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Sample records for bacterial metabolic networks

  1. Identifying essential genes in bacterial metabolic networks with machine learning methods

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2010-05-01

    Full Text Available Abstract Background Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective. Results We developed a machine learning technique to identify essential genes using the experimental data of genome-wide knock-out screens from one bacterial organism to infer essential genes of another related bacterial organism. We used a broad variety of topological features, sequence characteristics and co-expression properties potentially associated with essentiality, such as flux deviations, centrality, codon frequencies of the sequences, co-regulation and phyletic retention. An organism-wise cross-validation on bacterial species yielded reliable results with good accuracies (area under the receiver-operator-curve of 75% - 81%. Finally, it was applied to drug target predictions for Salmonella typhimurium. We compared our predictions to the viability of experimental knock-outs of S. typhimurium and identified 35 enzymes, which are highly relevant to be considered as potential drug targets. Specifically, we detected promising drug targets in the non-mevalonate pathway. Conclusions Using elaborated features characterizing network topology, sequence information and microarray data enables to predict essential genes from a bacterial reference organism to a related query organism without any knowledge about the essentiality of genes of the query organism. In general, such a method is beneficial for inferring drug targets when experimental data about genome-wide knockout screens is not available for the investigated organism.

  2. Prebiotic metabolic networks?

    OpenAIRE

    Luisi, Pier Luigi

    2014-01-01

    A prebiotic origin of metabolism has been proposed as one of several scenarios for the origin of life. In their recent work, Ralser and colleagues (Keller et al, 2014) observe an enzyme‐free, metabolism‐like reaction network under conditions reproducing a possible prebiotic environment.

  3. Robustness of metabolic networks

    Science.gov (United States)

    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.

  4. Impact of genome reduction on bacterial metabolism and its regulation.

    Science.gov (United States)

    Yus, Eva; Maier, Tobias; Michalodimitrakis, Konstantinos; van Noort, Vera; Yamada, Takuji; Chen, Wei-Hua; Wodke, Judith A H; Güell, Marc; Martínez, Sira; Bourgeois, Ronan; Kühner, Sebastian; Raineri, Emanuele; Letunic, Ivica; Kalinina, Olga V; Rode, Michaela; Herrmann, Richard; Gutiérrez-Gallego, Ricardo; Russell, Robert B; Gavin, Anne-Claude; Bork, Peer; Serrano, Luis

    2009-11-27

    To understand basic principles of bacterial metabolism organization and regulation, but also the impact of genome size, we systematically studied one of the smallest bacteria, Mycoplasma pneumoniae. A manually curated metabolic network of 189 reactions catalyzed by 129 enzymes allowed the design of a defined, minimal medium with 19 essential nutrients. More than 1300 growth curves were recorded in the presence of various nutrient concentrations. Measurements of biomass indicators, metabolites, and 13C-glucose experiments provided information on directionality, fluxes, and energetics; integration with transcription profiling enabled the global analysis of metabolic regulation. Compared with more complex bacteria, the M. pneumoniae metabolic network has a more linear topology and contains a higher fraction of multifunctional enzymes; general features such as metabolite concentrations, cellular energetics, adaptability, and global gene expression responses are similar, however.

  5. Metabolic aspects of bacterial persisters

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    Marcel ePrax

    2014-10-01

    Full Text Available Persister cells form a multi-drug tolerant subpopulation within an isogenic culture of bacteria that are genetically susceptible to antibiotics. Studies with different Gram negative and Gram positive bacteria have identified a large number of genes associated with the persister state. In contrast, the revelation of persister metabolism has only been addressed recently. We here summarize metabolic aspects of persisters, which includes an overview about the bifunctional role of selected carbohydrates as both triggers for the exit from the drug tolerant state and metabolites which persisters feed on. Also alarmones as indicators for starvation have been shown to influence persister levels via different signaling cascades involving the activation of toxin-antitoxin systems and other regulatory factors. Finally, recent data obtained by 13C-isotopologue profiling demonstrated an active amino acid anabolism in Staphylococcus aureus cultures challenged with high drug concentrations. Understanding the metabolism of persister cells poses challenges but also paves the way for the development of anti-persister compounds.

  6. The role of metabolism in bacterial persistence

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    Stephanie M. Amato

    2014-03-01

    Full Text Available Bacterial persisters are phenotypic variants with extraordinary tolerances toward antibiotics. Persister survival has been attributed to inhibition of essential cell functions during antibiotic stress, followed by reversal of the process and resumption of growth upon removal of the antibiotic. Metabolism plays a critical role in this process, since it participates in the entry, maintenance, and exit from the persister phenotype. Here, we review the experimental evidence that demonstrates the importance of metabolism to persistence, highlight the successes and potential for targeting metabolism in the search for anti-persister therapies, and discuss the current methods and challenges to understand persister physiology.

  7. Context-dependent metabolic networks

    CERN Document Server

    Beguerisse-Díaz, Mariano; Oyarzún, Diego; Picó, Jesús; Barahona, Mauricio

    2016-01-01

    Cells adapt their metabolism to survive changes in their environment. We present a framework for the construction and analysis of metabolic reaction networks that can be tailored to reflect different environmental conditions. Using context-dependent flux distributions from Flux Balance Analysis (FBA), we produce directed networks with weighted links representing the amount of metabolite flowing from a source reaction to a target reaction per unit time. Such networks are analyzed with tools from network theory to reveal salient features of metabolite flows in each biological context. We illustrate our approach with the directed network of the central carbon metabolism of Escherichia coli, and study its properties in four relevant biological scenarios. Our results show that both flow and network structure depend drastically on the environment: networks produced from the same metabolic model in different contexts have different edges, components, and flow communities, capturing the biological re-routing of metab...

  8. Metabolism links bacterial biofilms and colon carcinogenesis.

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    Johnson, Caroline H; Dejea, Christine M; Edler, David; Hoang, Linh T; Santidrian, Antonio F; Felding, Brunhilde H; Ivanisevic, Julijana; Cho, Kevin; Wick, Elizabeth C; Hechenbleikner, Elizabeth M; Uritboonthai, Winnie; Goetz, Laura; Casero, Robert A; Pardoll, Drew M; White, James R; Patti, Gary J; Sears, Cynthia L; Siuzdak, Gary

    2015-06-01

    Bacterial biofilms in the colon alter the host tissue microenvironment. A role for biofilms in colon cancer metabolism has been suggested but to date has not been evaluated. Using metabolomics, we investigated the metabolic influence that microbial biofilms have on colon tissues and the related occurrence of cancer. Patient-matched colon cancers and histologically normal tissues, with or without biofilms, were examined. We show the upregulation of polyamine metabolites in tissues from cancer hosts with significant enhancement of N(1), N(12)-diacetylspermine in both biofilm-positive cancer and normal tissues. Antibiotic treatment, which cleared biofilms, decreased N(1), N(12)-diacetylspermine levels to those seen in biofilm-negative tissues, indicating that host cancer and bacterial biofilm structures contribute to the polyamine metabolite pool. These results show that colonic mucosal biofilms alter the cancer metabolome to produce a regulator of cellular proliferation and colon cancer growth potentially affecting cancer development and progression.

  9. Genetic and computational identification of a conserved bacterial metabolic module.

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    Cara C Boutte

    2008-12-01

    Full Text Available We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the alpha-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1 confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2 defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3 identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other alpha-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo

  10. Optimal flux patterns in cellular metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. Genome-scale metabolic network reconstruction.

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    Fondi, Marco; Liò, Pietro

    2015-01-01

    Bacterial metabolism is an important source of novel products/processes for everyday life and strong efforts are being undertaken to discover and exploit new usable substances of microbial origin. Computational modeling and in silico simulations are powerful tools in this context since they allow the exploration and a deeper understanding of bacterial metabolic circuits. Many approaches exist to quantitatively simulate chemical reaction fluxes within the whole microbial metabolism and, regardless of the technique of choice, metabolic model reconstruction is the first step in every modeling pipeline. Reconstructing a metabolic network consists in drafting the list of the biochemical reactions that an organism can carry out together with information on cellular boundaries, a biomass assembly reaction, and exchange fluxes with the external environment. Building up models able to represent the different functional cellular states is universally recognized as a tricky task that requires intensive manual effort and much additional information besides genome sequence. In this chapter we present a general protocol for metabolic reconstruction in bacteria and the main challenges encountered during this process. PMID:25343869

  12. Complex networks theory for analyzing metabolic networks

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; YU Hong; LUO Jianhua; CAO Z.W.; LI Yixue

    2006-01-01

    One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism,while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.

  13. Metabolic Responses of Bacterial Cells to Immobilization

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    Joanna Żur

    2016-07-01

    Full Text Available In recent years immobilized cells have commonly been used for various biotechnological applications, e.g., antibiotic production, soil bioremediation, biodegradation and biotransformation of xenobiotics in wastewater treatment plants. Although the literature data on the physiological changes and behaviour of cells in the immobilized state remain fragmentary, it is well documented that in natural settings microorganisms are mainly found in association with surfaces, which results in biofilm formation. Biofilms are characterized by genetic and physiological heterogeneity and the occurrence of altered microenvironments within the matrix. Microbial cells in communities display a variety of metabolic differences as compared to their free-living counterparts. Immobilization of bacteria can occur either as a natural phenomenon or as an artificial process. The majority of changes observed in immobilized cells result from protection provided by the supports. Knowledge about the main physiological responses occurring in immobilized cells may contribute to improving the efficiency of immobilization techniques. This paper reviews the main metabolic changes exhibited by immobilized bacterial cells, including growth rate, biodegradation capabilities, biocatalytic efficiency and plasmid stability.

  14. Metabolic Responses of Bacterial Cells to Immobilization.

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    Żur, Joanna; Wojcieszyńska, Danuta; Guzik, Urszula

    2016-01-01

    In recent years immobilized cells have commonly been used for various biotechnological applications, e.g., antibiotic production, soil bioremediation, biodegradation and biotransformation of xenobiotics in wastewater treatment plants. Although the literature data on the physiological changes and behaviour of cells in the immobilized state remain fragmentary, it is well documented that in natural settings microorganisms are mainly found in association with surfaces, which results in biofilm formation. Biofilms are characterized by genetic and physiological heterogeneity and the occurrence of altered microenvironments within the matrix. Microbial cells in communities display a variety of metabolic differences as compared to their free-living counterparts. Immobilization of bacteria can occur either as a natural phenomenon or as an artificial process. The majority of changes observed in immobilized cells result from protection provided by the supports. Knowledge about the main physiological responses occurring in immobilized cells may contribute to improving the efficiency of immobilization techniques. This paper reviews the main metabolic changes exhibited by immobilized bacterial cells, including growth rate, biodegradation capabilities, biocatalytic efficiency and plasmid stability. PMID:27455220

  15. Bacterial Metabolism Shapes the Host-Pathogen Interface.

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    Passalacqua, Karla D; Charbonneau, Marie-Eve; O'Riordan, Mary X D

    2016-06-01

    Bacterial pathogens have evolved to exploit humans as a rich source of nutrients to support survival and replication. The pathways of bacterial metabolism that permit successful colonization are surprisingly varied and highlight remarkable metabolic flexibility. The constraints and immune pressures of distinct niches within the human body set the stage for understanding the mechanisms by which bacteria acquire critical nutrients. In this article we discuss how different bacterial pathogens carry out carbon and energy metabolism in the host and how they obtain or use key nutrients for replication and immune evasion. PMID:27337445

  16. Genome-scale models of bacterial metabolism: reconstruction and applications

    OpenAIRE

    Durot, Maxime; Bourguignon, Pierre-Yves; Schachter, Vincent

    2008-01-01

    Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety...

  17. Carbon and phosphorus regulating bacterial metabolism in oligotrophic boreal lakes

    DEFF Research Database (Denmark)

    Vidal, L. O.; Graneli, W.; Daniel, C. B.;

    2011-01-01

    -P and glucose-C alone or in combination (0.01 and 0.3 mg L(-1), respectively) was added to 1.0 mu m filtered lake water and incubated in darkness at 20 degrees C. Additions of glucose (C) and phosphorus (P) alone did not lead to changes in the rates of bacterial metabolic processes, whereas bacterial...... respiration and bacterial production responded positively to C + P enrichment for most of the lakes sampled. Bacterial growth efficiency showed a wide range (2.5-28.7%) and low mean value (12%). These variations were not correlated with the DOC concentration. Our results show that heterotrophic bacterial...

  18. Remodeling bacterial polysaccharides by metabolic pathway engineering

    OpenAIRE

    Yi, Wen; Liu, Xianwei; Li, Yanhong; Li, Jianjun; Xia, Chengfeng; Zhou, Guangyan; Zhang, Wenpeng; Zhao, Wei; Chen, Xi; Wang, Peng George

    2009-01-01

    Introducing structural modifications into biomolecules represents a powerful approach to dissect their functions and roles in biological processes. Bacterial polysaccharides, despite their rich structural information and essential roles in bacterium-host interactions and bacterial virulence, have largely been unexplored for in vivo structural modifications. In this study, we demonstrate the incorporation of a panel of monosaccharide analogs into bacterial polysaccharides in a highly homogenou...

  19. Highly optimised global organisation of metabolic networks

    OpenAIRE

    Tanaka, R.; Csete, M.; Doyle, J.

    2005-01-01

    High-level, mathematically precise descriptions of the global organisation of complex metabolic networks are necessary for understanding the global structure of metabolic networks, the interpretation and integration of large amounts of biologic data (sequences, various -omics) and ultimately for rational design of therapies for disease processes. Metabolic networks are highly organised to execute their function efficiently while tolerating wide variation in their environment. These network...

  20. Bacterial microcompartments and the modular construction of microbial metabolism.

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    Kerfeld, Cheryl A; Erbilgin, Onur

    2015-01-01

    Bacterial microcompartments (BMCs) are protein-bound organelles predicted to be present across 23 bacterial phyla. BMCs facilitate carbon fixation as well as the aerobic and anaerobic catabolism of a variety of organic compounds. These functions have been linked to ecological nutrient cycling, symbiosis, pathogenesis, and cardiovascular disease. Within bacterial cells, BMCs are metabolic modules that can be further dissociated into their constituent structural and functional protein domains. Viewing BMCs as genetic, structural, functional, and evolutionary modules provides a framework for understanding both BMC-mediated metabolism and for adapting their architectures for applications in synthetic biology.

  1. Predicting effects of structural stress in a genome-reduced model bacterial metabolism

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    Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

    2012-08-01

    Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

  2. A network perspective on metabolic inconsistency

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    Sonnenschein Nikolaus

    2012-05-01

    Full Text Available Abstract Background Integrating gene expression profiles and metabolic pathways under different experimental conditions is essential for understanding the coherence of these two layers of cellular organization. The network character of metabolic systems can be instrumental in developing concepts of agreement between expression data and pathways. A network-driven interpretation of gene expression data has the potential of suggesting novel classifiers for pathological cellular states and of contributing to a general theoretical understanding of gene regulation. Results Here, we analyze the coherence of gene expression patterns and a reconstruction of human metabolism, using consistency scores obtained from network and constraint-based analysis methods. We find a surprisingly strong correlation between the two measures, demonstrating that a substantial part of inconsistencies between metabolic processes and gene expression can be understood from a network perspective alone. Prompted by this finding, we investigate the topological context of the individual biochemical reactions responsible for the observed inconsistencies. On this basis, we are able to separate the differential contributions that bear physiological information about the system, from the unspecific contributions that unravel gaps in the metabolic reconstruction. We demonstrate the biological potential of our network-driven approach by analyzing transcriptome profiles of aldosterone producing adenomas that have been obtained from a cohort of Primary Aldosteronism patients. We unravel systematics in the data that could not have been resolved by conventional microarray data analysis. In particular, we discover two distinct metabolic states in the adenoma expression patterns. Conclusions The methodology presented here can help understand metabolic inconsistencies from a network perspective. It thus serves as a mediator between the topology of metabolic systems and their dynamical

  3. Computational Methods for Modification of Metabolic Networks

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    Takeyuki Tamura

    2015-01-01

    Full Text Available In metabolic engineering, modification of metabolic networks is an important biotechnology and a challenging computational task. In the metabolic network modification, we should modify metabolic networks by newly adding enzymes or/and knocking-out genes to maximize the biomass production with minimum side-effect. In this mini-review, we briefly review constraint-based formalizations for Minimum Reaction Cut (MRC problem where the minimum set of reactions is deleted so that the target compound becomes non-producible from the view point of the flux balance analysis (FBA, elementary mode (EM, and Boolean models. Minimum Reaction Insertion (MRI problem where the minimum set of reactions is added so that the target compound newly becomes producible is also explained with a similar formalization approach. The relation between the accuracy of the models and the risk of overfitting is also discussed.

  4. Phenotype prediction in regulated metabolic networks

    OpenAIRE

    Centler Florian; Kaleta Christoph; di Fenizio Pietro; Dittrich Peter

    2008-01-01

    Abstract Background Due to the growing amount of biological knowledge that is incorporated into metabolic network models, their analysis has become more and more challenging. Here, we examine the capabilities of the recently introduced chemical organization theory (OT) to ease this task. Considering only network stoichiometry, the theory allows the prediction of all potentially persistent species sets and therewith rigorously relates the structure of a network to its potential dynamics. By th...

  5. Regulatory schemes to achieve optimal flux partitioning in bacterial metabolism

    Science.gov (United States)

    Tang, Lei-Han; Yang, Zhu; Hui, Sheng; Kim, Pan-Jun; Li, Xue-Fei; Hwa, Terence

    2012-02-01

    The flux balance analysis (FBA) offers a way to compute the optimal performance of a given metabolic network when the maximum incoming flux of nutrient molecules and other essential ingredients for biosynthesis are specified. Here we report a theoretical and computational analysis of the network structure and regulatory interactions in an E. coli cell. An automated scheme is devised to simplify the network topology and to enumerate the independent flux degrees of freedom. The network organization revealed by the scheme enables a detailed interpretation of the three layers of metabolic regulation known in the literature: i) independent transcriptional regulation of biosynthesis and salvage pathways to render the network tree-like under a given nutrient condition; ii) allosteric end-product inhibition of enzyme activity at entry points of synthesis pathways for metabolic flux partitioning according to consumption; iii) homeostasis of currency and carrier compounds to maintain sufficient supply of global commodities. Using the amino-acid synthesis pathways as an example, we show that the FBA result can be reproduced with suitable implementation of the three classes of regulatory interactions with literature evidence.

  6. Phenotype prediction in regulated metabolic networks

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    Centler Florian

    2008-04-01

    Full Text Available Abstract Background Due to the growing amount of biological knowledge that is incorporated into metabolic network models, their analysis has become more and more challenging. Here, we examine the capabilities of the recently introduced chemical organization theory (OT to ease this task. Considering only network stoichiometry, the theory allows the prediction of all potentially persistent species sets and therewith rigorously relates the structure of a network to its potential dynamics. By this, the phenotypes implied by a metabolic network can be predicted without the need for explicit knowledge of the detailed reaction kinetics. Results We propose an approach to deal with regulation – and especially inhibitory interactions – in chemical organization theory. One advantage of this approach is that the metabolic network and its regulation are represented in an integrated way as one reaction network. To demonstrate the feasibility of this approach we examine a model by Covert and Palsson (J Biol Chem, 277(31, 2002 of the central metabolism of E. coli that incorporates the regulation of all involved genes. Our method correctly predicts the known growth phenotypes on 16 different substrates. Without specific assumptions, organization theory correctly predicts the lethality of knockout experiments in 101 out of 116 cases. Taking into account the same model specific assumptions as in the regulatory flux balance analysis (rFBA by Covert and Palsson, the same performance is achieved (106 correctly predicted cases. Two model specific assumptions had to be considered: first, we have to assume that secreted molecules do not influence the regulatory system, and second, that metabolites with increasing concentrations indicate a lethal state. Conclusion The introduced approach to model a metabolic network and its regulation in an integrated way as one reaction network makes organization analysis a universal technique to study the potential behavior of

  7. Dispersal networks for enhancing bacterial degradation in heterogeneous environments

    Energy Technology Data Exchange (ETDEWEB)

    Banitz, Thomas, E-mail: thomas.banitz@ufz.de [Department of Ecological Modelling, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Wick, Lukas Y.; Fetzer, Ingo [Department of Environmental Microbiology, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Frank, Karin [Department of Ecological Modelling, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Harms, Hauke [Department of Environmental Microbiology, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Johst, Karin [Department of Ecological Modelling, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany)

    2011-10-15

    Successful biodegradation of organic soil pollutants depends on their bioavailability to catabolically active microorganisms. In particular, environmental heterogeneities often limit bacterial access to pollutants. Experimental and modelling studies revealed that fungal networks can facilitate bacterial dispersal and may thereby improve pollutant bioavailability. Here, we investigate the influence of such bacterial dispersal networks on biodegradation performance under spatially heterogeneous abiotic conditions using a process-based simulation model. To match typical situations in polluted soils, two types of abiotic conditions are studied: heterogeneous bacterial dispersal conditions and heterogeneous initial resource distributions. The model predicts that networks facilitating bacterial dispersal can enhance biodegradation performance for a wide range of these conditions. Additionally, the time horizon over which this performance is assessed and the network's spatial configuration are key factors determining the degree of biodegradation improvement. Our results support the idea of stimulating the establishment of fungal mycelia for enhanced bioremediation of polluted soils. - Highlights: > Bacterial dispersal networks can considerably improve biodegradation performance. > They facilitate bacterial access to dispersal-limited areas and remote resources. > Abiotic conditions, time horizon and network structure govern the improvements. > Stimulating the establishment of fungal mycelia promises enhanced soil remediation. - Simulation modelling demonstrates that fungus-mediated bacterial dispersal can considerably improve the bioavailability of organic pollutants under spatially heterogeneous abiotic conditions typical for water-unsaturated soils.

  8. Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

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    van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

    2012-01-01

    This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

  9. Metabolic flux analysis of Gluconacetobacter xylinus for bacterial cellulose production.

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    Zhong, Cheng; Zhang, Gui-Cai; Liu, Miao; Zheng, Xin-Tong; Han, Pei-Pei; Jia, Shi-Ru

    2013-07-01

    Metabolic flux analysis was used to reveal the metabolic distributions in Gluconacetobacter xylinus (CGMCC no. 2955) cultured on different carbon sources. Compared with other sources, glucose, fructose, and glycerol could achieve much higher bacterial cellulose (BC) yields from G. xylinus (CGMCC no. 2955). The glycerol led to the highest BC production with a metabolic yield of 14.7 g/mol C, which was approximately 1.69-fold and 2.38-fold greater than that produced using fructose and glucose medium, respectively. The highest BC productivity from G. xylinus CGMCC 2955 was 5.97 g BC/L (dry weight) when using glycerol as the sole carbon source. Metabolic flux analysis for the central carbon metabolism revealed that about 47.96 % of glycerol was transformed into BC, while only 19.05 % of glucose and 24.78 % of fructose were transformed into BC. Instead, when glucose was used as the sole carbon source, 40.03 % of glucose was turned into the by-product gluconic acid. Compared with BC from glucose and fructose, BC from the glycerol medium showed the highest tensile strength at 83.5 MPa, with thinner fibers and lower porosity. As a main byproduct of biodiesel production, glycerol holds great potential to produce BC with superior mechanical and microstructural characteristics.

  10. High resolution deuterium NMR studies of bacterial metabolism

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    Aguayo, J.B.; Gamcsik, M.P.; Dick, J.D.

    1988-12-25

    High resolution deuterium NMR spectra were obtained from suspensions of five bacterial strains: Escherichia coli, Clostridium perfringens, Klebsiella pneumoniae, Proteus mirabilis, and Staphylococcus aureus. Deuterium-labeled D-glucose at C-1, C-2, and C-6 was used to monitor dynamically anaerobic metabolism. The flux of glucose through the various bacterial metabolic pathways could be determined by following the disappearance of glucose and the appearance of the major end products in the 2H NMR spectrum. The presence of both labeled and unlabeled metabolites could be detected using 1H NMR spectroscopy since the proton resonances in the labeled species are shifted upfield due to an isotopic chemical shift effect. The 1H-1H scalar coupling observed in both the 2H and 1H NMR spectra was used to assign definitively the resonances of labeled species. An increase in the intensity of natural abundance deuterium signal of water can be used to monitor pathways in which a deuteron is lost from the labeled metabolite. The steps in which label loss can occur are outlined, and the influence these processes have on the ability of 2H NMR spectroscopy to monitor metabolism are assessed.

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

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    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

  12. Constructing a fish metabolic network model

    OpenAIRE

    Li, S.; Pozhitkov, A.; R. Ryan; Manning, C; Brown-Peterson, N.; Brouwer, M

    2010-01-01

    We report the construction of a genome-wide fish metabolic network model, MetaFishNet, and its application to analyzing high throughput gene expression data. This model is a stepping stone to broader applications of fish systems biology, for example by guiding study design through comparison with human metabolism and the integration of multiple data types. MetaFishNet resources, including a pathway enrichment analysis tool, are accessible at http://metafishnet.appspot.com.

  13. Some metabolic effects of bacterial endotoxins in salmonid fishes

    Science.gov (United States)

    Wedemeyer, G.A.; Ross, A.J.; Smith, L.

    1968-01-01

    Coho salmon (Oncorhynchus kisutch) and rainbow trout (Salmo gairdneri) were highly resistant to endotoxins from both Escherichia coli and Aeromonas salmonicida (a fish pathogen) at 14 and 18 C.This resistance was investigated with liver tryptophan pyrrolase, liver glycogen depletion in vitro, and the arterial blood pressure as indicators. Liver glycogen depletion was accelerated by both endotoxins, but there was no significant cardiovascular response or effect on liver tryptophan pyrrolase activity. Since the cardiovascular effects of histamine were also limited, it was concluded that the metabolic effects of bacterial endotoxins in salmonids are qualitatively different from those of the higher vertebrates.

  14. Hierarchical modularity of nested bow-ties in metabolic networks

    OpenAIRE

    Luo Jian-Hua; Yu Hong; Zhao Jing; Cao Zhi-Wei; Li Yi-Xue

    2006-01-01

    Abstract Background The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structure and functionality of metabolic networks. Topological analysis of graph models has often been applied to study the structural characteristics of complex metabolic networks. Results In this work, metabolic networks of 75 organisms were investigated from a topological point of view. Network decom...

  15. Dissecting Germ Cell Metabolism through Network Modeling.

    Directory of Open Access Journals (Sweden)

    Leanne S Whitmore

    Full Text Available 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.

  16. On Functional Module Detection in Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Ina Koch

    2013-08-01

    Full Text Available 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.

  17. On functional module detection in metabolic networks.

    Science.gov (United States)

    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

  18. Kinetic analysis of complex metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Stephanopoulos, G. [MIT, Cambridge, MA (United States)

    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.

  19. Stability of multispecies bacterial communities: signaling networks may stabilize microbiomes.

    Directory of Open Access Journals (Sweden)

    Ádám Kerényi

    Full Text Available Multispecies bacterial communities can be remarkably stable and resilient even though they consist of cells and species that compete for environmental resources. In silico models suggest that common signals released into the environment may help selected bacterial species cluster at common locations and that sharing of public goods (i.e. molecules produced and released for mutual benefit can stabilize this coexistence. In contrast, unilateral eavesdropping on signals produced by a potentially invading species may protect a community by keeping invaders away from limited resources. Shared bacterial signals, such as those found in quorum sensing systems, may thus play a key role in fine tuning competition and cooperation within multi-bacterial communities. We suggest that in addition to metabolic complementarity, signaling dynamics may be important in further understanding complex bacterial communities such as the human, animal as well as plant microbiomes.

  20. Genotype networks, innovation, and robustness in sulfur metabolism

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2011-03-01

    Full Text Available Abstract Background A metabolism is a complex network of chemical reactions. This network synthesizes multiple small precursor molecules of biomass from chemicals that occur in the environment. The metabolic network of any one organism is encoded by a metabolic genotype, defined as the set of enzyme-coding genes whose products catalyze the network's reactions. Each metabolic genotype has a metabolic phenotype. We define this metabolic phenotype as the spectrum of different sources of a chemical element that a metabolism can use to synthesize biomass. We here focus on the element sulfur. We study properties of the space of all possible metabolic genotypes in sulfur metabolism by analyzing random metabolic genotypes that are viable on different numbers of sulfur sources. Results We show that metabolic genotypes with the same phenotype form large connected genotype networks - networks of metabolic networks - that extend far through metabolic genotype space. How far they reach through this space depends linearly on the number of super-essential reactions. A super-essential reaction is an essential reaction that occurs in all networks viable in a given environment. Metabolic networks can differ in how robust their phenotype is to the removal of individual reactions. We find that this robustness depends on metabolic network size, and on other variables, such as the size of minimal metabolic networks whose reactions are all essential in a specific environment. We show that different neighborhoods of any genotype network harbor very different novel phenotypes, metabolic innovations that can sustain life on novel sulfur sources. We also analyze the ability of evolving populations of metabolic networks to explore novel metabolic phenotypes. This ability is facilitated by the existence of genotype networks, because different neighborhoods of these networks contain very different novel phenotypes. Conclusions We show that the space of metabolic genotypes

  1. Bacterial microcompartments as metabolic modules for plant synthetic biology.

    Science.gov (United States)

    Gonzalez-Esquer, C Raul; Newnham, Sarah E; Kerfeld, Cheryl A

    2016-07-01

    Bacterial microcompartments (BMCs) are megadalton-sized protein assemblies that enclose segments of metabolic pathways within cells. They increase the catalytic efficiency of the encapsulated enzymes while sequestering volatile or toxic intermediates from the bulk cytosol. The first BMCs discovered were the carboxysomes of cyanobacteria. Carboxysomes compartmentalize the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) with carbonic anhydrase. They enhance the carboxylase activity of RuBisCO by increasing the local concentration of CO2 in the vicinity of the enzyme's active site. As a metabolic module for carbon fixation, carboxysomes could be transferred to eukaryotic organisms (e.g. plants) to increase photosynthetic efficiency. Within the scope of synthetic biology, carboxysomes and other BMCs hold even greater potential when considered a source of building blocks for the development of nanoreactors or three-dimensional scaffolds to increase the efficiency of either native or heterologously expressed enzymes. The carboxysome serves as an ideal model system for testing approaches to engineering BMCs because their expression in cyanobacteria provides a sensitive screen for form (appearance of polyhedral bodies) and function (ability to grow on air). We recount recent progress in the re-engineering of the carboxysome shell and core to offer a conceptual framework for the development of BMC-based architectures for applications in plant synthetic biology. PMID:26991644

  2. Mining metabolic networks for optimal drug targets.

    Science.gov (United States)

    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

  3. Complex network perspective on structure and function of Staphylococcus aureus metabolic network

    Indian Academy of Sciences (India)

    L Ying; D W Ding

    2013-02-01

    With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on `bow tie' structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.

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

    OpenAIRE

    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...

  5. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.;

    2003-01-01

    and the environment were included. A total of 708 structural open reading frames (ORFs) were accounted for in the reconstructed network, corresponding to 1035 metabolic reactions. Further, 140 reactions were included on the basis of biochemical evidence resulting in a genome-scale reconstructed metabolic network...... with Escherichia coli. The reconstructed metabolic network is the first comprehensive network for a eukaryotic organism, and it may be used as the basis for in silico analysis of phenotypic functions....

  6. Human Metabolic Network: Reconstruction, Simulation, and Applications in Systems Biology

    Science.gov (United States)

    Wu, Ming; Chan, Christina

    2012-01-01

    Metabolism is crucial to cell growth and proliferation. Deficiency or alterations in metabolic functions are known to be involved in many human diseases. Therefore, understanding the human metabolic system is important for the study and treatment of complex diseases. Current reconstructions of the global human metabolic network provide a computational platform to integrate genome-scale information on metabolism. The platform enables a systematic study of the regulation and is applicable to a wide variety of cases, wherein one could rely on in silico perturbations to predict novel targets, interpret systemic effects, and identify alterations in the metabolic states to better understand the genotype-phenotype relationships. In this review, we describe the reconstruction of the human metabolic network, introduce the constraint based modeling approach to analyze metabolic networks, and discuss systems biology applications to study human physiology and pathology. We highlight the challenges and opportunities in network reconstruction and systems modeling of the human metabolic system. PMID:24957377

  7. From genomes to in silico cells via metabolic networks

    DEFF Research Database (Denmark)

    Borodina, Irina; Nielsen, Jens

    2005-01-01

    Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...

  8. Hierarchical modularity of nested bow-ties in metabolic networks

    Directory of Open Access Journals (Sweden)

    Luo Jian-Hua

    2006-08-01

    Full Text Available Abstract Background The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structure and functionality of metabolic networks. Topological analysis of graph models has often been applied to study the structural characteristics of complex metabolic networks. Results In this work, metabolic networks of 75 organisms were investigated from a topological point of view. Network decomposition of three microbes (Escherichia coli, Aeropyrum pernix and Saccharomyces cerevisiae shows that almost all of the sub-networks exhibit a highly modularized bow-tie topological pattern similar to that of the global metabolic networks. Moreover, these small bow-ties are hierarchically nested into larger ones and collectively integrated into a large metabolic network, and important features of this modularity are not observed in the random shuffled network. In addition, such a bow-tie pattern appears to be present in certain chemically isolated functional modules and spatially separated modules including carbohydrate metabolism, cytosol and mitochondrion respectively. Conclusion The highly modularized bow-tie pattern is present at different levels and scales, and in different chemical and spatial modules of metabolic networks, which is likely the result of the evolutionary process rather than a random accident. Identification and analysis of such a pattern is helpful for understanding the design principles and facilitate the modelling of metabolic networks.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  11. Deciphering transcriptional and metabolic networks associated with lysine metabolism during Arabidopsis seed development.

    Science.gov (United States)

    Angelovici, Ruthie; Fait, Aaron; Zhu, Xiaohong; Szymanski, Jedrzej; Feldmesser, Ester; Fernie, Alisdair R; Galili, Gad

    2009-12-01

    In order to elucidate transcriptional and metabolic networks associated with lysine (Lys) metabolism, we utilized developing Arabidopsis (Arabidopsis thaliana) seeds as a system in which Lys synthesis could be stimulated developmentally without application of chemicals and coupled this to a T-DNA insertion knockout mutation impaired in Lys catabolism. This seed-specific metabolic perturbation stimulated Lys accumulation starting from the initiation of storage reserve accumulation. Our results revealed that the response of seed metabolism to the inducible alteration of Lys metabolism was relatively minor; however, that which was observable operated in a modular manner. They also demonstrated that Lys metabolism is strongly associated with the operation of the tricarboxylic acid cycle while largely disconnected from other metabolic networks. In contrast, the inducible alteration of Lys metabolism was strongly associated with gene networks, stimulating the expression of hundreds of genes controlling anabolic processes that are associated with plant performance and vigor while suppressing a small number of genes associated with plant stress interactions. The most pronounced effect of the developmentally inducible alteration of Lys metabolism was an induction of expression of a large set of genes encoding ribosomal proteins as well as genes encoding translation initiation and elongation factors, all of which are associated with protein synthesis. With respect to metabolic regulation, the inducible alteration of Lys metabolism was primarily associated with altered expression of genes belonging to networks of amino acids and sugar metabolism. The combined data are discussed within the context of network interactions both between and within metabolic and transcriptional control systems.

