering approaches based on the mathematical optimization have been used extensively for the analysis and manipulation of metabolic networks. Experimental evidence shows that mutants reflect resilience phenomena against gene alterations. Although researchers have published many studies on the design of metabolic systems based on kinetic models and optimization strategies, almost no studies discuss the multi-objective optimization problem for enzyme manipulations in metabolic networks considering resilience phenomenon. Results This study proposes a generalized fuzzy multi-objective optimization approach to formulate the enzyme intervention problem for metabolic networks considering resilience phenomena and cell viability. This approach is a general framework that can be applied to any metabolic networks to investigate the influence of resilience phenomena on gene intervention strategies and maximum target synthesis rates. This study evaluates the performance of the proposed approach by applying it to two metabolic systems: S. cerevisiae and E. coli. Results show that the maximum synthesis rates of target products by genetic interventions are always over-estimated in metabolic networks that do not consider the resilience effects. Conclusions Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. The proposed generalized fuzzy multi-objective optimization approach has the potential to be a good and practical framework in the design of metabolic networks. PMID:21929795

  7. Flux Coupling Analysis of Genome-Scale Metabolic Network Reconstructions

    PubMed Central

    Burgard, Anthony P.; Nikolaev, Evgeni V.; Schilling, Christophe H.; Maranas, Costas D.

    2004-01-01

    In this paper, we introduce the Flux Coupling Finder (FCF) framework for elucidating the topological and flux connectivity features of genome-scale metabolic networks. The framework is demonstrated on genome-scale metabolic reconstructions of Helicobacter pylori, Escherichia coli, and Saccharomyces cerevisiae. The analysis allows one to determine whether any two metabolic fluxes, v1 and v2, are (1) directionally coupled, if a non-zero flux for v1 implies a non-zero flux for v2 but not necessarily the reverse; (2) partially coupled, if a non-zero flux for v1 implies a non-zero, though variable, flux for v2 and vice versa; or (3) fully coupled, if a non-zero flux for v1 implies not only a non-zero but also a fixed flux for v2 and vice versa. Flux coupling analysis also enables the global identification of blocked reactions, which are all reactions incapable of carrying flux under a certain condition; equivalent knockouts, defined as the set of all possible reactions whose deletion forces the flux through a particular reaction to zero; and sets of affected reactions denoting all reactions whose fluxes are forced to zero if a particular reaction is deleted. The FCF approach thus provides a novel and versatile tool for aiding metabolic reconstructions and guiding genetic manipulations. PMID:14718379

  8. Evidence that the tri-cellular metabolism of N-acetylaspartate functions as the brain's "operating system": how NAA metabolism supports meaningful intercellular frequency-encoded communications.

    PubMed

    Baslow, Morris H

    2010-11-01

    N-acetylaspartate (NAA), an acetylated derivative of L-aspartate (Asp), and N-acetylaspartylglutamate (NAAG), a derivative of NAA and L-glutamate (Glu), are synthesized by neurons in brain. However, neurons cannot catabolize either of these substances, and so their metabolism requires the participation of two other cell types. Neurons release both NAA and NAAG to extra-cellular fluid (ECF) upon stimulation, where astrocytes, the target cells for NAAG, hydrolyze it releasing NAA back into ECF, and oligodendrocytes, the target cells for NAA, hydrolyze it releasing Asp to ECF for recycling to neurons. This sequence is unique as it is the only known amino acid metabolic cycle in brain that requires three cell types for its completion. The results of this cycling are two-fold. First, neuronal metabolic water is transported to ECF for its removal from brain. Second, the rate of neuronal activity is coupled with focal hyperemia, providing stimulated neurons with the energy required for transmission of meaningful frequency-encoded messages. In this paper, it is proposed that the tri-cellular metabolism of NAA functions as the "operating system" of the brain, and is essential for normal cognitive and motor activities. Evidence in support of this hypothesis is provided by the outcomes of two human inborn errors in NAA metabolism. PMID:20563610

  9. Use of randomized sampling for analysis of metabolic networks.

    PubMed

    Schellenberger, Jan; Palsson, Bernhard Ø

    2009-02-27

    Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise in analyzing the systemic properties of these network reconstructions. Notably, constraint-based models have been used successfully to predict the phenotypic effects of knock-outs and for metabolic engineering. The inherent uncertainty in both parameters and variables of large-scale models is significant and is well suited to study by Monte Carlo sampling of the solution space. These techniques have been applied extensively to the reaction rate (flux) space of networks, with more recent work focusing on dynamic/kinetic properties. Monte Carlo sampling as an analysis tool has many advantages, including the ability to work with missing data, the ability to apply post-processing techniques, and the ability to quantify uncertainty and to optimize experiments to reduce uncertainty. We present an overview of this emerging area of research in systems biology. PMID:18940807

  10. Cellular automata with object-oriented features for parallel molecular network modeling.

    PubMed

    Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

    2005-06-01

    Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented. PMID:16117022

  11. Response of C2C12 Myoblasts to Hypoxia: The Relative Roles of Glucose and Oxygen in Adaptive Cellular Metabolism

    PubMed Central

    Li, Wei; Hu, Zhen-Fu; Chen, Bin; Ni, Guo-Xin

    2013-01-01

    Background. Oxygen and glucose are two important nutrients for mammalian cell function. In this study, the effect of glucose and oxygen concentrations on C2C12 cellular metabolism was characterized with an emphasis on detecting whether cells show oxygen conformance (OC) in response to hypoxia. Methods. After C2C12 cells being cultured in the levels of glucose at 0.6 mM (LG), 5.6 mM (MG), or 23.3 mM(HG) under normoxic or hypoxic (1% oxygen) condition, cellular oxygen consumption, glucose consumption, lactate production, and metabolic status were determined. Short-term oxygen consumption was measured with a novel oxygen biosensor technique. Longer-term measurements were performed with standard glucose, lactate, and cell metabolism assays. Results. It was found that oxygen depletion in normoxia is dependent on the glucose concentration in the medium. Cellular glucose uptake and lactate production increased significantly in hypoxia than those in normoxia. In hypoxia the cellular response to the level of glucose was different to that in normoxia. The metabolic activities decreased while glucose concentration increased in normoxia, while in hypoxia, metabolic activity was reduced in LG and MG, but unchanged in HG condition. The OC phenomenon was not observed in the present study. Conclusions. Our findings suggested that a combination of low oxygen and low glucose damages the viability of C2C12 cells more seriously than low oxygen alone. In addition, when there is sufficient glucose, C2C12 cells will respond to hypoxia by upregulating anaerobic respiration, as shown by lactate production. PMID:24294605

  12. Interference Avoiding Radio Resource Allocation Scheme for Multi-hop OFDMA Cellular Networks with Random Topology

    NASA Astrophysics Data System (ADS)

    Lim, Sunggook; Lee, Jaiyong

    Relaying technology is the one of the solutions to expand the coverage and enhance the throughput of a cellular network with low cost, therefore numerous smart relay stations (RSs) which are able to schedule its own transmission frame and manage radio resources allocated by its serving base station (BS) will be deployed within the cellular network. while more RSs are deployed, the network topology is turning to the random topology. In the random topology, however, conventional frequency reuse schemes based on the uniformly distributed RSs are not adoptable because of the randomness for locations of RSs. Another problem is severe increase of interference during the transmission period for an access link because more transmitters including BSs and RSs are existed within a cell. We suggest the random-topology frequency reuse (RFR) scheme supporting the frequency reuse in the cellular multi-hop network with random topology to reduce intra-cell interference. The simulation results show RFR is reducing the overall intra-cell interference compared to the full allocation scheme whose reuse factor is one. The throughput and average signal to interference plus noise ratio (SINR) is still greater than the full allocation scheme although the spectral efficiency is lower than the compared scheme.

  13. Alteration of cellular lipids and lipid metabolism markers in RTL-W1 cells exposed to model endocrine disrupters.

    PubMed

    Dimastrogiovanni, Giorgio; Córdoba, Marlon; Navarro, Isabel; Jáuregui, Olga; Porte, Cinta

    2015-08-01

    This work investigates the suitability of the rainbow trout liver cell line (RTL-W1) as an in-vitro model to study the ability of model endocrine disrupters, namely TBT, TPT, 4-NP, BPA and DEHP, to act as metabolic disrupters by altering cellular lipids and markers of lipid metabolism. Among the tested compounds, BPA and DEHP significantly increased the intracellular accumulation of triacylglycerols (TAGs), while all the compounds -apart from TPT-, altered membrane lipids - phosphatidylcholines (PCs) and plasmalogen PCs - indicating a strong interaction of the toxicants with cell membranes and cell signaling. RTL-W1 expressed a number of genes involved in lipid metabolism that were modulated by exposure to BPA, TBT and TPT (up-regulation of FATP1 and FAS) and 4-NP and DEHP (down-regulation of FAS and LPL). Multiple and complex modes of action of these chemicals were observed in RTL-W1 cells, both in terms of expression of genes related to lipid metabolism and alteration of cellular lipids. Although further characterization is needed, this might be a useful model for the detection of chemicals leading to steatosis or other diseases associated with lipid metabolism in fish. PMID:26143618

  14. Adaptation of chondrocytes to low oxygen tension: relationship between hypoxia and cellular metabolism.

    PubMed

    Rajpurohit, R; Koch, C J; Tao, Z; Teixeira, C M; Shapiro, I M

    1996-08-01

    In endochondral bone, the growth cartilage is the site of rapid growth. Since the vascular supply to the cartilage is limited, it is widely assumed that cells of the cartilage are hypoxic and that limitations in the oxygen supply regulate the energetic state of the maturing cells. In this report, we evaluate the effects of oxygen tension on chondrocyte energy metabolism, thiol status, and expression of transcription elements, HIF and AP-1. Imposition of an hypoxic environment on cultured chondrocytes caused a proportional increase in glucose utilization and elevated levels of lactate synthesis. Although we observed a statistical increase in the activities of phosphofructokinase, pyruvate kinase, lactate dehydrogenase, and creatine kinase after exposure to lowered oxygen concentrations, the effect was small. The cultured cells exhibited a decreased utilization of glutamine, possibly due to down regulation of mitochondrial function and inhibition of oxidative deamination. With respect to total energy generation, we noted that these cells are quite capable of maintaining the energy charge of the cell at low oxygen tensions. Indeed, no changes in the absolute quantity of adenine nucleotides or the energy charge ratio was observed. Hypoxia caused a decrease in the glutathione content of cultured chondrocytes and a concomitant rise in cell and medium cysteine levels. It is likely that the fall in cell glutathione level is due to decreased synthesis of the tripeptide under reduced oxygen stress and the limited supply of glutamate. The observed rise in cellular and medium cysteine levels probably reflects an increase in the rate of degradation of glutathione and a decrease in synthesis of the peptide. To explore how cells transduce these metabolic effects, gel retardation assays were used to study chondrocyte HIF and AP-1 binding activities. Chondrocyte nuclear preparations bound an HIF-oligonucleotide; however, at low oxygen tensions, no increase in HIF binding was

  15. Relating the sequential dynamics of excitatory neural networks to synaptic cellular automata.

    PubMed

    Nekorkin, V I; Dmitrichev, A S; Kasatkin, D V; Afraimovich, V S

    2011-12-01

    We have developed a new approach for the description of sequential dynamics of excitatory neural networks. Our approach is based on the dynamics of synapses possessing the short-term plasticity property. We suggest a model of such synapses in the form of a second-order system of nonlinear ODEs. In the framework of the model two types of responses are realized-the fast and the slow ones. Under some relations between their timescales a cellular automaton (CA) on the graph of connections is constructed. Such a CA has only a finite number of attractors and all of them are periodic orbits. The attractors of the CA determine the regimes of sequential dynamics of the original neural network, i.e., itineraries along the network and the times of successive firing of neurons in the form of bunches of spikes. We illustrate our approach on the example of a Morris-Lecar neural network. PMID:22225361

  16. Two programmed replicative lifespans of Saccharomyces cerevisiae formed by the endogenous molecular-cellular network.

    PubMed

    Hu, Jie; Zhu, Xiaomei; Wang, Xinan; Yuan, Ruoshi; Zheng, Wei; Xu, Minjuan; Ao, Ping

    2014-12-01

    Cellular replicative capacity is a therapeutic target for regenerative medicine as well as cancer treatment. The mechanism of replicative senescence and cell immortality is still unclear. We investigated the diauxic growth of Saccharomyces cerevisiae and demonstrate that the replicative capacity revealed by the yeast growth curve can be understood by using the dynamical property of the molecular-cellular network regulating S. cerevisiae. The endogenous network we proposed has a limit cycle when pheromone signaling is disabled, consistent with the exponential growth phase with an infinite replicative capacity. In the post-diauxic phase, the cooperative effect of the pheromone activated mitogen-activated protein kinase (MAPK) signaling pathway with the cell cycle leads to a fixed point attractor instead of the limit cycle. The cells stop dividing after several generations counting from the beginning of the post-diauxic growth. By tuning the MAPK pathway, S. cerevisiae therefore programs the number of offsprings it replicates. PMID:24447585

  17. A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy

    NASA Astrophysics Data System (ADS)

    Müller, Jens; Müller, Jan; Tetzlaff, Ronald

    2011-05-01

    For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.

  18. Application of GA in optimization of pore network models generated by multi-cellular growth algorithms

    NASA Astrophysics Data System (ADS)

    Jamshidi, Saeid; Boozarjomehry, Ramin Bozorgmehry; Pishvaie, Mahmoud Reza

    2009-10-01

    In pore network modeling, the void space of a rock sample is represented at the microscopic scale by a network of pores connected by throats. Construction of a reasonable representation of the geometry and topology of the pore space will lead to a reliable prediction of the properties of porous media. Recently, the theory of multi-cellular growth (or L-systems) has been used as a flexible tool for generation of pore network models which do not require any special information such as 2D SEM or 3D pore space images. In general, the networks generated by this method are irregular pore network models which are inherently closer to the complicated nature of the porous media rather than regular lattice networks. In this approach, the construction process is controlled only by the production rules that govern the development process of the network. In this study, genetic algorithm has been used to obtain the optimum values of the uncertain parameters of these production rules to build an appropriate irregular lattice network capable of the prediction of both static and hydraulic information of the target porous medium.

  19. Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli

    PubMed Central

    Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem; O’Brien, Edward J.; Szubin, Richard; Palsson, Bernhard O.

    2014-01-01

    The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response to iron availability using genome-wide measurements (ChIP-exo and RNA-seq). Integrative data analysis reveals that a total of 81 genes in 42 transcription units are directly regulated by three different modes of Fur regulation, including apo- and holo-Fur activation and holo-Fur repression. We show that Fur connects iron transport and utilization enzymes with negative-feedback loop pairs for iron homeostasis. In addition, direct involvement of Fur in the regulation of DNA synthesis, energy metabolism, and biofilm development is found. These results show how Fur exhibits a comprehensive regulatory role affecting many fundamental cellular processes linked to iron metabolism in order to coordinate the overall response of E. coli to iron availability. PMID:25222563

  20. Application of neural networks to channel assignment for cellular CDMA networks with multiple services and mobile base stations

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    1996-03-01

    The use of artificial neural networks to the channel assignment problem for cellular code- division multiple access (CDMA) telecommunications systems is considered. CDMA takes advantage of voice activity and spatial isolation because its capacity is only interference limited, unlike time-division multiple access (TDMA) and frequency-division multiple access (FDMA) where capacities are bandwidth limited. Any reduction in interference in CDMA translates linearly into increased capacity. FDMA and TDMA use a frequency reuse pattern as a method to increase capacity, while CDMA reuses the same frequency for all cells and gains a reuse efficiency by means of orthogonal codes. The latter method can improve system capacity by factors of four to six over digital TDMA or FDMA. Cellular carriers are planning to provide multiple communication services using CDMA in the next generation cellular system infrastructure. The approach of this study is the use of neural network methods for automatic and local network control, based on traffic behavior in specific cell cites and demand history. The goal is to address certain problems associated with the management of mobile and personal communication services in a cellular radio communications environment. In planning a cellular radio network, the operator assigns channels to the radio cells so that the probability of the processed carrier-to-interference ratio, CII, exceeding a predefined value is sufficiently low. The RF propagation, determined from the topography and infrastructure in the operating area, is used in conjunction with the densities of expected communications traffic to formulate interference constraints. These constraints state which radio cells may use the same code (channel) or adjacent channels at a time. The traffic loading and the number of service grades can also be used to calculate the number of required channels (codes) for each cell. The general assignment problem is the task of assigning the required number

  1. Co-evolution of Hormone Metabolism and Signaling Networks Expands Plant Adaptive Plasticity.

    PubMed

    Weng, Jing-Ke; Ye, Mingli; Li, Bin; Noel, Joseph P

    2016-08-11

    Classically, hormones elicit specific cellular responses by activating dedicated receptors. Nevertheless, the biosynthesis and turnover of many of these hormone molecules also produce chemically related metabolites. These molecules may also possess hormonal activities; therefore, one or more may contribute to the adaptive plasticity of signaling outcomes in host organisms. Here, we show that a catabolite of the plant hormone abscisic acid (ABA), namely phaseic acid (PA), likely emerged in seed plants as a signaling molecule that fine-tunes plant physiology, environmental adaptation, and development. This trait was facilitated by both the emergence-selection of a PA reductase that modulates PA concentrations and by the functional diversification of the ABA receptor family to perceive and respond to PA. Our results suggest that PA serves as a hormone in seed plants through activation of a subset of ABA receptors. This study demonstrates that the co-evolution of hormone metabolism and signaling networks can expand organismal resilience. PMID:27518563

  2. Cellular Neural Network Models of Growth and Immune of Effector Cells Response to Cancer

    NASA Astrophysics Data System (ADS)

    Su, Yongmei; Min, Lequan

    Four reaction-diffusion cellular neural network (R-D CNN) models are set up based on the differential equation models for the growths of effector cells and cancer cells, and the model of the immune response to cancer proposed by Allison et al. The CNN models have different reaction-diffusion coefficients and coupling parameters. The R-D CNN models may provide possible quantitative interpretations, and are good in agreement with the in vitro experiment data reported by Allison et al.