  12. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism.

    Science.gov (United States)

    Vital-Lopez, Francisco G; Reifman, Jaques; Wallqvist, Anders

    2015-10-01

    A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm

  13. Steady states and stability in metabolic networks without regulation

    NARCIS (Netherlands)

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

    2016-01-01

    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 properti

  14. Environmental versatility promotes modularity in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2011-08-01

    Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional

  15. Cerebral blood flow and metabolism in adults with acute bacterial meningitis

    DEFF Research Database (Denmark)

    Møller, Kirsten

    2007-01-01

    The intense intrathecal inflammation observed in acute bacterial meningitis (ABM) is associated with pronounced changes in cerebral blood flow (CBF) and metabolism. In seven substudies, CBF and metabolism were measured in adults with ABM as well as healthy volunteers during various interventions...

  16. Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Henry, Christopher S.; Bernstein, Hans C.; Weisenhorn, Pamela; Taylor, Ronald C.; Lee, Joon-Yong; Zucker, Jeremy D.; Song, Hyun-Seob

    2016-06-02

    Metabolic network modeling of microbial communities provides an in-depth understanding of community-wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high-quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community-level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph-heterotroph consortium that was used to provide data needed for a community-level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources.

  17. Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction.

    Science.gov (United States)

    Henry, Christopher S; Bernstein, Hans C; Weisenhorn, Pamela; Taylor, Ronald C; Lee, Joon-Yong; Zucker, Jeremy; Song, Hyun-Seob

    2016-11-01

    Metabolic network modeling of microbial communities provides an in-depth understanding of community-wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high-quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community-level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph-heterotroph consortium that was used to provide data needed for a community-level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources. J. Cell. Physiol. 231: 2339-2345, 2016. © 2016 Wiley Periodicals, Inc. PMID:27186840

  18. Graph methods for the investigation of metabolic networks in parasitology.

    Science.gov (United States)

    Cottret, Ludovic; Jourdan, Fabien

    2010-08-01

    Recently, a way was opened with the development of many mathematical methods to model and analyze genome-scale metabolic networks. Among them, methods based on graph models enable to us quickly perform large-scale analyses on large metabolic networks. However, it could be difficult for parasitologists to select the graph model and methods adapted to their biological questions. In this review, after briefly addressing the problem of the metabolic network reconstruction, we propose an overview of the graph-based approaches used in whole metabolic network analyses. Applications highlight the usefulness of this kind of approach in the field of parasitology, especially by suggesting metabolic targets for new drugs. Their development still represents a major challenge to fight against the numerous diseases caused by parasites.

  19. Hydrological pulse regulating the bacterial heterotrophic metabolism between Amazonian mainstems and floodplain lakes

    Directory of Open Access Journals (Sweden)

    Luciana Oliveira Vidal

    2015-09-01

    Full Text Available We evaluated in situ rates of bacterial carbon processing in Amazonian floodplain lakes and mainstems, during both high and low water phases (p < 0.05. Our results showed that Bacterial Production (BP was lower and more variable than Bacterial Respiration (BR, determined as total respiration. Bacterial Carbon Demand (BCD was mostly accounted by BR and presented the same pattern that BR in both water phases. Bacterial growth efficiency showed a wide range (0.2–23% and low mean value of 3 and 6 %, (in high and low water respectively suggesting that dissolved organic carbon (DOC was mostly allocated to catabolic metabolism. However, BGE was regulated by BP in low water phase. Consequently, changes in BGE showed the same pattern that BP. In addition, the hydrological pulse effects on mainstems and floodplains lakes connectivity were found for BP and BGE in low water. Multiple correlation analyses revealed that indexes of organic matter quality (chlorophyll-a, N stable isotopes and C/N ratios were the strongest seasonal drivers of bacterial carbon metabolism. Our work indicated that: (1 the bacterial metabolism was mostly driven by respiration in Amazonian aquatic ecosystems resulting in low BGE in either high and low water phase; (2 the hydrological pulse regulated

  20. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli

    Science.gov (United States)

    De Martino, Daniele; Capuani, Fabrizio; De Martino, Andrea

    2016-06-01

    The solution space of genome-scale models of cellular metabolism provides a map between physically viable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the corresponding growth rates. By sampling the solution space of E. coli's metabolic network, we show that empirical growth rate distributions recently obtained in experiments at single-cell resolution can be explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the higher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of a large bacterial population that captures this trade-off. The scaling relationships observed in experiments encode, in such frameworks, for the same distance from the maximum achievable growth rate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being grounded on genome-scale metabolic network reconstructions, these results allow for multiple implications and extensions in spite of the underlying conceptual simplicity.

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

    Science.gov (United States)

    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

  2. Cerebral blood flow, oxidative metabolism and cerebrovascular carbon dioxide reactivity in patients with acute bacterial meningitis

    DEFF Research Database (Denmark)

    Møller, Kirsten; Strauss, Gitte Irene; Thomsen, Gerda;

    2002-01-01

    BACKGROUND: The optimal arterial carbon dioxide tension (P(a)CO(2)) in patients with acute bacterial meningitis (ABM) is unknown and controversial. The objective of this study was to measure global cerebral blood flow (CBF), cerebrovascular CO(2) reactivity (CO(2)R), and cerebral metabolic rates...... to baseline ventilation, whereas CMR(glu) increased. CONCLUSION: In patients with acute bacterial meningitis, we found variable levels of CBF and cerebrovascular CO(2) reactivity, a low a-v DO(2), low cerebral metabolic rates of oxygen and glucose, and a cerebral lactate efflux. In these patients...

  3. Computing autocatalytic sets to unravel inconsistencies in metabolic network reconstructions

    DEFF Research Database (Denmark)

    Schmidt, R.; Waschina, S.; Boettger-Schmidt, D.;

    2015-01-01

    MOTIVATION: Genome-scale metabolic network reconstructions have been established as a powerful tool for the prediction of cellular phenotypes and metabolic capabilities of organisms. In recent years, the number of network reconstructions has been constantly increasing, mostly because...... of the availability of novel (semi-)automated procedures, which enabled the reconstruction of metabolic models based on individual genomes and their annotation. The resulting models are widely used in numerous applications. However, the accuracy and predictive power of network reconstructions are commonly limited...... by inherent inconsistencies and gaps. RESULTS: Here we present a novel method to validate metabolic network reconstructions based on the concept of autocatalytic sets. Autocatalytic sets correspond to collections of metabolites that, besides enzymes and a growth medium, are required to produce all biomass...

  4. Thiosulfate as a metabolic product: the bacterial fermentation of taurine

    OpenAIRE

    Denger, Karin; Laue, Heike; Cook, Alasdair M.

    1997-01-01

    Thiosulfate (S2O3²-) is a natural product that is widely utilized in natural ecosystems as an electron sink or as an electron donor. However, the major biological source(s) of this thiosulfate is unknown. We present the first report that taurine (2-aminoethanesulfonate), the major mammalian solute, is subject to fermentation. This bacterial fermentation was found to be catalyzed by a new isolate, strain GKNTAU, a strictly anaerobic, gram-positive, motile rod that formed subterminal spores. Th...

  5. Horizontal and vertical growth of S. cerevisiae metabolic network.

    KAUST Repository

    Grassi, Luigi

    2011-10-14

    BACKGROUND: The growth and development of a biological organism is reflected by its metabolic network, the evolution of which relies on the essential gene duplication mechanism. There are two current views about the evolution of metabolic networks. The retrograde model hypothesizes that a pathway evolves by recruiting novel enzymes in a direction opposite to the metabolic flow. The patchwork model is instead based on the assumption that the evolution is based on the exploitation of broad-specificity enzymes capable of catalysing a variety of metabolic reactions. RESULTS: We analysed a well-studied unicellular eukaryotic organism, S. cerevisiae, and studied the effect of the removal of paralogous gene products on its metabolic network. Our results, obtained using different paralog and network definitions, show that, after an initial period when gene duplication was indeed instrumental in expanding the metabolic space, the latter reached an equilibrium and subsequent gene duplications were used as a source of more specialized enzymes rather than as a source of novel reactions. We also show that the switch between the two evolutionary strategies in S. cerevisiae can be dated to about 350 million years ago. CONCLUSIONS: Our data, obtained through a novel analysis methodology, strongly supports the hypothesis that the patchwork model better explains the more recent evolution of the S. cerevisiae metabolic network. Interestingly, the effects of a patchwork strategy acting before the Euascomycete-Hemiascomycete divergence are still detectable today.

  6. A compendium of inborn errors of metabolism mapped onto the human metabolic network.

    Science.gov (United States)

    Sahoo, Swagatika; Franzson, Leifur; Jonsson, Jon J; Thiele, Ines

    2012-10-01

    Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through metabolomic analysis of dried blood spot samples. To enable the mapping of these metabolomic data onto the published human metabolic reconstruction, we added missing reactions and pathways involved in acylcarnitine (AC) and fatty acid oxidation (FAO) metabolism. Using literary data, we reconstructed an AC/FAO module consisting of 352 reactions and 139 metabolites. When this module was combined with the human metabolic reconstruction, the synthesis of 39 acylcarnitines and 22 amino acids, which are routinely measured, was captured and 235 distinct IEMs could be mapped. We collected phenotypic and clinical features for each IEM enabling comprehensive classification. We found that carbohydrate, amino acid, and lipid metabolism were most affected by the IEMs, while the brain was the most commonly affected organ. Furthermore, we analyzed the IEMs in the context of metabolic network topology to gain insight into common features between metabolically connected IEMs. While many known examples were identified, we discovered some surprising IEM pairs that shared reactions as well as clinical features but not necessarily causal genes. Moreover, we could also re-confirm that acetyl-CoA acts as a central metabolite. This network based analysis leads to further insight of hot spots in human metabolism with respect to IEMs. The presented comprehensive knowledge base of IEMs will provide a valuable tool in studying metabolic changes involved in inherited metabolic diseases. PMID:22699794

  7. Thiosulfate as a metabolic product: the bacterial fermentation of taurine.

    Science.gov (United States)

    Denger, K; Laue, H; Cook, A M

    1997-10-01

    Thiosulfate (S2O32-) is a natural product that is widely utilized in natural ecosystems as an electron sink or as an electron donor. However, the major biological source(s) of this thiosulfate is unknown. We present the first report that taurine (2-aminoethanesulfonate), the major mammalian solute, is subject to fermentation. This bacterial fermentation was found to be catalyzed by a new isolate, strain GKNTAU, a strictly anaerobic, gram-positive, motile rod that formed subterminal spores. Thiosulfate was a quantitative fermentation product. The other fermentation products were ammonia and acetate, and all could be formed by cell-free extracts.

  8. Bacterial metabolism in biofilm consortia: Consequences for potential ennoblement

    Energy Technology Data Exchange (ETDEWEB)

    Chandrasekaran, P.; Dexter, S.C. [Univ. of Delaware, Lewes, DE (United States). Graduate College of Marine Studies

    1994-12-31

    Platinum metal coupons were used in studying the mechanism of ennoblement in the presence of mature seawater biofilms. Presence of a bacterial consortia, rather than any single organism is determined to be necessary for ennoblement. Millimolar concentrations of iron and manganese were measured in biofilms formed over platinum. EDAX and ICP techniques were used for measuring the chemistry of particles in a biofilm. Utilization of various electron acceptors like oxygen, iron, manganese, etc. are thought to be important for ennoblement to take place over platinum. Heavy metal accumulation is hypothesized to favor the low pH mechanism of ennoblement due to heavy metal hydrolysis. Monoculture biofilms cannot support ennoblement on platinum.

  9. Dynamic Metabolic Modeling of Denitrifying Bacterial Growth: The Cybernetic Approach

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Liu, Chongxuan

    2015-06-29

    Denitrification is a multistage reduction process converting nitrate ultimately to nitrogen gas, carried out mostly by facultative bacteria. Modeling of the denitrification process is challenging due to the complex metabolic regulation that modulates sequential formation and consumption of a series of nitrogen oxide intermediates, which serve as the final electron acceptors for denitrifying bacteria. In this work, we examined the effectiveness and accuracy of the cybernetic modeling framework in simulating the growth dynamics of denitrifying bacteria in comparison with kinetic models. In four different case studies using the literature data, we successfully simulated diauxic and triauxic growth patterns observed in anoxic and aerobic conditions, only by tuning two or three parameters. In order to understand the regulatory structure of the cybernetic model, we systematically analyzed the effect of cybernetic control variables on simulation accuracy. The results showed that the consideration of both enzyme synthesis and activity control through u- and v-variables is necessary and relevant and that uvariables are of greater importance in comparison to v-variables. In contrast, simple kinetic models were unable to accurately capture dynamic metabolic shifts across alternative electron acceptors, unless an inhibition term was additionally incorporated. Therefore, the denitrification process represents a reasonable example highlighting the criticality of considering dynamic regulation for successful metabolic modeling.

  10. Sirtuins as regulators of the yeast metabolic network

    Directory of Open Access Journals (Sweden)

    Markus eRalser

    2012-03-01

    Full Text Available There is growing evidence that the metabolic network is an integral regulator of cellularphysiology. Dynamic changes in metabolite concentrations, metabolic flux, or networktopology act as reporters of biological or environmental signals, and are required for the cellto trigger an appropriate biological reaction. Changes in the metabolic network are recognizedby specific sensory macromolecules and translated into a transcriptional or translationalresponse. The protein family of sirtuins, discovered more than 30 years ago as regulators ofsilent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions ofcaloric restriction. NAD+/NADH interconverting metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved inNAD(H, synthesis provide or deprive NAD+ in close proximity to Sir2. This influence sirtuinactivity, and facilitates a dynamic response of the metabolic network to changes inmetabolism with effects on physiology and aging. The molecular network downstream Sir2,however, is complex. In just two orders, Sir2’s metabolism-related interactions span half ofthe yeast proteome, and are connected with virtually every physiological process. Thus,although it is fundamental to analyze single molecular mechanisms, it is at the same timecrucial to consider this genome-scale complexity when correlating single molecular eventswith phenotypes such as aging, cell growth, or stress resistance.

  11. Bedside Evaluation of Cerebral Energy Metabolism in Severe Community-Acquired Bacterial Meningitis

    DEFF Research Database (Denmark)

    Rom Poulsen, Frantz; Schulz, Mette; Jacobsen, Anne;

    2015-01-01

    BACKGROUND: Mortality and morbidity have remained high in bacterial meningitis. Impairment of cerebral energy metabolism probably contributes to unfavorable outcome. Intracerebral microdialysis is routinely used to monitor cerebral energy metabolism, and recent experimental studies indicate...... that this technique may separate ischemia and non-ischemic mitochondrial dysfunction. The present study is a retrospective interpretation of biochemical data obtained in a series of patients with severe community-acquired meningitis. METHODS: Cerebral energy metabolism was monitored in 15 patients with severe...... community-acquired meningitis utilizing intracerebral microdialysis and bedside biochemical analysis. According to previous studies, cerebral ischemia was defined as lactate/pyruvate (LP) ratio >30 with intracerebral pyruvate level

  12. Recombinant bacterial hemoglobin alters metabolism of Aspergillus niger

    DEFF Research Database (Denmark)

    Hofmann, Gerald; Diano, Audrey; Nielsen, Jens

    2009-01-01

    The filamentous fungus Aspergillus niger is used extensively for the production of enzymes and organic acids. A major problem in industrial fermentations with this fungus is to ensure sufficient supply of oxygen required for respiratory metabolism of the fungus. In case of oxygen limitation...... behind the strong gpdA promoter from Aspergillus nidulans. Analysis of secreted metabolites, oxygen uptake, CO2 evolution and biomass formation points towards a relief of stress in the mutant expressing VHB when it is exposed to oxygen limitation. Our findings therefore point to an interesting strategy...

  13. Metabolic network analysis-based identification of antimicrobial drug targets in category A bioterrorism agents.

    Science.gov (United States)

    Ahn, Yong-Yeol; Lee, Deok-Sun; Burd, Henry; Blank, William; Kapatral, Vinayak

    2014-01-01

    The 2001 anthrax mail attacks in the United States demonstrated the potential threat of bioterrorism, hence driving the need to develop sophisticated treatment and diagnostic protocols to counter biological warfare. Here, by performing flux balance analyses on the fully-annotated metabolic networks of multiple, whole genome-sequenced bacterial strains, we have identified a large number of metabolic enzymes as potential drug targets for each of the three Category A-designated bioterrorism agents including Bacillus anthracis, Francisella tularensis and Yersinia pestis. Nine metabolic enzymes- belonging to the coenzyme A, folate, phosphatidyl-ethanolamine and nucleic acid pathways common to all strains across the three distinct genera were identified as targets. Antimicrobial agents against some of these enzymes are available. Thus, a combination of cross species-specific antibiotics and common antimicrobials against shared targets may represent a useful combinatorial therapeutic approach against all Category A bioterrorism agents.

  14. Metabolic network analysis-based identification of antimicrobial drug targets in category A bioterrorism agents.

    Directory of Open Access Journals (Sweden)

    Yong-Yeol Ahn

    Full Text Available The 2001 anthrax mail attacks in the United States demonstrated the potential threat of bioterrorism, hence driving the need to develop sophisticated treatment and diagnostic protocols to counter biological warfare. Here, by performing flux balance analyses on the fully-annotated metabolic networks of multiple, whole genome-sequenced bacterial strains, we have identified a large number of metabolic enzymes as potential drug targets for each of the three Category A-designated bioterrorism agents including Bacillus anthracis, Francisella tularensis and Yersinia pestis. Nine metabolic enzymes- belonging to the coenzyme A, folate, phosphatidyl-ethanolamine and nucleic acid pathways common to all strains across the three distinct genera were identified as targets. Antimicrobial agents against some of these enzymes are available. Thus, a combination of cross species-specific antibiotics and common antimicrobials against shared targets may represent a useful combinatorial therapeutic approach against all Category A bioterrorism agents.

  15. Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

    Directory of Open Access Journals (Sweden)

    Gengjie Jia

    2012-11-01

    Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

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

    Science.gov (United States)

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Nikos Vlassis

    2014-01-01

    Full Text Available 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.

  20. Metabolic Network Prediction of Drug Side Effects.

    Science.gov (United States)

    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

  1. GROWTH AND METABOLISM OF INDIVIDUAL BACTERIAL CELLS UTILIZING NANOSIMS

    Energy Technology Data Exchange (ETDEWEB)

    NEALSON, H. K.

    2007-08-03

    This work involved the use of the Nano-SIMS Instrument at Lawrence Livermore Laboratory, in an effort to utilize this unique tool for experiments in Biology. The work consisted primarily of experiments to measure in real time, C and N fixation in cyanobacteria. The work revealed a number of the difficulties in using the nano-SIMS approach with biological material, but with collaboration from a number of individuals at USC and LLNL, major progress was made. The collaborators from LLNL were from the Chemistry Group (Dr. Peter Weber), and the Biology Group (Dr. Jennifer Pett-Ridge). In addition, there were a number of other scientists involved from LLNL. The USC group consisted of Dr. K.H. Nealson, the PI on the grant, Dr. R. Popa, a postdoctoral fellow and research associate at USC, Professor Douglas Capone, and Juliet Finze, a graduate student in biology. Two major experiments were done, both of which yielded new and exciting data. (1) We studied nitrogen and carbon fixation in Anabaena, demonstrating that fixation ofN occurred rapidly in the heterocysts, and that the fixed N was transported rapidly and completely to the vegetative cells. C fixation occurred in the vegetative cells, with labeled C remaining in these cells in support of their growth and metabolism. This work was accepted in the ISME Journal (Nature Publication), and published last month. (2) We studied nitrogen and carbon fixation in Trichodesmium, a non-heterocystous cyanobacterium that also fixes nitrogen. Interestingly, the nitrogen fixation was confined to regions within the filaments that seem to be identical to the so-called cyanophycaen granules. The fixed N is then transported to other parts of the cyanobacterium, as judged by movement of the heavy N throughout the filaments. On the basis of these very exciting results, we have applied for funding from the NSF to continue the collaboration with LLNL. The results of both studies were presented in the summer of 2007 at the Gordon Research

  2. Transcriptional regulation and steady-state modeling of metabolic networks

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej

    become a focal point in diagnosing and treating diseases such as diabetes and cancer. Type 2 diabetes mellitus is a complex metabolic disease which is recognized as one of the largest threats to human health in the 21st century. Recent studies of gene expression levels in human tissue samples have...... indicated that multiple metabolic pathways are dys-regulated in diabetes and in individuals at risk for diabetes; which of these are primary, or central to disease pathogenesis, remains a key question. Cellular metabolic networks are highly interconnected and often tightly regulated; any perturbations...... diagnostics for type 2 diabetes and impaired glucose metabolism. In a broader context, the study provides a framework for analysis of gene expression datasets from complex heterogeneous diseases, genetic, and environmental perturbations that are reflected in and/or mediated through changes in metabolism...

  3. Effect of bacterial protein meal on protein and energy metabolism in growing chickens

    DEFF Research Database (Denmark)

    Hellwing, Anne Louise Frydendahl; Tauson, Anne-Helene; Skrede, Anders

    2006-01-01

    This experiment investigates the effect of increasing the dietary content of bacterial protein meal (BPM) on the protein and energy metabolism, and carcass chemical composition of growing chickens. Seventy-two Ross male chickens were allocated to four diets, each in three replicates with 0% (D0), 2...... for protein and energy retention found in the balance and respiration experiments. It was concluded that the overall protein and energy metabolism as well as carcass composition were not influenced by a dietary content of up to 6% BPM corresponding to 20% of dietary N....

  4. Delayed bactericidal response of Mycobacterium tuberculosis to bedaquiline involves remodelling of bacterial metabolism

    DEFF Research Database (Denmark)

    Koul, A.; Vranckx, L.; Dhar, N.;

    2014-01-01

    Bedaquiline (BDQ), an ATP synthase inhibitor, is the first drug to be approved for treatment of multidrug-resistant tuberculosis in decades. Though BDQ has shown excellent efficacy in clinical trials, its early bactericidal activity during the first week of chemotherapy is minimal. Here, using mi......-fermentable energy sources such as lipids (impeding ATP synthesis via glycolysis). Our results show that BDQ exposure triggers a metabolic remodelling in mycobacteria, thereby enabling transient bacterial survival....... and proteomic analyses reveal that M. tuberculosis responds to BDQ by induction of the dormancy regulon and activation of ATP-generating pathways, thereby maintaining bacterial viability during initial drug exposure. BDQ-induced bacterial killing is significantly enhanced when the mycobacteria are grown on non...

  5. Opposing Effects of Fasting Metabolism on Tissue Tolerance in Bacterial and Viral Inflammation.

    Science.gov (United States)

    Wang, Andrew; Huen, Sarah C; Luan, Harding H; Yu, Shuang; Zhang, Cuiling; Gallezot, Jean-Dominique; Booth, Carmen J; Medzhitov, Ruslan

    2016-09-01

    Acute infections are associated with a set of stereotypic behavioral responses, including anorexia, lethargy, and social withdrawal. Although these so-called sickness behaviors are the most common and familiar symptoms of infections, their roles in host defense are largely unknown. Here, we investigated the role of anorexia in models of bacterial and viral infections. We found that anorexia was protective while nutritional supplementation was detrimental in bacterial sepsis. Furthermore, glucose was necessary and sufficient for these effects. In contrast, nutritional supplementation protected against mortality from influenza infection and viral sepsis, whereas blocking glucose utilization was lethal. In both bacterial and viral models, these effects were largely independent of pathogen load and magnitude of inflammation. Instead, we identify opposing metabolic requirements tied to cellular stress adaptations critical for tolerance of differential inflammatory states. VIDEO ABSTRACT. PMID:27610573

  6. Relationship between topology and functions in metabolic network evolution

    Institute of Scientific and Technical Information of China (English)

    WANG Zhuo; CHEN Qi; LIU Lei

    2009-01-01

    What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related or-ganisms? Here we investigated the relationship between enzyme connectivity and functions in meta-bolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coil, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different func-tional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly con-served modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its pre-cursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution.

  7. Systematic assignment of thermodynamic constraints in metabolic network models

    NARCIS (Netherlands)

    Kümmel, Anne; Panke, Sven; Heinemann, Matthias

    2006-01-01

    Background: The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models. For this, several computational tools have been developed that par

  8. Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism

    DEFF Research Database (Denmark)

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu;

    2012-01-01

    Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and...

  9. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Directory of Open Access Journals (Sweden)

    Kovaleva Galina

    2011-06-01

    Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

  10. Single-cell level based approach to investigate bacterial metabolism during batch industrial fermentation

    DEFF Research Database (Denmark)

    Nierychlo, Marta; Larsen, Poul; Eriksen, Niels T.;

    , and performance of Escherichia coli. An insight into glucose and acetate fate on the level of individual cell can provide the type of information which are valuable for the understanding of bacterial metabolism in fermentation process and can shed more light on the differentiation of isogenic fermenting...... can exhibit different phenotypes under specific environmental conditions that show significant differences in physiological parameters from the population average. However, studies concerning segregation of populations into metabolically diversified subpopulations are scarce. Acetate is a product...... of Escherichia coli overflow metabolism when the bacteria are grown under aerobic conditions and glucose is present in excessive concentrations. Acetate accumulation is of the utmost importance in batch fermentation processes as it is an undesirable byproduct that negatively affects growth, physiology...

  11. The solution space of metabolic networks: Producibility, robustness and fluctuations

    Energy Technology Data Exchange (ETDEWEB)

    Martino, A De [CNR/IPCF, UoS Roma-Sapienza (Italy); Marinari, E, E-mail: andrea.demartino@roma1.infn.i, E-mail: enzo.marinari@roma1.infn.i [Dipartimento di Fisica, Sapienza Universita di Roma, p.le A. Moro 2, 00185 Roma (Italy)

    2010-06-01

    By flux analysis one generically indicates a class of constraint-based approaches to the study of biochemical reaction networks concerned with the calculation of the flux configurations compatible with given stoichiometric and thermodynamic constraints. One of its main areas of application is the study of cellular metabolic networks. We briefly and selectively review the main approaches to this problem and then, building on recent work, we provide a characterization of the productive capabilities of the metabolic network of the bacterium E.coli in a specified growth medium in terms of the producible biochemical species. While a robust and physiologically meaningful production profile clearly emerges, the underlying constraints still allow for significant fluctuations in the net production even for key metabolites like ATP and, as a consequence, apparently lay the ground for different growth scenarios.

  12. Selective pressure on metabolic network structures as measured from the random blind-watchmaker network

    International Nuclear Information System (INIS)

    A random null model termed the blind-watchmaker network (BW) has been shown to reproduce the degree distribution found in metabolic networks. This might suggest that natural selection has had little influence on this particular network property. We investigate here the extent to which other structural network properties have evolved under selective pressure from the corresponding ones of the random null model: the clustering coefficient and the assortativity measures are chosen and it is found that these measures for the metabolic network structure are close enough to the BW network so as to fit inside its reachable random phase space. It is, furthermore, shown that the use of this null model indicates an evolutionary pressure towards low assortativity and that this pressure is stronger for larger networks. It is also shown that selecting for BW networks with low assortativity causes the BW degree distribution to deviate slightly from its power-law shape in the same way as the metabolic networks. This implies that an equilibrium model with fluctuating degree distribution is more suitable as a null model, when identifying selective pressures, than a randomized counterpart with fixed degree sequence, since the overall degree sequence itself can change under selective pressure on other global network properties.

  13. Optimality Principles in the Regulation of Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Jan Berkhout

    2012-08-01

    Full Text Available One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

  14. Parameter estimation in tree graph metabolic networks.

    Science.gov (United States)

    Astola, Laura; Stigter, Hans; Gomez Roldan, Maria Victoria; van Eeuwijk, Fred; Hall, Robert D; Groenenboom, Marian; Molenaar, Jaap J

    2016-01-01

    We study the glycosylation processes that convert initially toxic substrates to nutritionally valuable metabolites in the flavonoid biosynthesis pathway of tomato (Solanum lycopersicum) seedlings. To estimate the reaction rates we use ordinary differential equations (ODEs) to model the enzyme kinetics. A popular choice is to use a system of linear ODEs with constant kinetic rates or to use Michaelis-Menten kinetics. In reality, the catalytic rates, which are affected among other factors by kinetic constants and enzyme concentrations, are changing in time and with the approaches just mentioned, this phenomenon cannot be described. Another problem is that, in general these kinetic coefficients are not always identifiable. A third problem is that, it is not precisely known which enzymes are catalyzing the observed glycosylation processes. With several hundred potential gene candidates, experimental validation using purified target proteins is expensive and time consuming. We aim at reducing this task via mathematical modeling to allow for the pre-selection of most potential gene candidates. In this article we discuss a fast and relatively simple approach to estimate time varying kinetic rates, with three favorable properties: firstly, it allows for identifiable estimation of time dependent parameters in networks with a tree-like structure. Secondly, it is relatively fast compared to usually applied methods that estimate the model derivatives together with the network parameters. Thirdly, by combining the metabolite concentration data with a corresponding microarray data, it can help in detecting the genes related to the enzymatic processes. By comparing the estimated time dynamics of the catalytic rates with time series gene expression data we may assess potential candidate genes behind enzymatic reactions. As an example, we show how to apply this method to select prominent glycosyltransferase genes in tomato seedlings. PMID:27688960

  15. What can causal networks tell us about metabolic pathways?

    Directory of Open Access Journals (Sweden)

    Rachael Hageman Blair

    Full Text Available Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: "What can causal networks tell us about metabolic pathways?". Using data from an Arabidopsis Bay[Formula: see text]Sha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies.

  16. Analysis of Data on Xanthan Fermentation in Stationary Phase Using Black Box and Metabolic Network Models

    Institute of Scientific and Technical Information of China (English)

    马红武; 赵学明; 唐寅杰

    1999-01-01

    The xanthan fermentation data in the stationary phase was analyzed using the black box and the metabolic network models. The data consistency ls checked through the elemental balance in the black box model. In the metabolic network model, the metabolic flux distribution in the cell is calculated using the metabolic flux analysis method, then the maintenance coefficients is calculated.

  17. Expanded flux variability analysis on metabolic network of Escherichia coli

    Institute of Scientific and Technical Information of China (English)

    CHEN Tong; XIE ZhengWei; OUYANG Qi

    2009-01-01

    Flux balance analysis,based on the mass conservation law in a cellular organism,has been extensively employed to study the interplay between structures and functions of cellular metabolic networks.Consequently,the phenotypes of the metabolism can be well elucidated.In this paper,we introduce the Expanded Flux Variability Analysis (EFVA) to characterize the intrinsic nature of metabolic reactions,such as flexibility,modularity and essentiality,by exploring the trend of the range,the maximum and the minimum flux of reactions.We took the metabolic network of Escherichia coli as an example and analyzed the variability of reaction fluxes under different growth rate constraints.The average variability of all reactions decreases dramatically when the growth rate increases.Consider the noise effect on the metabolic system,we thus argue that the microorganism may practically grow under a suboptimal state.Besides,under the EFVA framework,the reactions are easily to be grouped into catabolic and anabolic groups.And the anabolic groups can be further assigned to specific biomass constitute.We also discovered the growth rate dependent essentiality of reactions.

  18. Selective pressure on metabolic network structures as measured from the random blind-watchmaker network

    CERN Document Server

    Bernhardsson, Sebastian; 10.1088/1367-2630/12/10/103047

    2010-01-01

    A random null model termed the Blind Watchmaker network (BW) has been shown to reproduce the degree distribution found in metabolic networks. This might suggest that natural selection has had little influence on this particular network property. We here investigate to what extent other structural network properties have evolved under selective pressure from the corresponding ones of the random null model: The clustering coefficient and the assortativity measures are chosen and it is found that these measures for the metabolic network structure are close enough to the BW-network so as to fit inside its reachable random phase space. It is furthermore shown that the use of this null model indicates an evolutionary pressure towards low assortativity and that this pressure is stronger for larger networks. It is also shown that selecting for BW networks with low assortativity causes the BW degree distribution to slightly deviate from its power-law shape in the same way as the metabolic networks. This implies that a...

  19. Context-specific metabolic networks are consistent with experiments.

    Directory of Open Access Journals (Sweden)

    Scott A Becker

    2008-05-01

    Full Text Available Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are "genome-scale" and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.

  20. Comprehensive Structural Characterization of the Bacterial Homospermidine Synthase–an Essential Enzyme of the Polyamine Metabolism

    Science.gov (United States)

    Krossa, Sebastian; Faust, Annette; Ober, Dietrich; Scheidig, Axel J.

    2016-01-01

    The highly conserved bacterial homospermidine synthase (HSS) is a key enzyme of the polyamine metabolism of many proteobacteria including pathogenic strains such as Legionella pneumophila and Pseudomonas aeruginosa; The unique usage of NAD(H) as a prosthetic group is a common feature of bacterial HSS, eukaryotic HSS and deoxyhypusine synthase (DHS). The structure of the bacterial enzyme does not possess a lysine residue in the active center and thus does not form an enzyme-substrate Schiff base intermediate as observed for the DHS. In contrast to the DHS the active site is not formed by the interface of two subunits but resides within one subunit of the bacterial HSS. Crystal structures of Blastochloris viridis HSS (BvHSS) reveal two distinct substrate binding sites, one of which is highly specific for putrescine. BvHSS features a side pocket in the direct vicinity of the active site formed by conserved amino acids and a potential substrate discrimination, guiding, and sensing mechanism. The proposed reaction steps for the catalysis of BvHSS emphasize cation-π interaction through a conserved Trp residue as a key stabilizer of high energetic transition states. PMID:26776105

  1. Comprehensive Structural Characterization of the Bacterial Homospermidine Synthase-an Essential Enzyme of the Polyamine Metabolism.

    Science.gov (United States)

    Krossa, Sebastian; Faust, Annette; Ober, Dietrich; Scheidig, Axel J

    2016-01-01

    The highly conserved bacterial homospermidine synthase (HSS) is a key enzyme of the polyamine metabolism of many proteobacteria including pathogenic strains such as Legionella pneumophila and Pseudomonas aeruginosa; The unique usage of NAD(H) as a prosthetic group is a common feature of bacterial HSS, eukaryotic HSS and deoxyhypusine synthase (DHS). The structure of the bacterial enzyme does not possess a lysine residue in the active center and thus does not form an enzyme-substrate Schiff base intermediate as observed for the DHS. In contrast to the DHS the active site is not formed by the interface of two subunits but resides within one subunit of the bacterial HSS. Crystal structures of Blastochloris viridis HSS (BvHSS) reveal two distinct substrate binding sites, one of which is highly specific for putrescine. BvHSS features a side pocket in the direct vicinity of the active site formed by conserved amino acids and a potential substrate discrimination, guiding, and sensing mechanism. The proposed reaction steps for the catalysis of BvHSS emphasize cation-π interaction through a conserved Trp residue as a key stabilizer of high energetic transition states. PMID:26776105

  2. Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach.

    Directory of Open Access Journals (Sweden)

    Miguel Ponce-de-Leon

    Full Text Available Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22% are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-scale model. Finally, a set of 36 models that had not been considered during the construction of the metamodel was used, as a proof of concept, to extend the metamodel with new biochemical information, and to assess its impact on gap-filling results. The analysis performed on the metamodel allowed to conclude: 1 the recurrent inconsistencies found in the models were already present in the metabolic database used during the reconstructions process; 2 the presence of inconsistencies in a metabolic database can be propagated to the reconstructed models; 3 there are reactions not manifested as blocked which are active as a consequence of some classes of artifacts, and; 4 the results of an automatic gap-filling are highly dependent on the consistency and completeness of the metamodel or metabolic database used as the reference network. In conclusion the consistency analysis should be applied to metabolic databases in order to detect and fill gaps as well as to detect and remove artifacts and redundant information.

  3. Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach.

    Science.gov (United States)

    Ponce-de-Leon, Miguel; Calle-Espinosa, Jorge; Peretó, Juli; Montero, Francisco

    2015-01-01

    Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22%) are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-scale model. Finally, a set of 36 models that had not been considered during the construction of the metamodel was used, as a proof of concept, to extend the metamodel with new biochemical information, and to assess its impact on gap-filling results. The analysis performed on the metamodel allowed to conclude: 1) the recurrent inconsistencies found in the models were already present in the metabolic database used during the reconstructions process; 2) the presence of inconsistencies in a metabolic database can be propagated to the reconstructed models; 3) there are reactions not manifested as blocked which are active as a consequence of some classes of artifacts, and; 4) the results of an automatic gap-filling are highly dependent on the consistency and completeness of the metamodel or metabolic database used as the reference network. In conclusion the consistency analysis should be applied to metabolic databases in order to detect and fill gaps as well as to detect and remove artifacts and redundant information. PMID:26629901

  4. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen;

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome...

  5. Systematic assignment of thermodynamic constraints in metabolic network models

    Directory of Open Access Journals (Sweden)

    Heinemann Matthias

    2006-11-01

    Full Text Available Abstract Background The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models. For this, several computational tools have been developed that particularly assist in identifying and compiling the organism-specific lists of metabolic reactions. In contrast, the last step of the model reconstruction process, which is the definition of the thermodynamic constraints in terms of reaction directionalities, still needs to be done manually. No computational method exists that allows for an automated and systematic assignment of reaction directions in genome-scale models. Results We present an algorithm that – based on thermodynamics, network topology and heuristic rules – automatically assigns reaction directions in metabolic models such that the reaction network is thermodynamically feasible with respect to the production of energy equivalents. It first exploits all available experimentally derived Gibbs energies of formation to identify irreversible reactions. As these thermodynamic data are not available for all metabolites, in a next step, further reaction directions are assigned on the basis of network topology considerations and thermodynamics-based heuristic rules. Briefly, the algorithm identifies reaction subsets from the metabolic network that are able to convert low-energy co-substrates into their high-energy counterparts and thus net produce energy. Our algorithm aims at disabling such thermodynamically infeasible cyclic operation of reaction subnetworks by assigning reaction directions based on a set of thermodynamics-derived heuristic rules. We demonstrate our algorithm on a genome-scale metabolic model of E. coli. The introduced systematic direction assignment yielded 130 irreversible reactions (out of 920 total reactions, which corresponds to about 70% of all irreversible

  6. Bacterial Metabolism in Humans of the Carcinogen IQ to the Direct Acting Mutagen Hydroxy-IQ

    OpenAIRE

    Van Tassell, R L; Carman, R. J.; Kingston, D. G. I.; Wilkins, T D

    2011-01-01

    7-hydroxy-IQ is the major product of the bacterial metabolism of IQ, a potent dietary carcinogen. Yet, unlike IQ, hydroxy-IQ is directly active in the salmonella/microsomal mutagenicity assay. Two subjects consumed a meal of fried meats containing IQ but no detectable hydroxy-IQ. Hydroxy-IQ was isolated from the subjects’ faeces collected within 30 h following the fried meat meal; it was absent from the subjects’ faeces before and after the meal. This is the first evidence that hy...

  7. Second Law of Thermodynamics Applied to Metabolic Networks

    Science.gov (United States)

    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.

  8. Radial Basis Function Networks Applied in Bacterial Classification Based on MALDI-TOF-MS

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteria cultured at different time was discussed and the effect of the network parameters on the classification was investigated. The cross-validation method was used to test the trained networks. The correctness of the classification of different bacteria investigated changes in a wide range from 61.5% to 92.8%. Owing to the complexity of biological effects in bacterial growth, the more rigid control of bacterial culture conditions seems to be a critical factor for improving the rate of correctness for bacterial classification.

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

    Directory of Open Access Journals (Sweden)

    Joëlle K Muhlemann

    Full Text Available 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.

  10. A joint model of regulatory and metabolic networks

    Directory of Open Access Journals (Sweden)

    Vingron Martin

    2006-07-01

    Full Text Available Abstract Background Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is less well understood. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions. Results We integrate regulatory and metabolic networks by adding links specifying the feedback control from the substrates of metabolic reactions to enzyme gene expressions. We adopt two alternative approaches to build those links: inferring the links between metabolites and transcription factors to fit the data or explicitly encoding the general hypotheses of feedback control as links between metabolites and enzyme expressions. A perturbation data is explained by paths in the joint network if the predicted response along the paths is consistent with the observed response. The consistency requirement for explaining the perturbation data imposes constraints on the attributes in the network such as the functions of links and the activities of paths. We build a probabilistic graphical model over the attributes to specify these constraints, and apply an inference algorithm to identify the attribute values which optimally explain the data. The inferred models allow us to 1 identify the feedback links between metabolites and regulators and their functions, 2 identify the active paths responsible for relaying perturbation effects, 3 computationally test the general hypotheses pertaining to the feedback control of enzyme expressions, 4 evaluate the advantage of an integrated model over separate systems. Conclusion The modeling results provide insight about the mechanisms of the coupling between the two systems and possible "design rules" pertaining to enzyme gene regulation. The model can be used to investigate the less well-probed systems and generate consistent hypotheses and predictions for further validation.

  11. Metabolic Requirements of Escherichia coli in Intracellular Bacterial Communities during Urinary Tract Infection Pathogenesis

    Science.gov (United States)

    Conover, Matt S.; Hadjifrangiskou, Maria; Palermo, Joseph J.; Hibbing, Michael E.; Dodson, Karen W.

    2016-01-01

    ABSTRACT Uropathogenic Escherichia coli (UPEC) is the primary etiological agent of over 85% of community-acquired urinary tract infections (UTIs). Mouse models of infection have shown that UPEC can invade bladder epithelial cells in a type 1 pilus-dependent mechanism, avoid a TLR4-mediated exocytic process, and escape into the host cell cytoplasm. The internalized UPEC can clonally replicate into biofilm-like intracellular bacterial communities (IBCs) of thousands of bacteria while avoiding many host clearance mechanisms. Importantly, IBCs have been documented in urine from women and children suffering acute UTI. To understand this protected bacterial niche, we elucidated the transcriptional profile of bacteria within IBCs using microarrays. We delineated the upregulation within the IBC of genes involved in iron acquisition, metabolism, and transport. Interestingly, lacZ was highly upregulated, suggesting that bacteria were sensing and/or utilizing a galactoside for metabolism in the IBC. A ΔlacZ strain displayed significantly smaller IBCs than the wild-type strain and was attenuated during competitive infection with a wild-type strain. Similarly, a galK mutant resulted in smaller IBCs and attenuated infection. Further, analysis of the highly upregulated gene yeaR revealed that this gene contributes to oxidative stress resistance and type 1 pilus production. These results suggest that bacteria within the IBC are under oxidative stress and, consistent with previous reports, utilize nonglucose carbon metabolites. Better understanding of the bacterial mechanisms used for IBC development and establishment of infection may give insights into development of novel anti-virulence strategies. PMID:27073089

  12. Metabolic Requirements of Escherichia coli in Intracellular Bacterial Communities during Urinary Tract Infection Pathogenesis

    Directory of Open Access Journals (Sweden)

    Matt S. Conover

    2016-04-01

    Full Text Available Uropathogenic Escherichia coli (UPEC is the primary etiological agent of over 85% of community-acquired urinary tract infections (UTIs. Mouse models of infection have shown that UPEC can invade bladder epithelial cells in a type 1 pilus-dependent mechanism, avoid a TLR4-mediated exocytic process, and escape into the host cell cytoplasm. The internalized UPEC can clonally replicate into biofilm-like intracellular bacterial communities (IBCs of thousands of bacteria while avoiding many host clearance mechanisms. Importantly, IBCs have been documented in urine from women and children suffering acute UTI. To understand this protected bacterial niche, we elucidated the transcriptional profile of bacteria within IBCs using microarrays. We delineated the upregulation within the IBC of genes involved in iron acquisition, metabolism, and transport. Interestingly, lacZ was highly upregulated, suggesting that bacteria were sensing and/or utilizing a galactoside for metabolism in the IBC. A ΔlacZ strain displayed significantly smaller IBCs than the wild-type strain and was attenuated during competitive infection with a wild-type strain. Similarly, a galK mutant resulted in smaller IBCs and attenuated infection. Further, analysis of the highly upregulated gene yeaR revealed that this gene contributes to oxidative stress resistance and type 1 pilus production. These results suggest that bacteria within the IBC are under oxidative stress and, consistent with previous reports, utilize nonglucose carbon metabolites. Better understanding of the bacterial mechanisms used for IBC development and establishment of infection may give insights into development of novel anti-virulence strategies.

  13. Design of optimally constructed metabolic networks of minimal functionality.

    Directory of Open Access Journals (Sweden)

    David E Ruckerbauer

    Full Text Available BACKGROUND: Metabolic engineering aims to design microorganisms that will generate a product of interest at high yield. Thus, a variety of in silico modeling strategies has been applied successfully, including the concepts of elementary flux modes (EFMs and constrained minimal cut sets (cMCSs. The EFMs (minimal, steady state pathways through the system can be calculated given a metabolic model. cMCSs are sets of reaction deletions in such a network that will allow desired pathways to survive and disable undesired ones (e.g., those with low product secretion or low growth rates. Grouping the modes into desired and undesired categories had to be done manually until now. RESULTS: Although the optimal solution for a given set of pathways will always be found with the currently available tools, manual selection may lead to a sub-optimal solution with respect to a metabolic engineering target. A small change in the selection of modes can reduce the number of necessary deletions while only slightly reducing production. Based on our recently introduced formulation of cut set calculations using binary linear programming, we suggest an algorithm that does not require manual selection of the desired pathways. CONCLUSIONS: We demonstrated the principle of our algorithm with the help of a small toy network and applied it to a model of E. coli using different design objectives. Furthermore we validated our method by reproducing previously obtained results without requiring manual grouping of modes.

  14. Evaluation and characterization of bacterial metabolic dynamics with a novel profiling technique, real-time metabolotyping.

    Directory of Open Access Journals (Sweden)

    Shinji Fukuda

    Full Text Available BACKGROUND: Environmental processes in ecosystems are dynamically altered by several metabolic responses in microorganisms, including intracellular sensing and pumping, battle for survival, and supply of or competition for nutrients. Notably, intestinal bacteria maintain homeostatic balance in mammals via multiple dynamic biochemical reactions to produce several metabolites from undigested food, and those metabolites exert various effects on mammalian cells in a time-dependent manner. We have established a method for the analysis of bacterial metabolic dynamics in real time and used it in combination with statistical NMR procedures. METHODOLOGY/PRINCIPAL FINDINGS: We developed a novel method called real-time metabolotyping (RT-MT, which performs sequential (1H-NMR profiling and two-dimensional (2D (1H, (13C-HSQC (heteronuclear single quantum coherence profiling during bacterial growth in an NMR tube. The profiles were evaluated with such statistical methods as Z-score analysis, principal components analysis, and time series of statistical TOtal Correlation SpectroScopY (TOCSY. In addition, using 2D (1H, (13C-HSQC with the stable isotope labeling technique, we observed the metabolic kinetics of specific biochemical reactions based on time-dependent 2D kinetic profiles. Using these methods, we clarified the pathway for linolenic acid hydrogenation by a gastrointestinal bacterium, Butyrivibrio fibrisolvens. We identified trans11, cis13 conjugated linoleic acid as the intermediate of linolenic acid hydrogenation by B. fibrisolvens, based on the results of (13C-labeling RT-MT experiments. In addition, we showed that the biohydrogenation of polyunsaturated fatty acids serves as a defense mechanism against their toxic effects. CONCLUSIONS: RT-MT is useful for the characterization of beneficial bacterium that shows potential for use as probiotic by producing bioactive compounds.

  15. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    DEFF Research Database (Denmark)

    Herrgard, Markus; Swainston, Neil; Dobson, Paul;

    2008-01-01

    and content, and use different terminologies to describe the same chemical entities. This makes comparisons between them difficult and underscores the desirability of a consolidated metabolic network that collects and formalizes the 'community knowledge' of yeast metabolism. We describe how we have produced...... of yeast. Similar strategies should benefit communities studying genome-scale metabolic networks of other organisms....

  16. Improvement of bacterial cellulose production by manipulating the metabolic pathways in which ethanol and sodium citrate involved.

    Science.gov (United States)

    Li, Yuanjing; Tian, Chunjie; Tian, Hua; Zhang, Jiliang; He, Xin; Ping, Wenxiang; Lei, Hong

    2012-12-01

    Nowadays, bacterial cellulose has played more and more important role as new biological material for food industry and medical and industrial products based on its unique properties. However, it is still a difficult task to improve the production of bacterial cellulose, especially a large number of byproducts are produced in the metabolic biosynthesis processes. To improve bacterial cellulose production, ethanol and sodium citrate are added into the medium during the fermentation, and the activities of key enzymes and concentration of extracellular metabolites are measured to assess the changes of the metabolic flux of the hexose monophosphate pathway (HMP), the Embden-Meyerhof-Parnas pathway (EMP), and the tricarboxylic acid cycle (TCA). Our results indicate that ethanol functions as energy source for ATP generation at the early stage of the fermentation in the HMP pathway and the supplementation of ethanol significantly reduces glycerol generation (a major byproduct). While in the EMP pathway, sodium citrate plays a key role, and its supplementation results in the byproducts (mainly acetic acid and pyruvic acid) entering the gluconeogenesis pathway for cellulose synthesis. Furthermore, by adding ethanol and sodium citrate, the main byproduct citric acid in the TCA cycle is also reduced significantly. It is concluded that bacterial cellulose production can be improved by increasing energy metabolism and reducing the formation of metabolic byproducts through the metabolic regulations of the bypasses.

  17. Rapid countermeasure discovery against Francisella tularensis based on a metabolic network reconstruction.

    Directory of Open Access Journals (Sweden)

    Sidhartha Chaudhury

    Full Text Available In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of

  18. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    J. Levering; T. Fiedler; A. Sieg; K.W.A. van Grinsven; S. Hering; N. Veith; B.G. Olivier; L. Klett; J. Hugenholtz; B. Teusink; B. Kreikemeyer; U. Kummer

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49

  19. Metabolic pathways of Pseudomonas aeruginosa involved in competition with respiratory bacterial pathogens

    Directory of Open Access Journals (Sweden)

    Marie eBeaume

    2015-04-01

    Full Text Available Background: Chronic airway infection by Pseudomonas aeruginosa considerably contributes to lung tissue destruction and impairment of pulmonary function in cystic-fibrosis (CF patients. Complex interplays between P. aeruginosa and other co-colonizing pathogens including Staphylococcus aureus, Burkholderia spp and Klebsiella pneumoniae may be crucial for pathogenesis and disease progression.Methods: We generated a library of PA14 transposon insertion mutants to identify P. aeruginosa genes required for exploitative and direct competitions with S. aureus, B. cenocepacia, and K. pneumoniae. Results: Whereas wild type PA14 inhibited S. aureus growth, two transposon insertions located in pqsC and carB, resulted in reduced growth inhibition. PqsC is involved in the synthesis of 4-hydroxy-2-alkylquinolines (HAQs, a family of molecules having antibacterial properties, while carB is a key gene in pyrimidine biosynthesis. The carB mutant was also unable to grow in the presence of B. cepacia and K. pneumoniae but not E. coli and S. epidermidis. We further identified a transposon insertion in purF, encoding a key enzyme of purine metabolism. This mutant displayed a severe growth deficiency in the presence of Gram-negative but not of Gram-positive bacteria. We identified a beneficial interaction in a bioA transposon mutant, unable to grow on rich medium. This growth defect could be restored either by addition of biotin or by co-culturing the mutant in the presence of K. pneumoniae or E. coli.Conclusions: Complex interactions take place between the various bacterial species colonizing CF-lungs. This work identified both detrimental and beneficial interactions occurring between P. aeruginosa and three other respiratory pathogens involving several major metabolic pathways. Manipulating these pathways could be used to interfere with bacterial interactions and influence the colonization by respiratory pathogens.

  20. Bow-tie topological features of metabolic networks and the functional significance

    OpenAIRE

    Jing, Zhao; Lin, Tao; Hong, Yu; Jian-Hua, Luo; Cao, Z W; Yixue, Li

    2006-01-01

    Exploring the structural topology of genome-based large-scale metabolic network is essential for investigating possible relations between structure and functionality. Visualization would be helpful for obtaining immediate information about structural organization. In this work, metabolic networks of 75 organisms were investigated from a topological point of view. A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks. The revealed top...

  1. Bow-tie topological features of metabolic networks and the functional significance

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; TAO Lin; YU Hong; LUO JianHua; GAO ZhiWei; LI YiXue

    2007-01-01

    Exploring the structural topology of genome-based large-scale metabolic network is essential for in vestigating possible relations between structure and functionality. Visualization would be helpful for obtaining immediate information about structural organization. In this work, metabolic networks of 75 organisms were investigated from a topological point of view. A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks. The revealed topological pattern helps to design more efficient algorithm specifically for metabolic networks. This coarsegrained graph also visualizes the vulnerable connections in the network, and thus could have important implication for disease studies and drug target identifications. In addition, analysis on the reciprocal links and main cores in the GSC part of bow-tie also reveals that the bow-tie structure of metabolic networks has its own intrinsic and significant features which are significantly different from those of random networks.

  2. Comparison between elementary flux modes analysis and 13C-metabolic fluxes measured in bacterial and plant cells

    Directory of Open Access Journals (Sweden)

    Dieuaide-Noubhani Martine

    2011-06-01

    Full Text Available Abstract Background 13C metabolic flux analysis is one of the pertinent ways to compare two or more physiological states. From a more theoretical standpoint, the structural properties of metabolic networks can be analysed to explore feasible metabolic behaviours and to define the boundaries of steady state flux distributions. Elementary flux mode analysis is one of the most efficient methods for performing this analysis. In this context, recent approaches have tended to compare experimental flux measurements with topological network analysis. Results Metabolic networks describing the main pathways of central carbon metabolism were set up for a bacteria species (Corynebacterium glutamicum and a plant species (Brassica napus for which experimental flux maps were available. The structural properties of each network were then studied using the concept of elementary flux modes. To do this, coefficients of flux efficiency were calculated for each reaction within the networks by using selected sets of elementary flux modes. Then the relative differences - reflecting the change of substrate i.e. a sugar source for C. glutamicum and a nitrogen source for B. napus - of both flux efficiency and flux measured experimentally were compared. For both organisms, there is a clear relationship between these parameters, thus indicating that the network structure described by the elementary flux modes had captured a significant part of the metabolic activity in both biological systems. In B. napus, the extension of the elementary flux mode analysis to an enlarged metabolic network still resulted in a clear relationship between the change in the coefficients and that of the measured fluxes. Nevertheless, the limitations of the method to fit some particular fluxes are discussed. Conclusion This consistency between EFM analysis and experimental flux measurements, validated on two metabolic systems allows us to conclude that elementary flux mode analysis could be a

  3. Metabolic Investigation in Gluconacetobacter xylinus and Its Bacterial Cellulose Production under a Direct Current Electric Field.

    Science.gov (United States)

    Liu, Miao; Zhong, Cheng; Zhang, Yu Ming; Xu, Ze Ming; Qiao, Chang Sheng; Jia, Shi Ru

    2016-01-01

    The effects of a direct current (DC) electric field on the growth and metabolism of Gluconacetobacter xylinus were investigated in static culture. When a DC electric field at 10 mA was applied using platinum electrodes to the culture broth, bacterial cellulose (BC) production was promoted in 12 h but was inhibited in the last 12 h as compared to the control (without DC electric field). At the cathode, the presence of the hydrogen generated a strong reductive environment that is beneficial to cell growth. As compared to the control, the activities of glycolysis and tricarboxylic acid cycle, as well as BC productivity were observed to be slightly higher in the first 12 h. However, due to the absence of sufficient oxygen, lactic acid was accumulated from pyruvic acid at 18 h, which was not in favor of BC production. At the anode, DC inhibited cell growth in 6 h when compared to the control. The metabolic activity in G. xylinus was inhibited through the suppression of the tricarboxylic acid cycle and glycolysis. At 18-24 h, cell density was observed to decrease, which might be due to the electrolysis of water that significantly dropped the pH of cultural broth far beyond the optimal range. Meanwhile, metabolites for self-protection were accumulated, for instance proline, glutamic acid, gluconic acid, and fatty acids. Notably, the accumulation of gluconic acid and lactic acid made it a really tough acid stress to cells at the anode and finally led to depression of cell growth.

  4. Metabolism of 2,4-dichlorophenol in tobacco engineered with bacterial degradative genes

    Energy Technology Data Exchange (ETDEWEB)

    Perkins, E.J.; Sekine, M.; Gordon, M.P. (Univ. of Washington, Seattle (USA))

    1990-05-01

    The potential use of plants in toxic waste remediation has been overlooked. While chlorophenols are relatively slowly metabolized in Nicotiana tabacum var. Xanthi leaf extracts, chlorocatechols are rapidly metabolized, presumably by polyphenol oxidases. Our initial focus has been the fate of 2,4-dichlorophenol (2,4DCP) in var. Xanthi plants which express a bacterial 2,4DCP hydroxylase, which converts 2,4DCP to 3,5-dichlorocatechol. The roots of wild type and 2,4DCP hydroxylase transgenic plants growing in hydroponics were exposed to {sup 14}C-2,4DCP. Approximately 95% of {sup 14}C-2,4DCP metabolites remained in the roots when exposed to 2,4DCP. Upon extraction of root tissue, three major metabolites were found in untransformed plants and four major metabolites in transformed plants. Upon digestion with beta-D-glucosidase, these metabolites disappeared concomitant with the appearance of free 2,4DCP in wild type plants and 2,4DCP and 3,5-dichlorocatechol in transgenic plants. It is apparent that the chlorophenols are not readily available substrates for polyphenol oxidases in whole plants.

  5. Molecular characterization of total and metabolically active bacterial communities of "white colonizations" in the Altamira Cave, Spain.

    Science.gov (United States)

    Portillo, M Carmen; Saiz-Jimenez, Cesareo; Gonzalez, Juan M

    2009-01-01

    Caves with paleolithic paintings are influenced by bacterial development. Altamira Cave (Spain) contains some of the most famous paintings from the Paleolithic era. An assessment of the composition of bacterial communities that have colonized this cave represents a first step in understanding and potentially controlling their proliferation. In this study, areas showing colonization with uncolored microorganisms, referred to as "white colonizations", were analyzed. Microorganisms present in these colonizations were studied using DNA analysis, and those showing significant metabolic activity were detected in RNA-based RNA analysis. Bacterial community fingerprints were obtained both from DNA and RNA analyses, indicating differences between the microorganisms present and metabolically active in these white colonizations. Metabolically active microorganisms represented only a fraction of the total bacterial community present in the colonizations. 16S rRNA gene libraries were used to identify the major representative members of the studied communities. Proteobacteria constituted the most frequently found division both among metabolically active microorganisms (from RNA-based analysis) and those present in the community (from DNA analysis). Results suggest the existence of a huge variety of taxa in white colonizations of the Altamira Cave which represent a potential risk for the conservation of the cave and its paintings. PMID:18984039

  6. A new method for determining the metabolic activity of specific bacterial populations in soil using tritiated leucine and immunomagnetic separation

    DEFF Research Database (Denmark)

    Sengeløv, Gitte; Sørensen, Søren Johannes; Frette, Lone;

    2000-01-01

    A new assay, using immunomagnetic separation and uptake of tritiated leucine ([3H]-Leu), was developed for measuring the in situ metabolic activity of specific bacterial populations in soil. Such assays are needed to assess the role individual species play in diverse microbial soil communities...... reduced this unspecific binding, resulting in metabolic activity of the target cells. As expected, a linear relationship...... between activity and temperature was observed, demonstrating the sensitivity of the assay. The method was applied to compare activities of the target strain in bulk soil and in the rhizosphere of barley. Contrary to what was anticipated, no significant difference in metabolic activity was observed....

  7. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    Directory of Open Access Journals (Sweden)

    Yihan Lin

    Full Text Available Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS.

  8. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Energy Technology Data Exchange (ETDEWEB)

    Rodionov, Dmitry A.; Novichkov, Pavel; Stavrovskaya, Elena D.; Rodionova, Irina A.; Li, Xiaoqing; Kazanov, Marat D.; Ravcheev, Dmitry A.; Gerasimova, Anna V.; Kazakov, Alexey E.; Kovaleva, Galina Y.; Permina, Elizabeth A.; Laikova, Olga N.; Overbeek, Ross; Romine, Margaret F.; Fredrickson, Jim K.; Arkin, Adam P.; Dubchak, Inna; Osterman, Andrei L.; Gelfand, Mikhail S.

    2011-06-15

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. Despite the growing number of genome-scale gene expression studies, our abilities to convert the results of these studies into accurate regulatory annotations and to project them from model to other organisms are extremely limited. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. However, even orthologous regulators with conserved DNA-binding motifs may control substantially different gene sets, revealing striking differences in regulatory strategies between the Shewanella spp. and E. coli. Multiple examples of regulatory network rewiring include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), and numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. NagR for N-acetylglucosamine catabolism and PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).

  9. Early Changes in Soil Metabolic Diversity and Bacterial Community Structure in Sugarcane under Two Harvest Management Systems

    Directory of Open Access Journals (Sweden)

    Lucas Carvalho Basilio Azevedo

    2015-06-01

    Full Text Available Preharvest burning is widely used in Brazil for sugarcane cropping. However, due to environmental restrictions, harvest without burning is becoming the predominant option. Consequently, changes in the microbial community are expected from crop residue accumulation on the soil surface, as well as alterations in soil metabolic diversity as of the first harvest. Because biological properties respond quickly and can be used to monitor environmental changes, we evaluated soil metabolic diversity and bacterial community structure after the first harvest under sugarcane management without burning compared to management with preharvest burning. Soil samples were collected under three sugarcane varieties (SP813250, SP801842 and RB72454 and two harvest management systems (without and with preharvest burning. Microbial biomass C (MBC, carbon (C substrate utilization profiles, bacterial community structure (based on profiles of 16S rRNA gene amplicons, and soil chemical properties were determined. MBC was not different among the treatments. C-substrate utilization and metabolic diversity were lower in soil without burning, except for the evenness index of C-substrate utilization. Soil samples under the variety SP801842 showed the greatest changes in substrate utilization and metabolic diversity, but showed no differences in bacterial community structure, regardless of the harvest management system. In conclusion, combined analysis of soil chemical and microbiological data can detect early changes in microbial metabolic capacity and diversity, with lower values in management without burning. However, after the first harvest, there were no changes in the soil bacterial community structure detected by PCR-DGGE under the sugarcane variety SP801842. Therefore, the metabolic profile is a more sensitive indicator of early changes in the soil microbial community caused by the harvest management system.

  10. Characterizing the interplay betwen mulitple levels of organization within bacterial sigma factor regulatory networks

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Qiu [University of California, San Diego; Nagarajan, Harish [University of California, San Diego; Embree, Mallory [University of California, San Diego; Shieu, Wendy [University of California, San Diego; Abate, Elisa [University of California, San Diego; Juarez, Katy [Universidad Nacional Autonoma de Mexico (UNAM); Cho, Byung-Kwan [University of California, San Diego; Elkins, James G [ORNL; Nevin, Kelly P. [University of Massachusetts, Amherst; Barrett, Christian [University of California, San Diego; Lovley, Derek [University of Massachusetts, Amherst; Palsson, Bernhard O. [University of California, San Diego; Zengler, Karsten [University of California, San Diego

    2013-01-01

    Bacteria contain multiple sigma factors, each targeting diverse, but often overlapping sets of promoters, thereby forming a complex network. The layout and deployment of such a sigma factor network directly impacts global transcriptional regulation and ultimately dictates the phenotype. Here we integrate multi-omic data sets to determine the topology, the operational, and functional states of the sigma factor network in Geobacter sulfurreducens, revealing a unique network topology of interacting sigma factors. Analysis of the operational state of the sigma factor network shows a highly modular structure with sN being the major regulator of energy metabolism. Surprisingly, the functional state of the network during the two most divergent growth conditions is nearly static, with sigma factor binding profiles almost invariant to environmental stimuli. This first comprehensive elucidation of the interplay between different levels of the sigma factor network organization is fundamental to characterize transcriptional regulatory mechanisms in bacteria.

  11. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    NARCIS (Netherlands)

    Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Blüthgen, Nils; Borger, Simon; Costenoble, Roeland; Heinemann, Matthias; Hucka, Michael; Novère, Nicolas Le; Li, Peter; Liebermeister, Wolfram; Mo, Monica L.; Oliveira, Ana Paula; Petranovic, Dina; Pettifer, Stephen; Simeonidis, Evangelos; Smallbone, Kieran; Spasić, Irena; Weichart, Dieter; Brent, Roger; Broomhead, David S.; Westerhoff, Hans V.; Kırdar, Betül; Penttilä, Merja; Klipp, Edda; Palsson, Bernhard Ø.; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B.

    2008-01-01

    Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and cont

  12. Differential response of high-elevation planktonic bacterial community structure and metabolism to experimental nutrient enrichment.

    Directory of Open Access Journals (Sweden)

    Craig E Nelson

    Full Text Available Nutrient enrichment of high-elevation freshwater ecosystems by atmospheric deposition is increasing worldwide, and bacteria are a key conduit for the metabolism of organic matter in these oligotrophic environments. We conducted two distinct in situ microcosm experiments in a high-elevation lake (Emerald Lake, Sierra Nevada, California, USA to evaluate responses in bacterioplankton growth, carbon utilization, and community structure to short-term enrichment by nitrate and phosphate. The first experiment, conducted just following ice-off, employed dark dilution culture to directly assess the impact of nutrients on bacterioplankton growth and consumption of terrigenous dissolved organic matter during snowmelt. The second experiment, conducted in transparent microcosms during autumn overturn, examined how bacterioplankton in unmanipulated microbial communities responded to nutrients concomitant with increasing phytoplankton-derived organic matter. In both experiments, phosphate enrichment (but not nitrate caused significant increases in bacterioplankton growth, changed particulate organic stoichiometry, and induced shifts in bacterial community composition, including consistent declines in the relative abundance of Actinobacteria. The dark dilution culture showed a significant increase in dissolved organic carbon removal in response to phosphate enrichment. In transparent microcosms nutrient enrichment had no effect on concentrations of chlorophyll, carbon, or the fluorescence characteristics of dissolved organic matter, suggesting that bacterioplankton responses were independent of phytoplankton responses. These results demonstrate that bacterioplankton communities in unproductive high-elevation habitats can rapidly alter their taxonomic composition and metabolism in response to short-term phosphate enrichment. Our results reinforce the key role that phosphorus plays in oligotrophic lake ecosystems, clarify the nature of bacterioplankton nutrient

  13. Metabolic investigation in Gluconacetobacter xylinus and its bacterial cellulose production under a direct current electric field

    Directory of Open Access Journals (Sweden)

    Miao eLiu

    2016-03-01

    Full Text Available The effects of a direct current (DC electric field on the growth and metabolism of Gluconacetobacter xylinus were investigated in static culture. When a DC electric field at 10 mA was applied using platinum electrodes to the culture broth, bacterial cellulose (BC production was promoted in 12 hours (h but was inhibited in the last 12 h as compared to the control (without DC electric field. At the cathode, the presence of the hydrogen generated a strong reductive environment that is beneficial to cell growth. As compared to the control, the activities of glycolysis and tricarboxylic acid cycle, as well as BC productivity were observed to be slightly higher in the first 12 h. However, due to the absence of sufficient oxygen, lactic acid was accumulated from pyruvic acid at 18 h, which was not in favor of BC production. At the anode, DC inhibited cell growth in 6 h when compared to the control. The metabolic activity in G. xylinus was inhibited through the suppression of the tricarboxylic acid cycle and glycolysis. At 18-24 h, cell density was observed to decrease, which might be due to the electrolysis of water that significantly dropped the pH of cultural broth far beyond the optimal range. Meanwhile, metabolites for self-protection were accumulated, for instance proline, glutamic acid, gluconic acid and fatty acids. Notably, the accumulation of gluconic acid and lactic acid made it a really tough acid stress to cells at the anode and finally led to depression of cell growth.

  14. Metabolic Investigation in Gluconacetobacter xylinus and Its Bacterial Cellulose Production under a Direct Current Electric Field.

    Science.gov (United States)

    Liu, Miao; Zhong, Cheng; Zhang, Yu Ming; Xu, Ze Ming; Qiao, Chang Sheng; Jia, Shi Ru

    2016-01-01

    The effects of a direct current (DC) electric field on the growth and metabolism of Gluconacetobacter xylinus were investigated in static culture. When a DC electric field at 10 mA was applied using platinum electrodes to the culture broth, bacterial cellulose (BC) production was promoted in 12 h but was inhibited in the last 12 h as compared to the control (without DC electric field). At the cathode, the presence of the hydrogen generated a strong reductive environment that is beneficial to cell growth. As compared to the control, the activities of glycolysis and tricarboxylic acid cycle, as well as BC productivity were observed to be slightly higher in the first 12 h. However, due to the absence of sufficient oxygen, lactic acid was accumulated from pyruvic acid at 18 h, which was not in favor of BC production. At the anode, DC inhibited cell growth in 6 h when compared to the control. The metabolic activity in G. xylinus was inhibited through the suppression of the tricarboxylic acid cycle and glycolysis. At 18-24 h, cell density was observed to decrease, which might be due to the electrolysis of water that significantly dropped the pH of cultural broth far beyond the optimal range. Meanwhile, metabolites for self-protection were accumulated, for instance proline, glutamic acid, gluconic acid, and fatty acids. Notably, the accumulation of gluconic acid and lactic acid made it a really tough acid stress to cells at the anode and finally led to depression of cell growth. PMID:27014248

  15. Feedback control architecture and the bacterial chemotaxis network.

    Directory of Open Access Journals (Sweden)

    Abdullah Hamadeh

    2011-05-01

    Full Text Available Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to 'reset' (adapt the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a 'cascade control' feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance.