  3. Cellular metabolic energy modulation by tangeretin in 7,12-dimethylbenz(a) anthracene-induced breast cancer

    PubMed Central

    Periyasamy, Kuppusamy; Sivabalan, Venkatachalam; Baskaran, Kuppusamy; Kasthuri, Kannayiram; Sakthisekaran, Dhanapal

    2016-01-01

    Abstract Breast cancer is the leading cause of death among women worldwide. Chemoprevention and chemotherapy play beneficial roles in reducing the incidence and mortality of cancer. Epidemiological and experimental studies showed that naturally-occurring antioxidants present in the diet may act as anticancer agents. Identifying the abnormalities of cellular energy metabolism facilitates early detection and management of breast cancer. The present study evaluated the effect of tangeretin on cellular metabolic energy fluxes in 7,12-dimethylbenz(a) anthracene (DMBA)-induced proliferative breast cancer. The results showed that the activities of glycolytic enzymes significantly increased in mammary tissues of DMBA-induced breast cancer bearing rats. The gluconeogenic tricarboxylic acid (TCA) cycle and respiratory chain enzyme activities significantly decreased in breast cancer-bearing rats. In addition, proliferating cell nuclear antigen (PCNA) was highly expressed in breast cancer tissues. However, the activities of glycolytic enzymes were significantly normalized in the tangeretin pre- and post-treated rats and the TCA cycle and respiratory chain enzyme activities were significantly increased in tangeretin treated rats. Furthermore, tangeretin down-regulated PCNA expression on breast cancer-bearing rats. Our study demonstrates that tangeretin specifically regulates cellular metabolic energy fluxes in DMBA-induced breast cancer-bearing rats.

  4. Measuring information flow in cellular networks by the systems biology method through microarray data

    PubMed Central

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells. PMID:26082788

  5. Inactivation of Metabolic Genes Causes Short- and Long-Range dys-Regulation in Escherichia coli Metabolic Network

    PubMed Central

    Barupal, Dinesh Kumar; Lee, Sang Jun; Karoly, Edward D.; Adhya, Sankar

    2013-01-01

    The metabolic network in E. coli can be severely affected by the inactivation of metabolic genes that are required to catabolize a nutrient (D-galactose). We hypothesized that the resulting accumulation of small molecules can yield local as well as systemic effects on the metabolic network. Analysis of metabolomics data in wild-type and D-galactose non-utilizing mutants, galT, galU and galE, reveal the large metabolic differences between the wild-type and the mutants when the strains were grown in D-galactose. Network mapping suggested that the enzymatic defects affected the metabolic modules located both at short- and long-ranges from the D-galactose metabolic module. These modules suggested alterations in glutathione, energy, nucleotide and lipid metabolism and disturbed carbon to nitrogen ratio in mutant strains. The altered modules are required for normal cell growth for the wild-type strain, explaining why the cell growth is inhibited in the mutants in the presence of D-galactose. Identification of these distance-based dys-regulations would enhance the systems level understanding of metabolic networks of microorganisms having importance in biomedical and biotechnological research. PMID:24363806

  6. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols.

    PubMed

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-01-01

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

  7. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols

    PubMed Central

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-01-01

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

  8. An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

    PubMed

    Matsubara, Takashi; Torikai, Hiroyuki

    2016-04-01

    Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources. PMID:25974951

  9. SIRT1-dependent regulation of chromatin and transcription: linking NAD(+) metabolism and signaling to the control of cellular functions.

    PubMed

    Zhang, Tong; Kraus, W Lee

    2010-08-01

    Sirtuins comprise a family of NAD(+)-dependent protein deacetylases and ADP-ribosyltransferases. Mammalian SIRT1 - a homolog of yeast Sir2, the prototypical member of the sirtuin family - is an important regulator of metabolism, cell differentiation and senescence, stress response, and cancer. As an NAD(+)-dependent enzyme, SIRT1 regulates gene expression programs in response to cellular metabolic status, thereby coordinating metabolic adaptation of the whole organism. Several important mechanisms have emerged for SIRT1-dependent regulation of transcription. First, SIRT1 can modulate chromatin function through direct deacetylation of histones as well as by promoting alterations in the methylation of histones and DNA, leading to the repression of transcription. The latter is accomplished through the recruitment of other nuclear enzymes to chromatin for histone methylation and DNA CpG methylation, suggesting a broader role of SIRT1 in epigenetic regulation. Second, SIRT1 can interact and deacetylate a broad range of transcription factors and coregulators, thereby regulating target gene expression both positively and negatively. Cellular energy state, specifically NAD(+) metabolism, plays a major role in the regulation of SIRT1 activity. Recent studies on the NAD(+) biosynthetic enzymes in the salvage pathway, nicotinamide phosphoribosyltransferase (NAMPT) and nicotinamide mononucleotide adenylyltransferase 1 (NMNAT-1), have revealed important functions for these enzymes in SIRT1-dependent transcription regulation. The collective molecular actions of SIRT1 control specific patterns of gene expression that modulate a wide variety of physiological outcomes. PMID:19879981

  10. Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network

    PubMed Central

    Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  11. Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network.

    PubMed

    Li, Limin; Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  12. Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes

    NASA Astrophysics Data System (ADS)

    Stamper, I. J.; Jackson, Elais; Wang, Xujing

    2014-01-01

    In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

  13. Perspectives for a better understanding of the metabolic integration of photorespiration within a complex plant primary metabolism network.

    PubMed

    Hodges, Michael; Dellero, Younès; Keech, Olivier; Betti, Marco; Raghavendra, Agepati S; Sage, Rowan; Zhu, Xin-Guang; Allen, Doug K; Weber, Andreas P M

    2016-05-01

    Photorespiration is an essential high flux metabolic pathway that is found in all oxygen-producing photosynthetic organisms. It is often viewed as a closed metabolic repair pathway that serves to detoxify 2-phosphoglycolic acid and to recycle carbon to fuel the Calvin-Benson cycle. However, this view is too simplistic since the photorespiratory cycle is known to interact with several primary metabolic pathways, including photosynthesis, nitrate assimilation, amino acid metabolism, C1 metabolism and the Krebs (TCA) cycle. Here we will review recent advances in photorespiration research and discuss future priorities to better understand (i) the metabolic integration of the photorespiratory cycle within the complex network of plant primary metabolism and (ii) the importance of photorespiration in response to abiotic and biotic stresses. PMID:27053720

  14. Flavonoid apigenin is an inhibitor of the NAD+ ase CD38: implications for cellular NAD+ metabolism, protein acetylation, and treatment of metabolic syndrome.

    PubMed

    Escande, Carlos; Nin, Veronica; Price, Nathan L; Capellini, Verena; Gomes, Ana P; Barbosa, Maria Thereza; O'Neil, Luke; White, Thomas A; Sinclair, David A; Chini, Eduardo N

    2013-04-01

    Metabolic syndrome is a growing health problem worldwide. It is therefore imperative to develop new strategies to treat this pathology. In the past years, the manipulation of NAD(+) metabolism has emerged as a plausible strategy to ameliorate metabolic syndrome. In particular, an increase in cellular NAD(+) levels has beneficial effects, likely because of the activation of sirtuins. Previously, we reported that CD38 is the primary NAD(+)ase in mammals. Moreover, CD38 knockout mice have higher NAD(+) levels and are protected against obesity and metabolic syndrome. Here, we show that CD38 regulates global protein acetylation through changes in NAD(+) levels and sirtuin activity. In addition, we characterize two CD38 inhibitors: quercetin and apigenin. We show that pharmacological inhibition of CD38 results in higher intracellular NAD(+) levels and that treatment of cell cultures with apigenin decreases global acetylation as well as the acetylation of p53 and RelA-p65. Finally, apigenin administration to obese mice increases NAD(+) levels, decreases global protein acetylation, and improves several aspects of glucose and lipid homeostasis. Our results show that CD38 is a novel pharmacological target to treat metabolic diseases via NAD(+)-dependent pathways. PMID:23172919

  15. A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue

    PubMed Central

    2011-01-01

    Background Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate. Results We have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung. Conclusions The results presented here describe the construction of a cellular stress network model and its

  16. Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

    NASA Astrophysics Data System (ADS)

    Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

    2015-05-01

    Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

  17. The in vitro manipulation of carbohydrate metabolism: a new strategy for deciphering the cellular defence mechanisms against nitric oxide attack.

    PubMed Central

    Le Goffe, C; Vallette, G; Jarry, A; Bou-Hanna, C; Laboisse, C L

    1999-01-01

    This study was aimed at examining the effects of manipulating the carbohydrate source of the culture medium on the cellular sensitivity of epithelial cells to an oxidative attack. Our rationale was that substituting galactose for glucose in culture media would remove the protection afforded by glucose utilization in two major metabolic pathways, i.e. anaerobic glycolysis and/or the pentose phosphate pathway (PPP), which builds up cellular reducing power. Indeed, we show that the polarized human colonic epithelial cell line HT29-Cl.16E was sensitive to the deleterious effects of the NO donor PAPANONOate [3-(2-hydroxy-2-nitroso-1-propylhydrazino)-1-propanamine] only in galactose-containing medium. In such medium NO attack led to cytotoxic and apoptotic cell death, associated with formation of derivatives of NO auto-oxidation (collectively termed NOx) and peroxynitrite, leading to intracellular GSH depletion and nitrotyrosine formation. The addition of 2-deoxyglucose, a non-glycolytic substrate, to galactose-fed cells protected HT29-Cl. 16E cells from NO attack and maintained control GSH levels through its metabolic utilization in the PPP, as shown by (14)CO(2) production from 2-deoxy[1-(14)C]glucose. Therefore, increasing the availability of reducing equivalents without interfering with energy metabolism is able to prevent NO-induced cell injury. Finally, this background provides the conceptual framework for establishing nutritional manipulation of cellular metabolic pathways that could provide new means for (i) deciphering the mechanisms of cell injury by reactive nitrogen species and reactive oxygen species at the whole-cell level and (ii) establishing the hierarchy of intracellular defence mechanisms against these attacks. PMID:10585850

  18. A flexible state-space approach for the modeling of metabolic networks II: advanced interrogation of hybridoma metabolism.

    PubMed

    Baughman, Adam C; Sharfstein, Susan T; Martin, Lealon L

    2011-03-01

    Having previously introduced the mathematical framework of topological metabolic analysis (TMA) - a novel optimization-based technique for modeling metabolic networks of arbitrary size and complexity - we demonstrate how TMA facilitates unique methods of metabolic interrogation. With the aid of several hybridoma metabolic investigations as case-studies (Bonarius et al., 1995, 1996, 2001), we first establish that the TMA framework identifies biologically important aspects of the metabolic network under investigation. We also show that the use of a structured weighting approach within our objective provides a substantial modeling benefit over an unstructured, uniform, weighting approach. We then illustrate the strength of TAM as an advanced interrogation technique, first by using TMA to prove the existence of (and to quantitatively describe) multiple topologically distinct configurations of a metabolic network that each optimally model a given set of experimental observations. We further show that such alternate topologies are indistinguishable using existing stoichiometric modeling techniques, and we explain the biological significance of the topological variables appearing within our model. By leveraging the manner in which TMA implements metabolite inputs and outputs, we also show that metabolites whose possible metabolic fates are inadequately described by a given network reconstruction can be quickly identified. Lastly, we show how the use of the TMA aggregate objective function (AOF) permits the identification of modeling solutions that can simultaneously consider experimental observations, underlying biological motivations, or even purely engineering- or design-based goals. PMID:21163360

  19. Optimal design of sewer networks using cellular automata-based hybrid methods: Discrete and continuous approaches

    NASA Astrophysics Data System (ADS)

    Afshar, M. H.; Rohani, M.

    2012-01-01

    In this article, cellular automata based hybrid methods are proposed for the optimal design of sewer networks and their performance is compared with some of the common heuristic search methods. The problem of optimal design of sewer networks is first decomposed into two sub-optimization problems which are solved iteratively in a two stage manner. In the first stage, the pipe diameters of the network are assumed fixed and the nodal cover depths of the network are determined by solving a nonlinear sub-optimization problem. A cellular automata (CA) method is used for the solution of the optimization problem with the network nodes considered as the cells and their cover depths as the cell states. In the second stage, the nodal cover depths calculated from the first stage are fixed and the pipe diameters are calculated by solving a second nonlinear sub-optimization problem. Once again a CA method is used to solve the optimization problem of the second stage with the pipes considered as the CA cells and their corresponding diameters as the cell states. Two different updating rules are derived and used for the CA of the second stage depending on the treatment of the pipe diameters. In the continuous approach, the pipe diameters are considered as continuous variables and the corresponding updating rule is derived mathematically from the original objective function of the problem. In the discrete approach, however, an adhoc updating rule is derived and used taking into account the discrete nature of the pipe diameters. The proposed methods are used to optimally solve two sewer network problems and the results are presented and compared with those obtained by other methods. The results show that the proposed CA based hybrid methods are more efficient and effective than the most powerful search methods considered in this work.

  20. Cellular neural network-based hybrid approach toward automatic image registration

    NASA Astrophysics Data System (ADS)

    Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

    2013-01-01

    Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

  1. Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

    PubMed Central

    Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; Overall, Christopher C.; Hill, Eric A.; Beliaev, Alexander S.

    2015-01-01

    Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as “topologically important.” Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as “functionally important” genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles. PMID:25826650

  2. Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

    SciTech Connect

    Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; Overall, Christopher C.; Hill, Eric A.; Beliaev, Alex S.

    2015-03-27

    Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

  3. Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

    DOE PAGESBeta

    Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; Overall, Christopher C.; Hill, Eric A.; Beliaev, Alex S.