  16. Coordinations between gene modules control the operation of plant amino acid metabolic networks

    Directory of Open Access Journals (Sweden)

    Galili Gad

    2009-01-01

    Full Text Available Abstract Background Being sessile organisms, plants should adjust their metabolism to dynamic changes in their environment. Such adjustments need particular coordination in branched metabolic networks in which a given metabolite can be converted into multiple other metabolites via different enzymatic chains. In the present report, we developed a novel "Gene Coordination" bioinformatics approach and use it to elucidate adjustable transcriptional interactions of two branched amino acid metabolic networks in plants in response to environmental stresses, using publicly available microarray results. Results Using our "Gene Coordination" approach, we have identified in Arabidopsis plants two oppositely regulated groups of "highly coordinated" genes within the branched Asp-family network of Arabidopsis plants, which metabolizes the amino acids Lys, Met, Thr, Ile and Gly, as well as a single group of "highly coordinated" genes within the branched aromatic amino acid metabolic network, which metabolizes the amino acids Trp, Phe and Tyr. These genes possess highly coordinated adjustable negative and positive expression responses to various stress cues, which apparently regulate adjustable metabolic shifts between competing branches of these networks. We also provide evidence implying that these highly coordinated genes are central to impose intra- and inter-network interactions between the Asp-family and aromatic amino acid metabolic networks as well as differential system interactions with other growth promoting and stress-associated genome-wide genes. Conclusion Our novel Gene Coordination elucidates that branched amino acid metabolic networks in plants are regulated by specific groups of highly coordinated genes that possess adjustable intra-network, inter-network and genome-wide transcriptional interactions. We also hypothesize that such transcriptional interactions enable regulatory metabolic adjustments needed for adaptation to the stresses.

  17. Investigating genotype-phenotype relationships in Saccharomyces cerevisiae metabolic network through stoichiometric modeling

    DEFF Research Database (Denmark)

    Brochado, Ana Rita

    at better characterizing genotype to phenotype relationships. Metabolic Engineering is one of the fields in which the complete understanding of such relationship would have a striking impact, since phenotype prediction based on genotype is fundamental for rationally engineering metabolic networks....... This chapter aims at providing the reader with relevant state-of-the-art information concerning Systems Biology, Genome-Scale Metabolic Modeling and Metabolic Engineering. Particular attention is given to the yeast Saccharomyces cerevisiae, the eukaryotic model organism used thought the thesis....

  18. Bacterial DNA Sequence Compression Models Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Armando J. Pinho

    2013-08-01

    Full Text Available It is widely accepted that the advances in DNA sequencing techniques have contributed to an unprecedented growth of genomic data. This fact has increased the interest in DNA compression, not only from the information theory and biology points of view, but also from a practical perspective, since such sequences require storage resources. Several compression methods exist, and particularly, those using finite-context models (FCMs have received increasing attention, as they have been proven to effectively compress DNA sequences with low bits-per-base, as well as low encoding/decoding time-per-base. However, the amount of run-time memory required to store high-order finite-context models may become impractical, since a context-order as low as 16 requires a maximum of 17.2 x 109 memory entries. This paper presents a method to reduce such a memory requirement by using a novel application of artificial neural networks (ANN to build such probabilistic models in a compact way and shows how to use them to estimate the probabilities. Such a system was implemented, and its performance compared against state-of-the art compressors, such as XM-DNA (expert model and FCM-Mx (mixture of finite-context models , as well as with general-purpose compressors. Using a combination of order-10 FCM and ANN, similar encoding results to those of FCM, up to order-16, are obtained using only 17 megabytes of memory, whereas the latter, even employing hash-tables, uses several hundreds of megabytes.

  19. Metabolic and phylogenetic profile of bacterial community in Guishan coastal water (Pearl River Estuary), South China Sea

    Science.gov (United States)

    Hu, Xiaojuan; Liu, Qing; Li, Zhuojia; He, Zhili; Gong, Yingxue; Cao, Yucheng; Yang, Yufeng

    2014-10-01

    Characteristics of a microbial community are important as they indicate the status of aquatic ecosystems. In the present study, the metabolic and phylogenetic profile of the bacterioplankton community in Guishan coastal water (Pearl River Estuary), South China Sea, at 12 sites (S1-S12) were explored by community-level physiological profiling (CLPP) with BIOLOG Eco-plate and denaturing gradient gel electrophoresis (DGGE). Our results showed that the core mariculture area (S6, S7 and S8) and the sites associating with human activity and sewage discharge (S11 and S12) had higher microbial metabolic capability and bacterial community diversity than others (S1-5, S9-10). Especially, the diversity index of S11 and S12 calculated from both CLPP and DGGE data ( H>3.2) was higher than that of others as sewage discharge may increase water nitrogen and phosphorus nutrient. The bacterial community structure of S6, S8, S11 and S12 was greatly influenced by total phosphorous, salinity and total nitrogen. Based on DGGE fingerprinting, proteobacteria, especially γ- and α-proteobacteria, were found dominant at all sites. In conclusion, the aquaculture area and wharf had high microbial metabolic capability. The structure and composition of bacterial community were closely related to the level of phosphorus, salinity and nitrogen.

  20. Many means to a common end: the intricacies of (p)ppGpp metabolism and its control of bacterial homeostasis.

    Science.gov (United States)

    Gaca, Anthony O; Colomer-Winter, Cristina; Lemos, José A

    2015-04-01

    In nearly all bacterial species examined so far, amino acid starvation triggers the rapid accumulation of the nucleotide second messenger (p)ppGpp, the effector of the stringent response. While for years the enzymes involved in (p)ppGpp metabolism and the significance of (p)ppGpp accumulation to stress survival were considered well defined, a recent surge of interest in the field has uncovered an unanticipated level of diversity in how bacteria metabolize and utilize (p)ppGpp to rapidly synchronize a variety of biological processes important for growth and stress survival. In addition to the classic activation of the stringent response, it has become evident that (p)ppGpp exerts differential effects on cell physiology in an incremental manner rather than simply acting as a biphasic switch that controls growth or stasis. Of particular interest is the intimate relationship of (p)ppGpp with persister cell formation and virulence, which has spurred the pursuit of (p)ppGpp inhibitors as a means to control recalcitrant infections. Here, we present an overview of the enzymes responsible for (p)ppGpp metabolism, elaborate on the intricacies that link basal production of (p)ppGpp to bacterial homeostasis, and discuss the implications of targeting (p)ppGpp synthesis as a means to disrupt long-term bacterial survival strategies.

  1. The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles

    Directory of Open Access Journals (Sweden)

    Walther Dirk

    2008-11-01

    Full Text Available Abstract Background The study of biological interaction networks is a central theme of systems biology. Here, we investigate the relationships between two distinct types of interaction networks: the metabolic pathway map and the protein-protein interaction network (PIN. It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzymes complexes. Inspecting high-throughput PIN data, it was shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In our study, we expanded this line of research to include comparisons of the underlying respective network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Results Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and may thus be essential for the structural integrity of several biosynthetic systems. Conclusion Our results reveal topological equivalences between the protein

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

    Directory of Open Access Journals (Sweden)

    Richard A Notebaart

    2008-01-01

    Full Text Available 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.

  3. A toolbox model of evolution of metabolic pathways on networks of arbitrary topology.

    Directory of Open Access Journals (Sweden)

    Tin Yau Pang

    2011-05-01

    Full Text Available In prokaryotic genomes the number of transcriptional regulators is known to be proportional to the square of the total number of protein-coding genes. A toolbox model of evolution was recently proposed to explain this empirical scaling for metabolic enzymes and their regulators. According to its rules, the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes in the toolbox model. Here we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We prove that critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for quadratic scaling. We further generalize the rules of the model to incorporate reactions with multiple substrates/products as well as branched and cyclic metabolic pathways. To achieve its metabolic tasks, the new model employs evolutionary optimized pathways with minimal number of reactions. Numerical simulations of this realistic model on the universal network of all reactions in the KEGG database produced approximately quadratic scaling between the number of regulated pathways and the size of the metabolic network. To quantify the geometrical structure of individual pathways, we investigated the relationship between their number of reactions, byproducts, intermediate, and feedback metabolites. Our results validate and explain the ubiquitous appearance of the quadratic scaling for a broad spectrum of topologies of underlying universal metabolic networks. They also demonstrate why, in spite of "small-world" topology, real-life metabolic networks are characterized by a broad

  4. Involvement of a bacterial microcompartment in the metabolism of fucose and rhamnose by Clostridium phytofermentans.

    Directory of Open Access Journals (Sweden)

    Elsa Petit

    Full Text Available BACKGROUND: Clostridium phytofermentans, an anaerobic soil bacterium, can directly convert plant biomass into biofuels. The genome of C. phytofermentans contains three loci with genes encoding shell proteins of bacterial microcompartments (BMC, organelles composed entirely of proteins. METHODOLOGY AND PRINCIPAL FINDINGS: One of the BMC loci has homology to a BMC-encoding locus implicated in the conversion of fucose to propanol and propionate in a human gut commensal, Roseburia inulinivorans. We hypothesized that it had a similar role in C. phytofermentans. When C. phytofermentans was grown on fucose, the major products identified were ethanol, propanol and propionate. Transmission electron microscopy of fucose- and rhamnose-grown cultures revealed polyhedral structures, presumably BMCs. Microarray analysis indicated that during growth on fucose, operons coding for the BMC locus, fucose dissimilatory enzymes, and an ATP-binding cassette transporter became the dominant transcripts. These data are consistent with fucose fermentation producing a 1,2-propanediol intermediate that is further metabolized in the microcompartment encoded in the BMC locus. Growth on another deoxyhexose sugar, rhamnose, resulted in the expression of the same BMC locus and similar fermentation products. However, a different set of dissimilatory enzymes and transport system genes were induced. Quite surprisingly, growth on fucose or rhamnose also led to the expression of a diverse array of complex plant polysaccharide-degrading enzymes. CONCLUSIONS/SIGNIFICANCE: Based on physiological, genomic, and microarray analyses, we propose a model for the fermentation of fucose and rhamnose in C. phytofermentans that includes enzymes encoded in the same BMC locus. Comparative genomic analysis suggests that this BMC may be present in other clostridial species.

  5. Metabolic complementarity and genomics of the dual bacterial symbiosis of sharpshooters.

    Directory of Open Access Journals (Sweden)

    Dongying Wu

    2006-06-01

    Full Text Available Mutualistic intracellular symbiosis between bacteria and insects is a widespread phenomenon that has contributed to the global success of insects. The symbionts, by provisioning nutrients lacking from diets, allow various insects to occupy or dominate ecological niches that might otherwise be unavailable. One such insect is the glassy-winged sharpshooter (Homalodisca coagulata, which feeds on xylem fluid, a diet exceptionally poor in organic nutrients. Phylogenetic studies based on rRNA have shown two types of bacterial symbionts to be coevolving with sharpshooters: the gamma-proteobacterium Baumannia cicadellinicola and the Bacteroidetes species Sulcia muelleri. We report here the sequencing and analysis of the 686,192-base pair genome of B. cicadellinicola and approximately 150 kilobase pairs of the small genome of S. muelleri, both isolated from H. coagulata. Our study, which to our knowledge is the first genomic analysis of an obligate symbiosis involving multiple partners, suggests striking complementarity in the biosynthetic capabilities of the two symbionts: B. cicadellinicola devotes a substantial portion of its genome to the biosynthesis of vitamins and cofactors required by animals and lacks most amino acid biosynthetic pathways, whereas S. muelleri apparently produces most or all of the essential amino acids needed by its host. This finding, along with other results of our genome analysis, suggests the existence of metabolic codependency among the two unrelated endosymbionts and their insect host. This dual symbiosis provides a model case for studying correlated genome evolution and genome reduction involving multiple organisms in an intimate, obligate mutualistic relationship. In addition, our analysis provides insight for the first time into the differences in symbionts between insects (e.g., aphids that feed on phloem versus those like H. coagulata that feed on xylem. Finally, the genomes of these two symbionts provide potential

  6. Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

    Science.gov (United States)

    Martínez-Romero, Marcos; Vázquez-Naya, José M; Rabuñal, Juan R; Pita-Fernández, Salvador; Macenlle, Ramiro; Castro-Alvariño, Javier; López-Roses, Leopoldo; Ulla, José L; Martínez-Calvo, Antonio V; Vázquez, Santiago; Pereira, Javier; Porto-Pazos, Ana B; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

    2010-05-01

    Colorectal cancer is one of the most frequent types of cancer in the world and generates important social impact. The understanding of the specific metabolism of this disease and the transformations of the specific drugs will allow finding effective prevention, diagnosis and treatment of the colorectal cancer. All the terms that describe the drug metabolism contribute to the construction of ontology in order to help scientists to link the correlated information and to find the most useful data about this topic. The molecular components involved in this metabolism are included in complex network such as metabolic pathways in order to describe all the molecular interactions in the colorectal cancer. The graphical method of processing biological information such as graphs and complex networks leads to the numerical characterization of the colorectal cancer drug metabolic network by using invariant values named topological indices. Thus, this method can help scientists to study the most important elements in the metabolic pathways and the dynamics of the networks during mutations, denaturation or evolution for any type of disease. This review presents the last studies regarding ontology and complex networks of the colorectal cancer drug metabolism and a basic topology characterization of the drug metabolic process sub-ontology from the Gene Ontology.

  7. Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation.

    Science.gov (United States)

    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

  8. INFLUENCE OF ROOT EXUDATES AND BACTERIAL METABOLIC ACTIVITY ON APPARENT CONJUGAL GENE TRANSFER FREQUENCIES IN THE RHIZOSPHERE OF WATER GRASS (ECHINOCLORA CRUSGALLI)

    Science.gov (United States)

    The premise that genetic exchange is primarily localized in niches characterized by dense bacterial populations and high availability of growth substrates was tested by relating conjugal gene transfer of an RP4 derivative to availability of root exudates and bacterial metabolic a...

  9. Integrating large-scale functional genomics data to dissect metabolic networks for hydrogen production

    Energy Technology Data Exchange (ETDEWEB)

    Harwood, Caroline S

    2012-12-17

    The goal of this project is to identify gene networks that are critical for efficient biohydrogen production by leveraging variation in gene content and gene expression in independently isolated Rhodopseudomonas palustris strains. Coexpression methods were applied to large data sets that we have collected to define probabilistic causal gene networks. To our knowledge this a first systems level approach that takes advantage of strain-to strain variability to computationally define networks critical for a particular bacterial phenotypic trait.

  10. Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions

    Directory of Open Access Journals (Sweden)

    Orth Jeffrey D

    2012-05-01

    Full Text Available Abstract Background The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network. Results A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing reactions in the reconstructed network, adding reactions from a KEGG based universal set of metabolic reactions. The feasibility of these putative reactions was determined by comparing updated versions of the model to the experimental dataset, and genes were predicted for the most feasible reactions. Conclusions Numerous improvements to the iJO1366 metabolic reconstruction were suggested by these analyses. Experiments were performed to verify several computational predictions, including a new mechanism for growth on myo-inositol. The other predictions made in this study should be experimentally verifiable by similar means. Validating all of the predictions made here represents a substantial but important undertaking.

  11. Metabolic design based on a coupled gene expression-metabolic network model of tryptophan production in Escherichia coli.

    Science.gov (United States)

    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

  12. Petri Net Based Metabolic Network Parameters Fitting with GPU Acceleration%Petri Net Based Metabolic Network Parameters Fitting with GPU Acceleration

    Institute of Scientific and Technical Information of China (English)

    Gao, Jun; Zhu, Ruixin; Liu, Qi; Cao, Zhiwei

    2011-01-01

    Classical Petri net has been applied into biological analysis, especially as a qualitative model for biochemical pathways analysis, but lack of the ability for quantitative kinetic simulations. In our study, we presented an integra- tion work of the qualitative model--Petri nets with the quantitative approach-ordinary differential equations (ODEs) for the modeling and analysis of metabolic networks. As an application of our study, the computational modeling of arachidonic acid (AA) biochemical network was provided. A Petri net was set up to present the constraint-based dynamic simulations on AA metabolic network combined with the validated ODEs model. Furthermore, Graphics Processing Unit (GPU) was adopted to accelerate the calculation of kinetic parameters unavailable from experi- ments. Our results have indicated that the proposed simulation method was practicable and useful with GPU accel- eration, and provides new clues for the large-scale qualitative and quantitative models of biochemical networks.

  13. Metabolic network reconstruction, growth characterization and 13C-metabolic flux analysis of the extremophile Thermus thermophilus HB8.

    Science.gov (United States)

    Swarup, Aditi; Lu, Jing; DeWoody, Kathleen C; Antoniewicz, Maciek R

    2014-07-01

    Thermus thermophilus is an extremely thermophilic bacterium with significant biotechnological potential. In this work, we have characterized aerobic growth characteristics of T. thermophilus HB8 at temperatures between 50 and 85°C, constructed a metabolic network model of its central carbon metabolism and validated the model using (13)C-metabolic flux analysis ((13)C-MFA). First, cells were grown in batch cultures in custom constructed mini-bioreactors at different temperatures to determine optimal growth conditions. The optimal temperature for T. thermophilus grown on defined medium with glucose was 81°C. The maximum growth rate was 0.25h(-1). Between 50 and 81°C the growth rate increased by 7-fold and the temperature dependence was described well by an Arrhenius model with an activation energy of 47kJ/mol. Next, we performed a (13)C-labeling experiment with [1,2-(13)C] glucose as the tracer and calculated intracellular metabolic fluxes using (13)C-MFA. The results provided support for the constructed network model and highlighted several interesting characteristics of T. thermophilus metabolism. We found that T. thermophilus largely uses glycolysis and TCA cycle to produce biosynthetic precursors, ATP and reducing equivalents needed for cells growth. Consistent with its proposed metabolic network model, we did not detect any oxidative pentose phosphate pathway flux or Entner-Doudoroff pathway activity. The biomass precursors erythrose-4-phosphate and ribose-5-phosphate were produced via the non-oxidative pentose phosphate pathway, and largely via transketolase, with little contribution from transaldolase. The high biomass yield on glucose that was measured experimentally was also confirmed independently by (13)C-MFA. The results presented here provide a solid foundation for future studies of T. thermophilus and its metabolic engineering applications.

  14. Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide.

    Science.gov (United States)

    Orth, Jeffrey D; Fleming, R M T; Palsson, Bernhard Ø

    2010-09-01

    Biochemical network reconstructions have become popular tools in systems biology. Metabolicnetwork reconstructions are biochemically, genetically, and genomically (BiGG) structured databases of biochemical reactions and metabolites. They contain information such as exact reaction stoichiometry, reaction reversibility, and the relationships between genes, proteins, and reactions. Network reconstructions have been used extensively to study the phenotypic behavior of wild-type and mutant stains under a variety of conditions, linking genotypes with phenotypes. Such phenotypic simulations have allowed for the prediction of growth after genetic manipulations, prediction of growth phenotypes after adaptive evolution, and prediction of essential genes. Additionally, because network reconstructions are organism specific, they can be used to understand differences between organisms of species in a functional context.There are different types of reconstructions representing various types of biological networks (metabolic, regulatory, transcription/translation). This chapter serves as an introduction to metabolic and regulatory network reconstructions and models and gives a complete description of the core Escherichia coli metabolic model. This model can be analyzed in any computational format (such as MATLAB or Mathematica) based on the information given in this chapter. The core E. coli model is a small-scale model that can be used for educational purposes. It is meant to be used by senior undergraduate and first-year graduate students learning about constraint-based modeling and systems biology. This model has enough reactions and pathways to enable interesting and insightful calculations, but it is also simple enough that the results of such calculations can be understoodeasily.

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

    DEFF Research Database (Denmark)

    Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem;

    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...... fundamental cellular processes linked to iron metabolism in order to coordinate the overall response of E. coli to iron availability....

  16. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  17. Dissimilatory Metabolism of Nitrogen Oxides in Bacteria:Comparative Reconstruction of Transcriptional Networks

    Energy Technology Data Exchange (ETDEWEB)

    Rodionov, Dmitry A.; Dubchak, Inna L.; Arkin, Adam P.; Alm, EricJ.; Gelfand, Mikhail S.

    2005-09-01

    Bacterial response to nitric oxide (NO) is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR and NnrR, two-component systems NarXL and NarQP, NO-responsive activator NorR, and nitrite sensitive repressor NsrR. Using comparative genomics approaches we predict DNA-binding signals for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA signal. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria including Clostridia, Thermotogales and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides metabolism not only in most gamma- and beta-proteobacteria (including well-studied species like Escherichia coli), but also in Gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding signal. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon includes also two nitrite-responsive loci, nipAB (hcp-hcr) and nipC(dnrN), thus confirming the identity of the effector, i.e., nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include denitrification genes. As the

  18. Dissimilatory metabolism of nitrogen oxides in bacteria: comparative reconstruction of transcriptional networks.

    Directory of Open Access Journals (Sweden)

    2005-10-01

    Full Text Available Bacterial response to nitric oxide (NO is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR, and NnrR; two-component systems NarXL and NarQP; NO-responsive activator NorR; and nitrite-sensitive repressor NsrR. Using comparative genomics approaches, we predict DNA-binding motifs for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA recognition motif. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria, including Clostridia, Thermotogales, and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides' metabolism, not only in most gamma- and beta-proteobacteria (including well-studied species such as Escherichia coli, but also in Gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding motif. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon also includes two nitrite-responsive loci, nipAB (hcp-hcr and nipC (dnrN, thus confirming the identity of the effector, i.e. nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include

  19. Dissimilatory metabolism of nitrogen oxides in bacteria: comparative reconstruction of transcriptional networks.

    Directory of Open Access Journals (Sweden)

    Dmitry A Rodionov

    2005-10-01

    Full Text Available Bacterial response to nitric oxide (NO is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR, and NnrR; two-component systems NarXL and NarQP; NO-responsive activator NorR; and nitrite-sensitive repressor NsrR. Using comparative genomics approaches, we predict DNA-binding motifs for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA recognition motif. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria, including Clostridia, Thermotogales, and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides' metabolism, not only in most gamma- and beta-proteobacteria (including well-studied species such as Escherichia coli, but also in gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding motif. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon also includes two nitrite-responsive loci, nipAB (hcp-hcr and nipC (dnrN, thus confirming the identity of the effector, i.e. nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include

  20. Diet-induced bacterial immunogens in the gastrointestinal tract of dairy cows: Impacts on immunity and metabolism

    Directory of Open Access Journals (Sweden)

    Zhou Jun

    2011-08-01

    Full Text Available Abstract Dairy cows are often fed high grain diets to meet the energy demand for high milk production or simply due to a lack of forages at times. As a result, ruminal acidosis, especially subacute ruminal acidosis (SARA, occurs frequently in practical dairy production. When SARA occurs, bacterial endotoxin (or lipopolysaccharide, LPS is released in the rumen and the large intestine in a large amount. Many other bacterial immunogens may also be released in the digestive tract following feeding dairy cows diets containing high proportions of grain. LPS can be translocated into the bloodstream across the epithelium of the digestive tract, especially the lower tract, due to possible alterations of permeability and injuries of the epithelial tissue. As a result, the concentration of blood LPS increases. Immune responses are subsequently caused by circulating LPS, and the systemic effects include increases in concentrations of neutrophils and the acute phase proteins such as serum amyloid-A (SAA, haptoglobin (Hp, LPS binding protein (LBP, and C-reactive protein (CRP in blood. Entry of LPS into blood can also result in metabolic alterations. Blood glucose and nonesterified fatty acid concentrations are enhanced accompanying an increase of blood LPS after increasing the amount of grain in the diet, which adversely affects feed intake of dairy cows. As the proportions of grain in the diet increase, patterns of plasma β-hydoxybutyric acid, cholesterol, and minerals (Ca, Fe, and Zn are also perturbed. The bacterial immunogens can also lead to reduced supply of nutrients for synthesis of milk components and depressed functions of the epithelial cells in the mammary gland. The immune responses and metabolic alterations caused by circulating bacterial immunogens will exert an effect on milk production. It has been demonstrated that increases in concentrations of ruminal LPS and plasma acute phase proteins (CRP, SAA, and LBP are associated with declines in

  1. Combining Flux Balance and Energy Balance Analysis for Large-Scale Metabolic Network: Biochemical Circuit Theory for Analysis of Large-Scale Metabolic Networks

    Science.gov (United States)

    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.

  2. Forward selection radial basis function networks applied to bacterial classification based on MALDI-TOF-MS.

    Science.gov (United States)

    Zhang, Zhuoyong; Wang, Dan; Harrington, Peter de B; Voorhees, Kent J; Rees, Jon

    2004-06-17

    Forward selection improved radial basis function (RBF) network was applied to bacterial classification based on the data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The classification of each bacterium cultured at different time was discussed and the effect of parameters of the RBF network was investigated. The new method involves forward selection to prevent overfitting and generalized cross-validation (GCV) was used as model selection criterion (MSC). The original data was compressed by using wavelet transformation to speed up the network training and reduce the number of variables of the original MS data. The data was normalized prior training and testing a network to define the area the neural network to be trained in, accelerate the training rate, and reduce the range the parameters to be selected in. The one-out-of-n method was used to split the data set of p samples into a training set of size p-1 and a test set of size 1. With the improved method, the classification correctness for the five bacteria discussed in the present paper are 87.5, 69.2, 80, 92.3, and 92.8%, respectively.

  3. Consistent abnormalities in metabolic network activity in idiopathic rapid eye movement sleep behaviour disorder

    OpenAIRE

    Wu, Ping; Yu, Huan; Peng, Shichun; Dauvilliers, Yves; Wang, Jian; Ge, Jingjie; Zhang, Huiwei; Eidelberg, David; Ma, Yilong; Zuo, Chuantao

    2014-01-01

    Idiopathic REM sleep behaviour disorder is characterized by dream-enactment behaviour and loss of REM atonia, and is considered a prodromal symptom of Parkinson’s disease. Wu et al. identify an abnormal brain metabolic network associated with the disorder, and show that evolution of this network occurs with progression to Parkinson’s disease.

  4. Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

    Directory of Open Access Journals (Sweden)

    Amanda Mackie

    Full Text Available The EcoCyc database is an online scientific database which provides an integrated view of the metabolic and regulatory network of the bacterium Escherichia coli K-12 and facilitates computational exploration of this important model organism. We have analysed the occurrence of dead end metabolites within the database--these are metabolites which lack the requisite reactions (either metabolic or transport that would account for their production or consumption within the metabolic network. 127 dead end metabolites were identified from the 995 compounds that are contained within the EcoCyc metabolic network. Their presence reflects either a deficit in our representation of the network or in our knowledge of E. coli metabolism. Extensive literature searches resulted in the addition of 38 transport reactions and 3 metabolic reactions to the database and led to an improved representation of the pathway for Vitamin B12 salvage. 39 dead end metabolites were identified as components of reactions that are not physiologically relevant to E. coli K-12--these reactions are properties of purified enzymes in vitro that would not be expected to occur in vivo. Our analysis led to improvements in the software that underpins the database and to the program that finds dead end metabolites within EcoCyc. The remaining dead end metabolites in the EcoCyc database likely represent deficiencies in our knowledge of E. coli metabolism.

  5. FluxExplorer: A general platform for modeling and analyses of metabolic networks based on stoichiometry

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Stoichiometry-based analyses of meta- bolic networks have aroused significant interest of systems biology researchers in recent years. It is necessary to develop a more convenient modeling platform on which users can reconstruct their network models using completely graphical operations, and explore them with powerful analyzing modules to get a better understanding of the properties of metabolic systems. Herein, an in silico platform, FluxExplorer, for metabolic modeling and analyses based on stoichiometry has been developed as a publicly available tool for systems biology research. This platform integrates various analytic approaches, in- cluding flux balance analysis, minimization of meta- bolic adjustment, extreme pathways analysis, shadow prices analysis, and singular value decom- position, providing a thorough characterization of the metabolic system. Using a graphic modeling process, metabolic networks can be reconstructed and modi- fied intuitively and conveniently. The inconsistencies of a model with respect to the FBA principles can be proved automatically. In addition, this platform sup- ports systems biology markup language (SBML). FluxExplorer has been applied to rebuild a metabolic network in mammalian mitochondria, producing meaningful results. Generally, it is a powerful and very convenient tool for metabolic network modeling and analysis.

  6. Characterization of the Usage of the Serine Metabolic Network in Human Cancer

    Directory of Open Access Journals (Sweden)

    Mahya Mehrmohamadi

    2014-11-01

    Full Text Available The serine, glycine, one-carbon (SGOC metabolic network is implicated in cancer pathogenesis, but its general functions are unknown. We carried out a computational reconstruction of the SGOC network and then characterized its expression across thousands of cancer tissues. Pathways including methylation and redox metabolism exhibited heterogeneous expression indicating a strong context dependency of their usage in tumors. From an analysis of coexpression, simultaneous up- or downregulation of nucleotide synthesis, NADPH, and glutathione synthesis was found to be a common occurrence in all cancers. Finally, we developed a method to trace the metabolic fate of serine using stable isotopes, high-resolution mass spectrometry, and a mathematical model. Although the expression of single genes didn’t appear indicative of flux, the collective expression of several genes in a given pathway allowed for successful flux prediction. Altogether, these findings identify expansive and heterogeneous functions for the SGOC metabolic network in human cancer.

  7. Docosahexaenoic Acid, Inflammation, and Bacterial Dysbiosis in Relation to Periodontal Disease, Inflammatory Bowel Disease, and the Metabolic Syndrome

    Directory of Open Access Journals (Sweden)

    Michael F. Roizen

    2013-08-01

    Full Text Available Docosahexaenoic acid (DHA, a long-chain omega-3 polyunsaturated fatty acid, has been used to treat a range of different conditions, including periodontal disease (PD and inflammatory bowel disease (IBD. That DHA helps with these oral and gastrointestinal diseases in which inflammation and bacterial dysbiosis play key roles, raises the question of whether DHA may assist in the prevention or treatment of other inflammatory conditions, such as the metabolic syndrome, which have also been linked with inflammation and alterations in normal host microbial populations. Here we review established and investigated associations between DHA, PD, and IBD. We conclude that by beneficially altering cytokine production and macrophage recruitment, the composition of intestinal microbiota and intestinal integrity, lipopolysaccharide- and adipose-induced inflammation, and insulin signaling, DHA may be a key tool in the prevention of metabolic syndrome.

  8. Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks

    DEFF Research Database (Denmark)

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.;

    2012-01-01

    Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary...... for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although...... linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using...

  9. Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej; Pers, Tune Hannes; Pinho Soares, Simao Pedro;

    2010-01-01

    Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular...... mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets...... with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment...

  10. Soil Parameters Drive the Structure, Diversity and Metabolic Potentials of the Bacterial Communities Across Temperate Beech Forest Soil Sequences.

    Science.gov (United States)

    Jeanbille, M; Buée, M; Bach, C; Cébron, A; Frey-Klett, P; Turpault, M P; Uroz, S

    2016-02-01

    Soil and climatic conditions as well as land cover and land management have been shown to strongly impact the structure and diversity of the soil bacterial communities. Here, we addressed under a same land cover the potential effect of the edaphic parameters on the soil bacterial communities, excluding potential confounding factors as climate. To do this, we characterized two natural soil sequences occurring in the Montiers experimental site. Spatially distant soil samples were collected below Fagus sylvatica tree stands to assess the effect of soil sequences on the edaphic parameters, as well as the structure and diversity of the bacterial communities. Soil analyses revealed that the two soil sequences were characterized by higher pH and calcium and magnesium contents in the lower plots. Metabolic assays based on Biolog Ecoplates highlighted higher intensity and richness in usable carbon substrates in the lower plots than in the middle and upper plots, although no significant differences occurred in the abundance of bacterial and fungal communities along the soil sequences as assessed using quantitative PCR. Pyrosequencing analysis of 16S ribosomal RNA (rRNA) gene amplicons revealed that Proteobacteria, Acidobacteria and Bacteroidetes were the most abundantly represented phyla. Acidobacteria, Proteobacteria and Chlamydiae were significantly enriched in the most acidic and nutrient-poor soils compared to the Bacteroidetes, which were significantly enriched in the soils presenting the higher pH and nutrient contents. Interestingly, aluminium, nitrogen, calcium, nutrient availability and pH appeared to be the best predictors of the bacterial community structures along the soil sequences. PMID:26370112

  11. Soil Parameters Drive the Structure, Diversity and Metabolic Potentials of the Bacterial Communities Across Temperate Beech Forest Soil Sequences.

    Science.gov (United States)

    Jeanbille, M; Buée, M; Bach, C; Cébron, A; Frey-Klett, P; Turpault, M P; Uroz, S

    2016-02-01

    Soil and climatic conditions as well as land cover and land management have been shown to strongly impact the structure and diversity of the soil bacterial communities. Here, we addressed under a same land cover the potential effect of the edaphic parameters on the soil bacterial communities, excluding potential confounding factors as climate. To do this, we characterized two natural soil sequences occurring in the Montiers experimental site. Spatially distant soil samples were collected below Fagus sylvatica tree stands to assess the effect of soil sequences on the edaphic parameters, as well as the structure and diversity of the bacterial communities. Soil analyses revealed that the two soil sequences were characterized by higher pH and calcium and magnesium contents in the lower plots. Metabolic assays based on Biolog Ecoplates highlighted higher intensity and richness in usable carbon substrates in the lower plots than in the middle and upper plots, although no significant differences occurred in the abundance of bacterial and fungal communities along the soil sequences as assessed using quantitative PCR. Pyrosequencing analysis of 16S ribosomal RNA (rRNA) gene amplicons revealed that Proteobacteria, Acidobacteria and Bacteroidetes were the most abundantly represented phyla. Acidobacteria, Proteobacteria and Chlamydiae were significantly enriched in the most acidic and nutrient-poor soils compared to the Bacteroidetes, which were significantly enriched in the soils presenting the higher pH and nutrient contents. Interestingly, aluminium, nitrogen, calcium, nutrient availability and pH appeared to be the best predictors of the bacterial community structures along the soil sequences.

  12. Efficient Reconstruction of Predictive Consensus Metabolic Network Models

    Science.gov (United States)

    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

  13. Efficient Reconstruction of Predictive Consensus Metabolic Network Models.

    Science.gov (United States)

    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

  14. Dynamic Metabolic Footprinting Reveals the Key Components of Metabolic Network in Yeast Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Chumnanpuen, Pramote; Hansen, Michael Adsetts Edberg; Smedsgaard, Jørn;

    2014-01-01

    Metabolic footprinting offers a relatively easy approach to exploit the potentials of metabolomics for phenotypic characterization of microbial cells. To capture the highly dynamic nature of metabolites, we propose the use of dynamic metabolic footprinting instead of the traditional method which...

  15. Dynamics of bacterial communities before and after distribution in a full-scale drinking water network

    KAUST Repository

    El-Chakhtoura, Joline

    2015-05-01

    Understanding the biological stability of drinking water distribution systems is imperative in the framework of process control and risk management. The objective of this research was to examine the dynamics of the bacterial community during drinking water distribution at high temporal resolution. Water samples (156 in total) were collected over short time-scales (minutes/hours/days) from the outlet of a treatment plant and a location in its corresponding distribution network. The drinking water is treated by biofiltration and disinfectant residuals are absent during distribution. The community was analyzed by 16S rRNA gene pyrosequencing and flow cytometry as well as conventional, culture-based methods. Despite a random dramatic event (detected with pyrosequencing and flow cytometry but not with plate counts), the bacterial community profile at the two locations did not vary significantly over time. A diverse core microbiome was shared between the two locations (58-65% of the taxa and 86-91% of the sequences) and found to be dependent on the treatment strategy. The bacterial community structure changed during distribution, with greater richness detected in the network and phyla such as Acidobacteria and Gemmatimonadetes becoming abundant. The rare taxa displayed the highest dynamicity, causing the major change during water distribution. This change did not have hygienic implications and is contingent on the sensitivity of the applied methods. The concept of biological stability therefore needs to be revised. Biostability is generally desired in drinking water guidelines but may be difficult to achieve in large-scale complex distribution systems that are inherently dynamic.

  16. Metabolic and molecular characterization of bacterial community associated to Patagonian Chilean oligotrophic-lakes of quaternary glacial origin.

    Science.gov (United States)

    Leon, Carla; Campos, Víctor; Urrutia, Roberto; Mondaca, María-Angélica

    2012-04-01

    The Patagonian Lakes have particular environmental conditions with or without intermittent disturbances. The study of the microorganisms present in aquatic ecosystems has increased notably because they can be used as micro-scale bioindicators of, among others, anthropogenic pollution and climatic change. The aim of the work was to compare the composition of the bacterial communities associated with sediments of three Patagonian Lakes with different geomorphologic patterns and disturbances. The lake sediments were characterized by molecular techniques, physiology profiles and physico-chemical analyses. The metabolic and physiological profiles of the microbial community demonstrated that non-impacted Tranquilo Lake is statistically different to impacted Bertrand and Plomo Lakes. Similar results were detected by DGGE profiles. FISH results demonstrated that betaproteobacteria showed the highest count in the Tranquilo Lake while gammaproteobacteria showed the highest counts in the Bertrand and Plomo Lakes, indicating that their sediments are highly dystrophic. The results demonstrate differences in the metabolic activity and structural and functional composition of bacterial communities of the studied lakes, which have different geomorphological patterns due to disturbances such as volcanic activity and the climatic change.

  17. An experimental study of Au removal from solution by non-metabolizing bacterial cells and their exudates

    Science.gov (United States)

    Kenney, Janice P. L.; Song, Zhen; Bunker, Bruce A.; Fein, Jeremy B.

    2012-06-01

    In this study, we examine the initial interactions between aqueous Au(III)-hydroxide-chloride aqueous complexes and bacteria by measuring the effects of non-metabolizing cells on the speciation and distribution of Au. We conducted batch Au(III) removal experiments, measuring the kinetics and pH dependence of Au removal, and tracking valence state transformations and binding environments using XANES spectroscopy. These experiments were conducted using non-metabolizing cells of Bacillus subtilis or Pseudomonas putida suspended in a 5 ppm Au(III)-(hydroxide)-chloride starting solution of 0.1 M NaClO4 to buffer ionic strength. Both bacterial species removed greater than 85% of the Au from solution after 2 h of exposure time below approximately pH 5. Above pH 5, the extent of Au removed from solution decreased with increasing pH, with less than approximately 10% removal of Au from solution above pH 7.5. Kinetics experiments indicated that the Au removal with both bacterial species was rapid at pH 3, and slowed with increasing pH. Reversibility experiments demonstrated that (1) once the Au was removed from solution, adjusting 35 the pH alone did not remobilize the Au into solution and (2) the presence of cysteine in solution in the reversibility experiments caused Au to desorb, suggesting that the Au was not internalized within the bacterial cells. Our results suggest that Au removal occurs as a two-step pH-dependent adsorption reduction process. The speciation of the aqueous Au and the bacterial surface appears to control the rate of Au removal from solution. Under low pH conditions, the cell walls are only weakly negatively charged and aqueous Au complexes adsorb readily and rapidly. With increasing pH, the cell wall becomes more negatively charged, slowing adsorption significantly. The XANES data demonstrate that the reduction of Au(III) by bacterial exudates is slower and less extensive than the reduction observed in the bacteria-bearing systems, and we conclude that

  18. Effect of Condensed Tannins on Bacterial Diversity and Metabolic Activity in the Rat Gastrointestinal Tract

    OpenAIRE

    Smith, Alexandra H.; Mackie, Roderick I.

    2004-01-01

    The effect of dietary condensed tannins (proanthocyanidins) on rat fecal bacterial populations was ascertained in order to determine whether the proportion on tannin-resistant bacteria increased and if there was a change in the predominant bacterial populations. After 3 weeks of tannin diets the proportion of tannin-resistant bacteria increased significantly (P < 0.05) from 0.3% ± 5.5% to 25.3% ± 8.3% with a 0.7% tannin diet and to 47.2% ± 5.1% with a 2% tannin diet. The proportion of tannin-...

  19. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    Science.gov (United States)

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-07-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states.

  20. Effect of metabolic transformation of monoterpenes on antimutagenic potential in bacterial tests

    OpenAIRE

    Stajković-Srbinović Olivera; Vuković-Gačić Branka; Knežević-Vukčević Jelena; Nikolić Biljana; Mitić-Ćulafić Dragana

    2012-01-01

    The effect of metabolic transformation of the monoterpenes Linalool (Lin), Myrcene (Myr) and Eucalyptol (Euc) was evaluated on their antimutagenic potential against t-butyl hydroperoxide (t-BOOH) and 2-nitropropane (2NP) in E. coli WP2 and in S. typhimurium reversion assays, respectively. Spontaneous mutagenesis was also monitored in both assays. Mammalian metabolic transformation was provided by rat liver microsomes (S9 fraction). None of the monoterpenes was mutagenic, either with or ...

  1. Comparative analysis of Salmonella genomes identifies a metabolic network for escalating growth in the inflamed gut.

    Science.gov (United States)

    Nuccio, Sean-Paul; Bäumler, Andreas J

    2014-03-18

    The Salmonella genus comprises a group of pathogens associated with illnesses ranging from gastroenteritis to typhoid fever. We performed an in silico analysis of comparatively reannotated Salmonella genomes to identify genomic signatures indicative of disease potential. By removing numerous annotation inconsistencies and inaccuracies, the process of reannotation identified a network of 469 genes involved in central anaerobic metabolism, which was intact in genomes of gastrointestinal pathogens but degrading in genomes of extraintestinal pathogens. This large network contained pathways that enable gastrointestinal pathogens to utilize inflammation-derived nutrients as well as many of the biochemical reactions used for the enrichment and biochemical discrimination of Salmonella serovars. Thus, comparative genome analysis identifies a metabolic network that provides clues about the strategies for nutrient acquisition and utilization that are characteristic of gastrointestinal pathogens. IMPORTANCE While some Salmonella serovars cause infections that remain localized to the gut, others disseminate throughout the body. Here, we compared Salmonella genomes to identify characteristics that distinguish gastrointestinal from extraintestinal pathogens. We identified a large metabolic network that is functional in gastrointestinal pathogens but decaying in extraintestinal pathogens. While taxonomists have used traits from this network empirically for many decades for the enrichment and biochemical discrimination of Salmonella serovars, our findings suggest that it is part of a "business plan" for growth in the inflamed gastrointestinal tract. By identifying a large metabolic network characteristic of Salmonella serovars associated with gastroenteritis, our in silico analysis provides a blueprint for potential strategies to utilize inflammation-derived nutrients and edge out competing gut microbes.

  2. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

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

    Science.gov (United States)

    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

  4. Resource niche overlap promotes stability of bacterial community metabolism in experimental microcosms

    NARCIS (Netherlands)

    E.R. Hunting; M.G. Vijver; H.G. van der Geest; C. Mulder; M.H.S. Kraak; A.M. Breure; W. Admiraal

    2015-01-01

    Decomposition of organic matter is an important ecosystem process governed in part by bacteria. The process of decomposition is expected to benefit from interspecific bacterial interactions such as resource partitioning and facilitation. However, the relative importance of resource niche breadth (me

  5. Effect of CO2 enrichment on bacterial metabolism in an Arctic fjord

    NARCIS (Netherlands)

    C. Motegi; T. Tanaka; J. Piontek; C.P.D. Brussaard; J.P. Gattuso; M.G. Weinbauer

    2013-01-01

    The anthropogenic increase of carbon dioxide (CO2) alters the seawater carbonate chemistry, with a decline of pH and an increase in the partial pressure of CO2 (pCO2). Although bacteria play a major role in carbon cycling, little is known about the impact of rising pCO2 on bacterial carbon metabolis

  6. Metabolic network rewiring of propionate flux compensates vitamin B12 deficiency in C. elegans.

    Science.gov (United States)

    Watson, Emma; Olin-Sandoval, Viridiana; Hoy, Michael J; Li, Chi-Hua; Louisse, Timo; Yao, Victoria; Mori, Akihiro; Holdorf, Amy D; Troyanskaya, Olga G; Ralser, Markus; Walhout, Albertha Jm

    2016-01-01

    Metabolic network rewiring is the rerouting of metabolism through the use of alternate enzymes to adjust pathway flux and accomplish specific anabolic or catabolic objectives. Here, we report the first characterization of two parallel pathways for the breakdown of the short chain fatty acid propionate in Caenorhabditis elegans. Using genetic interaction mapping, gene co-expression analysis, pathway intermediate quantification and carbon tracing, we uncover a vitamin B12-independent propionate breakdown shunt that is transcriptionally activated on vitamin B12 deficient diets, or under genetic conditions mimicking the human diseases propionic- and methylmalonic acidemia, in which the canonical B12-dependent propionate breakdown pathway is blocked. Our study presents the first example of transcriptional vitamin-directed metabolic network rewiring to promote survival under vitamin deficiency. The ability to reroute propionate breakdown according to B12 availability may provide C. elegans with metabolic plasticity and thus a selective advantage on different diets in the wild. PMID:27383050

  7. Understanding the control of acyl flux through the lipid metabolic network of plant oil biosynthesis.

    Science.gov (United States)

    Bates, Philip D

    2016-09-01

    Plant oil biosynthesis involves a complex metabolic network with multiple subcellular compartments, parallel pathways, cycles, and pathways that have a dual function to produce essential membrane lipids and triacylglycerol. Modern molecular biology techniques provide tools to alter plant oil compositions through bioengineering, however with few exceptions the final composition of triacylglycerol cannot be predicted. One reason for limited success in oilseed bioengineering is the inadequate understanding of how to control the flux of fatty acids through various fatty acid modification, and triacylglycerol assembly pathways of the lipid metabolic network. This review focuses on the mechanisms of acyl flux through the lipid metabolic network, and highlights where uncertainty resides in our understanding of seed oil biosynthesis. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner. PMID:27003249

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

    DEFF Research Database (Denmark)

    Fenger, Mogens; Linneberg, Allan; Jeppesen, Jørgen

    2015-01-01

    -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...

  9. Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

    Directory of Open Access Journals (Sweden)

    Mahadevan Radhakrishnan

    2010-05-01

    Full Text Available Abstract Background Geobacter sulfurreducens is a member of the Geobacter species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for Geobacter sulfurreducens. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of G. sulfurreducens using thermodynamic variability analysis. Findings As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in E. coli by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of G. sulfurreducens that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility is significant for these reactions. Conclusions Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of ΔrG' of every reaction in the model

  10. Reconstruction of a genome-scale metabolic network for Streptococcus pneumoniae R6

    OpenAIRE

    J.P. Saraiva; Pinto, Francisco; Rocha, I

    2013-01-01

    The gram-positive, lancet-shaped bacteria Streptococcus pneumoniae thrives in almost any environment. Under certain conditions this pathogen can cause several infections such as meningitis, otitis media, endocarditis or pneumonia. Genome-scale metabolic networks (GSMs) are commonly used to study phenotype-genotype relationships using biochemical, physiological and genomic information. These relationships might shed some light on identification of targets for metabolic engineering or, in t...

  11. Resource constrained flux balance analysis predicts selective pressure on the global structure of metabolic networks

    OpenAIRE

    Abedpour, Nima; Kollmann, Markus

    2015-01-01

    Background A universal feature of metabolic networks is their hourglass or bow-tie structure on cellular level. This architecture reflects the conversion of multiple input nutrients into multiple biomass components via a small set of precursor metabolites. However, it is yet unclear to what extent this structural feature is the result of natural selection. Results We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networ...

  12. The many forms of a pleomorphic bacterial pathogen—the developmental network of Legionella pneumophila

    Science.gov (United States)

    Robertson, Peter; Abdelhady, Hany; Garduño, Rafael A.

    2014-01-01

    Legionella pneumophila is a natural intracellular bacterial parasite of free-living freshwater protozoa and an accidental human pathogen that causes Legionnaires' disease. L. pneumophila differentiates, and does it in style. Recent experimental data on L. pneumophila's differentiation point at the existence of a complex network that involves many developmental forms. We intend readers to: (i) understand the biological relevance of L. pneumophila's forms found in freshwater and their potential to transmit Legionnaires' disease, and (ii) learn that the common depiction of L. pneumophila's differentiation as a biphasic developmental cycle that alternates between a replicative and a transmissive form is but an oversimplification of the actual process. Our specific objectives are to provide updates on the molecular factors that regulate L. pneumophila's differentiation (Section The Differentiation Process and Its Regulation), and describe the developmental network of L. pneumophila (Section Dissecting Lp's Developmental Network), which for clarity's sake we have dissected into five separate developmental cycles. Finally, since each developmental form seems to contribute differently to the human pathogenic process and the transmission of Legionnaires' disease, readers are presented with a challenge to develop novel methods to detect the various L. pneumophila forms present in water (Section Practical Implications), as a means to improve our assessment of risk and more effectively prevent legionellosis outbreaks. PMID:25566200

  13. Development and analysis of an in vivo-compatible metabolic network of Mycobacterium tuberculosis

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2010-11-01

    Full Text Available Abstract Background During infection, Mycobacterium tuberculosis confronts a generally hostile and nutrient-poor in vivo host environment. Existing models and analyses of M. tuberculosis metabolic networks are able to reproduce experimentally measured cellular growth rates and identify genes required for growth in a range of different in vitro media. However, these models, under in vitro conditions, do not provide an adequate description of the metabolic processes required by the pathogen to infect and persist in a host. Results To better account for the metabolic activity of M. tuberculosis in the host environment, we developed a set of procedures to systematically modify an existing in vitro metabolic network by enhancing the agreement between calculated and in vivo-measured gene essentiality data. After our modifications, the new in vivo network contained 663 genes, 838 metabolites, and 1,049 reactions and had a significantly increased sensitivity (0.81 in predicted gene essentiality than the in vitro network (0.31. We verified the modifications generated from the purely computational analysis through a review of the literature and found, for example, that, as the analysis suggested, lipids are used as the main source for carbon metabolism and oxygen must be available for the pathogen under in vivo conditions. Moreover, we used the developed in vivo network to predict the effects of double-gene deletions on M. tuberculosis growth in the host environment, explore metabolic adaptations to life in an acidic environment, highlight the importance of different enzymes in the tricarboxylic acid-cycle under different limiting nutrient conditions, investigate the effects of inhibiting multiple reactions, and look at the importance of both aerobic and anaerobic cellular respiration during infection. Conclusions The network modifications we implemented suggest a distinctive set of metabolic conditions and requirements faced by M. tuberculosis during

  14. Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

    Science.gov (United States)

    Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

    2016-04-01

    The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu. PMID:27081850

  15. Towards stable kinetics of large metabolic networks: Nonequilibrium potential function approach

    Science.gov (United States)

    Chen, Yong-Cong; Yuan, Ruo-Shi; Ao, Ping; Xu, Min-Juan; Zhu, Xiao-Mei

    2016-06-01

    While the biochemistry of metabolism in many organisms is well studied, details of the metabolic dynamics are not fully explored yet. Acquiring adequate in vivo kinetic parameters experimentally has always been an obstacle. Unless the parameters of a vast number of enzyme-catalyzed reactions happened to fall into very special ranges, a kinetic model for a large metabolic network would fail to reach a steady state. In this work we show that a stable metabolic network can be systematically established via a biologically motivated regulatory process. The regulation is constructed in terms of a potential landscape description of stochastic and nongradient systems. The constructed process draws enzymatic parameters towards stable metabolism by reducing the change in the Lyapunov function tied to the stochastic fluctuations. Biologically it can be viewed as interplay between the flux balance and the spread of workloads on the network. Our approach allows further constraints such as thermodynamics and optimal efficiency. We choose the central metabolism of Methylobacterium extorquens AM1 as a case study to demonstrate the effectiveness of the approach. Growth efficiency on carbon conversion rate versus cell viability and futile cycles is investigated in depth.

  16. Colonic transit time relates to bacterial metabolism and mucosal turnover in the human gut

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Hansen, Lea Benedicte Skov; Bahl, Martin Iain;

    Little is known about how colonic transit time relates to human colonic metabolism, and its importance for host health, although stool consistency, a proxy for colonic transit time, has recently been negatively associated with gut microbial richness. To address the relationships between colonic...... transit time and the gut microbial composition and metabolism, we assessed the colonic transit time of 98 subjects using radiopaque markers, and profiled their gut microbiota by16S rRNA gene sequencingand their urine metabolome by ultra performance liquid chromatography mass spectrometry. Based...... on correlation analyses,we show that colonic transit time is associated with overall gutmicrobial composition, diversity and metabolism. A relatively prolonged colonic transit time associates with high microbial species richness and a shift in colonic metabolismfrom carbohydrate fermentation to protein...

  17. Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Hansen, Lea Benedicte Skov; Bahl, Martin Iain;

    2016-01-01

    Little is known about how colonic transit time relates to human colonic metabolism and its importance for host health, although a firm stool consistency, a proxy for a long colonic transit time, has recently been positively associated with gut microbial richness. Here, we show that colonic transit...... time in humans, assessed using radio-opaque markers, is associated with overall gut microbial composition, diversity and metabolism. We find that a long colonic transit time associates with high microbial richness and is accompanied by a shift in colonic metabolism from carbohydrate fermentation...... to protein catabolism as reflected by higher urinary levels of potentially deleterious protein-derived metabolites. Additionally, shorter colonic transit time correlates with metabolites possibly reflecting increased renewal of the colonic mucosa. Together, this suggests that a high gut microbial richness...

  18. Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Palsson, Bernhard; Feist, Adam

    2013-01-01

    The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction...... include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy....

  19. An Evidence-Based Review of Related Metabolites and Metabolic Network Research on Cerebral Ischemia

    Science.gov (United States)

    Liu, Mengting; Tang, Liying; Liu, Xin; Fang, Jing; Zhan, Hao; Wu, Hongwei; Yang, Hongjun

    2016-01-01

    In recent years, metabolomics analyses have been widely applied to cerebral ischemia research. This paper introduces the latest proceedings of metabolomics research on cerebral ischemia. The main techniques, models, animals, and biomarkers of cerebral ischemia will be discussed. With analysis help from the MBRole website and the KEGG database, the altered metabolites in rat cerebral ischemia were used for metabolic pathway enrichment analyses. Our results identify the main metabolic pathways that are related to cerebral ischemia and further construct a metabolic network. These results will provide useful information for elucidating the pathogenesis of cerebral ischemia, as well as the discovery of cerebral ischemia biomarkers. PMID:27274780

  20. Involvement of a Bacterial Microcompartment in the Metabolism of Fucose and Rhamnose by Clostridium phytofermentans

    OpenAIRE

    Elsa Petit; W Greg LaTouf; Coppi, Maddalena V.; Warnick, Thomas A.; Devin Currie; Igor Romashko; Supriya Deshpande; Kelly Haas; Alvelo-Maurosa, Jesús G.; Colin Wardman; Schnell, Danny J.; Leschine, Susan B.; Blanchard, Jeffrey L.

    2013-01-01

    BACKGROUND: Clostridium phytofermentans, an anaerobic soil bacterium, can directly convert plant biomass into biofuels. The genome of C. phytofermentans contains three loci with genes encoding shell proteins of bacterial microcompartments (BMC), organelles composed entirely of proteins. METHODOLOGY AND PRINCIPAL FINDINGS: One of the BMC loci has homology to a BMC-encoding locus implicated in the conversion of fucose to propanol and propionate in a human gut commensal, Roseburia inulinivorans....

  1. Heterotrophic bacterial production and metabolic balance during the VAHINE mesocosm experiment in the New Caledonia lagoon

    Science.gov (United States)

    Van Wambeke, F.; Pfreundt, U.; Barani, A.; Berthelot, H.; Moutin, T.; Rodier, M.; Hess, W. R.; Bonnet, S.

    2015-12-01

    N2 fixation fuels ~ 50 % of new primary production in the oligotrophic South Pacific Ocean. The VAHINE mesocosm experiment designed to track the fate of diazotroph derived nitrogen (DDN) in the New Caledonia lagoon. Here, we examined the temporal dynamics of heterotrophic bacterial production during this experiment. Three replicate large-volume (~ 50 m3) mesocosms were deployed and were intentionally fertilized with dissolved inorganic phosphorus (DIP) to stimulate N2 fixation. We specifically examined relationships between N2 fixation rates and primary production, determined bacterial growth efficiency and established carbon budgets of the system from the DIP fertilization to the end of the experiment (days 5-23). Heterotrophic bacterioplankton production (BP) and alkaline phosphatase activity (APA) were statistically higher during the second phase of the experiment (P2: days 15-23), when chlorophyll biomass started to increase compared to the first phase (P1: days 5-14). Among autotrophs, Synechococcus abundances increased during P2, possibly related to its capacity to assimilate leucine and to produce alkaline phosphatase. Bacterial growth efficiency based on the carbon budget was notably higher than generally cited for oligotrophic environments (27-43 %), possibly due to a high representation of proteorhodopsin-containing organisms within the picoplanctonic community. The carbon budget showed that the main fate of gross primary production (particulate + dissolved) was respiration (67 %), and export through sedimentation (17 %). BP was highly correlated with particulate primary production and chlorophyll biomass during both phases of the experiment but slightly correlated, and only during P2 phase, with N2 fixation rates. Our results suggest that most of the DDN reached the heterotrophic bacterial community through indirect processes, like mortality, lysis and grazing.

  2. Organization of enzyme concentration across the metabolic network in cancer cells.

    Directory of Open Access Journals (Sweden)

    Neel S Madhukar

    Full Text Available Rapid advances in mass spectrometry have allowed for estimates of absolute concentrations across entire proteomes, permitting the interrogation of many important biological questions. Here, we focus on a quantitative aspect of human cancer cell metabolism that has been limited by a paucity of available data on the abundance of metabolic enzymes. We integrate data from recent measurements of absolute protein concentration to analyze the statistics of protein abundance across the human metabolic network. At a global level, we find that the enzymes in glycolysis comprise approximately half of the total amount of metabolic proteins and can constitute up to 10% of the entire proteome. We then use this analysis to investigate several outstanding problems in cancer metabolism, including the diversion of glycolytic flux for biosynthesis, the relative contribution of nitrogen assimilating pathways, and the origin of cellular redox potential. We find many consistencies with current models, identify several inconsistencies, and find generalities that extend beyond current understanding. Together our results demonstrate that a relatively simple analysis of the abundance of metabolic enzymes was able to reveal many insights into the organization of the human cancer cell metabolic network.

  3. Towards Kinetic Modeling of Global Metabolic Networks Methylobacterium extorquens AM1 Growth as Validation

    Institute of Scientific and Technical Information of China (English)

    Ping Ao; Lik Wee Lee; Mary E. Lidstrom; Lan Yin; Xiaomei Zhu

    2008-01-01

    Here we report a systematic method for constructing a large scale kinetic metabolic model and its initial application to the modeling of central metabolism of Methylobacterium extorquens AM1, a methylotrophic and environmental important bacterium. Its central metabolic network includes formaldehyde metabolism, serine cycle, citric acid cycle, pentose phosphate pathway, ghiconeogensis, PHB synthesis and acetyl-CoA conversion pathway, respiration and energy metabolism. Through a systematic and consistent procedure of finding a set of parameters in the physiological range we overcome an outstanding difficulty in large scale kinetic modeling: the requirement for a massive number of enzymatic reaction parameters. We are able to construct the kinetic model based on general biological considerations and incomplete experimental kinetic parameters. Our method consists of the following major steps: 1) using a generic enzymatic rate equation to reduce the number of enzymatic parameters to a minimum set while still preserving their characteristics; 2) using a set of steady state fluxes and metabolite concenwations in the physiological range as the expected output steady state fluxes and metabolite concentrations for the kinetic model to restrict the parametric space of enzymatic reactions; 3) choosing enzyme constants K's and K'eqs optimized for reactions under physiological concentrations, if their experimental values are unknown; 4) for models which do not cover the entire metabolic network of the organisms, designing a dynamical exchange for the coupling between the metabolism represented in the model and the rest not included.

  4. Heterotrophic bacterial production and metabolic balance during the VAHINE mesocosm experiment in the New Caledonia lagoon

    Science.gov (United States)

    Van Wambeke, France; Pfreundt, Ulrike; Barani, Aude; Berthelot, Hugo; Moutin, Thierry; Rodier, Martine; Hess, Wolfgang R.; Bonnet, Sophie

    2016-06-01

    Studies investigating the fate of diazotrophs through the microbial food web are lacking, although N2 fixation can fuel up to 50 % of new production in some oligotrophic oceans. In particular, the role played by heterotrophic prokaryotes in this transfer is largely unknown. In the frame of the VAHINE (VAriability of vertical and tropHIc transfer of diazotroph derived N in the south wEst Pacific) experiment, three replicate large-volume (˜ 50 m3) mesocosms were deployed for 23 days in the new Caledonia lagoon and were intentionally fertilized on day 4 with dissolved inorganic phosphorus (DIP) to stimulate N2 fixation. We specifically examined relationships between heterotrophic bacterial production (BP) and N2 fixation or primary production, determined bacterial growth efficiency and established carbon budgets. BP was statistically higher during the second phase of the experiment (P2: days 15-23), when chlorophyll biomass started to increase compared to the first phase (P1: days 5-14). Phosphatase alkaline activity increased drastically during the second phase of the experiment, showing adaptations of microbial populations after utilization of the added DIP. Notably, among autotrophs, Synechococcus abundances increased during P2, possibly related to its capacity to assimilate leucine and to produce alkaline phosphatase. Bacterial growth efficiency based on the carbon budget (27-43 %), was notably higher than generally cited for oligotrophic environments and discussed in links with the presence of abundant species of bacteria expressing proteorhodopsin. The main fates of gross primary production (particulate + dissolved) were respiration (67 %) and export through sedimentation (17 %). BP was highly correlated with particulate primary production and chlorophyll biomass during both phases of the experiment but was slightly correlated, and only during P2 phase, with N2 fixation rates. Heterotrophic bacterial production was strongly stimulated after mineral N enrichment

  5. Genetic and metabolic signals during acute enteric bacterial infection alter the microbiota and drive progression to chronic inflammatory disease

    Energy Technology Data Exchange (ETDEWEB)

    Kamdar, Karishma; Khakpour, Samira; Chen, Jingyu; Leone, Vanessa; Brulc, Jennifer; Mangatu, Thomas; Antonopoulos, Dionysios A.; Chang, Eugene B; Kahn, Stacy A.; Kirschner, Barbara S; Young, Glenn; DePaolo, R. William

    2016-01-13

    Chronic inflammatory disorders are thought to arise due to an interplay between predisposing host genetics and environmental factors. For example, the onset of inflammatory bowel disease is associated with enteric proteobacterial infection, yet the mechanistic basis for this association is unclear. We have shown previously that genetic defiency in TLR1 promotes acute enteric infection by the proteobacteria Yersinia enterocolitica. Examining that model further, we uncovered an altered cellular immune response that promotes the recruitment of neutrophils which in turn increases metabolism of the respiratory electron acceptor tetrathionate by Yersinia. These events drive permanent alterations in anti-commensal immunity, microbiota composition, and chronic inflammation, which persist long after Yersinia clearence. Deletion of the bacterial genes involved in tetrathionate respiration or treatment using targeted probiotics could prevent microbiota alterations and inflammation. Thus, acute infection can drive long term immune and microbiota alterations leading to chronic inflammatory disease in genetically predisposed individuals.

  6. Topological Properties of Protein-Protein and Metabolic Interaction Networks of Drosophila melanogaster

    Institute of Scientific and Technical Information of China (English)

    Thanigaimani Rajarathinam; Yen-Han Lin

    2006-01-01

    The underlying principle governing the natural phenomena of life is one of the critical issues receiving due importance in recent years. A key feature of the scale-free architecture is the vitality of the most connected nodes (hubs). The major objective of this article was to analyze the protein-protein and metabolic interaction networks of Drosophila melanogaster by considering the architectural patterns and the consequence of removal of hubs on the topological parameter of the two interaction systems. Analysis showed that both interaction networks follow a scale-free model, establishing the fact that most real world networks,from varied situations, conform to the small world pattern. The average path length showed a two-fold and a three-fold increase (changing from 9.42 to 20.93 and from 5.29 to 17.75, respectively) for the protein-protein and metabolic interaction networks, respectively, due to the deletion of hubs. On the contrary, the arbitrary elimination of nodes did not show any remarkable disparity in the topological parameter of the protein-protein and metabolic interaction networks (average path length: 9.42±0.02 and 5.27±0.01, respectively). This aberrant behavior for the two cases underscores the significance of the most linked nodes to the natural topology of the networks.

  7. Environmental factors shaping cultured free-living amoebae and their associated bacterial community within drinking water network.

    Science.gov (United States)

    Delafont, Vincent; Bouchon, Didier; Héchard, Yann; Moulin, Laurent

    2016-09-01

    Free-living amoebae (FLA) constitute an important part of eukaryotic populations colonising drinking water networks. However, little is known about the factors influencing their ecology in such environments. Because of their status as reservoir of potentially pathogenic bacteria, understanding environmental factors impacting FLA populations and their associated bacterial community is crucial. Through sampling of a large drinking water network, the diversity of cultivable FLA and their bacterial community were investigated by an amplicon sequencing approach, and their correlation with physicochemical parameters was studied. While FLA ubiquitously colonised the water network all year long, significant changes in population composition were observed. These changes were partially explained by several environmental parameters, namely water origin, temperature, pH and chlorine concentration. The characterisation of FLA associated bacterial community reflected a diverse but rather stable consortium composed of nearly 1400 OTUs. The definition of a core community highlighted the predominance of only few genera, majorly dominated by Pseudomonas and Stenotrophomonas. Co-occurrence analysis also showed significant patterns of FLA-bacteria association, and allowed uncovering potentially new FLA - bacteria interactions. From our knowledge, this study is the first that combines a large sampling scheme with high-throughput identification of FLA together with associated bacteria, along with their influencing environmental parameters. Our results demonstrate the importance of physicochemical parameters in the ecology of FLA and their bacterial community in water networks.

  8. Identification and characterization of metabolic properties of bacterial populations recovered from arsenic contaminated ground water of North East India (Assam).

    Science.gov (United States)

    Ghosh, Soma; Sar, Pinaki

    2013-12-01

    Diversity of culturable bacterial populations within the Arsenic (As) contaminated groundwater of North Eastern state (Assam) of India is studied. From nine As contaminated samples 89 bacterial strains are isolated. 16S rRNA gene sequence analysis reveals predominance of Brevundimonas (35%) and Acidovorax (23%) along with Acinetobacter (10%), Pseudomonas (9%) and relatively less abundant (<5%) Undibacterium, Herbaspirillum, Rhodococcus, Staphylococcus, Bosea, Bacillus, Ralstonia, Caulobacter and Rhizobiales members. High As(III) resistance (MTC 10-50 mM) is observed for the isolates obtained from As(III) enrichment, particularly for 3 isolates of genus Brevundimonas (MTC 50 mM). In contrast, high resistance to As(V) (MTC as high as 550 mM) is present as a ubiquitous property, irrespective of isolates' enrichment condition. Bacterial genera affiliated to other groups showed relatively lower degree of As resistance [MTCs of 15-20 mM As(III) and 250-350 mM As(V)]. As(V) reductase activity is detected in strains with high As(V) as well as As(III) resistance. A strong correlation could be established among isolates capable of reductase activity and siderophore production as well as As(III) tolerance. A large number of isolates (nearly 50%) is capable of anaerobic respiration using alternate inorganic electron acceptors [As(V), Se(VI), Fe(III), [NO(3)(2), SO(4)(2), S(2)O(3)(2). Ability to utilize different carbon sources ranging from C2-C6 compounds along with some complex sugars is also observed. Particularly, a number of strains is found to possess ability to grow chemolithotrophically using As(III) as the electron donor. The study reports for the first time the identity and metabolic abilities of bacteria in As contaminated ground water of North East India, useful to elucidate the microbial role in influencing mobilization of As in the region. PMID:24210546

  9. Samuel Ruben's Contributions to Research on Photosynthesis and Bacterial Metabolism with Radioactive Carbon.

    Science.gov (United States)

    Gest, Howard

    2004-01-01

    The earliest experiments on the pathways of carbon in photosynthetic and heterotrophic metabolism using radioactive carbon, (11)C, as a tracer were performed by Samuel (Sam) Ruben, Martin Kamen, and their colleagues. The short half-life of (11)C (20 min), however, posed severe limitations on identification of metabolic intermediates, and this was a major stimulus to search for a radioactive carbon isotope of longer half-life. (14)C was discovered by Ruben and Kamen in 1940, but circumstances prevented continuation of their research using the long-lived isotope. Because of the untimely accidental death of Ruben in 1943, there are very few published accounts on the life and work of this extraordinary scientist. This paper summarizes highlights of Ruben's outstanding accomplishments. PMID:16328812

  10. Glucose Metabolic Brain Networks in Early-Onset vs. Late-Onset Alzheimer's Disease

    Science.gov (United States)

    Chung, Jinyong; Yoo, Kwangsun; Kim, Eunjoo; Na, Duk L.; Jeong, Yong

    2016-01-01

    Objective: Early-onset Alzheimer's disease (EAD) shows distinct features from late-onset Alzheimer's disease (LAD). To explore the characteristics of EAD, clinical, neuropsychological, and functional imaging studies have been conducted. However, differences between EAD and LAD are not clear, especially in terms of brain connectivity and networks. In this study, we investigated the differences in metabolic connectivity between EAD and LAD by adopting graph theory measures. Methods: We analyzed 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) images to investigate the distinct features of metabolic connectivity between EAD and LAD. Using metabolic connectivity and graph theory analysis, metabolic network differences between LAD and EAD were explored. Results: Results showed the decreased connectivity centered in the cingulate gyri and occipital regions in EAD, whereas decreased connectivity in the occipital and temporal regions as well as increased connectivity in the supplementary motor area were observed in LAD when compared with age-matched control groups. Global efficiency and clustering coefficients were decreased in EAD but not in LAD. EAD showed progressive network deterioration as a function of disease severity and clinical dementia rating (CDR) scores, mainly in terms of connectivity between the cingulate gyri and occipital regions. Global efficiency and clustering coefficients were also decreased along with disease severity. Conclusion: These results indicate that EAD and LAD have distinguished features in terms of metabolic connectivity, with EAD demonstrating more extensive and progressive deterioration. PMID:27445800

  11. Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders

    Directory of Open Access Journals (Sweden)

    Qingying Meng

    2016-05-01

    Full Text Available Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient–host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control and hippocampus (cognitive processing from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine.