    2015-03-27

    Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

  4. A Bayesian Approach to the Evolution of Metabolic Networks on a Phylogeny

    PubMed Central

    Mithani, Aziz; Preston, Gail M.; Hein, Jotun

    2010-01-01

    The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks. PMID:20700467

  5. Dopaminergic correlates of metabolic network activity in Parkinson's disease.

    PubMed

    Holtbernd, Florian; Ma, Yilong; Peng, Shichun; Schwartz, Frank; Timmermann, Lars; Kracht, Lutz; Fink, Gereon R; Tang, Chris C; Eidelberg, David; Eggers, Carsten

    2015-09-01

    Parkinson's disease (PD) is associated with distinct metabolic covariance patterns that relate to the motor and cognitive manifestations of the disorder. It is not known, however, how the expression of these patterns relates to measurements of nigrostriatal dopaminergic activity from the same individuals. To explore these associations, we studied 106 PD subjects who underwent cerebral PET with both (18) F-fluorodeoxyglucose (FDG) and (18) F-fluoro-L-dopa (FDOPA). Expression values for the PD motor- and cognition-related metabolic patterns (PDRP and PDCP, respectively) were computed for each subject; these measures were correlated with FDOPA uptake on a voxel-by-voxel basis. To explore the relationship between dopaminergic function and local metabolic activity, caudate and putamen FDOPA PET signal was correlated voxel-wise with FDG uptake over the entire brain. PDRP expression correlated with FDOPA uptake in caudate and putamen (P < 0.001), while PDCP expression correlated with uptake in the anterior striatum (P < 0.001). While statistically significant, the correlations were only of modest size, accounting for less than 20% of the overall variation in these measures. After controlling for PDCP expression, PDRP correlations were significant only in the posterior putamen. Of note, voxel-wise correlations between caudate/putamen FDOPA uptake and whole-brain FDG uptake were significant almost exclusively in PDRP regions. Overall, the data indicate that PDRP and PDCP expression correlates significantly with PET indices of presynaptic dopaminergic functioning obtained in the same individuals. Even so, the modest size of these correlations suggests that in PD patients, individual differences in network activity cannot be explained solely by nigrostriatal dopamine loss. PMID:26037537

  6. Microbial diversity and metabolic networks in acid mine drainage habitats

    PubMed Central

    Méndez-García, Celia; Peláez, Ana I.; Mesa, Victoria; Sánchez, Jesús; Golyshina, Olga V.; Ferrer, Manuel

    2015-01-01

    Acid mine drainage (AMD) emplacements are low-complexity natural systems. Low-pH conditions appear to be the main factor underlying the limited diversity of the microbial populations thriving in these environments, although temperature, ionic composition, total organic carbon, and dissolved oxygen are also considered to significantly influence their microbial life. This natural reduction in diversity driven by extreme conditions was reflected in several studies on the microbial populations inhabiting the various micro-environments present in such ecosystems. Early studies based on the physiology of the autochthonous microbiota and the growing success of omics-based methodologies have enabled a better understanding of microbial ecology and function in low-pH mine outflows; however, complementary omics-derived data should be included to completely describe their microbial ecology. Furthermore, recent updates on the distribution of eukaryotes and archaea recovered through sterile filtering (herein referred to as filterable fraction) in these environments demand their inclusion in the microbial characterization of AMD systems. In this review, we present a complete overview of the bacterial, archaeal (including filterable fraction), and eukaryotic diversity in these ecosystems, and include a thorough depiction of the metabolism and element cycling in AMD habitats. We also review different metabolic network structures at the organismal level, which is necessary to disentangle the role of each member of the AMD communities described thus far. PMID:26074887

  7. Effects of in vitro Brevetoxin Exposure on Apoptosis and Cellular Metabolism in a Leukemic T Cell Line (Jurkat)

    PubMed Central

    Walsh, Catherine J.; Leggett, Stephanie R.; Strohbehn, Kathryn; Pierce, Richard H.; Sleasman, John W.

    2008-01-01

    Harmful algal blooms (HABs) of the toxic dinoflagellate, Karenia brevis, produce red tide toxins, or brevetoxins. Significant health effects associated with red tide toxin exposure have been reported in sea life and in humans, with brevetoxins documented within immune cells from many species. The objective of this research was to investigate potential immunotoxic effects of brevetoxins using a leukemic T cell line (Jurkat) as an in vitro model system. Viability, cell proliferation, and apoptosis assays were conducted using brevetoxin congeners PbTx-2, PbTx-3, and PbTx-6. The effects of in vitro brevetoxin exposure on cell viability and cellular metabolism or proliferation were determined using trypan blue and MTT (1-(4,5-dimethylthiazol-2-yl)-3,5-diphenylformazan), respectively. Using MTT, cellular metabolic activity was decreased in Jurkat cells exposed to 5 – 10 μg/ml PbTx-2 or PbTx-6. After 3 h, no significant effects on cell viability were observed with any toxin congener in concentrations up to 10 μg/ml. Viability decreased dramatically after 24 h in cells treated with PbTx-2 or -6. Apoptosis, as measured by caspase-3 activity, was significantly increased in cells exposed to PbTx-2 or PbTx-6. In summary, brevetoxin congeners varied in effects on Jurkat cells, with PbTx-2 and PbTx-6 eliciting greater cellular effects compared to PbTx-3. PMID:18728729

  8. Expression of transferrin receptors on mitogen-stimulated human peripheral blood lymphocytes: relation to cellular activation and related metabolic events.

    PubMed Central

    Galbraith, R M; Galbraith, G M

    1981-01-01

    Mitogen-activated normal human peripheral blood lymphocytes bind transferrin to specific membrane receptors. In this study, lymphocytes stimulated with phytohaemagglutinin for 0-66 hr were examined to determine the relation of this phenomenon to cellular activation and related metabolic events. Transferrin receptors were first detected at 20-24 hr. This event was consistently preceded by RNA and protein turnover which commenced during the first 6 hr of culture, whereas initiation of DNA synthesis was detected concurrently with the appearance of receptors or slightly later (24-30 hr). Exposure of cells to inhibitors of RNA and protein synthesis early during culture (at 0 or 24 hr) prevented the expression of transferrin receptors, but also caused generalized metabolic failure, and abrogated cellular activation. In contrast, later addition of these agents at 48 hr did not interfere significantly with the process of activation, but did suppress the terminal increase in receptor-bearing cells observed during the final 18 hr in control cultures lacking inhibitor. After deliberate thermal stripping of receptors from activated cells, the reappearance of membrance binding sites which normally occurred within 30 min, was also blocked by cycloheximide, puromycin and actinomycin D. However, similar inhibition of DNA which was induced by hydroxyurea had much less effect upon both the initial appearance of receptors and their reappearance after ligand-induced depletion. These results demonstrate that the appearance of transferrin receptors upon human lymphocytes is dependent upon cellular activation and requires synthesis of protein and RNA. PMID:6172372

  9. A multimedia session-aware QoS provisioning scheme for cellular networks

    NASA Astrophysics Data System (ADS)

    Rizvi, Mona E.; Olariu, Stephan

    2005-03-01

    Multimedia applications often involve a set of cooperating streams that together form a multimedia session. We propose a novel local QoS provisioning scheme for cellular networks that is aware of the relationships between the streams that compose a session. As a rule, existing schemes either allow composite streams to compete with one another for resources or else provide QoS to the session as an atomic entity, leaving to the application the task of managing QoS for the individual streams. Our new MUltimedia SessIon-aware Cellular (MUSIC) QoS provisioning scheme manages the QoS of the individual streams in a session, and with the knowledge of their relationships, it prevents competition between the streams. Further, by allowing an application-specified prioritization between streams in a session, MUSIC scheme features a significant improvement in performance over session-unaware schemes.

  10. Segmentation algorithm via Cellular Neural/Nonlinear Network: implementation on Bio-inspired hardware platform

    NASA Astrophysics Data System (ADS)

    Karabiber, Fethullah; Vecchio, Pietro; Grassi, Giuseppe

    2011-12-01

    The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.

  11. Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise

    NASA Astrophysics Data System (ADS)

    Hinczewski, Michael; Thirumalai, D.

    2014-10-01

    Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.

  12. Cellular network formation of hydrophobic alkanethiol capped gold nanoparticles on mica surface mediated by water islands.

    PubMed

    John, Neena S; Raina, Gargi; Sharma, Ashutosh; Kulkarni, Giridhar U

    2010-09-01

    Dendritic and cellular networks of nanoparticles are known to form commonly either by random diffusion-limited aggregation or by solvent evaporation dynamics. Using alkanethiol capped gold nanoparticles deposited on mica imaged under ambient and controlled water vapor conditions by atomic force microscope and in situ scanning electron microscope, respectively, we show a third mechanism in action. The cellular network consisting of open and closed polygons is formed by the nucleation and lateral growth of adsorbed water islands, the contact lines of which push the randomly distributed hydrophobic nanoparticles along the growth directions, eventually leading to the polygonal structure formation as the boundaries of the growing islands meet. Such nanoparticle displacement has been possible due to the weakly adhering nature of the hydrophilic substrate, mica. These results demonstrate an important but hitherto neglected effect of adsorbed water in the structure formation on hydrophilic substrates and provide a facile tool for the fabrication of nanoparticle networks without specific particle or substrate modifications and without a tight control on particle deposition conditions during the solvent evaporation. PMID:20831330

  13. Rearrangements of the transcriptional regulatory networks of metabolic pathways in fungi

    PubMed Central

    Lavoie, Hugo; Hogues, Hervé; Whiteway, Malcolm

    2013-01-01

    Growing evidence suggests that transcriptional regulatory networks in many organisms are highly flexible. Here, we discuss the evolution of transcriptional regulatory networks governing the metabolic machinery of sequenced ascomycetes. In particular, recent work has shown that transcriptional rewiring is common in regulons controlling processes such as production of ribosome components and metabolism of carbohydrates and lipids. We note that dramatic rearrangements of the transcriptional regulatory components of metabolic functions have occurred among ascomycetes species. PMID:19875326

  14. Automated refinement and inference of analytical models for metabolic networks

    NASA Astrophysics Data System (ADS)

    Schmidt, Michael D.; Vallabhajosyula, Ravishankar R.; Jenkins, Jerry W.; Hood, Jonathan E.; Soni, Abhishek S.; Wikswo, John P.; Lipson, Hod

    2011-10-01

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model--suggesting nonlinear terms and structural modifications--or even constructing a new model that agrees with the system's time series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real time.

  15. 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

  16. Automated refinement and inference of analytical models for metabolic networks

    PubMed Central

    Schmidt, Michael D; Vallabhajosyula, Ravishankar R; Jenkins, Jerry W; Hood, Jonathan E; Soni, Abhishek S; Wikswo, John P; Lipson, Hod

    2013-01-01

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model – suggesting nonlinear terms and structural modifications – or even constructing a new model that agrees with the system’s time-series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real-time. PMID:21832805

  17. Cellular oxidative damage is more sensitive to biosynthetic rate than to metabolic rate: A test of the theoretical model on hornworms (Manduca sexta larvae).

    PubMed

    Amunugama, Kaushalya; Jiao, Lihong; Olbricht, Gayla R; Walker, Chance; Huang, Yue-Wern; Nam, Paul K; Hou, Chen

    2016-09-01

    We develop a theoretical model from an energetic viewpoint for unraveling the entangled effects of metabolic and biosynthetic rates on oxidative cellular damage accumulation during animal's growth, and test the model by experiments in hornworms. The theoretical consideration suggests that most of the cellular damages caused by the oxidative metabolism can be repaired by the efficient maintenance mechanisms, if the energy required by repair is unlimited. However, during growth a considerable amount of energy is allocated to the biosynthesis, which entails tradeoffs with the requirements of repair. Thus, the model predicts that cellular damage is more influenced by the biosynthetic rate than the metabolic rate. To test the prediction, we induced broad variations in metabolic and biosynthetic rates in hornworms, and assayed the lipid peroxidation and protein carbonyl. We found that the increase in the cellular damage was mainly caused by the increase in biosynthetic rate, and the variations in metabolic rate had negligible effect. The oxidative stress hypothesis of aging suggests that high metabolism leads to high cellular damage and short lifespan. However, some empirical studies showed that varying biosynthetic rate, rather than metabolic rate, changes animal's lifespan. The conflicts between the empirical evidence and the hypothesis are reconciled by this study. PMID:27296440

  18. The effect of fluid mechanical stress on cellular arachidonic acid metabolism

    NASA Technical Reports Server (NTRS)

    Mcintire, L. V.; Frangos, J. A.; Rhee, B. G.; Eskin, S. G.; Hall, E. R.

    1987-01-01

    The effect of sublytic levels of mechanical perturations of cells on cell metabolism were investigated by analyzing the products of arachidonic acid (used as a marker metabolite) in blood platelets, polymorphonuclear leucocytes, and cultured umbilical-vein endothelial cells after the suspensions of these cells were subjected to a shear stress in a modified viscometer. It is shown that the sublytic levels of mechanical stress stimulated the arachidonic acid metabolism in all these cell types. Possible biological implications of this stress-metabolism coupling are discussed.

  19. Robust tracking by cellular automata and neural networks with nonlocal weights

    NASA Astrophysics Data System (ADS)

    Ososkov, Gennadii A.

    1995-04-01

    A modified rotor model of the Hopfield neural networks (HNN) is proposed for finding tracks in multiwire proportional chambers. That requires us to apply both raw data prefiltering by cellular automaton and HNN weights furnishing by a special robust multiplier. Then this model is developed to be applicable for a more general type of data and detectors. As an example, data processing of ionospheric measurements are considered. For handling tracks detected by high pressure drift chambers with their up-down ambiguity a modification of deformable templates method is proposed. A new concept of controlled HNN is proposed for solving the so-called track-match problem.

  20. Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response

    NASA Astrophysics Data System (ADS)

    Nikiforov, M. P.; Reukov, V. V.; Thompson, G. L.; Vertegel, A. A.; Guo, S.; Kalinin, S. V.; Jesse, S.

    2009-10-01

    Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

  1. Existence and stability of traveling wave solutions for multilayer cellular neural networks

    NASA Astrophysics Data System (ADS)

    Hsu, Cheng-Hsiung; Lin, Jian-Jhong; Yang, Tzi-Sheng

    2015-08-01

    The purpose of this article is to investigate the existence and stability of traveling wave solutions for one-dimensional multilayer cellular neural networks. We first establish the existence of traveling wave solutions using the truncated technique. Then we study the asymptotic behaviors of solutions for the Cauchy problem of the neural model. Applying two kinds of comparison principles and the weighed energy method, we show that all solutions of the Cauchy problem converge exponentially to the traveling wave solutions provided that the initial data belong to a suitable weighted space.

  2. A new design for reconfigurable XOR function based on cellular neural networks

    NASA Astrophysics Data System (ADS)

    Liu, Yanyi; Liu, Wenbo

    2014-10-01

    We have described a new method to construct the reconfigurable XOR logic circuit by using the modification of the standard uncoupled cellular neural network (CNN) cells. The modification of the cell is easier to implement in engineering applications. The scheme proposed in this paper, using the modification of standard uncoupled CNN cells, allows less hardware consumption in comparison to the utilisation of chaos computing system or harnessing piecewise-linear systems. The template parameters of the modified cell have been discussed, and the physical circuit implementing the reconfigurable two-input and three-input XOR function has also been presented.

  3. Anisotropic optical flow algorithm based on self-adaptive cellular neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Congxuan; Chen, Zhen; Li, Ming; Sun, Kaiqiong

    2013-01-01

    An anisotropic optical flow estimation method based on self-adaptive cellular neural networks (CNN) is proposed. First, a novel optical flow energy function which contains a robust data term and an anisotropic smoothing term is projected. Next, the CNN model which has the self-adaptive feedback operator and threshold is presented according to the Euler-Lagrange partial differential equations of the proposed optical flow energy function. Finally, the elaborate evaluation experiments indicate the significant effects of the various proposed strategies for optical flow estimation, and the comparison results with the other methods show that the proposed algorithm has better performance in computing accuracy and efficiency.

  4. Interferon-γ regulates cellular metabolism and mRNA translation to potentiate macrophage activation.

    PubMed

    Su, Xiaodi; Yu, Yingpu; Zhong, Yi; Giannopoulou, Eugenia G; Hu, Xiaoyu; Liu, Hui; Cross, Justin R; Rätsch, Gunnar; Rice, Charles M; Ivashkiv, Lionel B

    2015-08-01

    Interferon-γ (IFN-γ) primes macrophages for enhanced microbial killing and inflammatory activation by Toll-like receptors (TLRs), but little is known about the regulation of cell metabolism or mRNA translation during this priming. We found that IFN-γ regulated the metabolism and mRNA translation of human macrophages by targeting the kinases mTORC1 and MNK, both of which converge on the selective regulator of translation initiation eIF4E. Physiological downregulation of mTORC1 by IFN-γ was associated with autophagy and translational suppression of repressors of inflammation such as HES1. Genome-wide ribosome profiling in TLR2-stimulated macrophages showed that IFN-γ selectively modulated the macrophage translatome to promote inflammation, further reprogram metabolic pathways and modulate protein synthesis. These results show that IFN-γ-mediated metabolic reprogramming and translational regulation are key components of classical inflammatory macrophage activation. PMID:26147685

  5. Differentiation of Peptococcus and Peptostreptococcus by gas-liquid chromatography of cellular fatty acids and metabolic products.

    PubMed Central

    Lambert, M A; Armfield, A Y

    1979-01-01

    Gas-liquid chromatographic (GLC) profiles of cellular fatty acids and metabolic products were useful in identifying strains of Peptococcus saccharolyticus, Peptococcus asaccharolyticus, Peptostreptococcus anaerobius, Peptostreptococcus micros, and Streptococcus intermedius. The GLC results supported the recent taxonomic decision to transfer aerotolerant Peptostreptococcus species to the genus Streptococcus. Because inconsistencies in the results prevented our differentiating Peptococcus prevotii. Peptococcus magnus, and Peptococcus variabilis by GLC, additional strains will have to been examined. These GLC techniques are amenable to routine use; however, for interlaboratory results to be meaningful, the classification and nomenclature of the anaerobic gram-positive cocci should be standardized. PMID:528680

  6. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    PubMed

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould. PMID

  7. Cellular telephone-based radiation sensor and wide-area detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2006-12-12

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  8. Multilayer cellular neural network and fuzzy C-mean classifiers: comparison and performance analysis

    NASA Astrophysics Data System (ADS)

    Trujillo San-Martin, Maite; Hlebarov, Vejen; Sadki, Mustapha

    2004-11-01

    Neural Networks and Fuzzy systems are considered two of the most important artificial intelligent algorithms which provide classification capabilities obtained through different learning schemas which capture knowledge and process it according to particular rule-based algorithms. These methods are especially suited to exploit the tolerance for uncertainty and vagueness in cognitive reasoning. By applying these methods with some relevant knowledge-based rules extracted using different data analysis tools, it is possible to obtain a robust classification performance for a wide range of applications. This paper will focus on non-destructive testing quality control systems, in particular, the study of metallic structures classification according to the corrosion time using a novel cellular neural network architecture, which will be explained in detail. Additionally, we will compare these results with the ones obtained using the Fuzzy C-means clustering algorithm and analyse both classifiers according to its classification capabilities.

  9. Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

    According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

  10. Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification

    PubMed Central

    2016-01-01

    For many complex diseases, an earlier and more reliable diagnosis is considered a key prerequisite for developing more effective therapies to prevent or delay disease progression. Classical statistical learning approaches for specimen classification using omics data, however, often cannot provide diagnostic models with sufficient accuracy and robustness for heterogeneous diseases like cancers or neurodegenerative disorders. In recent years, new approaches for building multivariate biomarker models on omics data have been proposed, which exploit prior biological knowledge from molecular networks and cellular pathways to address these limitations. This survey provides an overview of these recent developments and compares pathway- and network-based specimen classification approaches in terms of their utility for improving model robustness, accuracy and biological interpretability. Different routes to translate omics-based multifactorial biomarker models into clinical diagnostic tests are discussed, and a previous study is presented as example. PMID:26141830

  11. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches

    PubMed Central

    2012-01-01

    Background Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. Results We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. Conclusions The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach

  12. Effect of crystals and fibrous network polymer additives on cellular morphology of microcellular foams

    NASA Astrophysics Data System (ADS)

    Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro

    2015-05-01

    In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.

  13. ComPPI: a cellular compartment-specific database for protein–protein interaction network analysis

    PubMed Central

    Veres, Daniel V.; Gyurkó, Dávid M.; Thaler, Benedek; Szalay, Kristóf Z.; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein–protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein–protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein–protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design. PMID:25348397

  14. Uniqueness and stability of traveling waves for cellular neural networks with multiple delays

    NASA Astrophysics Data System (ADS)

    Yu, Zhi-Xian; Mei, Ming

    2016-01-01

    In this paper, we investigate the properties of traveling waves to a class of lattice differential equations for cellular neural networks with multiple delays. Following the previous study [38] on the existence of the traveling waves, here we focus on the uniqueness and the stability of these traveling waves. First of all, by establishing the a priori asymptotic behavior of traveling waves and applying Ikehara's theorem, we prove the uniqueness (up to translation) of traveling waves ϕ (n - ct) with c ≤c* for the cellular neural networks with multiple delays, where c* < 0 is the critical wave speed. Then, by the weighted energy method together with the squeezing technique, we further show the global stability of all non-critical traveling waves for this model, that is, for all monotone waves with the speed c

  15. Involvement of cellular metabolism in age-related LTP modifications in rat hippocampal slices

    PubMed Central

    Drulis-Fajdasz, Dominika; Wójtowicz, Tomasz; Wawrzyniak, Marcin; Wlodarczyk, Jakub; Mozrzymas, Jerzy W.; Rakus, Dariusz

    2015-01-01

    Recent studies emphasized crucial role of astrocytic glycogen metabolism in regulation of synaptic transmission and plasticity in young animals. However, the interplay between age-related synaptic plasticity impairments and changes in energetic metabolism remains obscure. To address this issue, we investigated, in hippocampal slices of young (one month) and aged rats (20-22-months), the impact of glycogen degradation inhibition on LTP, mRNA expression for glycogen metabolism enzymes and morphology of dendritic spines. We show that, whereas in young hippocampi, inhibition of glycogen phosphorolysis disrupts the late phase of LTP in the Schaffer collateral-CA1 pathway, in aged rats, blockade of glycogen phosphorylase tends to enhance it. Gene expression for key energy metabolism enzymes, such as glycogen synthase and phosphorylase and glutamine synthetase showed marked differences between young and aged groups and changes in expression of these enzymes preceded plasticity phenomena. Interestingly, in the aged group, a prominent expression of these enzymes was found also in neurons. Concluding, we show that LTP in the considered pathway is differentially modulated by metabolic processes in young and aging animals, indicating a novel venue of studies aiming at preventing cognitive decline during aging. PMID:26101857

  16. A cellular and metabolic assessment of the thermal stress responses in the endemic gastropod Benedictia limnaeoides ongurensis from Lake Baikal.

    PubMed

    Axenov-Gribanov, Denis V; Bedulina, Daria S; Shatilina, Zhanna M; Lubyaga, Yulia A; Vereshchagina, Kseniya P; Timofeyev, Maxim A

    2014-01-01

    Our objective was to determine if the Lake Baikal endemic gastropod Benedictia limnaeoides ongurensis, which inhabits in stable cold waters expresses a thermal stress response. We hypothesized that the evolution of this species in the stable cold waters of Lake Baikal resulted in a reduction of its thermal stress-response mechanisms at the biochemical and cellular levels. Contrary to our hypothesis, our results show that exposure to a thermal challenge activates the cellular and biochemical mechanisms of thermal resistance, such as heat shock proteins and antioxidative enzymes, and alters energetic metabolism in B. limnaeoides ongurensis. Thermal stress caused the elevation of heat shock protein 70 and the products of anaerobic glycolysis together with the depletion of glucose and phosphagens in the studied species. Thus, a temperature increase activates the complex biochemical system of stress response and alters the energetic metabolism in this endemic Baikal gastropod. It is concluded that the deepwater Lake Baikal endemic gastropod B. limnaeoides ongurensis retains the ability to activate well-developed biochemical stress-response mechanisms when exposed to a thermal challenge. PMID:24076104

  17. Function and expression of a novel rat salt-tolerant protein: evidence of a role in cellular sodium metabolism.

    PubMed

    Tsuji, E; Tsuji, Y; Sasaguri, M; Arakawa, K

    1998-09-01

    Higher dietary salt intake in humans is associated with higher BP, but the BP response to NaCl, so-called salt sensitivity, is heterogeneous among individuals. It has been postulated that modifications in cellular cation metabolism may be related to salt sensitivity in mammalian hypertension. The authors have isolated a novel rat complementary DNA, called salt-tolerant protein (STP), that can functionally complement Saccharomyces cervisiae HAL1, which improves salt tolerance by modulating the cation transport system. On high-salt (8% NaCl) diets, both Dahl salt-sensitive and salt-resistant rats displayed an elevated BP and increased STP mRNA expression. Immunohistochemistry using an anti-rat STP antibody demonstrated the presence of STP immunoreactivity in the proximal tubules. In cells that transiently expressed STP, the intracellular [Na+]/[K+] ratio was higher than that in control cells. STP contains predicted coiled-coil and Src homology 3 domains, and shows a partially high degree of nucleotide identity to human thyroid-hormone receptor interacting protein. These results suggest that STP may play an important role in salt sensitivity through cellular sodium metabolism by mediating signal transduction and a hormone-dependent transcription mechanism. PMID:9727364

  18. Identification of Circular RNAs from the Parental Genes Involved in Multiple Aspects of Cellular Metabolism in Barley

    PubMed Central

    Darbani, Behrooz; Noeparvar, Shahin; Borg, Søren

    2016-01-01

    RNA circularization made by head-to-tail back-splicing events is involved in the regulation of gene expression from transcriptional to post-translational levels. By exploiting RNA-Seq data and down-stream analysis, we shed light on the importance of circular RNAs in plants. The results introduce circular RNAs as novel interactors in the regulation of gene expression in plants and imply the comprehensiveness of this regulatory pathway by identifying circular RNAs for a diverse set of genes. These genes are involved in several aspects of cellular metabolism as hormonal signaling, intracellular protein sorting, carbohydrate metabolism and cell-wall biogenesis, respiration, amino acid biosynthesis, transcription and translation, and protein ubiquitination. Additionally, these parental loci of circular RNAs, from both nuclear and mitochondrial genomes, encode for different transcript classes including protein coding transcripts, microRNA, rRNA, and long non-coding/microprotein coding RNAs. The results shed light on the mitochondrial exonic circular RNAs and imply the importance of circular RNAs for regulation of mitochondrial genes. Importantly, we introduce circular RNAs in barley and elucidate their cellular-level alterations across tissues and in response to micronutrients iron and zinc. In further support of circular RNAs' functional roles in plants, we report several cases where fluctuations of circRNAs do not correlate with the levels of their parental-loci encoded linear transcripts. PMID:27375638

  19. Identification of Circular RNAs from the Parental Genes Involved in Multiple Aspects of Cellular Metabolism in Barley.

    PubMed

    Darbani, Behrooz; Noeparvar, Shahin; Borg, Søren

    2016-01-01

    RNA circularization made by head-to-tail back-splicing events is involved in the regulation of gene expression from transcriptional to post-translational levels. By exploiting RNA-Seq data and down-stream analysis, we shed light on the importance of circular RNAs in plants. The results introduce circular RNAs as novel interactors in the regulation of gene expression in plants and imply the comprehensiveness of this regulatory pathway by identifying circular RNAs for a diverse set of genes. These genes are involved in several aspects of cellular metabolism as hormonal signaling, intracellular protein sorting, carbohydrate metabolism and cell-wall biogenesis, respiration, amino acid biosynthesis, transcription and translation, and protein ubiquitination. Additionally, these parental loci of circular RNAs, from both nuclear and mitochondrial genomes, encode for different transcript classes including protein coding transcripts, microRNA, rRNA, and long non-coding/microprotein coding RNAs. The results shed light on the mitochondrial exonic circular RNAs and imply the importance of circular RNAs for regulation of mitochondrial genes. Importantly, we introduce circular RNAs in barley and elucidate their cellular-level alterations across tissues and in response to micronutrients iron and zinc. In further support of circular RNAs' functional roles in plants, we report several cases where fluctuations of circRNAs do not correlate with the levels of their parental-loci encoded linear transcripts. PMID:27375638

  20. Global analysis of the role of autophagy in cellular metabolism and energy homeostasis in Arabidopsis seedlings under carbon starvation.

    PubMed

    Avin-Wittenberg, Tamar; Bajdzienko, Krzysztof; Wittenberg, Gal; Alseekh, Saleh; Tohge, Takayuki; Bock, Ralph; Giavalisco, Patrick; Fernie, Alisdair R

    2015-02-01

    Germination and early seedling establishment are developmental stages in which plants face limited nutrient supply as their photosynthesis mechanism is not yet active. For this reason, the plant must mobilize the nutrient reserves provided by the mother plant in order to facilitate growth. Autophagy is a catabolic process enabling the bulk degradation of cellular constituents in the vacuole. The autophagy mechanism is conserved among eukaryotes, and homologs of many autophagy-related (ATG) genes have been found in Arabidopsis thaliana. T-DNA insertion mutants (atg mutants) of these genes display higher sensitivity to various stresses, particularly nutrient starvation. However, the direct impact of autophagy on cellular metabolism has not been well studied. In this work, we used etiolated Arabidopsis seedlings as a model system for carbon starvation. atg mutant seedlings display delayed growth in response to carbon starvation compared with wild-type seedlings. High-throughput metabolomic, lipidomic, and proteomic analyses were performed, as well as extensive flux analyses, in order to decipher the underlying causes of the phenotype. Significant differences between atg mutants and wild-type plants have been demonstrated, suggesting global effects of autophagy on central metabolism during carbon starvation as well as severe energy deprivation, resulting in a morphological phenotype. PMID:25649436

  1. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

    PubMed

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities. PMID:26909353

  2. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks

    PubMed Central

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities. PMID:26909353

  3. Metabolic networking in Brunfelsia calycina petals after flower opening.

    PubMed

    Bar-Akiva, Ayelet; Ovadia, Rinat; Rogachev, Ilana; Bar-Or, Carmiya; Bar, Einat; Freiman, Zohar; Nissim-Levi, Ada; Gollop, Natan; Lewinsohn, Efraim; Aharoni, Asaph; Weiss, David; Koltai, Hinanit; Oren-Shamir, Michal

    2010-03-01

    Brunfelsia calycina flowers change colour from purple to white due to anthocyanin degradation, parallel to an increase in fragrance and petal size. Here it was tested whether the production of the fragrant benzenoids is dependent on induction of the shikimate pathway, or if they are formed from the anthocyanin degradation products. An extensive characterization of the events taking place in Brunfelsia flowers is presented. Anthocyanin characterization was performed using ultraperfomance liquid chromatography-quadrupole time of flight-tandem mass specrometry (UPLC-QTOF-MS/MS). Volatiles emitted were identified by headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Accumulated proteins were identified by 2D gel electrophoresis. Transcription profiles were characterized by cross-species hybridization of Brunfelsia cDNAs to potato cDNA microarrays. Identification of accumulated metabolites was performed by UPLC-QTOF-MS non-targeted metabolite analysis. The results include characterization of the nine main anthocyanins in Brunfelsia flowers. In addition, 146 up-regulated genes, 19 volatiles, seven proteins, and 17 metabolites that increased during anthocyanin degradation were identified. A multilevel analysis suggests induction of the shikimate pathway. This pathway is the most probable source of the phenolic acids, which in turn are precursors of both the benzenoid and lignin production pathways. The knowledge obtained is valuable for future studies on degradation of anthocyanins, formation of volatiles, and the network of secondary metabolism in Brunfelsia and related species. PMID:20202996

  4. Cellular resilience.

    PubMed

    Smirnova, Lena; Harris, Georgina; Leist, Marcel; Hartung, Thomas

    2015-01-01

    Cellular resilience describes the ability of a cell to cope with environmental changes such as toxicant exposure. If cellular metabolism does not collapse directly after the hit or end in programmed cell death, the ensuing stress responses promote a new homeostasis under stress. The processes of reverting "back to normal" and reversal of apoptosis ("anastasis") have been studied little at the cellular level. Cell types show astonishingly similar vulnerability to most toxicants, except for those that require a very specific target, metabolism or mechanism present only in specific cell types. The majority of chemicals triggers "general cytotoxicity" in any cell at similar concentrations. We hypothesize that cells differ less in their vulnerability to a given toxicant than in their resilience (coping with the "hit"). In many cases, cells do not return to the naive state after a toxic insult. The phenomena of "pre-conditioning", "tolerance" and "hormesis" describe this for low-dose exposures to toxicants that render the cell more resistant to subsequent hits. The defense and resilience programs include epigenetic changes that leave a "memory/scar" - an alteration as a consequence of the stress the cell has experienced. These memories might have long-term consequences, both positive (resistance) and negative, that contribute to chronic and delayed manifestations of hazard and, ultimately, disease. This article calls for more systematic analyses of how cells cope with toxic perturbations in the long-term after stressor withdrawal. A technical prerequisite for these are stable (organotypic) cultures and a characterization of stress response molecular networks. PMID:26536287

  5. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    NASA Astrophysics Data System (ADS)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  6. Effects of Graphene Oxide and Oxidized Carbon Nanotubes on the Cellular Division, Microstructure, Uptake, Oxidative Stress, and Metabolic Profiles.