  12. Reconstruction of metabolic networks in a fluoranthene-degrading enrichments from polycyclic aromatic hydrocarbon polluted soil.

    Science.gov (United States)

    Zhao, Jian-Kang; Li, Xiao-Ming; Ai, Guo-Min; Deng, Ye; Liu, Shuang-Jiang; Jiang, Cheng-Ying

    2016-11-15

    Microbial degradation of polycyclic aromatic hydrocarbons (PAHs) is the primary process of removing PAHs from environments. The metabolic pathway of PAHs in pure cultures has been intensively studied, but cooperative metabolisms at community-level remained to be explored. In this study, we determined the dynamic composition of a microbial community and its metabolic intermediates during fluoranthene degradation using high-throughput metagenomics and gas chromatography-mass spectrometry (GC-MS), respectively. Subsequently, a cooperative metabolic network for fluoranthene degradation was constructed. The network shows that Mycobacterium contributed the majority of ring-hydroxylating and -cleavage dioxygenases, while Diaphorobacter contributed most of the dehydrogenases. Hyphomicrobium, Agrobacterium, and Sphingopyxis contributed to genes encoding enzymes involved in downstream reactions of fluoranthene degradation. The contributions of various microbial groups were calculated with the PICRUSt program. The contributions of Hyphomicrobium to alcohol dehydrogenases were 62.4% in stage 1 (i.e., when fluoranthene was rapidly removed) and 76.8% in stage 3 (i.e., when fluoranthene was not detectable), respectively; the contribution of Pseudomonas were 6.6% in stage 1 and decreased to 1.2% in subsequent stages. To the best of the author's knowledge, this report describes the first cooperative metabolic network to predict the contributions of various microbial groups during PAH-degradation at community-level. PMID:27415596

  13. Quantitative Tools for Dissection of Hydrogen-Producing Metabolic Networks-Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Rabinowitz, Joshua D.; Dismukes, G.Charles.; Rabitz, Herschel A.; Amador-Noguez, Daniel

    2012-10-19

    During this project we have pioneered the development of integrated experimental-computational technologies for the quantitative dissection of metabolism in hydrogen and biofuel producing microorganisms (i.e. C. acetobutylicum and various cyanobacteria species). The application of these new methodologies resulted in many significant advances in the understanding of the metabolic networks and metabolism of these organisms, and has provided new strategies to enhance their hydrogen or biofuel producing capabilities. As an example, using mass spectrometry, isotope tracers, and quantitative flux-modeling we mapped the metabolic network structure in C. acetobutylicum. This resulted in a comprehensive and quantitative understanding of central carbon metabolism that could not have been obtained using genomic data alone. We discovered that biofuel production in this bacterium, which only occurs during stationary phase, requires a global remodeling of central metabolism (involving large changes in metabolite concentrations and fluxes) that has the effect of redirecting resources (carbon and reducing power) from biomass production into solvent production. This new holistic, quantitative understanding of metabolism is now being used as the basis for metabolic engineering strategies to improve solvent production in this bacterium. In another example, making use of newly developed technologies for monitoring hydrogen and NAD(P)H levels in vivo, we dissected the metabolic pathways for photobiological hydrogen production by cyanobacteria Cyanothece sp. This investigation led to the identification of multiple targets for improving hydrogen production. Importantly, the quantitative tools and approaches that we have developed are broadly applicable and we are now using them to investigate other important biofuel producers, such as cellulolytic bacteria.

  14. The many forms of a pleomorphic bacterial pathogen – The developmental network of Legionella pneumophila

    Directory of Open Access Journals (Sweden)

    Peter eRobertson

    2014-12-01

    Full Text Available Legionella pneumophila is a natural intracellular bacterial parasite of free-living freshwater protozoa and an accidental human pathogen that causes Legionnaires’ disease. L. pneumophila differentiates, and does it in style. Recent experimental data on L. pneumophila’s differentiation point at the existence of a complex network that involves many developmental forms. We intend readers to: (i understand the biological relevance of L. pneumophila’s forms found in freshwater and their potential to transmit Legionnaires’ disease, and (ii learn that the common depiction of L. pneumophila’s differentiation as a biphasic developmental cycle that alternates between a replicative and a transmissive form is but an oversimplification of the actual process. Our specific objectives are to provide updates on the molecular factors that regulate L. pneumophila’s differentiation (section 2, and describe the developmental network of L. pneumophila (section 3, which for clarity’s sake we have dissected into five separate developmental cycles. Finally, since each developmental form seems to contribute differently to the human pathogenic process and the transmission of Legionnaires’ disease, readers are presented with a challenge to develop novel methods to detect the various L. pneumophila forms present in water (section 4, as a means to improve our assessment of risk and more effectively prevent legionellosis outbreaks.

  15. Double network bacterial cellulose hydrogel to build a biology-device interface

    Science.gov (United States)

    Shi, Zhijun; Li, Ying; Chen, Xiuli; Han, Hongwei; Yang, Guang

    2013-12-01

    Establishing a biology-device interface might enable the interaction between microelectronics and biotechnology. In this study, electroactive hydrogels have been produced using bacterial cellulose (BC) and conducting polymer (CP) deposited on the BC hydrogel surface to cover the BC fibers. The structures of these composites thus have double networks, one of which is a layer of electroactive hydrogels combined with BC and CP. The electroconductivity provides the composites with capabilities for voltage and current response, and the BC hydrogel layer provides good biocompatibility, biodegradability, bioadhesion and mass transport properties. Such a system might allow selective biological functions such as molecular recognition and specific catalysis and also for probing the detailed genetic and molecular mechanisms of life. A BC-CP composite hydrogel could then lead to a biology-device interface. Cyclic voltammetry and electrochemical impedance spectroscopy (EIS) are used here to study the composite hydrogels' electroactive property. BC-PAni and BC-PPy respond to voltage changes. This provides a mechanism to amplify electrochemical signals for analysis or detection. BC hydrogels were found to be able to support the growth, spreading and migration of human normal skin fibroblasts without causing any cytotoxic effect on the cells in the cell culture. These double network BC-CP hydrogels are biphasic Janus hydrogels which integrate electroactivity with biocompatibility, and might provide a biology-device interface to produce implantable devices for personalized and regenerative medicine.

  16. Effect of metabolic transformation of monoterpenes on antimutagenic potential in bacterial tests

    Directory of Open Access Journals (Sweden)

    Stajković-Srbinović Olivera

    2012-01-01

    Full Text Available The effect of metabolic transformation of the monoterpenes Linalool (Lin, Myrcene (Myr and Eucalyptol (Euc was evaluated on their antimutagenic potential against t-butyl hydroperoxide (t-BOOH and 2-nitropropane (2NP in E. coli WP2 and in S. typhimurium reversion assays, respectively. Spontaneous mutagenesis was also monitored in both assays. Mammalian metabolic transformation was provided by rat liver microsomes (S9 fraction. None of the monoterpenes was mutagenic, either with or without S9. Results obtained without S9 showed the antimutagenic potential of Lin against t-BOOH, of Myr against both t-BOOH and 2NP, and of Euc against spontaneous and mutagenesis induced with both mutagens. Mammalian enzymes significantly reduced the antimutagenic effect of Lin, completely diminished the antimutagenic effect of Myr, but did not alter the antimutagenic effect of Euc. Considering the results, metabolic transformation by host enzymes could significantly influence antimutagenic potential and should be included in antimutagenicity studies in prokaryotic assays. [Acknowledgments. This research was supported by the Ministry of Education and Science of Republic of Serbia, Project No. 172058.

  17. Anthropogenic N deposition slows decay by favoring bacterial metabolism: Insights from metagenomic analyses

    Directory of Open Access Journals (Sweden)

    Zachary B. Freedman

    2016-03-01

    Full Text Available Litter decomposition is an enzymatically-complex process that is mediated by a diverse assemblage of saprophytic microorganisms. It is a globally important biogeochemical process that can be suppressed by anthropogenic N deposition. In a northern hardwood forest ecosystem located in Michigan, USA, 20 years of experimentally increased atmospheric N deposition has reduced forest floor decay and increased soil C storage. Here, we paired extracellular enzyme assays with shotgun metagenomics to assess if anthropogenic N deposition has altered the functional potential of microbial communities inhabiting decaying forest floor. Experimental N deposition significantly reduced the activity of extracellular enzymes mediating plant cell wall decay, which occurred concurrently with changes in the relative abundance of metagenomic functional gene pathways mediating the metabolism of carbohydrates, aromatic compounds, as well as microbial respiration. Moreover, experimental N deposition increased the relative abundance of 50 of the 60 gene pathways, the majority of which were associated with saprotrophic bacteria. Conversely, the relative abundance and composition of fungal genes mediating the metabolism of plant litter was not affected by experimental N deposition. Future rates of atmospheric N deposition have favored saprotrophic soil bacteria, whereas the metabolic potential of saprotrophic fungi appears resilient to this agent of environmental change. Results presented here provide evidence that changes in the functional capacity of saprotrophic soil microorganisms mediate how anthropogenic N deposition increases C storage in soil.

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

    Science.gov (United States)

    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.

  19. Metabolic network modeling of microbial interactions in natural and engineered environmental systems

    Directory of Open Access Journals (Sweden)

    Octavio ePerez-Garcia

    2016-05-01

    Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

  20. Effects of bacterially produced precipitates on the metabolism of sulfate reducing bacteria during the bio-treatment process of copper-containing wastewater

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A large volume of bacterially produced precipitates are generated during the bio-treatment of heavy metal wastewater.The composition of the bacterially produced precipitates and its effects on sulfate reducing bacteria (SRB) in copper-containing waste stream were evaluated in this study.The elemental composition of the microbial precipitate was studied using electrodispersive X-ray spectroscopy (EDX),and it was found that the ratio of S:Cu was 1.12.Combining with the results of copper distribution in the SRB metabolism culture,which was analyzed by the sequential extraction procedure,copper in the precipitates was determined as covellite (CuS).The bacterially produced precipitates caused a decrease of the sulfate reduction rate,and the more precipitates were generated,the lower the sulfate reduction rate was.The particle sizes of bacterially generated covellite were ranging from 0.03 to 2 m by particles size distribution (PSD) analysis,which was smaller than that of the SRB cells.Transmission electron microscopy (TEM) analysis showed that the microbial covellite was deposited on the surface of the cell.The effects of the microbial precipitate on SRB metabolism were found to be weakened by increasing the precipitation time and adding microbial polymeric substances in later experiments.These results provided direct evidence that the SRB activity was inhibited by the bacterially produced covellite,which enveloped the bacterium and thus affected the metabolism of SRB on mass transfer.

  1. Hyperoxaluria leads to dysbiosis and drives selective enrichment of oxalate metabolizing bacterial species in recurrent kidney stone endures

    Science.gov (United States)

    Suryavanshi, Mangesh V.; Bhute, Shrikant S.; Jadhav, Swapnil D.; Bhatia, Manish S.; Gune, Rahul P.; Shouche, Yogesh S.

    2016-01-01

    Hyperoxaluria due to endogenously synthesized and exogenously ingested oxalates is a leading cause of recurrent oxalate stone formations. Even though, humans largely rely on gut microbiota for oxalate homeostasis, hyperoxaluria associated gut microbiota features remain largely unknown. Based on 16S rRNA gene amplicons, targeted metagenomic sequencing of formyl-CoA transferase (frc) gene and qPCR assay, we demonstrate a selective enrichment of Oxalate Metabolizing Bacterial Species (OMBS) in hyperoxaluria condition. Interestingly, higher than usual concentration of oxalate was found inhibitory to many gut microbes, including Oxalobacter formigenes, a well-characterized OMBS. In addition a concomitant enrichment of acid tolerant pathobionts in recurrent stone sufferers is observed. Further, specific enzymes participating in oxalate metabolism are found augmented in stone endures. Additionally, hyperoxaluria driven dysbiosis was found to be associated with oxalate content, stone episodes and colonization pattern of Oxalobacter formigenes. Thus, we rationalize the first in-depth surveillance of OMBS in the human gut and their association with hyperoxaluria. Our findings can be utilized in the treatment of hyperoxaluria associated recurrent stone episodes. PMID:27708409

  2. The influence of Glyceria maxima and nitrate input on the composition and nitrate metabolism of the dissimilatory nitrate-reducing bacterial community

    NARCIS (Netherlands)

    Nijburg, J.W.; Laanbroek, H.J.

    1997-01-01

    The influence of nitrate addition and the presence of Glyceria maxima (reed sweetgrass) on the composition and nitrate metabolism of the dissimilatory nitrate-reducing bacterial community was investigated. Anoxic freshwater sediment was incubated in pots with or without G. maxima and with or without

  3. Mycelium-Like Networks Increase Bacterial Dispersal, Growth, and Biodegradation in a Model Ecosystem at Various Water Potentials.

    Science.gov (United States)

    Worrich, Anja; König, Sara; Miltner, Anja; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin; Harms, Hauke; Kästner, Matthias; Wick, Lukas Y

    2016-05-15

    Fungal mycelia serve as effective dispersal networks for bacteria in water-unsaturated environments, thereby allowing bacteria to maintain important functions, such as biodegradation. However, poor knowledge exists on the effects of dispersal networks at various osmotic (Ψo) and matric (Ψm) potentials, which contribute to the water potential mainly in terrestrial soil environments. Here we studied the effects of artificial mycelium-like dispersal networks on bacterial dispersal dynamics and subsequent effects on growth and benzoate biodegradation at ΔΨo and ΔΨm values between 0 and -1.5 MPa. In a multiple-microcosm approach, we used a green fluorescent protein (GFP)-tagged derivative of the soil bacterium Pseudomonas putida KT2440 as a model organism and sodium benzoate as a representative of polar aromatic contaminants. We found that decreasing ΔΨo and ΔΨm values slowed bacterial dispersal in the system, leading to decelerated growth and benzoate degradation. In contrast, dispersal networks facilitated bacterial movement at ΔΨo and ΔΨm values between 0 and -0.5 MPa and thus improved the absolute biodegradation performance by up to 52 and 119% for ΔΨo and ΔΨm, respectively. This strong functional interrelationship was further emphasized by a high positive correlation between population dispersal, population growth, and degradation. We propose that dispersal networks may sustain the functionality of microbial ecosystems at low osmotic and matric potentials. PMID:26944849

  4. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  5. Kinetic model of metabolic network for xiamenmycin biosynthetic optimisation.

    Science.gov (United States)

    Xu, Min-juan; Chen, Yong-cong; Xu, Jun; Ao, Ping; Zhu, Xiao-mei

    2016-02-01

    Xiamenmycins, a series of prenylated benzopyran compounds with anti-fibrotic bioactivities, were isolated from a mangrove-derived Streptomyces xiamenensis. To fulfil the requirements of pharmaceutical investigations, a high production of xiamenmycin is needed. In this study, the authors present a kinetic metabolic model to evaluate fluxes in an engineered Streptomyces lividans with xiamenmycin-oriented genetic modification based on generic enzymatic rate equations and stability constraints. Lyapunov function was used for a viability optimisation. From their kinetic model, the flux distributions for the engineered S. lividans fed on glucose and glycerol as carbon sources were calculated. They found that if the bacterium can utilise glucose simultaneously with glycerol, xiamenmycin production can be enhanced by 40% theoretically, while maintaining the same growth rate. Glycerol may increase the flux for phosphoenolpyruvate synthesis without interfering citric acid cycle. They therefore believe this study demonstrates a possible new direction for bioengineering of S. lividans. PMID:26816395

  6. Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

    Science.gov (United States)

    Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-03-01

    "A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory.

  7. Using atom mapping rules for an improved detection of relevant routes in weighted metabolic networks.

    Science.gov (United States)

    Blum, Torsten; Kohlbacher, Oliver

    2008-01-01

    Computational analysis of pathways in metabolic networks has numerous applications in systems biology. While graph theory-based approaches have been presented that find biotransformation routes from one metabolite to another in these networks, most of these approaches suffer from finding too many routes, most of which are biologically infeasible or meaningless. We present a novel approach for finding relevant routes based on atom mapping rules (describing which educt atoms are mapped onto which product atoms in a chemical reaction). This leads to a reformulation of the problem as a lightest path search in a degree-weighted metabolic network. The key component of the approach is a new method of computing optimal atom mapping rules.

  8. Dose-dependent effects of dietary zinc oxide on bacterial communities and metabolic profiles in the ileum of weaned pigs.

    Science.gov (United States)

    Pieper, R; Vahjen, W; Neumann, K; Van Kessel, A G; Zentek, J

    2012-10-01

    Pharmacological levels of zinc oxide (ZnO) can improve the health of weaning piglets and influence the intestinal microbiota. This experiment aimed at studying the dose-response effect of five dietary concentrations of ZnO on small intestinal bacteria and metabolite profiles. Fifteen piglets, weaned at 25 ± 1 days of age, were allocated into five groups according to body weight and litter. Diets were formulated to contain 50 (basal diet), 150, 250, 1000 and 2500 mg zinc/kg by adding analytical-grade (>98% purity) ZnO to the basal diet and fed ad libitum for 14 days after a 7-day adaptation period on the basal diet. Ileal bacterial community profiles were analysed by denaturing gradient gel electrophoresis and selected bacterial groups quantified by real-time PCR. Concentrations of ileal volatile fatty acids (VFA), D- and L-lactate and ammonia were determined. Species richness, Shannon diversity and evenness were significantly higher at high ZnO levels. Quantitative PCR revealed lowest total bacterial counts in the 50 mg/kg group. Increasing ZnO levels led to an increase (p = 0.017) in enterobacteria from log 4.0 cfu/g digesta (50 mg/kg) to log 6.7 cfu/g digesta (2500 mg/kg). Lactic acid bacteria were not influenced (p = 0.687) and clostridial cluster XIVa declined (p = 0.035) at highest ZnO level. Concentration of total, D- and L-lactate and propionate was not affected (p = 0.736, p = 0.290 and p = 0.630), but concentrations of ileal total VFA, acetate and butyrate increased markedly from 50 to 150 mg/kg and decreased with further increasing zinc levels and reached low levels again at 2500 mg/kg (p = 0.048, p = 0.048 and p = 0.097). Ammonia decreased (p < 0.006) with increasing dietary ZnO level. In conclusion, increasing levels of dietary ZnO had strong and dose-dependent effects on ileal bacterial community composition and activity, suggesting taxonomic variation in metabolic response to ZnO. PMID:21929727

  9. FoodMicrobionet: A database for the visualisation and exploration of food bacterial communities based on network analysis.

    Science.gov (United States)

    Parente, Eugenio; Cocolin, Luca; De Filippis, Francesca; Zotta, Teresa; Ferrocino, Ilario; O'Sullivan, Orla; Neviani, Erasmo; De Angelis, Maria; Cotter, Paul D; Ercolini, Danilo

    2016-02-16

    Amplicon targeted high-throughput sequencing has become a popular tool for the culture-independent analysis of microbial communities. Although the data obtained with this approach are portable and the number of sequences available in public databases is increasing, no tool has been developed yet for the analysis and presentation of data obtained in different studies. This work describes an approach for the development of a database for the rapid exploration and analysis of data on food microbial communities. Data from seventeen studies investigating the structure of bacterial communities in dairy, meat, sourdough and fermented vegetable products, obtained by 16S rRNA gene targeted high-throughput sequencing, were collated and analysed using Gephi, a network analysis software. The resulting database, which we named FoodMicrobionet, was used to analyse nodes and network properties and to build an interactive web-based visualisation. The latter allows the visual exploration of the relationships between Operational Taxonomic Units (OTUs) and samples and the identification of core- and sample-specific bacterial communities. It also provides additional search tools and hyperlinks for the rapid selection of food groups and OTUs and for rapid access to external resources (NCBI taxonomy, digital versions of the original articles). Microbial interaction network analysis was carried out using CoNet on datasets extracted from FoodMicrobionet: the complexity of interaction networks was much lower than that found for other bacterial communities (human microbiome, soil and other environments). This may reflect both a bias in the dataset (which was dominated by fermented foods and starter cultures) and the lower complexity of food bacterial communities. Although some technical challenges exist, and are discussed here, the net result is a valuable tool for the exploration of food bacterial communities by the scientific community and food industry. PMID:26704067

  10. FoodMicrobionet: A database for the visualisation and exploration of food bacterial communities based on network analysis.

    Science.gov (United States)

    Parente, Eugenio; Cocolin, Luca; De Filippis, Francesca; Zotta, Teresa; Ferrocino, Ilario; O'Sullivan, Orla; Neviani, Erasmo; De Angelis, Maria; Cotter, Paul D; Ercolini, Danilo

    2016-02-16

    Amplicon targeted high-throughput sequencing has become a popular tool for the culture-independent analysis of microbial communities. Although the data obtained with this approach are portable and the number of sequences available in public databases is increasing, no tool has been developed yet for the analysis and presentation of data obtained in different studies. This work describes an approach for the development of a database for the rapid exploration and analysis of data on food microbial communities. Data from seventeen studies investigating the structure of bacterial communities in dairy, meat, sourdough and fermented vegetable products, obtained by 16S rRNA gene targeted high-throughput sequencing, were collated and analysed using Gephi, a network analysis software. The resulting database, which we named FoodMicrobionet, was used to analyse nodes and network properties and to build an interactive web-based visualisation. The latter allows the visual exploration of the relationships between Operational Taxonomic Units (OTUs) and samples and the identification of core- and sample-specific bacterial communities. It also provides additional search tools and hyperlinks for the rapid selection of food groups and OTUs and for rapid access to external resources (NCBI taxonomy, digital versions of the original articles). Microbial interaction network analysis was carried out using CoNet on datasets extracted from FoodMicrobionet: the complexity of interaction networks was much lower than that found for other bacterial communities (human microbiome, soil and other environments). This may reflect both a bias in the dataset (which was dominated by fermented foods and starter cultures) and the lower complexity of food bacterial communities. Although some technical challenges exist, and are discussed here, the net result is a valuable tool for the exploration of food bacterial communities by the scientific community and food industry.

  11. GAM: a web-service for integrated transcriptional and metabolic network analysis.

    Science.gov (United States)

    Sergushichev, Alexey A; Loboda, Alexander A; Jha, Abhishek K; Vincent, Emma E; Driggers, Edward M; Jones, Russell G; Pearce, Edward J; Artyomov, Maxim N

    2016-07-01

    Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/. PMID:27098040

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

    Directory of Open Access Journals (Sweden)

    Andre Terzic

    2009-04-01

    Full Text Available 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.

  13. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  14. Bacterial metabolic 'toxins': a new mechanism for lactose and food intolerance, and irritable bowel syndrome.

    Science.gov (United States)

    Campbell, A K; Matthews, S B; Vassel, N; Cox, C D; Naseem, R; Chaichi, J; Holland, I B; Green, J; Wann, K T

    2010-12-30

    Lactose and food intolerance cause a wide range of gut and systemic symptoms, including gas, gut pain, diarrhoea or constipation, severe headaches, severe fatigue, loss of cognitive functions such as concentration, memory and reasoning, muscle and joint pain, heart palpitations, and a variety of allergies (Matthews and Campbell, 2000; Matthews et al., 2005; Waud et al., 2008). These can be explained by the production of toxic metabolites from gut bacteria, as a result of anaerobic digestion of carbohydrates and other foods, not absorbed in the small intestine. These metabolites include alcohols, diols such as butan 2,3 diol, ketones, acids, and aldehydes such as methylglyoxal (Campbell et al., 2005, 2009). These 'toxins' induce calcium signals in bacteria and affect their growth, thereby acting to modify the balance of microflora in the gut (Campbell et al., 2004, 2007a,b). These bacterial 'toxins' also affect signalling mechanisms in cells around the body, thereby explaining the wide range of symptoms in people with food intolerance. This new mechanism also explains the most common referral to gastroenterologists, irritable bowel syndrome (IBS), and the illness that afflicted Charles Darwin for 50 years (Campbell and Matthews, 2005a,b). We propose it will lead to a new understanding of the molecular mechanism of type 2 diabetes and some cancers. PMID:20851732

  15. Determination of the hydrocarbon-degrading metabolic capabilities of tropical bacterial isolates

    Energy Technology Data Exchange (ETDEWEB)

    Marquez-Rocha, F.J.; Olmos-Soto, J. [Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, San Diego, CA (United States). Departamento de Biotecnologia Marina; Rosano-Hernandez, M.A.; Muriel-Garcia, M. [Instituto Mexicano del Petroleo, CD Carmen Camp (Mexico). Zona Marina/Tecnologia Ambiental

    2005-01-01

    Of more than 20 bacteria isolated from a tropical soil using minimal medium supplemented with hydrocarbons, 11 grew well on diesel as sole carbon source, and another 11 grew in the presence of polynuclear aromatic hydrocarbons (PAHs). Ten isolates were identified phenotypically as Pseudomonas sp. and eight as Bacillus sp. Gene sequences representing the catabolic genes (alkM, todM, ndoM, and xylM) and 16S rRNA gene sequences characteristic for Pseudomona and Bacillus were amplified by PCR, using DNA recovered from the supernatant of hydrocarbon-contaminated soil suspensions. Based on their rapid growth characteristics in the presence of hydrocarbons and the formation of PCR products for the catabolic genes alkM and ndoM six isolates were selected for biodegradation assays. After 30 days a mixed culture of two isolates achieved close to 70% hydrocarbon removal and apparent mineralization of 16% of the hydrocarbons present in the soil. Biodegradation rates varied from 275 to 387 mg hydrocarbon kg{sup -1} day{sup -1}. Several bacterial isolates obtained in this study have catabolic capabilities for the biodegradation of alkanes and aromatic hydrocarbons including PAHs. (author)

  16. Modeling and Robustness Analysis of Biochemical Networks of Glycerol Metabolism by Klebsiella Pneumoniae

    Science.gov (United States)

    Ye, Jianxiong; Feng, Enmin; Wang, Lei; Xiu, Zhilong; Sun, Yaqin

    Glycerol bioconversion to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae) can be characterized by an intricate network of interactions among biochemical fluxes, metabolic compounds, key enzymes and genetic regulatory. To date, there still exist some uncertain factors in this complex network because of the limitation in bio-techniques, especially in measuring techniques for intracellular substances. In this paper, among these uncertain factors, we aim to infer the transport mechanisms of glycerol and 1,3-PD across the cell membrane, which have received intensive interest in recent years. On the basis of different inferences of the transport mechanisms, we reconstruct various metabolic networks correspondingly and subsequently develop their dynamical systems (S-systems). To determine the most reasonable metabolic network from all possible ones, we establish a quantitative definition of biological robustness and undertake parameter identification and robustness analysis for each system. Numerical results show that it is most possible that both glycerol and 1,3-PD pass the cell membrane by active transport and passive diffusion.

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

    Science.gov (United States)

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

    2016-09-01

    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.

  18. Multilevel correlations in the biological phosphorus removal process: From bacterial enrichment to conductivity-based metabolic batch tests and polyphosphatase assays.

    Science.gov (United States)

    Weissbrodt, David G; Maillard, Julien; Brovelli, Alessandro; Chabrelie, Alexandre; May, Jonathan; Holliger, Christof

    2014-12-01

    Enhanced biological phosphorus removal (EBPR) from wastewater relies on the preferential selection of active polyphosphate-accumulating organisms (PAO) in the underlying bacterial community continuum. Efficient management of the bacterial resource requires understanding of population dynamics as well as availability of bioanalytical methods for rapid and regular assessment of relative abundances of active PAOs and their glycogen-accumulating competitors (GAO). A systems approach was adopted here toward the investigation of multilevel correlations from the EBPR bioprocess to the bacterial community, metabolic, and enzymatic levels. Two anaerobic-aerobic sequencing-batch reactors were operated to enrich activated sludge in PAOs and GAOs affiliating with "Candidati Accumulibacter and Competibacter phosphates", respectively. Bacterial selection was optimized by dynamic control of the organic loading rate and the anaerobic contact time. The distinct core bacteriomes mainly comprised populations related to the classes Betaproteobacteria, Cytophagia, and Chloroflexi in the PAO enrichment and of Gammaproteobacteria, Alphaproteobacteria, Acidobacteria, and Sphingobacteria in the GAO enrichment. An anaerobic metabolic batch test based on electrical conductivity evolution and a polyphosphatase enzymatic assay were developed for rapid and low-cost assessment of the active PAO fraction and dephosphatation potential of activated sludge. Linear correlations were obtained between the PAO fraction, biomass specific rate of conductivity increase under anaerobic conditions, and polyphosphate-hydrolyzing activity of PAO/GAO mixtures. The correlations between PAO/GAO ratios, metabolic activities, and conductivity profiles were confirmed by simulations with a mathematical model developed in the aqueous geochemistry software PHREEQC. PMID:24975745

  19. Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

    Directory of Open Access Journals (Sweden)

    Heavner Benjamin D

    2012-06-01

    Full Text Available Abstract Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Additional file 1 Function testYeastModel.m.m. Click here for file Additional file 2 Function model

  20. PPARγ Expression and Function in Mycobacterial Infection: Roles in Lipid Metabolism, Immunity, and Bacterial Killing

    Directory of Open Access Journals (Sweden)

    Patricia E. Almeida

    2012-01-01

    Full Text Available Tuberculosis continues to be a global health threat, with drug resistance and HIV coinfection presenting challenges for its control. Mycobacterium tuberculosis, the etiological agent of tuberculosis, is a highly adapted pathogen that has evolved different strategies to subvert the immune and metabolic responses of host cells. Although the significance of peroxisome proliferator-activated receptor gamma (PPARγ activation by mycobacteria is not fully understood, recent findings are beginning to uncover a critical role for PPARγ during mycobacterial infection. Here, we will review the molecular mechanisms that regulate PPARγ expression and function during mycobacterial infection. Current evidence indicates that mycobacterial infection causes a time-dependent increase in PPARγ expression through mechanisms that involve pattern recognition receptor activation. Mycobacterial triggered increased PPARγ expression and activation lead to increased lipid droplet formation and downmodulation of macrophage response, suggesting that PPARγ expression might aid the mycobacteria in circumventing the host response acting as an escape mechanism. Indeed, inhibition of PPARγ enhances mycobacterial killing capacity of macrophages, suggesting a role of PPARγ in favoring the establishment of chronic infection. Collectively, PPARγ is emerging as a regulator of tuberculosis pathogenesis and an attractive target for the development of adjunctive tuberculosis therapies.

  1. Dynamics of bacterial metabolic profile and community structure during the mineralization of organic carbon in intensive swine farm wastewater

    Directory of Open Access Journals (Sweden)

    Xiaoyan Ma

    2015-06-01

    Full Text Available Land application of intensive swine farm wastewater has raised serious environmental concerns due to the accumulation and microbially mediated transformation of large amounts of swine wastewater organic C (SWOC. Therefore, the study of SWOC mineralization and dynamics of wastewater microorganisms is essential to understand the environmental impacts of swine wastewater application. We measured the C mineralization of incubated swine wastewaters with high (wastewater H and low (wastewater L organic C concentrations. The dynamics of bacteria metabolic profile and community structure were also investigated. The results showed that SWOC mineralization was properly fitted by the two-simultaneous reactions model. The initial potential rate of labile C mineralization of wastewater H was 46% higher than that of wastewater L, whereas the initial potential rates of recalcitrant C mineralization of wastewaters H and L were both around 23 mg L-1 d-1. The bacterial functional and structural diversities significantly decreased for both the wastewaters during SWOC mineralization, and were all negatively correlated to specific UV absorbance (SUVA254; P < 0.01. The bacteria in the raw wastewaters exhibited functional similarity, and both metabolic profile and community structure changed with the mineralization of SWOC, mainly under the influence of SUVA254 (P < 0.001. These results suggested that SWOC mineralization was characterized by rapid mineralization of labile C and subsequent slow decomposition of recalcitrant C pool, and the quality of SWOC varied between the wastewaters with different amounts of organic C. The decreased bio-availability of dissolved organic matter affected the dynamics of wastewater bacteria during SWOC mineralization.

  2. Metabolism

    Science.gov (United States)

    ... also influenced by body composition — people with more muscle and less fat generally have higher BMRs. previous continue Things That Can Go Wrong With Metabolism Most of the time your metabolism works effectively ...

  3. Computing smallest intervention strategies for multiple metabolic networks in a boolean model.

    Science.gov (United States)

    Lu, Wei; Tamura, Takeyuki; Song, Jiangning; Akutsu, Tatsuya

    2015-02-01

    This article considers the problem whereby, given two metabolic networks N1 and N2, a set of source compounds, and a set of target compounds, we must find the minimum set of reactions whose removal (knockout) ensures that the target compounds are not producible in N1 but are producible in N2. Similar studies exist for the problem of finding the minimum knockout with the smallest side effect for a single network. However, if technologies of external perturbations are advanced in the near future, it may be important to develop methods of computing the minimum knockout for multiple networks (MKMN). Flux balance analysis (FBA) is efficient if a well-polished model is available. However, that is not always the case. Therefore, in this article, we study MKMN in Boolean models and an elementary mode (EM)-based model. Integer linear programming (ILP)-based methods are developed for these models, since MKMN is NP-complete for both the Boolean model and the EM-based model. Computer experiments are conducted with metabolic networks of clostridium perfringens SM101 and bifidobacterium longum DJO10A, respectively known as bad bacteria and good bacteria for the human intestine. The results show that larger networks are more likely to have MKMN solutions. However, solving for these larger networks takes a very long time, and often the computation cannot be completed. This is reasonable, because small networks do not have many alternative pathways, making it difficult to satisfy the MKMN condition, whereas in large networks the number of candidate solutions explodes. Our developed software minFvskO is available online.

  4. Metabolism

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    2008255 Serum adiponectin level declines in the elderly with metabolic syndrome.WU Xiaoyan(吴晓琰),et al.Dept Geriatr,Huashan Hosp,Fudan UnivShanghai200040.Chin J Geriatr2008;27(3):164-167.Objective To investigate the correlation between ser-um adiponectin level and metabolic syndrome in the elderly·Methods Sixty-one subjects with metabolic syndrome and140age matched subjects without metabolic

  5. On the determining role of network structure titania in silicone against bacterial colonization: Mechanism and disruption of biofilm

    Energy Technology Data Exchange (ETDEWEB)

    Depan, D.; Misra, R.D.K., E-mail: dmisra@louisiana.edu

    2014-01-01

    Silicone-based biomedical devices are prone to microbial adhesion, which is the primary cause of concern in the functioning of the artificial device. Silicone exhibiting long-term and effective antibacterial ability is highly desirable to prevent implant related infections. In this regard, nanophase titania was incorporated in silicone as an integral part of the silicone network structure through cross-link mechanism, with the objective to reduce bacterial adhesion to a minimum. The bacterial adhesion was studied using crystal violet assay, while the mechanism of inhibition of biofilm formation was studied via electron microscopy. The incorporation of nanophase titania in silicone dramatically reduced the viability of Staphylococcus aureus (S. aureus) and the capability to adhere on the surface of hybrid silicone by ∼ 93% in relation to stand alone silicone. The conclusion of dramatic reduction in the viability of S. aureus is corroborated by different experimental approaches including biofilm inhibition assay, zone of inhibition, and through a novel experiment that involved incubation of biofilm with titania nanoparticles. It is proposed that the mechanism of disruption of bacterial film in the presence of titania involves puncturing of the bacterial cell membrane. - Highlights: • Network structure titania in silicone imparts antimicrobial activity. • Ability to microbial adhesion is significantly reduced. • Antimicrobial mechanism involves rupture of biofilm.