    PubMed

    Hu, Xiangang; Ouyang, Shaohu; Mu, Li; An, Jing; Zhou, Qixing

    2015-09-15

    Nanomaterial oxides are common formations of nanomaterials in the natural environment. Herein, the nanotoxicology of typical graphene oxide (GO) and carboxyl single-walled carbon nanotubes (C-SWCNT) was compared. The results showed that cell division of Chlorella vulgaris was promoted at 24 h and then inhibited at 96 h after nanomaterial exposure. At 96 h, GO and C-SWCNT inhibited the rates of cell division by 0.08-15% and 0.8-28.3%, respectively. Both GO and C-SWCNT covered the cell surface, but the uptake percentage of C-SWCNT was 2-fold higher than that of GO. C-SWCNT induced stronger plasmolysis and mitochondrial membrane potential loss and decreased the cell viability to a greater extent than GO. Moreover, C-SWCNT-exposed cells exhibited more starch grains and lysosome formation and higher reactive oxygen species (ROS) levels than GO-exposed cells. Metabolomics analysis revealed significant differences in the metabolic profiles among the control, C-SWCNT and GO groups. The metabolisms of alkanes, lysine, octadecadienoic acid and valine was associated with ROS and could be considered as new biomarkers of ROS. The nanotoxicological mechanisms involved the inhibition of fatty acid, amino acid and small molecule acid metabolisms. These findings provide new insights into the effects of GO and C-SWCNT on cellular responses. PMID:26295980

  7. Network, cellular, and molecular mechanisms underlying long-term memory formation.

    PubMed

    Carasatorre, Mariana; Ramírez-Amaya, Víctor

    2013-01-01

    The neural network stores information through activity-dependent synaptic plasticity that occurs in populations of neurons. Persistent forms of synaptic plasticity may account for long-term memory storage, and the most salient forms are the changes in the structure of synapses. The theory proposes that encoding should use a sparse code and evidence suggests that this can be achieved through offline reactivation or by sparse initial recruitment of the network units. This idea implies that in some cases the neurons that underwent structural synaptic plasticity might be a subpopulation of those originally recruited; However, it is not yet clear whether all the neurons recruited during acquisition are the ones that underwent persistent forms of synaptic plasticity and responsible for memory retrieval. To determine which neural units underlie long-term memory storage, we need to characterize which are the persistent forms of synaptic plasticity occurring in these neural ensembles and the best hints so far are the molecular signals underlying structural modifications of the synapses. Structural synaptic plasticity can be achieved by the activity of various signal transduction pathways, including the NMDA-CaMKII and ACh-MAPK. These pathways converge with the Rho family of GTPases and the consequent ERK 1/2 activation, which regulates multiple cellular functions such as protein translation, protein trafficking, and gene transcription. The most detailed explanation may come from models that allow us to determine the contribution of each piece of this fascinating puzzle that is the neuron and the neural network. PMID:22976275

  8. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways.

    PubMed

    Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

    2014-07-17

    Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of cofactors (cochaperones) that regulate their specificity and function. However, how these cochaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone-cochaperone-client interaction network in human cells. We uncover hundreds of chaperone clients, delineate their participation in specific cochaperone complexes, and establish a surprisingly distinct network of protein-protein interactions for cochaperones. As a salient example of the power of such analysis, we establish that NUDC family cochaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network and its regulation in development and disease and expand the use of chaperones as sensors for drug-target engagement. PMID:25036637

  9. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular.

    PubMed

    Okasaka, Shozo; Weiler, Richard J; Keusgen, Wilhelm; Pudeyev, Andrey; Maltsev, Alexander; Karls, Ingolf; Sakaguchi, Kei

    2016-01-01

    The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access. PMID:27571074

  10. Firing patterns in a random network cellular automata model of the brain

    NASA Astrophysics Data System (ADS)

    Acedo, L.; Lamprianidou, E.; Moraño, J.-A.; Villanueva-Oller, J.; Villanueva, R.-J.

    2015-10-01

    One of the main challenges in the simulation of even reduced areas of the brain is the presence of a large number of neurons and a large number of connections among them. Even from a theoretical point of view, the behaviour of dynamical models of complex networks with high connectivity is unknown, precisely because the cost of computation is still unaffordable and it will likely be in the near future. In this paper we discuss the simulation of a cellular automata network model of the brain including up to one million sites with a maximum average of three hundred connections per neuron. This level of connectivity was achieved thanks to a distributed computing environment based on the BOINC (Berkeley Open Infrastructure for Network Computing) platform. Moreover, in this work we consider the interplay among excitatory neurons (which induce the excitation of their neighbours) and inhibitory neurons (which prevent resting neurons from firing and induce firing neurons to pass to the refractory state). Our objective is to classify the normal (noisy but asymptotically constant patterns) and the abnormal (high oscillations with spindle-like behaviour) patterns of activity in the model brain and their stability and parameter ranges in order to determine the role of excitatory and inhibitory compensatory effects in healthy and diseased individuals.

  11. Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation.

    PubMed

    Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; Ng, Patrick; Khraiwesh, Basel; Jaiswal, Ashish; Jijakli, Kenan; Koussa, Joseph; Nelson, David R; Cai, Hong; Yang, Xinping; Chang, Roger L; Papin, Jason; Yu, Haiyuan; Balaji, Santhanam; Salehi-Ashtiani, Kourosh

    2016-07-19

    Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites. PMID:27357594

  12. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    PubMed

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. PMID:26576489

  13. The regulatory network of E. coli metabolism as a Boolean dynamical system exhibits both homeostasis and flexibility of response

    PubMed Central

    Samal, Areejit; Jain, Sanjay

    2008-01-01

    Background Elucidating the architecture and dynamics of large scale genetic regulatory networks of cells is an important goal in systems biology. We study the system level dynamical properties of the genetic network of Escherichia coli that regulates its metabolism, and show how its design leads to biologically useful cellular properties. Our study uses the database (Covert et al., Nature 2004) containing 583 genes and 96 external metabolites which describes not only the network connections but also the Boolean rule at each gene node that controls the switching on or off of the gene as a function of its inputs. Results We have studied how the attractors of the Boolean dynamical system constructed from this database depend on the initial condition of the genes and on various environmental conditions corresponding to buffered minimal media. We find that the system exhibits homeostasis in that its attractors, that turn out to be fixed points or low period cycles, are highly insensitive to initial conditions or perturbations of gene configurations for any given fixed environment. At the same time the attractors show a wide variation when external media are varied implying that the system mounts a highly flexible response to changed environmental conditions. The regulatory dynamics acts to enhance the cellular growth rate under changed media. Conclusion Our study shows that the reconstructed genetic network regulating metabolism in E. coli is hierarchical, modular, and largely acyclic, with environmental variables controlling the root of the hierarchy. This architecture makes the cell highly robust to perturbations of gene configurations as well as highly responsive to environmental changes. The twin properties of homeostasis and response flexibility are achieved by this dynamical system even though it is not close to the edge of chaos. PMID:18312613

  14. STAT3-Mediated Metabolic Reprograming in Cellular Transformation and Implications for Drug Resistance

    PubMed Central

    Poli, Valeria; Camporeale, Annalisa

    2015-01-01

    Signal transducer and activator of transcription (STAT)3 mediates the signaling downstream of cytokine and growth factor receptors, regulating the expression of target genes. It is constitutively phosphorylated on tyrosine (Y-P) in many tumors, where its transcriptional activity can induce a metabolic switch toward aerobic glycolysis and down-regulate mitochondrial activity, a prominent metabolic feature of most cancer cells, correlating with reduced production of ROS, delayed senescence, and protection from apoptosis. STAT3 can, however, also localize to mitochondria, where its serine-phosphorylated (S-P) form preserves mitochondrial oxidative phosphorylation and controls the opening of the mitochondrial permeability transition pore, also promoting survival and resistance to apoptosis in response to specific signals/oncogenes such as RAS. Thus, downstream of different signals, both nuclear, Y-P STAT3, and mitochondrial, S-P STAT3, can act by promoting cell survival and reducing ROS production. Here, we discuss these properties in the light of potential connections between STAT3-driven alterations of mitochondrial metabolism and the development of drug resistance in cancer patients. PMID:26106584

  15. ABCC6- a new player in cellular cholesterol and lipoprotein metabolism?

    PubMed Central

    2014-01-01

    Background Dysregulations in cholesterol and lipid metabolism have been linked to human diseases like hypercholesterolemia, atherosclerosis or the metabolic syndrome. Many ABC transporters are involved in trafficking of metabolites derived from these pathways. Pseudoxanthoma elasticum (PXE), an autosomal-recessive disease caused by ABCC6 mutations, is characterized by atherogenesis and soft tissue calcification. Methods In this study we investigated the regulation of cholesterol biosynthesis in human dermal fibroblasts from PXE patients and healthy controls. Results Gene expression analysis of 84 targets indicated dysregulations in cholesterol metabolism in PXE fibroblasts. Transcript levels of ABCC6 were strongly increased in lipoprotein-deficient serum (LPDS) and under serum starvation in healthy controls. For the first time, increased HMG CoA reductase activities were found in PXE fibroblasts. We further observed strongly elevated transcript and protein levels for the proprotein convertase subtilisin/kexin type 9 (PCSK9), as well as a significant reduction in APOE mRNA expression in PXE. Conclusion Increased cholesterol biosynthesis, elevated PCSK9 levels and reduced APOE mRNA expression newly found in PXE fibroblasts could enforce atherogenesis and cardiovascular risk in PXE patients. Moreover, the increase in ABCC6 expression accompanied by the induction of cholesterol biosynthesis supposes a functional role for ABCC6 in human lipoprotein and cholesterol homeostasis. PMID:25064003

  16. Effects of calmodulin inhibitors on the cellular metabolism of /sup 45/Ca and /sup 210/Pb

    SciTech Connect

    Pounds, J.G.; Nye, A.C.

    1987-01-01

    Altered Ca/sup + +/ homeostasis may result from the direct inhibition of calmodulin-dependent or -independent transport processes. Changes in cell function not directly related to the transport of Ca, e.g., uncoupling of oxidative phosphorylation or altered membrane permeability also disrupt cell calcium metabolism. Thus, the effects of the calmodulin inhibitor W-13 on cell Pb/sup + +/ metabolism may be due to its direct effects on Pb/sup + +/ transporting Ca/sup + +/ pumps, or indirectly as a result of changes in Ca/sup + +/ homeostasis. Direct comparison of the effects of W-13 on the metabolism of Pb and Ca is impaired by differences in the kinetic distribution and behavior of Pb and Ca. A further complication is that the calmodulin-dependent processes are most active during periods of elevated intracellular Ca/sup + +/. The preliminary experiments reported here were conducted in unstimulated cells which have a low resting level of cytosolic Ca/sup + +/. Therefore, W-13 induced alterations in cell Ca/sup + +/ and Pb/sup + +/ may not reflect the changes which could occur in stimulated cells. 1 ref., 1 fig.

  17. Metabolic design based on a coupled gene expression-metabolic network model of tryptophan production in Escherichia coli.

    PubMed

    Schmid, Joachim W; Mauch, Klaus; Reuss, Matthias; Gilles, Ernst D; Kremling, Andreas

    2004-10-01

    The presumably high potential of a holistic design approach for complex biochemical reaction networks is exemplified here for the network of tryptophan biosynthesis from glucose, a system whose components have been investigated thoroughly before. A dynamic model that combines the behavior of the trp operon gene expression with the metabolic network of central carbon metabolism and tryptophan biosynthesis is investigated. This model is analyzed in terms of metabolic fluxes, metabolic control, and nonlinear optimization. We compare two models for a wild-type strain and another model for a tryptophan producer. An integrated optimization of the whole network leads to a significant increase in tryptophan production rate for all systems under study. This enhancement is well above the increase that can be achieved by an optimization of subsystems. A constant ratio of control coefficients on tryptophan synthesis rate has been identified for the models regarding or disregarding trp operon expression. Although we found some examples where flux control coefficients even contradict the trends of enzyme activity changes in an optimized profile, flux control can be used as an indication for enzymes that have to be taken into account in optimization. PMID:15491865

  18. Functional essentiality from topology features in metabolic networks: a case study in yeast.

    PubMed

    Palumbo, Maria Concetta; Colosimo, Alfredo; Giuliani, Alessandro; Farina, Lorenzo

    2005-08-29

    The relation between the position of mutations in Saccharomyces cerevisiae metabolic network and their lethality is the subject of this work. We represent the topology of the network by a directed graph: nodes are metabolites and arcs represent the reactions; a mutation corresponds to the removal of all the arcs referring to the deleted enzyme. Using publicly available knock-out data, we show that lethality corresponds to the lack of alternative paths in the perturbed network linking the nodes affected by the enzyme deletion. Such feature is at the basis of the recently recognized importance of 'marginal' arcs of metabolic networks. PMID:16095595

  19. Viral Replication Protein Inhibits Cellular Cofilin Actin Depolymerization Factor to Regulate the Actin Network and Promote Viral Replicase Assembly

    PubMed Central

    Kovalev, Nikolay; de Castro Martín, Isabel Fernández; Barajas, Daniel; Risco, Cristina; Nagy, Peter D.

    2016-01-01

    RNA viruses exploit host cells by co-opting host factors and lipids and escaping host antiviral responses. Previous genome-wide screens with Tomato bushy stunt virus (TBSV) in the model host yeast have identified 18 cellular genes that are part of the actin network. In this paper, we show that the p33 viral replication factor interacts with the cellular cofilin (Cof1p), which is an actin depolymerization factor. Using temperature-sensitive (ts) Cof1p or actin (Act1p) mutants at a semi-permissive temperature, we find an increased level of TBSV RNA accumulation in yeast cells and elevated in vitro activity of the tombusvirus replicase. We show that the large p33 containing replication organelle-like structures are located in the close vicinity of actin patches in yeast cells or around actin cable hubs in infected plant cells. Therefore, the actin filaments could be involved in VRC assembly and the formation of large viral replication compartments containing many individual VRCs. Moreover, we show that the actin network affects the recruitment of viral and cellular components, including oxysterol binding proteins and VAP proteins to form membrane contact sites for efficient transfer of sterols to the sites of replication. Altogether, the emerging picture is that TBSV, via direct interaction between the p33 replication protein and Cof1p, controls cofilin activities to obstruct the dynamic actin network that leads to efficient subversion of cellular factors for pro-viral functions. In summary, the discovery that TBSV interacts with cellular cofilin and blocks the severing of existing filaments and the formation of new actin filaments in infected cells opens a new window to unravel the way by which viruses could subvert/co-opt cellular proteins and lipids. By regulating the functions of cofilin and the actin network, which are central nodes in cellular pathways, viruses could gain supremacy in subversion of cellular factors for pro-viral functions. PMID:26863541

  20. Cellular location and major terminal networks of the orexinergic system in the brain of two megachiropterans.

    PubMed

    Dell, Leigh-Anne; Kruger, Jean-Leigh; Pettigrew, John D; Manger, Paul R

    2013-11-01

    The present study describes the distribution of orexin-A immunoreactive neurons and their terminal networks in the brains of two species of megachiropterans. In general the organization of the orexinergic system in the mammalian brain is conserved across species, but as one of two groups of mammals that fly and have a high metabolic rate, it was of interest to determine whether there were any specific differences in the organization of this system in the megachiropterans. Orexinergic neurons were limited in distribution to the hypothalamus, and formed three distinct clusters, or nuclei, a main cluster with a perifornical location, a zona incerta cluster in the dorsolateral hypothalamus and an optic tract cluster in the ventrolateral hypothalamus. The nuclear parcellation of the orexinergic system in the megachiropterans is similar to that seen in many mammals, but differs from the microchiropterans where the optic tract cluster is absent. The terminal networks of the orexinergic neurons in the megachiropterans was similar to that seen in a range of mammalian species, with significant terminal networks being found in the hypothalamus, cholinergic pedunculopontine and laterodorsal tegemental nuclei, the noradrenergic locus coeruleus complex, all serotonergic nuclei, the paraventricular nuclei of the epithalamus and adjacent to the habenular nuclei. While the megachiropteran orexinergic system is typically mammalian in form, it does differ from that reported for microchiropterans, and thus provides an additional neural character arguing for independent evolution of these two chiropteran suborders. PMID:24041616

  1. Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks

    NASA Astrophysics Data System (ADS)

    Bardoscia, Marco; Marsili, Matteo; Samal, Areejit

    2015-07-01

    System-level properties of metabolic networks may be the direct product of natural selection or arise as a by-product of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov chain Monte Carlo (MCMC) sampling based on flux balance analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks.

  2. Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks.

    PubMed

    Bardoscia, Marco; Marsili, Matteo; Samal, Areejit

    2015-07-01

    System-level properties of metabolic networks may be the direct product of natural selection or arise as a by-product of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov chain Monte Carlo (MCMC) sampling based on flux balance analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks. PMID:26274227

  3. Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

    1997-01-01

    A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

  4. Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

    PubMed Central

    Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

    2012-01-01

    Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

  5. Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

    NASA Astrophysics Data System (ADS)

    Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma

    2007-09-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  6. Convergence and attractivity of memristor-based cellular neural networks with time delays.

    PubMed

    Qin, Sitian; Wang, Jun; Xue, Xiaoping

    2015-03-01

    This paper presents theoretical results on the convergence and attractivity of memristor-based cellular neural networks (MCNNs) with time delays. Based on a realistic memristor model, an MCNN is modeled using a differential inclusion. The essential boundedness of its global solutions is proven. The state of MCNNs is further proven to be convergent to a critical-point set located in saturated region of the activation function, when the initial state locates in a saturated region. It is shown that the state convergence time period is finite and can be quantitatively estimated using given parameters. Furthermore, the positive invariance and attractivity of state in non-saturated regions are also proven. The simulation results of several numerical examples are provided to substantiate the results. PMID:25562569

  7. Parallelism on the Intel 860 Hypercube:. Ising Magnets, Hydrodynamical Cellular Automata and Neural Networks

    NASA Astrophysics Data System (ADS)

    Kohring, G. A.; Stauffer, D.

    Geometric parallelization was tested on the Intel Hypercube with 32 MIMD processors of 1860 type, each with 16 Mbytes of distributed memory. We applied it to Ising models in two and three dimensions as well as to neural networks and two-dimensional hydrodynamic cellular automata. For system sizes suited to this machine, up to 60960*60960 and 1410*1410*1408 Ising spins, we found nearly hundred percent parallel efficiency in spite of the needed inter-processor communications. For small systems, the observed deviations from full efficiency were compared with the scaling concepts of Heermann and Burkitt and of Jakobs and Gerling. For Ising models, we determined the Glauber kinetic exponent z≃2.18 in two dimensions and confirmed the stretched exponential relaxation of the magnetization towards the spontaneous magnetization below Tc. For three dimensions we found z≃2.09 and simple exponential relaxation.

  8. Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

    PubMed Central

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. PMID:24959631

  9. Global detection of live virtual machine migration based on cellular neural networks.

    PubMed

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. PMID:24959631

  10. A novel method to assess human population exposure induced by a wireless cellular network.

    PubMed

    Varsier, Nadège; Plets, David; Corre, Yoann; Vermeeren, Günter; Joseph, Wout; Aerts, Sam; Martens, Luc; Wiart, Joe

    2015-09-01

    This paper presents a new metric to evaluate electromagnetic exposure induced by wireless cellular networks. This metric takes into account the exposure induced by base station antennas as well as exposure induced by wireless devices to evaluate average global exposure of the population in a specific geographical area. The paper first explains the concept and gives the formulation of the Exposure Index (EI). Then, the EI computation is illustrated through simple phone call scenarios (indoor office, in train) and a complete macro urban data long-term evolution scenario showing how, based on simulations, radio-planning predictions, realistic population statistics, user traffic data, and specific absorption rate calculations can be combined to assess the index. Bioelectromagnetics. 36:451-463, 2015. © 2015 Wiley Periodicals, Inc. PMID:26113174

  11. BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

    PubMed Central

    Feng, Song; Ollivier, Julien F.; Swain, Peter S.; Soyer, Orkun S.

    2015-01-01

    Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. PMID:26101250

  12. Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network

    PubMed Central

    Galhardo, Mafalda; Sinkkonen, Lasse; Berninger, Philipp; Lin, Jake; Sauter, Thomas; Heinäniemi, Merja

    2014-01-01

    Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions. PMID:24198249

  13. Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network.

    PubMed

    Galhardo, Mafalda; Sinkkonen, Lasse; Berninger, Philipp; Lin, Jake; Sauter, Thomas; Heinäniemi, Merja

    2014-02-01

    Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions. PMID:24198249

  14. Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting

    NASA Astrophysics Data System (ADS)

    Zhong, Yuan; Liu, Leifeng; Wikman, Stefan; Cui, Daqing; Shen, Zhijian

    2016-03-01

    A feasibility study was performed to fabricate ITER In-Vessel components by Selective Laser Melting (SLM) supported by Fusion for Energy (F4E). Almost fully dense 316L stainless steel (SS316L) components were prepared from gas-atomized powder and with optimized SLM processing parameters. Tensile tests and Charpy-V tests were carried out at 22 °C and 250 °C and the results showed that SLM SS316L fulfill the RCC-MR code. Microstructure characterization reveals the presence of hierarchical macro-, micro- and nano-structures in as-built samples that were very different from SS316L microstructures prepared by other established methods. The formation of a characteristic intragranular cellular segregation network microstructure appears to contribute to the increase of yield strength without losing ductility. Silicon oxide nano-inclusions were formed during the SLM process that generated a micro-hardness fluctuation in the building direction. The combined influence of a cellular microstructure and the nano-inclusions constraints the size of ductile dimples to nano-scale. The crack propagation is hindered by a pinning effect that improves the defect-tolerance of the SLM SS316L. This work proves that it was possible to manufacture SS316L with properties suitable for ITER First Wall panels. Further studies on irradiation properties of SLM SS316L and manufacturing of larger real-size components are needed.

  15. Computerized detection of pulmonary nodules using cellular neural networks in CT images

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangwei; McLennan, Geoffrey; Hoffman, Eric A.; Sonka, Milan

    2004-05-01

    The purpose of this study is to develop a computer-aided diagnosis (CAD) system to detect small-sized (from 2mm to 10mm) non-pleural pulmonary nodules in high resolution helical CT scans. A new 3D automated scheme using cellular neural networks is presented. Different from most previous methods, this scheme employed the local shape property to perform voxel classification. The shape index feature successfully captured the local shape difference between nodules and non-nodules, especially vessels. A 3D discrete-time cellular neural network (DTCNN) was constructed to give a reliable voxel classification by collecting information in a neighborhood. To tailor it for lung nodule detection, this DTCNN was trained using genetic algorithms (GAs) to derive the shape index variation pattern of nodules. 19 clinical thoracic CT cases involving a total of 4838 sectional images were used in this work, with 2 scans forming the training set, and the remaining 17 cases being the testing set. The evaluation was composed of two stages. During the first stage, a pulmonologist and our CAD system independently detected nodules in the testing set. Then, the suspected nodule areas located by the computer were reviewed by the pulmonologist to confirm nodules missed by the human in the first review. There were 32 true nodules detected by the computer but missed by the pulmonologist in the first review, in which 30 non-juxtapleural nodules were found. Considering the nodules detected by the pulmonologist during the first and second reviews as the truth, 52 of 62 non-pleural nodules were detected by the CAD system (sensitivity being 83.9%), with the number of false positives being 3.47 per case.

  16. Metabolism, Energetics, and Lipid Biology in the Podocyte – Cellular Cholesterol-Mediated Glomerular Injury

    PubMed Central

    Merscher, Sandra; Pedigo, Christopher E.; Mendez, Armando J.

    2014-01-01

    Chronic kidney disease (CKD) is associated with a high risk of death. Dyslipidemia is commonly observed in patients with CKD and is accompanied by a decrease in plasma high-density lipoprotein, and an increase in plasma triglyceride-rich lipoproteins and oxidized lipids. The observation that statins may decrease albuminuria but do not stop the progression of CKD indicates that pathways other than the cholesterol synthesis contribute to cholesterol accumulation in the kidneys of patients with CKD. Recently, it has become clear that increased lipid influx and impaired reverse cholesterol transport can promote glomerulosclerosis, and tubulointerstitial damage. Lipid-rafts are cholesterol-rich membrane domains with important functions in regulating membrane fluidity, membrane protein trafficking, and in the assembly of signaling molecules. In podocytes, which are specialized cells of the glomerulus, they contribute to the spatial organization of the slit diaphragm (SD) under physiological and pathological conditions. The discovery that podocyte-specific proteins such as podocin can bind and recruit cholesterol contributing to the formation of the SD underlines the importance of cholesterol homeostasis in podocytes and suggests cholesterol as an important regulator in the development of proteinuric kidney disease. Cellular cholesterol accumulation due to increased synthesis, influx, or decreased efflux is an emerging concept in podocyte biology. This review will focus on the role of cellular cholesterol accumulation in the pathogenesis of kidney diseases with a focus on glomerular diseases. PMID:25352833

  17. Targeting Cellular Metabolism Chemosensitizes the Doxorubicin-Resistant Human Breast Adenocarcinoma Cells.

    PubMed

    Ma, Shulan; Jia, Rongfei; Li, Dongju; Shen, Bo

    2015-01-01

    Metabolic energy preferentially produced by glycolysis was an advantageous metabolic phenotype of cancer cells. It is also an essential contributor to the progression of multidrug resistance in cancer cells. By developing human breast cancer MCF-7 cells resistant to doxorubicin (DOX) (MCF-7/MDR cells), the effects and mechanisms of 2-deoxy-D-glucose (2DG), a glucose analogue, on reversing multidrug resistance were investigated. 2DG significantly inhibited the viability of MCF-7/MDR cells and enhanced DOX-induced apoptosis by upregulating protein expression of AMPKα, P53, and caspase-3. The study demonstrated that energy restriction induced by 2DG was relevant to the synergistic effect of 2DG and DOX. The proteins of multidrug gene (the MDR-related protein, MRP1) and P-glycoprotein (P-gp) in MCF-7/MDR cells were downregulated after exposure to 2DG, accompanied with the suppression of the activity of ATP-dependent drug-efflux pump and transmembrane transporter, increasing the intracellular accumulation of DOX to reverse the chemoresistance in multidrug cancer cells. PMID:26558272

  18. Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious

    PubMed Central

    Wagner, Allon; Zarecki, Raphy; Reshef, Leah; Gochev, Camelia; Sorek, Rotem; Gophna, Uri; Ruppin, Eytan

    2013-01-01

    Gene suppression and overexpression are both fundamental tools in linking genotype to phenotype in model organisms. Computational methods have proven invaluable in studying and predicting the deleterious effects of gene deletions, and yet parallel computational methods for overexpression are still lacking. Here, we present Expression-Dependent Gene Effects (EDGE), an in silico method that can predict the deleterious effects resulting from overexpression of either native or foreign metabolic genes. We first test and validate EDGE’s predictive power in bacteria through a combination of small-scale growth experiments that we performed and analysis of extant large-scale datasets. Second, a broad cross-species analysis, ranging from microorganisms to multiple plant and human tissues, shows that genes that EDGE predicts to be deleterious when overexpressed are indeed typically down-regulated. This reflects a universal selection force keeping the expression of potentially deleterious genes in check. Third, EDGE-based analysis shows that cancer genetic reprogramming specifically suppresses genes whose overexpression impedes proliferation. The magnitude of this suppression is large enough to enable an almost perfect distinction between normal and cancerous tissues based solely on EDGE results. We expect EDGE to advance our understanding of human pathologies associated with up-regulation of particular transcripts and to facilitate the utilization of gene overexpression in metabolic engineering. PMID:24198337

  19. Extracellular Toxoplasma gondii tachyzoites metabolize and incorporate unnatural sugars into cellular proteins.

    PubMed

    Nazarova, Lidia A; Ochoa, Roxanna J; Jones, Krysten A; Morrissette, Naomi S; Prescher, Jennifer A

    2016-03-01

    Toxoplasma gondii is an obligate intracellular parasite that infects all nucleated cell types in diverse warm-blooded organisms. Many of the surface antigens and effector molecules secreted by the parasite during invasion and intracellular growth are modified by glycans. Glycosylated proteins in the nucleus and cytoplasm have also been reported. Despite their prevalence, the complete inventory and biological significance of glycosylated proteins in Toxoplasma remain unknown. In this study, we aimed to globally profile parasite glycoproteins using a bioorthogonal chemical reporter strategy. This strategy involves the metabolic incorporation of unnatural functional groups (i.e., "chemical reporters") into Toxoplasma glycans, followed by covalent labeling with visual probes or affinity tags. The two-step approach enables the visualization and identification of newly biosynthesized glycoconjugates in the parasite. Using a buffer that mimics intracellular conditions, extracellular Toxoplasma tachyzoites were found to metabolize and incorporate unnatural sugars (equipped with bioorthogonal functional groups) into diverse proteins. Covalent chemistries were used to visualize and retrieve these labeled structures. Subsequent mass spectrometry analysis revealed 89 unique proteins. This survey identified novel proteins as well as previously characterized proteins from lectin affinity analyses. PMID:26687036

  20. Cellular pathways of energy metabolism in the brain: is glucose used by neurons or astrocytes?

    PubMed

    Nehlig, Astrid; Coles, Jonathan A

    2007-09-01

    Most techniques presently available to measure cerebral activity in humans and animals, i.e. positron emission tomography (PET), autoradiography, and functional magnetic resonance imaging, do not record the activity of neurons directly. Furthermore, they do not allow the investigator to discriminate which cell type is using glucose, the predominant fuel provided to the brain by the blood. Here, we review the experimental approaches aimed at determining the percentage of glucose that is taken up by neurons and by astrocytes. This review is integrated in an overview of the current concepts on compartmentation and substrate trafficking between astrocytes and neurons. In the brain in vivo, about half of the glucose leaving the capillaries crosses the extracellular space and directly enters neurons. The other half is taken up by astrocytes. Calculations suggest that neurons consume more energy than do astrocytes, implying that astrocytes transfer an intermediate substrate to neurons. Experimental approaches in vitro on the honeybee drone retina and on the isolated vagus nerve also point to a continuous transfer of intermediate metabolites from glial cells to neurons in these tissues. Solid direct evidence of such transfer in the mammalian brain in vivo is still lacking. PET using [(18)F]fluorodeoxyglucose reflects in part glucose uptake by astrocytes but does not indicate to which step the glucose taken up is metabolized within this cell type. Finally, the sequence of metabolic changes occurring during a transient increase of electrical activity in specific regions of the brain remains to be clarified. PMID:17659529

  1. Protection effect of nicotinamide on cardiomyoblast hypoxia/re-oxygenation injury: study of cellular mitochondrial metabolism.

    PubMed

    Wang, He; Liang, Xiaoping; Luo, Guoan; Ding, Mingyu; Liang, Qionglin

    2016-06-21

    Hypoxia/re-oxygenation (H/R) injury is an important cause of heart failure and results in a critical metabolism dysfunction. In this paper, the cytoprotective effect of the nicotinamide adenine dinucleotide (NAD) precursor nicotinamide was evaluated using an in vitro model of cardiac H/R injury. Nicotinamide (0-20 mM) was applied to the myoblast cell line H9c2 which was subjected to hypoxia (12, 24, 36 h) followed by a re-oxygenation process (0, 4, 8, 12 h). Cell viability was measured, and mitochondrial metabolites were extracted and then measured by HPLC/MS/MS. The present study showed that nicotinamide could down-regulate the NADH/NAD ratio and then maintain the NAD-dependent metabolism processes. Furthermore, an aberrant decrease of fumarate levels and an increase of succinate levels were observed in the nicotinamide group, which was demonstrated to be caused by nicotinamide-induced succinate dehydrogenase (SDH) inhibition. These results suggest that nicotinamide exerts a protective effect on cardiomyoblasts against H/R-induced injury through both NADH/NAD regulation and reduction of reactive oxygen species generation via SDH inhibition. PMID:27156848

  2. Dissecting and engineering metabolic and regulatory networks of thermophilic bacteria for biofuel production.

    PubMed

    Lin, Lu; Xu, Jian

    2013-11-01

    Interest in thermophilic bacteria as live-cell catalysts in biofuel and biochemical industry has surged in recent years, due to their tolerance of high temperature and wide spectrum of carbon-sources that include cellulose. However their direct employment as microbial cellular factories in the highly demanding industrial conditions has been hindered by uncompetitive biofuel productivity, relatively low tolerance to solvent and osmic stresses, and limitation in genome engineering tools. In this work we review recent advances in dissecting and engineering the metabolic and regulatory networks of thermophilic bacteria for improving the traits of key interest in biofuel industry: cellulose degradation, pentose-hexose co-utilization, and tolerance of thermal, osmotic, and solvent stresses. Moreover, new technologies enabling more efficient genetic engineering of thermophiles were discussed, such as improved electroporation, ultrasound-mediated DNA delivery, as well as thermo-stable plasmids and functional selection systems. Expanded applications of such technological advancements in thermophilic microbes promise to substantiate a synthetic biology perspective, where functional parts, module, chassis, cells and consortia were modularly designed and rationally assembled for the many missions at industry and nature that demand the extraordinary talents of these extremophiles. PMID:23510903

  3. Combinatorics of feedback in cellular uptake and metabolism of small molecules.

    PubMed

    Krishna, Sandeep; Semsey, Szabolcs; Sneppen, Kim

    2007-12-26

    We analyze the connection between structure and function for regulatory motifs associated with cellular uptake and usage of small molecules. Based on the boolean logic of the feedback we suggest four classes: the socialist, consumer, fashion, and collector motifs. We find that the socialist motif is good for homeostasis of a useful but potentially poisonous molecule, whereas the consumer motif is optimal for nutrition molecules. Accordingly, examples of these motifs are found in, respectively, the iron homeostasis system in various organisms and in the uptake of sugar molecules in bacteria. The remaining two motifs have no obvious analogs in small molecule regulation, but we illustrate their behavior using analogies to fashion and obesity. These extreme motifs could inspire construction of synthetic systems that exhibit bistable, history-dependent states, and homeostasis of flux (rather than concentration). PMID:18093927

  4. Cellular Nonlinear Networks for the emergence of perceptual states: application to robot navigation control.

    PubMed

    Arena, Paolo; De Fiore, Sebastiano; Patané, Luca

    2009-01-01

    In this paper a new general purpose perceptual control architecture, based on nonlinear neural lattices, is presented and applied to solve robot navigation tasks. Insects show the ability to react to certain stimuli with simple reflexes, using direct sensory-motor pathways, which can be considered as basic behaviors, inherited and pre-wired. Relevant brain centres, known as Mushroom Bodies (MB) and Central Complex (CX) were recently identified in insects: though their functional details are not yet fully understood, it is known that they provide secondary pathways allowing the emergence of cognitive behaviors. These are gained through the coordination of the basic abilities to satisfy the insect's needs. Taking inspiration from this evidence, our architecture modulates, through a reinforcement learning, a set of competitive and concurrent basic behaviors in order to accomplish the task assigned through a reward function. The core of the architecture is constituted by the so-called Representation layer, used to create a concise picture of the current environment situation, fusing together different stimuli for the emergence of perceptual states. These perceptual states are steady state solutions of lattices of Reaction-Diffusion Cellular Nonlinear Networks (RD-CNN), designed to show Turing patterns. The exploitation of the dynamics of the multiple equilibria of the network is emphasized through the adaptive shaping of the basins of attraction for each emerged pattern. New experimental campaigns on standard robotic platforms are reported to demonstrate the potentiality and the effectiveness of the approach. PMID:19596552

  5. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

    PubMed Central

    Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

    2015-01-01

    The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

  6. Flavoprotein imaging in the cerebellar cortex in vivo: cellular and metabolic basis and insights into cerebellar function

    NASA Astrophysics Data System (ADS)

    Gao, Wangcai; Chen, Gang; Ebner, Timothy J.