  6. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  7. An X-ray Absorption Fine Structure study of Au adsorbed onto the non-metabolizing cells of two soil bacterial species

    Science.gov (United States)

    Song, Zhen; Kenney, Janice P. L.; Fein, Jeremy B.; Bunker, Bruce A.

    2012-06-01

    Gram-positive and Gram-negative bacterial cells can remove Au from Au(III)-chloride solutions, and the extent of removal is strongly pH dependent. In order to determine the removal mechanisms, X-ray Absorption Fine Structure (XAFS) spectroscopy experiments were conducted on non-metabolizing biomass of Bacillus subtilis and Pseudomonas putida with fixed Au(III) concentrations over a range of bacterial concentrations and pH values. X-ray Absorption Near Edge Structure (XANES) and Extended X-ray Absorption Fine Structure (EXAFS) data on both bacterial species indicate that more than 90% of the Au atoms on the bacterial cell walls were reduced to Au(I). In contrast to what has been observed for Au(III) interaction with metabolizing bacterial cells, no Au(0) or Au-Au nearest neighbors were observed in our experimental systems. All of the removed Au was present as adsorbed bacterial surface complexes. For both species, the XAFS data suggest that although Au-chloride-hydroxide aqueous complexes dominate the speciation of Au in solution, Au on the bacterial cell wall is characterized predominantly by binding of Au atoms to sulfhydryl functional groups and amine and/or carboxyl functional groups, and the relative importance of the sulfhydryl groups increases with increasing pH and with decreasing Au loading. The XAFS data for both microorganism species suggest that adsorption is the first step in the formation of Au nanoparticles by bacteria, and the results enhance our ability to account for the behavior of Au in bacteria-bearing geologic systems.

  8. An X-ray Absorption Fine Structure study of Au adsorbed onto the non-metabolizing cells of two soil bacterial species

    Energy Technology Data Exchange (ETDEWEB)

    Song, Zhen; Kenney, Janice P.L.; Fein, Jeremy B.; Bunker, Bruce A. (Notre)

    2015-02-09

    Gram-positive and Gram-negative bacterial cells can remove Au from Au(III)-chloride solutions, and the extent of removal is strongly pH dependent. In order to determine the removal mechanisms, X-ray Absorption Fine Structure (XAFS) spectroscopy experiments were conducted on non-metabolizing biomass of Bacillus subtilis and Pseudomonas putida with fixed Au(III) concentrations over a range of bacterial concentrations and pH values. X-ray Absorption Near Edge Structure (XANES) and Extended X-ray Absorption Fine Structure (EXAFS) data on both bacterial species indicate that more than 90% of the Au atoms on the bacterial cell walls were reduced to Au(I). In contrast to what has been observed for Au(III) interaction with metabolizing bacterial cells, no Au(0) or Au-Au nearest neighbors were observed in our experimental systems. All of the removed Au was present as adsorbed bacterial surface complexes. For both species, the XAFS data suggest that although Au-chloride-hydroxide aqueous complexes dominate the speciation of Au in solution, Au on the bacterial cell wall is characterized predominantly by binding of Au atoms to sulfhydryl functional groups and amine and/or carboxyl functional groups, and the relative importance of the sulfhydryl groups increases with increasing pH and with decreasing Au loading. The XAFS data for both microorganism species suggest that adsorption is the first step in the formation of Au nanoparticles by bacteria, and the results enhance our ability to account for the behavior of Au in bacteria-bearing geologic systems.

  9. Top-down controls on bacterial community structure: microbial network analysis of bacteria, T4-like viruses and protists

    OpenAIRE

    Chow, Cheryl-Emiliane T.; Kim, Diane Y.; Sachdeva, Rohan; Caron, David A.; Fuhrman, Jed A

    2013-01-01

    Characterizing ecological relationships between viruses, bacteria and protists in the ocean are critical to understanding ecosystem function, yet these relationships are infrequently investigated together. We evaluated these relationships through microbial association network analysis of samples collected approximately monthly from March 2008 to January 2011 in the surface ocean (0–5 m) at the San Pedro Ocean Time series station. Bacterial, T4-like myoviral and protistan communities were desc...

  10. Quantitative mass spectrometry reveals plasticity of metabolic networks in Mycobacterium smegmatis.

    Science.gov (United States)

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

    2014-11-01

    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.

  11. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... and lactate. Comparable flux values between in silico model and experimental values were seen, although some differences in the phenotypic behavior between the model and the experimental data were observed,...

  12. Cj1411c GENE OF CAMPYLOBACTER JEJUNI 11168 ENCODES FOR A CYTOCHROME P450 INVOLVED IN BACTERIAL CAPSULE SUGAR METABOLISM

    Directory of Open Access Journals (Sweden)

    N. CORCIONIVOSCHI

    2013-12-01

    Full Text Available After isolation in 1970s, Campylobacter jejuni become the most commonlyrecognized cause of bacterial gastroenteritis in man. In animals is frequently foundin bovines on ovines. Publishing of the genome sequence of Campylobacter jejuni11168 (Parkhill, 2000 revealed the presence of only one cytochrome P450 in anoperon involved in sugar and cell surface biosynthesis. The gene name is Cj1411c, is1359 bp long and encodes 453 aa. The sequence is strictly conserved inCampylobacter jejuni RM221. Similarities with two cytochrome P450s, one formSilicobacter sp. and one form Poloromonas sp., were identified. These two enzymesare known to be involved in ascorbate and aldarate metabolism. The recombinantconstruct allowed the expression of active P450 enzyme with a 450 nm peak whenbinds CO. The protein was purified in proportion of ~ 70 %. By deleting the P450gene from the Campylobacter jejuni 11168 genome clear changes in cellmorphology were identified cells becoming wider and shorter. The capsular sugarprofile of the NCI strain reveals the presence of arabinose which was not found inthe wild type strain. The arabinose was identified by both High Performance LiquidChromatography (HPLC and Nuclear Magnetic Resonance (NMR.

  13. The cockroach Blattella germanica obtains nitrogen from uric acid through a metabolic pathway shared with its bacterial endosymbiont.

    Science.gov (United States)

    Patiño-Navarrete, Rafael; Piulachs, Maria-Dolors; Belles, Xavier; Moya, Andrés; Latorre, Amparo; Peretó, Juli

    2014-07-01

    Uric acid stored in the fat body of cockroaches is a nitrogen reservoir mobilized in times of scarcity. The discovery of urease in Blattabacterium cuenoti, the primary endosymbiont of cockroaches, suggests that the endosymbiont may participate in cockroach nitrogen economy. However, bacterial urease may only be one piece in the entire nitrogen recycling process from insect uric acid. Thus, in addition to the uricolytic pathway to urea, there must be glutamine synthetase assimilating the released ammonia by the urease reaction to enable the stored nitrogen to be metabolically usable. None of the Blattabacterium genomes sequenced to date possess genes encoding for those enzymes. To test the host's contribution to the process, we have sequenced and analysed Blattella germanica transcriptomes from the fat body. We identified transcripts corresponding to all genes necessary for the synthesis of uric acid and its catabolism to urea, as well as for the synthesis of glutamine, asparagine, proline and glycine, i.e. the amino acids required by the endosymbiont. We also explored the changes in gene expression with different dietary protein levels. It appears that the ability to use uric acid as a nitrogen reservoir emerged in cockroaches after its age-old symbiotic association with bacteria.

  14. Cj1411c GENE OF CAMPYLOBACTER JEJUNI 11168 ENCODES FOR A CYTOCHROME P450 INVOLVED IN BACTERIAL CAPSULE SUGAR METABOLISM

    Directory of Open Access Journals (Sweden)

    CORCIONIVOSCHI N.

    2007-01-01

    Full Text Available After isolation in 1970s, Campylobacter jejuni become the most commonlyrecognized cause of bacterial gastroenteritis in man. In animals is frequently foundin bovines on ovines. Publishing of the genome sequence of Campylobacter jejuni11168 (Parkhill, 2000 revealed the presence of only one cytochrome P450 in anoperon involved in sugar and cell surface biosynthesis. The gene name is Cj1411c, is1359 bp long and encodes 453 aa. The sequence is strictly conserved inCampylobacter jejuni RM221. Similarities with two cytochrome P450s, one formSilicobacter sp. and one form Poloromonas sp., were identified. These two enzymesare known to be involved in ascorbate and aldarate metabolism. The recombinantconstruct allowed the expression of active P450 enzyme with a 450 nm peak whenbinds CO. The protein was purified in proportion of ~ 70 %. By deleting the P450gene from the Campylobacter jejuni 11168 genome clear changes in cellmorphology were identified cells becoming wider and shorter. The capsular sugarprofile of the NCI strain reveals the presence of arabinose which was not found inthe wild type strain. The arabinose was identified by both High Performance LiquidChromatography (HPLC and Nuclear Magnetic Resonance (NMR.

  15. Integration of Posttranscriptional Gene Networks into Metabolic Adaptation and Biofilm Maturation in Candida albicans.

    Directory of Open Access Journals (Sweden)

    Jiyoti Verma-Gaur

    2015-10-01

    Full Text Available The yeast Candida albicans is a human commensal and opportunistic pathogen. Although both commensalism and pathogenesis depend on metabolic adaptation, the regulatory pathways that mediate metabolic processes in C. albicans are incompletely defined. For example, metabolic change is a major feature that distinguishes community growth of C. albicans in biofilms compared to suspension cultures, but how metabolic adaptation is functionally interfaced with the structural and gene regulatory changes that drive biofilm maturation remains to be fully understood. We show here that the RNA binding protein Puf3 regulates a posttranscriptional mRNA network in C. albicans that impacts on mitochondrial biogenesis, and provide the first functional data suggesting evolutionary rewiring of posttranscriptional gene regulation between the model yeast Saccharomyces cerevisiae and C. albicans. A proportion of the Puf3 mRNA network is differentially expressed in biofilms, and by using a mutant in the mRNA deadenylase CCR4 (the enzyme recruited to mRNAs by Puf3 to control transcript stability we show that posttranscriptional regulation is important for mitochondrial regulation in biofilms. Inactivation of CCR4 or dis-regulation of mitochondrial activity led to altered biofilm structure and over-production of extracellular matrix material. The extracellular matrix is critical for antifungal resistance and immune evasion, and yet of all biofilm maturation pathways extracellular matrix biogenesis is the least understood. We propose a model in which the hypoxic biofilm environment is sensed by regulators such as Ccr4 to orchestrate metabolic adaptation, as well as the regulation of extracellular matrix production by impacting on the expression of matrix-related cell wall genes. Therefore metabolic changes in biofilms might be intimately linked to a key biofilm maturation mechanism that ultimately results in untreatable fungal disease.

  16. Metabolic network rewiring of propionate flux compensates vitamin B12 deficiency in C. elegans

    Science.gov (United States)

    Watson, Emma; Olin-Sandoval, Viridiana; Hoy, Michael J; Li, Chi-Hua; Louisse, Timo; Yao, Victoria; Mori, Akihiro; Holdorf, Amy D; Troyanskaya, Olga G; Ralser, Markus; Walhout, Albertha JM

    2016-01-01

    Metabolic network rewiring is the rerouting of metabolism through the use of alternate enzymes to adjust pathway flux and accomplish specific anabolic or catabolic objectives. Here, we report the first characterization of two parallel pathways for the breakdown of the short chain fatty acid propionate in Caenorhabditis elegans. Using genetic interaction mapping, gene co-expression analysis, pathway intermediate quantification and carbon tracing, we uncover a vitamin B12-independent propionate breakdown shunt that is transcriptionally activated on vitamin B12 deficient diets, or under genetic conditions mimicking the human diseases propionic- and methylmalonic acidemia, in which the canonical B12-dependent propionate breakdown pathway is blocked. Our study presents the first example of transcriptional vitamin-directed metabolic network rewiring to promote survival under vitamin deficiency. The ability to reroute propionate breakdown according to B12 availability may provide C. elegans with metabolic plasticity and thus a selective advantage on different diets in the wild. DOI: http://dx.doi.org/10.7554/eLife.17670.001 PMID:27383050

  17. 代谢网络的重构%Reconstruction of Metabolic Networks

    Institute of Scientific and Technical Information of China (English)

    邓世果; 吴干华; 杨会杰

    2012-01-01

    A new method was proposed to reconstruct metabolic networks on the basis of the existing method. As an illustration example, the method was used to build the metabolic network for a species of anabaena. By use of the data of organism's biochemical reaction,enzyme and gene in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the preliminary metabolic network for the anabaena was reconstructed. The structural behaviors such as degree distribution, hierarchy, and community were discussed.%在已有的构建代谢网络方法的基础上,提出了构造代谢网络的改进方法.以鱼腥藻作为实例,利用KEGG数据库中生物体的生化反应、酶、基因数据重构出鱼腥藻的初步代谢网络,并对初步代谢网络进行了修正,讨论了该网络的拓扑结构性质.

  18. Toolbox model of evolution of prokaryotic metabolic networks and their regulation.

    Science.gov (United States)

    Maslov, Sergei; Krishna, Sandeep; Pang, Tin Yau; Sneppen, Kim

    2009-06-16

    It has been reported that the number of transcription factors encoded in prokaryotic genomes scales approximately quadratically with their total number of genes. We propose a conceptual explanation of this finding and illustrate it using a simple model in which metabolic and regulatory networks of prokaryotes are shaped by horizontal gene transfer of coregulated metabolic pathways. Adapting to a new environmental condition monitored by a new transcription factor (e.g., learning to use another nutrient) involves both acquiring new enzymes and reusing some of the enzymes already encoded in the genome. As the repertoire of enzymes of an organism (its toolbox) grows larger, it can reuse its enzyme tools more often and thus needs to get fewer new ones to master each new task. From this observation, it logically follows that the number of functional tasks and their regulators increases faster than linearly with the total number of genes encoding enzymes. Genomes can also shrink, e.g., because of a loss of a nutrient from the environment, followed by deletion of its regulator and all enzymes that become redundant. We propose several simple models of network evolution elaborating on this toolbox argument and reproducing the empirically observed quadratic scaling. The distribution of lengths of pathway branches in our model agrees with that of the real-life metabolic network of Escherichia coli. Thus, our model provides a qualitative explanation for broad distributions of regulon sizes in prokaryotes. PMID:19482938

  19. New insights into Dehalococcoides mccartyi metabolism from a reconstructed metabolic network-based systems-level analysis of D. mccartyi transcriptomes.

    Directory of Open Access Journals (Sweden)

    M Ahsanul Islam

    Full Text Available Organohalide respiration, mediated by Dehalococcoides mccartyi, is a useful bioremediation process that transforms ground water pollutants and known human carcinogens such as trichloroethene and vinyl chloride into benign ethenes. Successful application of this process depends on the fundamental understanding of the respiration and metabolism of D. mccartyi. Reductive dehalogenases, encoded by rdhA genes of these anaerobic bacteria, exclusively catalyze organohalide respiration and drive metabolism. To better elucidate D. mccartyi metabolism and physiology, we analyzed available transcriptomic data for a pure isolate (Dehalococcoides mccartyi strain 195 and a mixed microbial consortium (KB-1 using the previously developed pan-genome-scale reconstructed metabolic network of D. mccartyi. The transcriptomic data, together with available proteomic data helped confirm transcription and expression of the majority genes in D. mccartyi genomes. A composite genome of two highly similar D. mccartyi strains (KB-1 Dhc from the KB-1 metagenome sequence was constructed, and operon prediction was conducted for this composite genome and other single genomes. This operon analysis, together with the quality threshold clustering analysis of transcriptomic data helped generate experimentally testable hypotheses regarding the function of a number of hypothetical proteins and the poorly understood mechanism of energy conservation in D. mccartyi. We also identified functionally enriched important clusters (13 for strain 195 and 11 for KB-1 Dhc of co-expressed metabolic genes using information from the reconstructed metabolic network. This analysis highlighted some metabolic genes and processes, including lipid metabolism, energy metabolism, and transport that potentially play important roles in organohalide respiration. Overall, this study shows the importance of an organism's metabolic reconstruction in analyzing various "omics" data to obtain improved understanding

  20. Counting and Correcting Thermodynamically Infeasible Flux Cycles in Genome-Scale Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    2013-10-01

    Full Text Available Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail to eliminate them. As test cases, we tackle (a the problem of identifying infeasible cycles in the E. coli metabolic network and (b the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type-specific metabolic networks. Results for (a are compared with previous analyses of the same issue, while results for (b are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method, on the one hand, outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.

  1. Difference in the distribution pattern of substrate enzymes in the metabolic network of Escherichia coli, according to chaperonin requirement

    Directory of Open Access Journals (Sweden)

    Niwa Tatsuya

    2011-06-01

    Full Text Available Abstract Background Chaperonins are important in living systems because they play a role in the folding of proteins. Earlier comprehensive analyses identified substrate proteins for which folding requires the chaperonin GroEL/GroES (GroE in Escherichia coli, and they revealed that many chaperonin substrates are metabolic enzymes. This result implies the importance of chaperonins in metabolism. However, the relationship between chaperonins and metabolism is still unclear. Results We investigated the distribution of chaperonin substrate enzymes in the metabolic network using network analysis techniques as a first step towards revealing this relationship, and found that as chaperonin requirement increases, substrate enzymes are more laterally distributed in the metabolic. In addition, comparative genome analysis showed that the chaperonin-dependent substrates were less conserved, suggesting that these substrates were acquired later on in evolutionary history. Conclusions This result implies the expansion of metabolic networks due to this chaperonin, and it supports the existing hypothesis of acceleration of evolution by chaperonins. The distribution of chaperonin substrate enzymes in the metabolic network is inexplicable because it does not seem to be associated with individual protein features such as protein abundance, which has been observed characteristically in chaperonin substrates in previous works. However, it becomes clear by considering this expansion process due to chaperonin. This finding provides new insights into metabolic evolution and the roles of chaperonins in living systems.

  2. Metabolic network analysis of an adipoyl-7-ADCA-producing strain of Penicillium chrysogenum: Elucidation of adipate degradation

    DEFF Research Database (Denmark)

    Thykær, Jette; Christensen, Bjarke; Nielsen, Jens

    2002-01-01

    An adipoyl-7-ADCA-producing, recombinant strain of Penicillium chrysogenum was characterized by metabolic network analysis, with special focus on the degradation of adipate and determination of the metabolic fluxes. Degradation of the side-chain precursor, adipate, causes an undesired consumption...

  3. Identification of genes and networks driving cardiovascular and metabolic phenotypes in a mouse F2 intercross.

    Directory of Open Access Journals (Sweden)

    Jonathan M J Derry

    Full Text Available To identify the genes and pathways that underlie cardiovascular and metabolic phenotypes we performed an integrated analysis of a mouse C57BL/6JxA/J F2 (B6AF2 cross by relating genome-wide gene expression data from adipose, kidney, and liver tissues to physiological endpoints measured in the population. We have identified a large number of trait QTLs including loci driving variation in cardiac function on chromosomes 2 and 6 and a hotspot for adiposity, energy metabolism, and glucose traits on chromosome 8. Integration of adipose gene expression data identified a core set of genes that drive the chromosome 8 adiposity QTL. This chromosome 8 trans eQTL signature contains genes associated with mitochondrial function and oxidative phosphorylation and maps to a subnetwork with conserved function in humans that was previously implicated in human obesity. In addition, human eSNPs corresponding to orthologous genes from the signature show enrichment for association to type II diabetes in the DIAGRAM cohort, supporting the idea that the chromosome 8 locus perturbs a molecular network that in humans senses variations in DNA and in turn affects metabolic disease risk. We functionally validate predictions from this approach by demonstrating metabolic phenotypes in knockout mice for three genes from the trans eQTL signature, Akr1b8, Emr1, and Rgs2. In addition we show that the transcriptional signatures for knockout of two of these genes, Akr1b8 and Rgs2, map to the F2 network modules associated with the chromosome 8 trans eQTL signature and that these modules are in turn very significantly correlated with adiposity in the F2 population. Overall this study demonstrates how integrating gene expression data with QTL analysis in a network-based framework can aid in the elucidation of the molecular drivers of disease that can be translated from mice to humans.

  4. Genome-scale reconstruction and analysis of the metabolic network in the hyperthermophilic archaeon Sulfolobus solfataricus.

    Directory of Open Access Journals (Sweden)

    Thomas Ulas

    Full Text Available We describe the reconstruction of a genome-scale metabolic model of the crenarchaeon Sulfolobus solfataricus, a hyperthermoacidophilic microorganism. It grows in terrestrial volcanic hot springs with growth occurring at pH 2-4 (optimum 3.5 and a temperature of 75-80°C (optimum 80°C. The genome of Sulfolobus solfataricus P2 contains 2,992,245 bp on a single circular chromosome and encodes 2,977 proteins and a number of RNAs. The network comprises 718 metabolic and 58 transport/exchange reactions and 705 unique metabolites, based on the annotated genome and available biochemical data. Using the model in conjunction with constraint-based methods, we simulated the metabolic fluxes induced by different environmental and genetic conditions. The predictions were compared to experimental measurements and phenotypes of S. solfataricus. Furthermore, the performance of the network for 35 different carbon sources known for S. solfataricus from the literature was simulated. Comparing the growth on different carbon sources revealed that glycerol is the carbon source with the highest biomass flux per imported carbon atom (75% higher than glucose. Experimental data was also used to fit the model to phenotypic observations. In addition to the commonly known heterotrophic growth of S. solfataricus, the crenarchaeon is also able to grow autotrophically using the hydroxypropionate-hydroxybutyrate cycle for bicarbonate fixation. We integrated this pathway into our model and compared bicarbonate fixation with growth on glucose as sole carbon source. Finally, we tested the robustness of the metabolism with respect to gene deletions using the method of Minimization of Metabolic Adjustment (MOMA, which predicted that 18% of all possible single gene deletions would be lethal for the organism.

  5. EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

    Science.gov (United States)

    Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

    2015-10-01

    Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP . PMID:26542446

  6. Effects of dietary inulin on bacterial growth, short-chain fatty acid production and hepatic lipid metabolism in gnotobiotic mice.

    Science.gov (United States)

    Weitkunat, Karolin; Schumann, Sara; Petzke, Klaus Jürgen; Blaut, Michael; Loh, Gunnar; Klaus, Susanne

    2015-09-01

    In literature, contradictory effects of dietary fibers and their fermentation products, short-chain fatty acids (SCFA), are described: On one hand, they increase satiety, but on the other hand, they provide additional energy and promote obesity development. We aimed to answer this paradox by investigating the effects of fermentable and non-fermentable fibers on obesity induced by high-fat diet in gnotobiotic C3H/HeOuJ mice colonized with a simplified human microbiota. Mice were fed a high-fat diet supplemented either with 10% cellulose (non-fermentable) or inulin (fermentable) for 6 weeks. Feeding the inulin diet resulted in an increased diet digestibility and reduced feces energy, compared to the cellulose diet with no differences in food intake, suggesting an increased intestinal energy extraction from inulin. However, we observed no increase in body fat/weight. The additional energy provided by the inulin diet led to an increased bacterial proliferation in this group. Supplementation of inulin resulted further in significantly elevated concentrations of total SCFA in cecum and portal vein plasma, with a reduced cecal acetate:propionate ratio. Hepatic expression of genes involved in lipogenesis (Fasn, Gpam) and fatty acid elongation/desaturation (Scd1, Elovl3, Elovl6, Elovl5, Fads1 and Fads2) were decreased in inulin-fed animals. Accordingly, plasma and liver phospholipid composition were changed between the different feeding groups. Concentrations of omega-3 and odd-chain fatty acids were increased in inulin-fed mice, whereas omega-6 fatty acids were reduced. Taken together, these data indicate that, during this short-term feeding, inulin has mainly positive effects on the lipid metabolism, which could cause beneficial effects during obesity development in long-term studies.

  7. Effects of dietary inulin on bacterial growth, short-chain fatty acid production and hepatic lipid metabolism in gnotobiotic mice.

    Science.gov (United States)

    Weitkunat, Karolin; Schumann, Sara; Petzke, Klaus Jürgen; Blaut, Michael; Loh, Gunnar; Klaus, Susanne

    2015-09-01

    In literature, contradictory effects of dietary fibers and their fermentation products, short-chain fatty acids (SCFA), are described: On one hand, they increase satiety, but on the other hand, they provide additional energy and promote obesity development. We aimed to answer this paradox by investigating the effects of fermentable and non-fermentable fibers on obesity induced by high-fat diet in gnotobiotic C3H/HeOuJ mice colonized with a simplified human microbiota. Mice were fed a high-fat diet supplemented either with 10% cellulose (non-fermentable) or inulin (fermentable) for 6 weeks. Feeding the inulin diet resulted in an increased diet digestibility and reduced feces energy, compared to the cellulose diet with no differences in food intake, suggesting an increased intestinal energy extraction from inulin. However, we observed no increase in body fat/weight. The additional energy provided by the inulin diet led to an increased bacterial proliferation in this group. Supplementation of inulin resulted further in significantly elevated concentrations of total SCFA in cecum and portal vein plasma, with a reduced cecal acetate:propionate ratio. Hepatic expression of genes involved in lipogenesis (Fasn, Gpam) and fatty acid elongation/desaturation (Scd1, Elovl3, Elovl6, Elovl5, Fads1 and Fads2) were decreased in inulin-fed animals. Accordingly, plasma and liver phospholipid composition were changed between the different feeding groups. Concentrations of omega-3 and odd-chain fatty acids were increased in inulin-fed mice, whereas omega-6 fatty acids were reduced. Taken together, these data indicate that, during this short-term feeding, inulin has mainly positive effects on the lipid metabolism, which could cause beneficial effects during obesity development in long-term studies. PMID:26033744

  8. Using artificial neural networks to predict the distribution of bacterial crop diseases from biotic and abiotic factors

    Directory of Open Access Journals (Sweden)

    Michael J. Watts

    2012-03-01

    Full Text Available Constructing accurate computational global distribution models is an important first step towards the understanding of bacterial crop diseases and can lead to insights into the biology of disease-causing bacteria species. We constructed artificial neural network models of the geographic distribution of six bacterial diseases of crop plants. These ANN modelled the distribution of these species from regional climatic factors and from regional assemblages of host crop plants. Multiple ANN were combined into ensembles using statistical methods. Tandem ANN, where an ANN combined the outputs of individual ANN, were also investigated. We found that for all but one species, superior accuracies were attained by methods that combined biotic and abiotic factors. These combinations were produced by both ensemble and cascaded ANN. This shows that firstly, ANN are able to model the geographic distribution of bacterial crop diseases, and secondly, that combining abiotic and biotic factors is necessary to achieve high modelling accuracies. The work reported in this paper therefore provides a basis for constructing models of the distribution of bacterial crop diseases.

  9. Metabolic networks to generate pyruvate, PEP and ATP from glycerol in Pseudomonas fluorescens.

    Science.gov (United States)

    Alhasawi, Azhar; Thomas, Sean C; Appanna, Vasu D

    2016-04-01

    Glycerol is a major by-product of the biodiesel industry. In this study we report on the metabolic networks involved in its transformation into pyruvate, phosphoenolpyruvate (PEP) and ATP. When the nutritionally-versatile Pseudomonas fluorescens was exposed to hydrogen peroxide (H2O2) in a mineral medium with glycerol as the sole carbon source, the microbe reconfigured its metabolism to generate adenosine triphosphate (ATP) primarily via substrate-level phosphorylation (SLP). This alternative ATP-producing stratagem resulted in the synthesis of copious amounts of PEP and pyruvate. The production of these metabolites was mediated via the enhanced activities of such enzymes as pyruvate carboxylase (PC) and phosphoenolpyruvate carboxylase (PEPC). The high energy PEP was subsequently converted into ATP with the aid of pyruvate phosphate dikinase (PPDK), phosphoenolpyruvate synthase (PEPS) and pyruvate kinase (PK) with the concomitant formation of pyruvate. The participation of the phospho-transfer enzymes like adenylate kinase (AK) and acetate kinase (ACK) ensured the efficiency of this O2-independent energy-generating machinery. The increased activity of glycerol dehydrogenase (GDH) in the stressed bacteria provided the necessary precursors to fuel this process. This H2O2-induced anaerobic life-style fortuitously evokes metabolic networks to an effective pathway that can be harnessed into the synthesis of ATP, PEP and pyruvate. The bioconversion of glycerol to pyruvate will offer interesting economic benefit. PMID:26920481

  10. 细菌应激反应中(p)ppGpp代谢的调控%Modulation of (p)ppGpp metabolism during bacterial stringent response

    Institute of Scientific and Technical Information of China (English)

    刘彪; 宁德刚

    2011-01-01

    (p)ppGpp is a well known intracellular signal that mediates bacterial stringent response to environment stresses through the change of its concentration level thus controls many important cellular processes for bacterial survival. In this review, we outline the mechanism of (p)ppGpp action, the enzyme system involved in (p)ppGpp metabolism, and summarize the signal transmission, the regulation and the diversity of (p)ppGpp metabolism. Moreover, we give a brief introduction on our achieved results recently about (p)ppGpp metabolism in cyanobacteria, and predict that a (p)ppGpp new metabolic mechanism different from those known exists in cyanobacteria.%(p)ppGpp是介导细菌细胞对环境胁迫产生应激反应的重要胞内信号,通过控制一系列重要的细胞活动使细菌得以生存.通过对蓝细菌中(p)ppGpp代谢的研究,对(p)ppGpp作用机制、控制(p)ppGpp代谢的酶系统、环境胁迫信号传递、细胞中(p)ppGpp水平的调控及其多样性进行了总结.

  11. Pseudomonas fluorescens induces strain-dependent and strain-independent host plant responses in defense networks, primary metabolism and photosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Pelletier, Dale A [ORNL; Morrell-Falvey, Jennifer L [ORNL; Karve, Abhijit A [ORNL; Lu, Tse-Yuan S [ORNL; Tschaplinski, Timothy J [ORNL; Tuskan, Gerald A [ORNL; Chen, Jay [ORNL; Martin, Madhavi Z [ORNL; Jawdy, Sara [ORNL; Weston, David [ORNL; Doktycz, Mitchel John [ORNL; Schadt, Christopher Warren [ORNL

    2012-01-01

    Colonization of plants by nonpathogenic Pseudomonas fluorescens strains can confer enhanced defense capacity against a broad spectrum of pathogens. Few studies, however, have linked defense pathway regulation to primary metabolism and physiology. In this study, physiological data, metabolites, and transcript profiles are integrated to elucidate how molecular networks initiated at the root-microbe interface influence shoot metabolism and whole-plant performance. Experiments with Arabidopsis thaliana were performed using the newly identified P. fluorescens GM30 or P. fluorescens Pf-5 strains. Co-expression networks indicated that Pf-5 and GM30 induced a subnetwork specific to roots enriched for genes participating in RNA regulation, protein degradation, and hormonal metabolism. In contrast, only GM30 induced a subnetwork enriched for calcium signaling, sugar and nutrient signaling, and auxin metabolism, suggesting strain dependence in network architecture. In addition, one subnetwork present in shoots was enriched for genes in secondary metabolism, photosynthetic light reactions, and hormone metabolism. Metabolite analysis indicated that this network initiated changes in carbohydrate and amino acid metabolism. Consistent with this, we observed strain-specific responses in tryptophan and phenylalanine abundance. Both strains reduced host plant carbon gain and fitness, yet provided a clear fitness benefit when plants were challenged with the pathogen P. syringae DC3000.

  12. Web-based metabolic network visualization with a zooming user interface

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2011-05-01

    Full Text Available Abstract Background Displaying complex metabolic-map diagrams, for Web browsers, and allowing users to interact with them for querying and overlaying expression data over them is challenging. Description We present a Web-based metabolic-map diagram, which can be interactively explored by the user, called the Cellular Overview. The main characteristic of this application is the zooming user interface enabling the user to focus on appropriate granularities of the network at will. Various searching commands are available to visually highlight sets of reactions, pathways, enzymes, metabolites, and so on. Expression data from single or multiple experiments can be overlaid on the diagram, which we call the Omics Viewer capability. The application provides Web services to highlight the diagram and to invoke the Omics Viewer. This application is entirely written in JavaScript for the client browsers and connect to a Pathway Tools Web server to retrieve data and diagrams. It uses the OpenLayers library to display tiled diagrams. Conclusions This new online tool is capable of displaying large and complex metabolic-map diagrams in a very interactive manner. This application is available as part of the Pathway Tools software that powers multiple metabolic databases including Biocyc.org: The Cellular Overview is accessible under the Tools menu.

  13. A Network Flow Analysis of the Nitrogen Metabolism in Beijing, China.

    Science.gov (United States)

    Zhang, Yan; Lu, Hanjing; Fath, Brian D; Zheng, Hongmei; Sun, Xiaoxi; Li, Yanxian

    2016-08-16

    Rapid urbanization results in high nitrogen flows and subsequent environmental consequences. In this study, we identified the main metabolic components (nitrogen inputs, flows, and outputs) and used ecological network analysis to track the direct and integral (direct + indirect) metabolic flows of nitrogen in Beijing, China, from 1996 to 2012 and to quantify the structure of Beijing's nitrogen metabolic processes. We found that Beijing's input of new reactive nitrogen (Q, which represents nitrogen obtained from the atmosphere or nitrogen-containing materials used in production and consumption to support human activities) increased from 431 Gg in 1996 to 507 Gg in 2012. Flows to the industry, atmosphere, and household, and components of the system were clearly largest, with total integrated inputs plus outputs from these nodes accounting for 31, 29, and 15%, respectively, of the total integral flows for all paths. The flows through the sewage treatment and transportation components showed marked growth, with total integrated inputs plus outputs increasing to 3.7 and 5.2 times their 1996 values, respectively. Our results can help policymakers to locate the key nodes and pathways in an urban nitrogen metabolic system so they can monitor and manage these components of the system. PMID:27406465

  14. Genome-scale reconstruction of metabolic network for a halophilic extremophile, Chromohalobacter salexigens DSM 3043

    Directory of Open Access Journals (Sweden)

    Oner Ebru

    2011-01-01

    Full Text Available Abstract Background Chromohalobacter salexigens (formerly Halomonas elongata DSM 3043 is a halophilic extremophile with a very broad salinity range and is used as a model organism to elucidate prokaryotic osmoadaptation due to its strong euryhaline phenotype. Results C. salexigens DSM 3043's metabolism was reconstructed based on genomic, biochemical and physiological information via a non-automated but iterative process. This manually-curated reconstruction accounts for 584 genes, 1386 reactions, and 1411 metabolites. By using flux balance analysis, the model was extensively validated against literature data on the C. salexigens phenotypic features, the transport and use of different substrates for growth as well as against experimental observations on the uptake and accumulation of industrially important organic osmolytes, ectoine, betaine, and its precursor choline, which play important roles in the adaptive response to osmotic stress. Conclusions This work presents the first comprehensive genome-scale metabolic model of a halophilic bacterium. Being a useful guide for identification and filling of knowledge gaps, the reconstructed metabolic network iOA584 will accelerate the research on halophilic bacteria towards application of systems biology approaches and design of metabolic engineering strategies.