    2009-02-01

    Flavoprotein autofluorescence is an activity dependent intrinsic signal. Flavoproteins are involved in the electron transport chain and change their fluorescence according to the cellular redox state. We have been using flavoprotein autofluorescence in the cerebellum to examine properties of cerebellar circuits. Studies have also focused on understanding the cellular and metabolic origins of this intrinsic optical signal. Parallel fiber stimulation evokes a beamlike response intersected by bands of decreased fluorescence. The beam response is biphasic, with an early fluorescence increase (light phase) followed by a slower decrease (dark phase). We show this signal originates from flavoproteins as determined by its wavelength selectivity and sensitivity to blockers of the electron transport chain. Selectively blocking glutamate receptors abolished the on-beam light phase with the dark phase remaining intact. This demonstrates that the light phase is due to postsynaptic neuronal activation and suggests the dark phase is primarily due to glial activation. The bands of reduced fluorescence intersecting the beam are primarily neuronal in origin, mediated by GABAergic transmission, and due to the inhibitory action of molecular layer interneurons on Purkinje cells and the interneurons themselves. This parasagittally organized molecular layer inhibition differentially modulates the spatial pattern of cerebellar cortical activity. Flavoprotein imaging also reveals the functional architectures underlying the responses to inferior olive and peripheral whisker pad stimulation. Therefore, flavoprotein autofluorescence imaging is providing new insights into cerebellar cortical function and neurometabolic coupling.

  7. Alterations in cellular energy metabolism associated with the antiproliferative effects of the ATM inhibitor KU-55933 and with metformin.

    PubMed

    Zakikhani, Mahvash; Bazile, Miguel; Hashemi, Sina; Javeshghani, Shiva; Avizonis, Daina; St Pierre, Julie; Pollak, Michael N

    2012-01-01

    KU-55933 is a specific inhibitor of the kinase activity of the protein encoded by Ataxia telangiectasia mutated (ATM), an important tumor suppressor gene with key roles in DNA repair. Unexpectedly for an inhibitor of a tumor suppressor gene, KU-55933 reduces proliferation. In view of prior preliminary evidence suggesting defective mitochondrial function in cells of patients with Ataxia Telangiectasia (AT), we examined energy metabolism of cells treated with KU-55933. The compound increased AMPK activation, glucose uptake and lactate production while reducing mitochondrial membrane potential and coupled respiration. The stimulation of glycolysis by KU-55933 did not fully compensate for the reduction in mitochondrial functions, leading to decreased cellular ATP levels and energy stress. These actions are similar to those previously described for the biguanide metformin, a partial inhibitor of respiratory complex I. Both compounds decreased mitochondrial coupled respiration and reduced cellular concentrations of fumarate, malate, citrate, and alpha-ketogluterate. Succinate levels were increased by KU-55933 levels and decreased by metformin, indicating that the effects of ATM inhibition and metformin are not identical. These observations suggest a role for ATM in mitochondrial function and show that both KU-55933 and metformin perturb the TCA cycle as well as oxidative phosphorylation. PMID:23185347

  8. Alterations in Cellular Energy Metabolism Associated with the Antiproliferative Effects of the ATM Inhibitor KU-55933 and with Metformin

    PubMed Central

    Zakikhani, Mahvash; Bazile, Miguel; Hashemi, Sina; Javeshghani, Shiva; Avizonis, Daina; Pierre, Julie St; Pollak, Michael N.

    2012-01-01

    KU-55933 is a specific inhibitor of the kinase activity of the protein encoded by Ataxia telangiectasia mutated (ATM), an important tumor suppressor gene with key roles in DNA repair. Unexpectedly for an inhibitor of a tumor suppressor gene, KU-55933 reduces proliferation. In view of prior preliminary evidence suggesting defective mitochondrial function in cells of patients with Ataxia Telangiectasia (AT), we examined energy metabolism of cells treated with KU-55933. The compound increased AMPK activation, glucose uptake and lactate production while reducing mitochondrial membrane potential and coupled respiration. The stimulation of glycolysis by KU-55933 did not fully compensate for the reduction in mitochondrial functions, leading to decreased cellular ATP levels and energy stress. These actions are similar to those previously described for the biguanide metformin, a partial inhibitor of respiratory complex I. Both compounds decreased mitochondrial coupled respiration and reduced cellular concentrations of fumarate, malate, citrate, and alpha-ketogluterate. Succinate levels were increased by KU-55933 levels and decreased by metformin, indicating that the effects of ATM inhibition and metformin are not identical. These observations suggest a role for ATM in mitochondrial function and show that both KU-55933 and metformin perturb the TCA cycle as well as oxidative phosphorylation. PMID:23185347

  9. Restriction on an Energy-Dense Diet Improves Markers of Metabolic Health and Cellular Aging in Mice Through Decreasing Hepatic mTOR Activity

    PubMed Central

    Schloesser, Anke; Campbell, Graeme; Glüer, Claus-Christian; Rimbach, Gerald

    2015-01-01

    Abstract Dietary restriction (DR) on a normal low-fat diet improves metabolic health and may prolong life span. However, it is still uncertain whether restriction of an energy-dense, high-fat diet would also be beneficial and mitigate age-related processes. In the present study, we determined biomarkers of metabolic health, energy metabolism, and cellular aging in obesity-prone mice subjected to 30% DR on a high-fat diet for 6 months. Dietary-restricted mice had significantly lower body weights, less adipose tissue, lower energy expenditure, and altered substrate oxidation compared to their ad libitum–fed counterparts. Hepatic major urinary proteins (Mup) expression, which is linked to glucose and energy metabolism, and biomarkers of metabolic health, including insulin, glucose, cholesterol, and leptin/adiponectin ratio, were likewise reduced in high-fat, dietary-restricted mice. Hallmarks of cellular senescence such as Lamp2a and Hsc70 that mediate chaperone-mediated autophagy were induced and mechanistic target of rapamycin (mTOR) signaling mitigated upon high-fat DR. In contrast to DR applied in low-fat diets, anti-oxidant gene expression, proteasome activity, as well as 5′-adenosine monophosphate–activated protein kinase (AMPK) activation were not changed, suggesting that high-fat DR may attenuate some processes associated with cellular aging without the induction of cellular stress response or energy deprivation. PMID:25405871

  10. Metabolic Brain Covariant Networks as Revealed by FDG-PET with Reference to Resting-State fMRI Networks

    PubMed Central

    Di, Xin

    2012-01-01

    Abstract The human brain is inherently organized as separate networks, as has been widely revealed by resting-state functional magnetic resonance imaging (fMRI). Although the large-scale functional connectivity can be partially explained by the underlying white-matter structural connectivity, the question of whether the underlying functional connectivity is related to brain metabolic factors is still largely unanswered. The present study investigated the presence of metabolic covariant networks across subjects using a set of fluorodeoxyglucose (18F, FDG) positron-emission tomography (PET) images. Spatial-independent component analysis was performed on the subject series of FDG-PET images. A number of networks that were mainly homotopic regions could be identified, including visual, auditory, motor, cerebellar, and subcortical networks. However, the anterior-posterior networks such as the default-mode and left frontoparietal networks could not be observed. Region-of-interest-based correlation analysis confirmed that the intersubject metabolic covariances within the default-mode and left frontoparietal networks were reduced as compared with corresponding time-series correlations using resting-state fMRI from an independent sample. In contrast, homotopic intersubject metabolic covariances observed using PET were comparable to the corresponding fMRI resting-state time-series correlations. The current study provides preliminary illustration, suggesting that the human brain metabolism pertains to organized covariance patterns that might partially reflect functional connectivity as revealed by resting-state blood oxygen level dependent (BOLD). The discrepancy between the PET covariance and BOLD functional connectivity might reflect the differences of energy consumption coupling and ongoing neural synchronization within these brain networks. PMID:23025619

  11. Alterations of circulating lymphoid committed progenitor cellular metabolism after allogeneic stem cell transplantation in humans.

    PubMed

    Glauzy, Salomé; Peffault de Latour, Régis; André-Schmutz, Isabelle; Lachuer, Joël; Servais, Sophie; Socié, Gérard; Clave, Emmanuel; Toubert, Antoine

    2016-09-01

    Lymphoid-committed CD34(+)lin(-)CD10(+)CD24(-) progenitors undergo a rebound at month 3 after allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the absence of acute graft-versus-host disease (aGVHD). Here, we analyzed transcriptional programs of cell-sorted circulating lymphoid-committed progenitors and CD34(+)Lin(-)CD10(-) nonlymphoid progenitors in 11 allo-HSCT patients who had (n = 5) or had not (n = 6) developed grade 2 or 3 aGVHD and in 7 age-matched healthy donors. Major upregulated pathways include protein synthesis, energy production, cell cycle regulation, and cytoskeleton organization. Notably, genes from protein biogenesis, translation machinery, and cell cycle (CDK6) were overexpressed in progenitors from patients in the absence of aGVHD compared with healthy donors and patients affected by aGVHD. Expression of many genes from the mitochondrial oxidative phosphorylation metabolic pathway leading to ATP production were more specifically increased in lymphoid-committed progenitors in the absence of aGVHD. This was also the case for genes involved in cell mobilization such as those regulating Rho GTPase activity. In all, we found that circulating lymphoid-committed progenitors undergo profound changes in metabolism, favoring cell proliferation, energy production, and cell mobilization after allo-HSCT in humans. These mechanisms are abolished in the case of aGVHD or its treatment, indicating a persistent cell-intrinsic defect after exit from the bone marrow. PMID:27321893

  12. Dysregulation of cellular iron metabolism in Friedreich ataxia: from primary iron-sulfur cluster deficit to mitochondrial iron accumulation

    PubMed Central

    Martelli, Alain; Puccio, Hélène

    2014-01-01

    Friedreich ataxia (FRDA) is the most common recessive ataxia in the Caucasian population and is characterized by a mixed spinocerebellar and sensory ataxia frequently associating cardiomyopathy. The disease results from decreased expression of the FXN gene coding for the mitochondrial protein frataxin. Early histological and biochemical study of the pathophysiology in patient's samples revealed that dysregulation of iron metabolism is a key feature of the disease, mainly characterized by mitochondrial iron accumulation and by decreased activity of iron-sulfur cluster enzymes. In the recent past years, considerable progress in understanding the function of frataxin has been provided through cellular and biochemical approaches, pointing to the primary role of frataxin in iron-sulfur cluster biogenesis. However, why and how the impact of frataxin deficiency on this essential biosynthetic pathway leads to mitochondrial iron accumulation is still poorly understood. Herein, we review data on both the primary function of frataxin and the nature of the iron metabolism dysregulation in FRDA. To date, the pathophysiological implication of the mitochondrial iron overload in FRDA remains to be clarified. PMID:24917819

  13. Combining Flux Balance and Energy Balance Analysis for Large-Scale Metabolic Network: Biochemical Circuit Theory for Analysis of Large-Scale Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)

    2001-01-01

    Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.

  14. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands. Errors in microwave link measurements were found to be the source that contributes most to the overall uncertainty.

  15. Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics

    PubMed Central

    2014-01-01

    Background Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Results Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. Conclusions By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade. PMID:25035808

  16. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    PubMed Central

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-01-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases. PMID:26608097

  17. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  18. Changes in the expression of the human adenine nucleotide translocase isoforms condition cellular metabolic/proliferative status

    PubMed Central

    Mampel, Teresa; Viñas, Octavi

    2016-01-01

    Human cells express four mitochondrial adenine nucleotide translocase (hANT) isoforms that are tissue-specific and developmentally regulated. hANT1 is mainly expressed in terminally differentiated muscle cells; hANT2 is growth-regulated and is upregulated in highly glycolytic and proliferative cells; and hANT3 is considered to be ubiquitous and non-specifically regulated. Here, we studied how the expression of hANT isoforms is regulated by proliferation and in response to metabolic stimuli, and examined the metabolic consequences of their silencing and overexpression. In HeLa and HepG2 cells, expression of hANT3 was upregulated by shifting metabolism towards oxidation or by slowed growth associated with contact inhibition or growth-factor deprivation, indicating that hANT3 expression is highly regulated. Under these conditions, changes in hANT2 mRNA expression were not observed in either HeLa or HepG2 cells, whereas in SGBS preadipocytes (which, unlike HeLa and HepG2 cells, are growth-arrest-sensitive cells), hANT2 mRNA levels decreased. Additionally, overexpression of hANT2 promoted cell growth and glycolysis, whereas silencing of hANT3 decreased cellular ATP levels, limited cell growth and induced a stress-like response. Thus, cancer cells require both hANT2 and hANT3, depending on their proliferation status: hANT2 when proliferation rates are high, and hANT3 when proliferation slows. PMID:26842067

  19. Identification of dually acylated proteins from complementary DNA resources by cell-free and cellular metabolic labeling.

    PubMed

    Moriya, Koko; Kimoto, Mayumi; Matsuzaki, Kanako; Kiwado, Aya; Takamitsu, Emi; Utsumi, Toshihiko

    2016-10-15

    To establish a strategy to identify dually fatty acylated proteins from cDNA resources, seven N-myristoylated proteins with cysteine (Cys) residues within the 10 N-terminal residues were selected as potential candidates among 27 N-myristoylated proteins identified from a model human cDNA resource. Seven proteins C-terminally tagged with FLAG tag or EGFP were generated and their susceptibility to protein N-myristoylation and S-palmitoylation were evaluated by metabolic labeling with [(3)H]myristic acid or [(3)H]palmitic acid either in an insect cell-free protein synthesis system or in transfected mammalian cells. As a result, EEPD1, one of five proteins (RFTN1, EEPD1, GNAI1, PDE2A, RNF11) found to be dually acylated, was shown to be a novel dually fatty acylated protein. Metabolic labeling experiments using G2A and C7S mutants of EEPD1-EGFP revealed that the palmitoylation site of EEPD1 is Cys at position 7. Analysis of the intracellular localization of EEPD1 C-terminally tagged with FLAG tag or EGFP and its G2A and C7S mutants revealed that the dual acylation directs EEPD1 to localize to the plasma membrane. Thus, dually fatty acylated proteins can be identified from cDNA resources by cell-free and cellular metabolic labeling of N-myristoylated proteins with Cys residue(s) close to the N-myristoylated N-terminus. PMID:27480498

  20. Astrocyte glycogenolysis is triggered by store-operated calcium entry and provides metabolic energy for cellular calcium homeostasis.

    PubMed

    Müller, Margit S; Fox, Rebecca; Schousboe, Arne; Waagepetersen, Helle S; Bak, Lasse K

    2014-04-01

    Astrocytic glycogen, the only storage form of glucose in the brain, has been shown to play a fundamental role in supporting learning and memory, an effect achieved by providing metabolic support for neurons. We have examined the interplay between glycogenolysis and the bioenergetics of astrocytic Ca(2+) homeostasis, by analyzing interdependency of glycogen and store-operated Ca(2+) entry (SOCE), a mechanism in cellular signaling that maintains high endoplasmatic reticulum (ER) Ca(2+) concentration and thus provides the basis for store-dependent Ca(2+) signaling. We stimulated SOCE in primary cultures of murine cerebellar and cortical astrocytes, and determined glycogen content to investigate the effects of SOCE on glycogen metabolism. By blocking glycogenolysis, we tested energetic dependency of SOCE-related Ca(2+) dynamics on glycogenolytic ATP. Our results show that SOCE triggers astrocytic glycogenolysis. Upon inhibition of adenylate cyclase with 2',5'-dideoxyadenosine, glycogen content was no longer significantly different from that in unstimulated control cells, indicating that SOCE triggers astrocytic glycogenolysis in a cAMP-dependent manner. When glycogenolysis was inhibited in cortical astrocytes by 1,4-dideoxy-1,4-imino-D-arabinitol, the amount of Ca(2+) loaded into ER via sarco/endoplasmic reticulum Ca(2)-ATPase (SERCA) was reduced, which suggests that SERCA pumps preferentially metabolize glycogenolytic ATP. Our study demonstrates SOCE as a novel pathway in stimulating astrocytic glycogenolysis. We also provide first evidence for a new functional role of brain glycogen, in providing local ATP to SERCA, thus establishing the bioenergetic basis for astrocytic Ca(2+) signaling. This mechanism could offer a novel explanation for the impact of glycogen on learning and memory. PMID:24464850

  1. Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome

    PubMed Central

    Loughran, Thomas P.; Papin, Jason A.; Albert, Reka

    2015-01-01

    We present a novel methodology to construct a Boolean dynamic model from time series metagenomic information and integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic underpinnings for microbial interactions. We apply this in the context of a critical health issue: clindamycin antibiotic treatment and opportunistic Clostridium difficile infection. Our model recapitulates known dynamics of clindamycin antibiotic treatment and C. difficile infection and predicts therapeutic probiotic interventions to suppress C. difficile infection. Genome-scale metabolic network reconstructions reveal metabolic differences between community members and are used to explore the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of our computational model, that B. intestinihominis can in fact slow C. difficile growth. PMID:26102287

  2. Exploring poly-beta-hydroxy-butyrate metabolism through network-based extreme pathway analysis.

    PubMed

    Ding, Dewu; Ding, Yanrui; Cai, Yujie; Chen, Shouwen; Xu, Wenbo

    2008-01-01

    The objective of this article is to obtain a more detailed insight into poly-beta-hydroxybutyrate (PHB) metabolism through network-based metabolic pathway analysis. We employ extreme pathways to perform this study, because calculating and interpreting extreme pathways is a promising way for pathway analysis and metabolic engineering. After giving an in silico model of butanoate metabolism of Bacillus thuringiensis 97-27 (btk), extreme pathways were calculated and classified. Furthermore, the type I and II extreme pathways were further classified and analyzed in detail based on their structure and functional capabilities. Besides "historical" biochemical pathways, the results also suggest that there are some novel pathways. PMID:18600631

  3. Cellular energy metabolism. Final technical report, May 1, 1987--April 30, 1991

    SciTech Connect

    Glaser, M.

    1991-06-01

    Studies have been carried out on adenylate kinase which is an important enzyme in determining the concentrations of the adenine nucleotides. An efficient method has been developed to clone mutant adenylate kinase genes in E. coli. Site-specific mutagenesis of the wild type gene also has been used to obtain forms of adenylate kinase with altered amino acids. The wild type and mutant forms of adenylate kinase have been overexpressed and large quantities were readily isolated. The kinetic and fluorescence properties of the different forms of adenylate kinase were characterized. This has led to a new model for the location of the AMP and ATP bindings sites on the enzyme and a proposal for the mechanism of substrate inhibition. Crystals of the wild type enzyme were obtained that diffract to at least 2.3 {angstrom} resolution. Experiments were also initiated to determine the function of adenylate kinase in vivo. In one set of experiments, E. coli strains with mutations in adenylate kinase showed large changes in cellular nucleotides after reaching the stationary phase in a low phosphate medium. This was caused by selective proteolytic degradation of the mutant adenylate kinase caused by phosphate starvation.

  4. Linking the population pharmacokinetics of tenofovir and its metabolites with its cellular uptake and metabolism.

    PubMed

    Madrasi, K; Burns, R N; Hendrix, C W; Fossler, M J; Chaturvedula, A

    2014-01-01

    Empirical pharmacokinetic models are used to explain the pharmacokinetics of the antiviral drug tenofovir (TFV) and its metabolite TFV diphosphate (TFV-DP) in peripheral blood mononuclear cells. These empirical models lack the ability to explain differences between the disposition of TFV-DP in HIV-infected patients vs. healthy individuals. Such differences may lie in the mechanisms of TFV transport and phosphorylation. Therefore, we developed an exploratory model based on mechanistic mass transport principles and enzyme kinetics to examine the uptake and phosphorylation kinetics of TFV. TFV-DP median Cmax from the model was 38.5 fmol/10(6) cells, which is bracketed by two reported healthy volunteer studies (38 and 51 fmol/10(6) cells). The model presented provides a foundation for exploration of TFV uptake and phosphorylation kinetics for various routes of TFV administration and can be updated as more is known on actual mechanisms of cellular transport of TFV. PMID:25390686

  5. Capsule Biosynthesis and Basic Metabolism in Streptococcus pneumoniae Are Linked through the Cellular Phosphoglucomutase

    PubMed Central

    Hardy, Gail G.; Caimano, Melissa J.; Yother, Janet

    2000-01-01

    Synthesis of the type 3 capsular polysaccharide of Streptococcus pneumoniae requires UDP-glucose (UDP-Glc) and UDP-glucuronic acid (UDP-GlcUA) for production of the [3)-β-d-GlcUA-(1→4)-β-d-Glc-(1→]n polymer. The generation of UDP-Glc proceeds by conversion of Glc-6-P to Glc-1-P to UDP-Glc and is mediated by a phosphoglucomutase (PGM) and a Glc-1-P uridylyltransferase, respectively. Genes encoding both a Glc-1-P uridylyltransferase (cps3U) and a PGM homologue (cps3M) are present in the type 3 capsule locus, but these genes are not essential for capsule production. In this study, we characterized a mutant that produces fourfold less capsule than the type 3 parent. The spontaneous mutation resulting in this phenotype was not contained in the type 3 capsule locus but was instead located in a distant gene (pgm) encoding a second PGM homologue. The function of this gene product as a PGM was demonstrated through enzymatic and complementation studies. Insertional inactivation of pgm reduced capsule production to less than 10% of the parental level. The loss of PGM activity in the insertion mutants also caused growth defects and a strong selection for isolates containing second-site suppressor mutations. These results demonstrate that most of the PGM activity required for type 3 capsule biosynthesis is derived from the cellular PGM. PMID:10714989

  6. Global metabolic network reorganization by adaptive mutations allows fast growth of Escherichia coli on glycerol.

    PubMed

    Cheng, Kian-Kai; Lee, Baek-Seok; Masuda, Takeshi; Ito, Takuro; Ikeda, Kazutaka; Hirayama, Akiyoshi; Deng, Lingli; Dong, Jiyang; Shimizu, Kazuyuki; Soga, Tomoyoshi; Tomita, Masaru; Palsson, Bernhard O; Robert, Martin

    2014-01-01

    Comparative whole-genome sequencing enables the identification of specific mutations during adaptation of bacteria to new environments and allelic replacement can establish their causality. However, the mechanisms of action are hard to decipher and little has been achieved for epistatic mutations, especially at the metabolic level. Here we show that a strain of Escherichia coli carrying mutations in the rpoC and glpK genes, derived from adaptation in glycerol, uses two distinct metabolic strategies to gain growth advantage. A 27-bp deletion in the rpoC gene first increases metabolic efficiency. Then, a point mutation in the glpK gene promotes growth by improving glycerol utilization but results in increased carbon wasting as overflow metabolism. In a strain carrying both mutations, these contrasting carbon/energy saving and wasting mechanisms work together to give an 89% increase in growth rate. This study provides insight into metabolic reprogramming during adaptive laboratory evolution for fast cellular growth. PMID:24481126

  7. Prosthetic gene networks as an alternative to standard pharmacotherapies for metabolic disorders.

    PubMed

    Heng, Boon Chin; Aubel, Dominique; Fussenegger, Martin

    2015-12-01

    Synthetic biology makes inroads into clinical therapy with the debut of closed-loop prosthetic gene networks specifically designed to treat human diseases. Prosthetic networks are synthetic sensor/effector devices that could functionally integrate and interface with host metabolism to monitor disease states and coordinate appropriate therapeutic responses in a self-sufficient, timely and automatic manner. Prosthetic networks hold particular promise for the current global epidemic of closely interrelated metabolic disorders encompassing obesity, type 2 diabetes, hypertension and hyperlipidaemia, which arise from the unhealthy lifestyle and dietary factors in the modern urbanised world. This review will critically examine the various attempts at constructing prosthetic gene networks for the treatment of these metabolic disorders, as well as provide insight into future developments in the field. PMID:25679308

  8. Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A

    PubMed Central

    Grimm, Christina; Lin, Suling J.; Wappler, Jessica; Klinger, Bertram; Blüthgen, Nils; Du Bois, Ilona; Schmeck, Bernd; Lehrach, Hans; de Graauw, Marjo; Goncalves, Emanuel; Saez-Rodriguez, Julio; Tan, Patrick; Grabsch, Heike I.; Prigione, Alessandro; Kempa, Stefan; Cramer, Thorsten

    2016-01-01

    Despite the approval of numerous molecular targeted drugs, long-term antiproliferative efficacy is rarely achieved and therapy resistance remains a central obstacle of cancer care. Combined inhibition of multiple cancer-driving pathways promises to improve antiproliferative efficacy. HIF-1 is a driver of gastric cancer and considered to be an attractive target for therapy. We noted that gastric cancer cells are able to functionally compensate the stable loss of HIF-1α. Via transcriptomics we identified a group of upregulated genes in HIF-1α-deficient cells and hypothesized that these genes confer survival upon HIF-1α loss. Strikingly, simultaneous knock-down of HIF-1α and Annexin A1 (ANXA1), one of the identified genes, resulted in complete cessation of proliferation. Using stable isotope-resolved metabolomics, oxidative and reductive glutamine metabolism was found to be significantly impaired in HIF-1α/ANXA1-deficient cells, potentially explaining the proliferation defect. In summary, we present a conceptually novel application of stable gene inactivation enabling in-depth deconstruction of resistance mechanisms. In theory, this experimental approach is applicable to any cancer-driving gene or pathway and promises to identify various new targets for combination therapies. PMID:26760764

  9. Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A.

    PubMed

    Rohwer, Nadine; Bindel, Fabian; Grimm, Christina; Lin, Suling J; Wappler, Jessica; Klinger, Bertram; Blüthgen, Nils; Du Bois, Ilona; Schmeck, Bernd; Lehrach, Hans; de Graauw, Marjo; Goncalves, Emanuel; Saez-Rodriguez, Julio; Tan, Patrick; Grabsch, Heike I; Prigione, Alessandro; Kempa, Stefan; Cramer, Thorsten

    2016-02-01

    Despite the approval of numerous molecular targeted drugs, long-term antiproliferative efficacy is rarely achieved and therapy resistance remains a central obstacle of cancer care. Combined inhibition of multiple cancer-driving pathways promises to improve antiproliferative efficacy. HIF-1 is a driver of gastric cancer and considered to be an attractive target for therapy. We noted that gastric cancer cells are able to functionally compensate the stable loss of HIF-1α. Via transcriptomics we identified a group of upregulated genes in HIF-1α-deficient cells and hypothesized that these genes confer survival upon HIF-1α loss. Strikingly, simultaneous knock-down of HIF-1α and Annexin A1 (ANXA1), one of the identified genes, resulted in complete cessation of proliferation. Using stable isotope-resolved metabolomics, oxidative and reductive glutamine metabolism was found to be significantly impaired in HIF-1α/ANXA1-deficient cells, potentially explaining the proliferation defect. In summary, we present a conceptually novel application of stable gene inactivation enabling in-depth deconstruction of resistance mechanisms. In theory, this experimental approach is applicable to any cancer-driving gene or pathway and promises to identify various new targets for combination therapies. PMID:26760764

  10. Cellular and subcellular localization of enzymes of arginine metabolism in rat kidney.

    PubMed Central

    Dhanakoti, S N; Brosnan, M E; Herzberg, G R; Brosnan, J T

    1992-01-01

    Rat kidneys extract citrulline derived from the intestinal metabolism of glutamine and convert it stoichiometrically into arginine. This pathway constitutes the major endogenous source of arginine. We investigated the localization of enzymes of arginine synthesis, argininosuccinate synthase and lyase, and of breakdown, arginase and ornithine aminotransferase, in five regions of rat kidney, in cortical tubule fractions and in subcellular fractions of cortex. Argininosuccinate synthase and lyase were found almost exclusively in cortex. Arginase and ornithine aminotransferase were found in inner cortex and outer medulla. Since cortical tissue primarily consists of proximal convoluted and straight tubules, distal tubules and glomeruli, we prepared cortical tubule fragments by collagenase digestion of cortices and fractionated them on a Percoll gradient. Argininosuccinate synthase and lyase were found to be markedly enriched in proximal convoluted tubules, whereas less than 10% of arginase and ornithine aminotransferase, were recovered in this fraction. Arginine production from citrulline was also enriched in proximal convoluted tubules. Subcellular fractionation of kidney cortex revealed that argininosuccinate synthase and lyase are cytosolic. We therefore conclude that arginine synthesis occurs in the cytoplasm of the cells of the proximal convoluted tubule. Images Fig. 1. Fig. 2. PMID:1312326

  11. Reconstruction of Tissue-Specific Metabolic Networks Using CORDA

    PubMed Central

    Schultz, André; Qutub, Amina A.

    2016-01-01

    Human metabolism involves thousands of reactions and metabolites. To interpret this complexity, computational modeling becomes an essential experimental tool. One of the most popular techniques to study human metabolism as a whole is genome scale modeling. A key challenge to applying genome scale modeling is identifying critical metabolic reactions across diverse human tissues. Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. CORDA performs more efficiently computationally, shows better agreement to experimental data, and displays better model functionality and capacity when compared to previous algorithms. CORDA also returns reaction associations that can greatly assist in any manual curation to be performed following the automated reconstruction process. Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions. These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation. PMID:26942765

  12. Noise-robust realization of Turing-complete cellular automata by using neural networks with pattern representation

    NASA Astrophysics Data System (ADS)

    Oku, Makito; Aihara, Kazuyuki

    2010-11-01

    A modularly-structured neural network model is considered. Each module, which we call a ‘cell’, consists of two parts: a Hopfield neural network model and a multilayered perceptron. An array of such cells is used to simulate the Rule 110 cellular automaton with high accuracy even when all the units of neural networks are replaced by stochastic binary ones. We also find that noise not only degrades but also facilitates computation if the outputs of multilayered perceptrons are below the threshold required to update the states of the cells, which is a stochastic resonance in computation.

  13. Molecular, cellular, and tissue impact of depleted uranium on xenobiotic-metabolizing enzymes.

    PubMed

    Gueguen, Yann; Rouas, Caroline; Monin, Audrey; Manens, Line; Stefani, Johanna; Delissen, Olivia; Grison, Stéphane; Dublineau, Isabelle

    2014-02-01

    Enzymes that metabolize xenobiotics (XME) are well recognized in experimental models as representative indicators of organ detoxification functions and of exposure to toxicants. As several in vivo studies have shown, uranium can alter XME in the rat liver or kidneys after either acute or chronic exposure. To determine how length or level of exposure affects these changes in XME, we continued our investigation of chronic rat exposure to depleted uranium (DU, uranyl nitrate). The first study examined the effect of duration (1-18 months) of chronic exposure to DU, the second evaluated dose dependence, from a level close to that found in the environment near mining sites (0.2 mg/L) to a supra-environmental dose (120 mg/L, 10 times the highest level naturally found in the environment), and the third was an in vitro assessment of whether DU exposure directly affects XME and, in particular, CYP3A. The experimental in vivo models used here demonstrated that CYP3A is the enzyme modified to the greatest extent: high gene expression changed after 6 and 9 months. The most substantial effects were observed in the liver of rats after 9 months of exposure to 120 mg/L of DU: CYP3A gene and protein expression and enzyme activity all decreased by more than 40 %. Nonetheless, no direct effect of DU by itself was observed after in vitro exposure of rat microsomal preparations, HepG2 cells, or human primary hepatocytes. Overall, these results probably indicate the occurrence of regulatory or adaptive mechanisms that could explain the indirect effect observed in vivo after chronic exposure. PMID:24146111

  14. SERCA2a upregulation ameliorates cellular alternans induced by metabolic inhibition.

    PubMed

    Stary, Victoria; Puppala, Dheeraj; Scherrer-Crosbie, Marielle; Dillmann, Wolfgang H; Armoundas, Antonis A

    2016-04-15

    Cardiac alternans has been