  15. The DtxR protein acting as dual transcriptional regulator directs a global regulatory network involved in iron metabolism of Corynebacterium glutamicum

    Directory of Open Access Journals (Sweden)

    Hüser Andrea T

    2006-02-01

    Full Text Available Abstract Background The knowledge about complete bacterial genome sequences opens the way to reconstruct the qualitative topology and global connectivity of transcriptional regulatory networks. Since iron is essential for a variety of cellular processes but also poses problems in biological systems due to its high toxicity, bacteria have evolved complex transcriptional regulatory networks to achieve an effective iron homeostasis. Here, we apply a combination of transcriptomics, bioinformatics, in vitro assays, and comparative genomics to decipher the regulatory network of the iron-dependent transcriptional regulator DtxR of Corynebacterium glutamicum. Results A deletion of the dtxR gene of C. glutamicum ATCC 13032 led to the mutant strain C. glutamicum IB2103 that was able to grow in minimal medium only under low-iron conditions. By performing genome-wide DNA microarray hybridizations, differentially expressed genes involved in iron metabolism of C. glutamicum were detected in the dtxR mutant. Bioinformatics analysis of the genome sequence identified a common 19-bp motif within the upstream region of 31 genes, whose differential expression in C. glutamicum IB2103 was verified by real-time reverse transcription PCR. Binding of a His-tagged DtxR protein to oligonucleotides containing the 19-bp motifs was demonstrated in vitro by DNA band shift assays. At least 64 genes encoding a variety of physiological functions in iron transport and utilization, in central carbohydrate metabolism and in transcriptional regulation are controlled directly by the DtxR protein. A comparison with the bioinformatically predicted networks of C. efficiens, C. diphtheriae and C. jeikeium identified evolutionary conserved elements of the DtxR network. Conclusion This work adds considerably to our currrent understanding of the transcriptional regulatory network of C. glutamicum genes that are controlled by DtxR. The DtxR protein has a major role in controlling the

  16. Metabolic network analysis of Bacillus clausii on minimal and semirich medium using C-13-Labeled glucose

    DEFF Research Database (Denmark)

    Christiansen, Torben; Christensen, Bjarke; Nielsen, Jens

    2002-01-01

    or zero flux through PEP carboxykinase was estimated, indicating that the latter enzyme was not active during growth on glucose. The uptake of the amino acids in a semirich medium containing 15 of the 20 amino acids normally present in proteins was estimated using fully labeled glucose in batch...... from the medium and partly synthesized from glucose. The metabolic network analysis was extended to include analysis of growth on the semirich medium containing amino acids, and the metabolic flux distribution on this medium was estimated and compared with growth on minimal medium....... cultivations. It was found that leucine, isoleucine, and phenylalanine were taken up from the medium and not synthesized de novo from glucose. In contrast, serine and threonine were completely synthesized from other metabolites and not taken up from the medium. Valine, proline, and lysine were partly taken up...

  17. Systematic construction of kinetic models from genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Natalie J Stanford

    Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

  18. Increasing galactose consumption by Saccharomyces cerevisiae through metabolic engineering of the GAL gene regulatory network

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Johnston, M.;

    2000-01-01

    by eliminating three known negative regulators of the GAL system: Gale, Gal80, and Mig1. This led to a 41% increase in flux through the galactose utilization pathway compared with the wild-type strain. This is of significant interest within the field of biotechnology since galactose is present in many industrial...... in the pathway, and ultimately, increasing metabolic flux through the pathway of interest, By manipulating the GAL gene regulatory network of Saccharomyces cerevisiae, which is a tightly regulated system, we produced prototroph mutant strains, which increased the flux through the galactose utilization pathway...... media. The improved galactose consumption of the gal mutants did not favor biomass formation, but rather caused excessive respiro-fermentative metabolism, with the ethanol production rate increasing linearly with glycolytic flux....

  19. Reconstruction and in silico analysis of metabolic network for an oleaginous yeast, Yarrowia lipolytica.

    Directory of Open Access Journals (Sweden)

    Pengcheng Pan

    Full Text Available With the emergence of energy scarcity, the use of renewable energy sources such as biodiesel is becoming increasingly necessary. Recently, many researchers have focused their minds on Yarrowia lipolytica, a model oleaginous yeast, which can be employed to accumulate large amounts of lipids that could be further converted to biodiesel. In order to understand the metabolic characteristics of Y. lipolytica at a systems level and to examine the potential for enhanced lipid production, a genome-scale compartmentalized metabolic network was reconstructed based on a combination of genome annotation and the detailed biochemical knowledge from multiple databases such as KEGG, ENZYME and BIGG. The information about protein and reaction associations of all the organisms in KEGG and Expasy-ENZYME database was arranged into an EXCEL file that can then be regarded as a new useful database to generate other reconstructions. The generated model iYL619_PCP accounts for 619 genes, 843 metabolites and 1,142 reactions including 236 transport reactions, 125 exchange reactions and 13 spontaneous reactions. The in silico model successfully predicted the minimal media and the growing abilities on different substrates. With flux balance analysis, single gene knockouts were also simulated to predict the essential genes and partially essential genes. In addition, flux variability analysis was applied to design new mutant strains that will redirect fluxes through the network and may enhance the production of lipid. This genome-scale metabolic model of Y. lipolytica can facilitate system-level metabolic analysis as well as strain development for improving the production of biodiesels and other valuable products by Y. lipolytica and other closely related oleaginous yeasts.

  20. Metabolism

    Science.gov (United States)

    ... a particular food provides to the body. A chocolate bar has more calories than an apple, so ... More Common in People With Type 1 Diabetes Metabolic Syndrome Your Child's Weight Healthy Eating Endocrine System Blood ...

  1. Metagenomic signatures of a tropical mining-impacted stream reveal complex microbial and metabolic networks.

    Science.gov (United States)

    Reis, Mariana P; Dias, Marcela F; Costa, Patrícia S; Ávila, Marcelo P; Leite, Laura R; de Araújo, Flávio M G; Salim, Anna C M; Bucciarelli-Rodriguez, Mônica; Oliveira, Guilherme; Chartone-Souza, Edmar; Nascimento, Andréa M A

    2016-10-01

    Bacteria from aquatic ecosystems significantly contribute to biogeochemical cycles, but details of their community structure in tropical mining-impacted environments remain unexplored. In this study, we analyzed a bacterial community from circumneutral-pH tropical stream sediment by 16S rRNA and shotgun deep sequencing. Carrapatos stream sediment, which has been exposed to metal stress due to gold and iron mining (21 [g Fe]/kg), revealed a diverse community, with predominance of Proteobacteria (39.4%), Bacteroidetes (12.2%), and Parcubacteria (11.4%). Among Proteobacteria, the most abundant reads were assigned to neutrophilic iron-oxidizing taxa, such as Gallionella, Sideroxydans, and Mariprofundus, which are involved in Fe cycling and harbor several metal resistance genes. Functional analysis revealed a large number of genes participating in nitrogen and methane metabolic pathways despite the low concentrations of inorganic nitrogen in the Carrapatos stream. Our findings provide important insights into bacterial community interactions in a mining-impacted environment. PMID:27441985

  2. optGpSampler: an improved tool for uniformly sampling the solution-space of genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Wout Megchelenbrink

    Full Text Available Constraint-based models of metabolic networks are typically underdetermined, because they contain more reactions than metabolites. Therefore the solutions to this system do not consist of unique flux rates for each reaction, but rather a space of possible flux rates. By uniformly sampling this space, an estimated probability distribution for each reaction's flux in the network can be obtained. However, sampling a high dimensional network is time-consuming. Furthermore, the constraints imposed on the network give rise to an irregularly shaped solution space. Therefore more tailored, efficient sampling methods are needed. We propose an efficient sampling algorithm (called optGpSampler, which implements the Artificial Centering Hit-and-Run algorithm in a different manner than the sampling algorithm implemented in the COBRA Toolbox for metabolic network analysis, here called gpSampler. Results of extensive experiments on different genome-scale metabolic networks show that optGpSampler is up to 40 times faster than gpSampler. Application of existing convergence diagnostics on small network reconstructions indicate that optGpSampler converges roughly ten times faster than gpSampler towards similar sampling distributions. For networks of higher dimension (i.e. containing more than 500 reactions, we observed significantly better convergence of optGpSampler and a large deviation between the samples generated by the two algorithms.optGpSampler for Matlab and Python is available for non-commercial use at: http://cs.ru.nl/~wmegchel/optGpSampler/.

  3. Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors

    Directory of Open Access Journals (Sweden)

    Holschneider Matthias

    2007-05-01

    Full Text Available Abstract Background The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A tight control over metabolite ratios will be reflected by a linear relationship of pairs of metabolite due to the flexibility of metabolic pathways. Hence, unbiased detection and validation of linear metabolic variance can be interpreted in terms of biological control. For robust analyses, criteria for rejecting or accepting linearities need to be developed despite technical measurement errors. The entirety of all pair wise linear metabolic relationships then yields insights into the network of cellular regulation. Results The Bayesian law was applied for detecting linearities that are validated by explaining the residues by the degree of technical measurement errors. Test statistics were developed and the algorithm was tested on simulated data using 3–150 samples and 0–100% technical error. Under the null hypothesis of the existence of a linear relationship, type I errors remained below 5% for data sets consisting of more than four samples, whereas the type II error rate quickly raised with increasing technical errors. Conversely, a filter was developed to balance the error rates in the opposite direction. A minimum of 20 biological replicates is recommended if technical errors remain below 20% relative standard deviation and if thresholds for false error rates are acceptable at less than 5%. The algorithm was proven to be robust against outliers, unlike Pearson's correlations. Conclusion The algorithm facilitates finding linear relationships in complex datasets, which is radically different from estimating linearity parameters from given linear relationships. Without filter, it provides high sensitivity and fair specificity. If the filter is activated, high specificity but only fair sensitivity is yielded. Total error rates are more favorable with

  4. Detection of denitrification genes by in situ rolling circle amplification - fluorescence in situ hybridization (in situ RCA-FISH) to link metabolic potential with identity inside bacterial cells

    DEFF Research Database (Denmark)

    Hoshino, Tatsuhiko; Schramm, Andreas

    2010-01-01

    A target-primed in situ rolling circle amplification (in situ RCA) protocol was developed for detection of single-copy genes inside bacterial cells and optimized with Pseudomonas stutzeri, targeting nitrite and nitrous oxide reductase genes (nirS and nosZ). Two padlock probes were designed per gene...... as Candidatus Accumulibacter phosphatis by combining in situ RCA-FISH with 16S rRNA-targeted FISH. While not suitable for quantification because of its low detection frequency, in situ RCA-FISH will allow to link metabolic potential with 16S rRNA (gene)-based identification of single microbial cells....

  5. Convergent evolution of modularity in metabolic networks through different community structures

    Directory of Open Access Journals (Sweden)

    Zhou Wanding

    2012-09-01

    Full Text Available Abstract Background It has been reported that the modularity of metabolic networks of bacteria is closely related to the variability of their living habitats. However, given the dependency of the modularity score on the community structure, it remains unknown whether organisms achieve certain modularity via similar or different community structures. Results In this work, we studied the relationship between similarities in modularity scores and similarities in community structures of the metabolic networks of 1021 species. Both similarities are then compared against the genetic distances. We revisited the association between modularity and variability of the microbial living environments and extended the analysis to other aspects of their life style such as temperature and oxygen requirements. We also tested both topological and biological intuition of the community structures identified and investigated the extent of their conservation with respect to the taxomony. Conclusions We find that similar modularities are realized by different community structures. We find that such convergent evolution of modularity is closely associated with the number of (distinct enzymes in the organism’s metabolome, a consequence of different life styles of the species. We find that the order of modularity is the same as the order of the number of the enzymes under the classification based on the temperature preference but not on the oxygen requirement. Besides, inspection of modularity-based communities reveals that these communities are graph-theoretically meaningful yet not reflective of specific biological functions. From an evolutionary perspective, we find that the community structures are conserved only at the level of kingdoms. Our results call for more investigation into the interplay between evolution and modularity: how evolution shapes modularity, and how modularity affects evolution (mainly in terms of fitness and evolvability. Further, our results

  6. Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology.

    Directory of Open Access Journals (Sweden)

    Jacek Puchałka

    2008-10-01

    Full Text Available A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile

  7. Metabolic network reconstruction and flux variability analysis of storage synthesis in developing oilseed rape (Brassica napus L.) embryos

    Energy Technology Data Exchange (ETDEWEB)

    Hay, J.; Schwender, J.

    2011-08-01

    Computational simulation of large-scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganic nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10-11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one-third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty-seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.

  8. Fibroblast growth factor 23 and Klotho: physiology and pathophysiology of an endocrine network of mineral metabolism.

    Science.gov (United States)

    Hu, Ming Chang; Shiizaki, Kazuhiro; Kuro-o, Makoto; Moe, Orson W

    2013-01-01

    The metabolically active and perpetually remodeling calcium phosphate-based endoskeleton in terrestrial vertebrates sets the demands on whole-organism calcium and phosphate homeostasis that involves multiple organs in terms of mineral flux and endocrine cross talk. The fibroblast growth factor (FGF)-Klotho endocrine networks epitomize the complexity of systems biology, and specifically, the FGF23-αKlotho axis highlights the concept of the skeleton holding the master switch of homeostasis rather than a passive target organ as hitherto conceived. Other than serving as a coreceptor for FGF23, αKlotho circulates as an endocrine substance with a multitude of effects. This review covers recent data on the physiological regulation and function of the complex FGF23-αKlotho network. Chronic kidney disease is a common pathophysiological state in which FGF23-αKlotho, a multiorgan endocrine network, is deranged in a self-amplifying vortex resulting in organ dysfunction of the utmost severity that contributes to its morbidity and mortality. PMID:23398153

  9. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks.

    Science.gov (United States)

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2013-05-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three subnetworks. It turns out that our reaction classifier, which is blind to the biochemical role of pathways, leads to three functionally relevant subnetworks that correspond to input, output, and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality. PMID:23767567

  10. Metabolic flux analysis of hydrogen production network by Clostridium butyricum W5: Effect of pH and glucose concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Cai, Guiqin [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); Jin, Bo [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); School of Chemical Engineering, The University of Adelaide, Adelaide, SA 5005 (Australia); Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia); Saint, Chris [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia); Monis, Paul [Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia)

    2010-07-15

    Fermentative hydrogen production by strict anaerobes has been widely reported. There is a lack of information related to metabolic flux distribution and its variation with respect to fermentation conditions in the metabolic production system. This study aimed to get a better understanding of the metabolic network and to conduct metabolic flux analysis (MFA) of fermentative hydrogen production by a recently isolated Clostridium butyricum strain W5. We chose the specific growth rate as the objective function and used specific H{sub 2} production rate as the criterion to evaluate the experimental results with the in silico MFA. For the first time, we constructed an in silico metabolic flux model for the anaerobic glucose metabolism of C. butyricum W5 with assistance of a modeling program MetaFluxNet. The model was used to evaluate metabolic flux distribution in the fermentative hydrogen production network, and to study the fractional flux response to variations in initial glucose concentration and operational pH. The MFA results suggested that pH has a more significant effect on hydrogen production yield compared to the glucose concentration. The MFA is a useful tool to provide valuable information for optimization and design of the fermentative hydrogen production process. (author)

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

    Science.gov (United States)

    Photorespiration is an important high flux metabolic pathway that is found in all oxygen-producing photosynthetic organisms. It is often viewed as a closed loop that recycles carbon to fuel the Calvin cycle. However, the photorespiratory cycle is known to interact with several primary metabolic path...

  12. Within-Host Bacterial Diversity Hinders Accurate Reconstruction of Transmission Networks from Genomic Distance Data

    OpenAIRE

    Worby, Colin J.; Marc Lipsitch; William P Hanage

    2014-01-01

    The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmis...

  13. Within-host bacterial diversity hinders accurate reconstruction of transmission networks from genomic distance data.

    OpenAIRE

    Worby, Colin J.; Marc Lipsitch; Hanage, William P

    2014-01-01

    The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmis...

  14. Rhinal hypometabolism on FDG PET in healthy APO-E4 carriers: impact on memory function and metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Didic, Mira; Felician, Olivier; Gour, Natalina; Ceccaldi, Mathieu [Pole de Neurosciences Cliniques, Centre Hospitalo-Universitaire de la Timone, AP-HM, Service de Neurologie and Neuropsychologie, Marseille (France); Aix Marseille Universite, Inserm, INS UMRS 1106, Marseille (France); Bernard, Rafaelle; Pecheux, Christophe [Centre Hospitalo-Universitaire de la Timone, AP-HM, et INSERM UMRS 910: ' ' Genetique Medicale et Genomique fonctionnelle' ' , Departement de Genetique Medicale, Marseille (France); Mundler, Olivier; Guedj, Eric [Centre Hospitalo-Universitaire de la Timone, AP-HM, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Aix Marseille Universite, CERIMED, CNRS UMR7289, INT, Marseille (France); Aix Marseille Universite, CNRS UMR7289, INT, Marseille (France)

    2015-09-15

    The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors. Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects. APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks. Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of

  15. Rhinal hypometabolism on FDG PET in healthy APO-E4 carriers: impact on memory function and metabolic networks

    International Nuclear Information System (INIS)

    The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors. Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects. APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks. Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of

  16. Integer programming-based method for designing synthetic metabolic networks by Minimum Reaction Insertion in a Boolean model.

    Directory of Open Access Journals (Sweden)

    Wei Lu

    Full Text Available In this paper, we consider the Minimum Reaction Insertion (MRI problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at "http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html."

  17. Integer programming-based method for designing synthetic metabolic networks by Minimum Reaction Insertion in a Boolean model.

    Science.gov (United States)

    Lu, Wei; Tamura, Takeyuki; Song, Jiangning; Akutsu, Tatsuya

    2014-01-01

    In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA)-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at "http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html."

  18. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

    OpenAIRE

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2012-01-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking ...

  19. Different brain networks underlying the acquisition and expression of contextual fear conditioning: a metabolic mapping study.

    Science.gov (United States)

    González-Pardo, H; Conejo, N M; Lana, G; Arias, J L

    2012-01-27

    The specific brain regions and circuits involved in the acquisition and expression of contextual fear conditioning are still a matter of debate. To address this issue, regional changes in brain metabolic capacity were mapped during the acquisition and expression of contextual fear conditioning using cytochrome oxidase (CO) quantitative histochemistry. In comparison with a group briefly exposed to a conditioning chamber, rats that received a series of randomly presented footshocks in the same conditioning chamber (fear acquisition group) showed increased CO activity in anxiety-related brain regions like the ventral periaqueductal gray, the ventral hippocampus, the lateral habenula, the mammillary bodies, and the laterodorsal thalamic nucleus. Another group received randomly presented footshocks, and it was re-exposed to the same conditioning chamber one week later (fear expression group). The conditioned group had significantly higher CO activity as compared with the matched control group in the following brain regions: the ventral periaqueductal gray, the central and lateral nuclei of the amygdala, and the bed nucleus of the stria terminalis. In addition, analysis of functional brain networks using interregional CO activity correlations revealed different patterns of functional connectivity between fear acquisition and fear expression groups. In particular, a network comprising the ventral hippocampus and amygdala nuclei was found in the fear acquisition group, whereas a closed reciprocal dorsal hippocampal network was detected in the fear expression group. These results suggest that contextual fear acquisition and expression differ as regards to the brain networks involved, although they share common brain regions involved in fear, anxiety, and defensive behavior. PMID:22173014

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

    Science.gov (United States)

    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

  1. Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction

    Directory of Open Access Journals (Sweden)

    Panda Gurudutta

    2011-05-01

    Full Text Available Abstract Background Burkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets. Results We reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets. Conclusions As the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.

  2. Integrated bioinformatics to decipher the ascorbic acid metabolic network in tomato.

    Science.gov (United States)

    Ruggieri, Valentino; Bostan, Hamed; Barone, Amalia; Frusciante, Luigi; Chiusano, Maria Luisa

    2016-07-01

    Ascorbic acid is involved in a plethora of reactions in both plant and animal metabolism. It plays an essential role neutralizing free radicals and acting as enzyme co-factor in several reaction. Since humans are ascorbate auxotrophs, enhancing the nutritional quality of a widely consumed vegetable like tomato is a desirable goal. Although the main reactions of the ascorbate biosynthesis, recycling and translocation pathways have been characterized, the assignment of tomato genes to each enzymatic step of the entire network has never been reported to date. By integrating bioinformatics approaches, omics resources and transcriptome collections today available for tomato, this study provides an overview on the architecture of the ascorbate pathway. In particular, 237 tomato loci were associated with the different enzymatic steps of the network, establishing the first comprehensive reference collection of candidate genes based on the recently released tomato gene annotation. The co-expression analyses performed by using RNA-Seq data supported the functional investigation of main expression patterns for the candidate genes and highlighted a coordinated spatial-temporal regulation of genes of the different pathways across tissues and developmental stages. Taken together these results provide evidence of a complex interplaying mechanism and highlight the pivotal role of functional related genes. The definition of genes contributing to alternative pathways and their expression profiles corroborates previous hypothesis on mechanisms of accumulation of ascorbate in the later stages of fruit ripening. Results and evidences here provided may facilitate the development of novel strategies for biofortification of tomato fruit with Vitamin C and offer an example framework for similar studies concerning other metabolic pathways and species. PMID:27007138

  3. Bistability in a metabolic network underpins the de novo evolution of colony switching in Pseudomonas fluorescens.

    Directory of Open Access Journals (Sweden)

    Jenna Gallie

    2015-03-01

    Full Text Available Phenotype switching is commonly observed in nature. This prevalence has allowed the elucidation of a number of underlying molecular mechanisms. However, little is known about how phenotypic switches arise and function in their early evolutionary stages. The first opportunity to provide empirical insight was delivered by an experiment in which populations of the bacterium Pseudomonas fluorescens SBW25 evolved, de novo, the ability to switch between two colony phenotypes. Here we unravel the molecular mechanism behind colony switching, revealing how a single nucleotide change in a gene enmeshed in central metabolism (carB generates such a striking phenotype. We show that colony switching is underpinned by ON/OFF expression of capsules consisting of a colanic acid-like polymer. We use molecular genetics, biochemical analyses, and experimental evolution to establish that capsule switching results from perturbation of the pyrimidine biosynthetic pathway. Of central importance is a bifurcation point at which uracil triphosphate is partitioned towards either nucleotide metabolism or polymer production. This bifurcation marks a cell-fate decision point whereby cells with relatively high pyrimidine levels favour nucleotide metabolism (capsule OFF, while cells with lower pyrimidine levels divert resources towards polymer biosynthesis (capsule ON. This decision point is present and functional in the wild-type strain. Finally, we present a simple mathematical model demonstrating that the molecular components of the decision point are capable of producing switching. Despite its simple mutational cause, the connection between genotype and phenotype is complex and multidimensional, offering a rare glimpse of how noise in regulatory networks can provide opportunity for evolution.

  4. Reduced metabolism in brain "control networks" following cocaine-cues exposure in female cocaine abusers.

    Directory of Open Access Journals (Sweden)

    Nora D Volkow

    Full Text Available OBJECTIVE: Gender differences in vulnerability for cocaine addiction have been reported. Though the mechanisms are not understood, here we hypothesize that gender differences in reactivity to conditioned-cues, which contributes to relapse, are involved. METHOD: To test this we compared brain metabolism (using PET and ¹⁸FDG between female (n = 10 and male (n = 16 active cocaine abusers when they watched a neutral video (nature scenes versus a cocaine-cues video. RESULTS: Self-reports of craving increased with the cocaine-cue video but responses did not differ between genders. In contrast, changes in whole brain metabolism with cocaine-cues differed by gender (p<0.05; females significantly decreased metabolism (-8.6%±10 whereas males tended to increase it (+5.5%±18. SPM analysis (Cocaine-cues vs Neutral in females revealed decreases in frontal, cingulate and parietal cortices, thalamus and midbrain (p<0.001 whereas males showed increases in right inferior frontal gyrus (BA 44/45 (only at p<0.005. The gender-cue interaction showed greater decrements with Cocaine-cues in females than males (p<0.001 in frontal (BA 8, 9, 10, anterior cingulate (BA 24, 32, posterior cingulate (BA 23, 31, inferior parietal (BA 40 and thalamus (dorsomedial nucleus. CONCLUSIONS: Females showed greater brain reactivity to cocaine-cues than males but no differences in craving, suggesting that there may be gender differences in response to cues that are not linked with craving but could affect subsequent drug use. Specifically deactivation of brain regions from "control networks" (prefrontal, cingulate, inferior parietal, thalamus in females could increase their vulnerability to relapse since it would interfere with executive function (cognitive inhibition. This highlights the importance of gender tailored interventions for cocaine addiction.

  5. Reduced Metabolism in Brain 'Control Networks' Following Cocaine-Cues Exposure in Female Cocaine Abusers

    International Nuclear Information System (INIS)

    Gender differences in vulnerability for cocaine addiction have been reported. Though the mechanisms are not understood, here we hypothesize that gender differences in reactivity to conditioned-cues, which contributes to relapse, are involved. To test this we compared brain metabolism (using PET and 18FDG) between female (n = 10) and male (n = 16) active cocaine abusers when they watched a neutral video (nature scenes) versus a cocaine-cues video. Self-reports of craving increased with the cocaine-cue video but responses did not differ between genders. In contrast, changes in whole brain metabolism with cocaine-cues differed by gender (p<0.05); females significantly decreased metabolism (-8.6% ± 10) whereas males tended to increase it (+5.5% ± 18). SPM analysis (Cocaine-cues vs Neutral) in females revealed decreases in frontal, cingulate and parietal cortices, thalamus and midbrain (p<0.001) whereas males showed increases in right inferior frontal gyrus (BA 44/45) (only at p<0.005). The gender-cue interaction showed greater decrements with Cocaine-cues in females than males (p<0.001) in frontal (BA 8, 9, 10), anterior cingulate (BA 24, 32), posterior cingulate (BA 23, 31), inferior parietal (BA 40) and thalamus (dorsomedial nucleus). Females showed greater brain reactivity to cocaine-cues than males but no differences in craving, suggesting that there may be gender differences in response to cues that are not linked with craving but could affect subsequent drug use. Specifically deactivation of brain regions from 'control networks' (prefrontal, cingulate, inferior parietal, thalamus) in females could increase their vulnerability to relapse since it would interfere with executive function (cognitive inhibition). This highlights the importance of gender tailored interventions for cocaine addiction.

  6. Regulatory network of secondary metabolism in Brassica rapa: insight into the glucosinolate pathway.

    Directory of Open Access Journals (Sweden)

    Dunia Pino Del Carpio

    Full Text Available Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leaves from six weeks-old plants of a Brassica rapa doubled haploid population, consisting of 92 genotypes, were profiled for their secondary metabolite composition, using both targeted and LC-MS-based untargeted metabolomics approaches. Furthermore, the same population was profiled for transcript variation using a microarray containing EST sequences mainly derived from three Brassica species: B. napus, B. rapa and B. oleracea. The biochemical pathway analysis was based on the network analyses of both metabolite QTLs (mQTLs and transcript QTLs (eQTLs. Co-localization of mQTLs and eQTLs lead to the identification of candidate regulatory genes involved in the biosynthesis of carotenoids, tocopherols and glucosinolates. We subsequently focused on the well-characterized glucosinolate pathway and revealed two hotspots of co-localization of eQTLs with mQTLs in linkage groups A03 and A09. Our results indicate that such a large-scale genetical genomics approach combining transcriptomics and metabolomics data can provide new insights into the genetic regulation of metabolite composition of Brassica vegetables.

  7. Metabolic network analysis on Phaffia rhodozyma yeast using C-13-labeled glucose and gas chromatography-mass spectrometry

    DEFF Research Database (Denmark)

    Cannizzaro, C.; Christensen, B.; Nielsen, Jens;

    2004-01-01

    labeling patterns, as determined by GC-MS, were in accordance with a metabolic network consisting of the Embden-Meyerhof-Parnas pathway, the pentose phosphate pathway, and the TCA cycle. Glucose was mainly consumed along the pentose phosphate pathway (similar to65% for wildtype strain), which reflected...

  8. Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes

    DEFF Research Database (Denmark)

    Min, Josine L; Nicholson, George; Halgrimsdottir, Ingileif;

    2012-01-01

    Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abdominal (ABD) and gluteal (GLU) adipose tissue, ...

  9. Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

    Directory of Open Access Journals (Sweden)

    Klipp Edda

    2006-12-01

    Full Text Available Abstract Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. Conclusion Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases.

  10. Evolutionary remodeling of global regulatory networks during long-term bacterial adaptation to human hosts

    DEFF Research Database (Denmark)

    Pedersen, Søren Damkiær; Yang, Lei; Molin, Søren;

    2013-01-01

    underwent substantial phenotypic changes, which correlated with temporal fixation of specific mutations in the genes mucA (frame-shift), algT (substitution), rpoN (substitution), lasR (deletion), and rpoD (in-frame deletion), all encoding regulators of large gene networks. To clarify the consequences...

  11. Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network

    Directory of Open Access Journals (Sweden)

    Jacopo Aguzzi

    2011-11-01

    Full Text Available The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada deploys seafloor camera systems at several sites. Our objective in this study was to implement new automated image analysis protocols for the recognition and counting of benthic decapods (i.e., the galatheid squat lobster, Munida quadrispina, as well as for the evaluation of changes in bacterial mat coverage (i.e., Beggiatoa spp., using a camera deployed in Saanich Inlet (103 m depth. For the counting of Munida we remotely acquired 100 digital photos at hourly intervals from 2 to 6 December 2009. In the case of bacterial mat coverage estimation, images were taken from 2 to 8 December 2009 at the same time frequency. The automated image analysis protocols for both study cases were created in MatLab 7.1. Automation for Munida counting incorporated the combination of both filtering and background correction (Median- and Top-Hat Filters with Euclidean Distances (ED on Red-Green-Blue (RGB channels. The Scale-Invariant Feature Transform (SIFT features and Fourier Descriptors (FD of tracked objects were then extracted. Animal classifications were carried out with the tools of morphometric multivariate statistic (i.e., Partial Least Square Discriminant Analysis; PLSDA on Mean RGB (RGBv value for each object and Fourier Descriptors (RGBv+FD matrices plus SIFT and ED. The SIFT approach returned the better results. Higher percentages of images were correctly classified and lower misclassification errors (an animal is present but not detected occurred. In contrast, RGBv+FD and ED resulted in a high incidence of records being generated for non-present animals. Bacterial mat coverage was estimated in terms of Percent

  12. Diverse ways of perturbing the human arachidonic acid metabolic network to control inflammation.

    Science.gov (United States)

    Meng, Hu; Liu, Ying; Lai, Luhua

    2015-08-18

    Inflammation and other common disorders including diabetes, cardiovascular disease, and cancer are often the result of several molecular abnormalities and are not likely to be resolved by a traditional single-target drug discovery approach. Though inflammation is a normal bodily reaction, uncontrolled and misdirected inflammation can cause inflammatory diseases such as rheumatoid arthritis and asthma. Nonsteroidal anti-inflammatory drugs including aspirin, ibuprofen, naproxen, or celecoxib are commonly used to relieve aches and pains, but often these drugs have undesirable and sometimes even fatal side effects. To facilitate safer and more effective anti-inflammatory drug discovery, a balanced treatment strategy should be developed at the biological network level. In this Account, we focus on our recent progress in modeling the inflammation-related arachidonic acid (AA) metabolic network and subsequent multiple drug design. We first constructed a mathematical model of inflammation based on experimental data and then applied the model to simulate the effects of commonly used anti-inflammatory drugs. Our results indicated that the model correctly reproduced the established bleeding and cardiovascular side effects. Multitarget optimal intervention (MTOI), a Monte Carlo simulated annealing based computational scheme, was then developed to identify key targets and optimal solutions for controlling inflammation. A number of optimal multitarget strategies were discovered that were both effective and safe and had minimal associated side effects. Experimental studies were performed to evaluate these multitarget control solutions further using different combinations of inhibitors to perturb the network. Consequently, simultaneous control of cyclooxygenase-1 and -2 and leukotriene A4 hydrolase, as well as 5-lipoxygenase and prostaglandin E2 synthase were found to be among the best solutions. A single compound that can bind multiple targets presents advantages including low

  13. Stereoselective metabolism of dibenz(a,h)anthracene to trans-dihydrodiols and their activation to bacterial mutagens.

    OpenAIRE

    Platt, K L; Schollmeier, M.; Frank, H; Oesch, F

    1990-01-01

    Dibenz(a,h)anthracene (DBA), a carcinogenic, polycyclic aromatic hydrocarbon ubiquitous in the environment, is metabolized by the hepatic microsomal fraction of immature Sprague-Dawley rats pretreated with Aroclor 1254 to 27 ethyl acetate-extractable metabolites. More than half of these metabolites (51%) consisted of trans-1,2-; -3,4-; and -5,6-dihydrodiols including their identified secondary metabolites. The three trans-dihydrodiols (4.9, 15.8, and 0.6% of total metabolic conversion) were h...

  14. Metabolic Engineering of Potato Carotenoid Content through Tuber-Specific Overexpression of a Bacterial Mini-Pathway

    OpenAIRE

    Gianfranco Diretto; Salim Al-Babili; Raffaela Tavazza; Velia Papacchioli; Peter Beyer; Giovanni Giuliano

    2007-01-01

    BACKGROUND: Since the creation of "Golden Rice", biofortification of plant-derived foods is a promising strategy for the alleviation of nutritional deficiencies. Potato is the most important staple food for mankind after the cereals rice, wheat and maize, and is extremely poor in provitamin A carotenoids. METHODOLOGY: We transformed potato with a mini-pathway of bacterial origin, driving the synthesis of beta-carotene (Provitamin A) from geranylgeranyl diphosphate. Three genes, encoding phyto...

  15. Metabolism of DMSP, DMS and DMSO by the cultivable bacterial community associated with the DMSP-producing dinoflagellate Scrippsiella trochoidea

    Digital Repository Service at National Institute of Oceanography (India)

    Hatton, A.D.; Shenoy, D.M.; Hart, M.C.; Mogg, A.; Green, D.H.

    (Table 3). However, in each case the full amount of the DMS lost could be accounted for via the formation of DMSO (Table 3). DMS oxidation rates were calculated for each species, both in the presence and absence of glucose. Results showed oxidation... experiments confirmed that of the thirteen cultivatable bacterial strains tested only two, DG1236 and DG1229, could metabolise DMSP. Both strains appeared to be capable of metabolising DMSP via both DMSP assimilatory pathways (e.g., demethylation) and DMSP...

  16. A Bacterial Glucanotransferase Can Replace the Complex Maltose Metabolism Required for Starch to Sucrose Conversion in Leaves at Night

    DEFF Research Database (Denmark)

    Ruzanski, Christian; Smirnova, Julia; Rejzek, Martin;

    2013-01-01

    Controlled conversion of leaf starch to sucrose at night is essential for the normal growth of Arabidopsis. The conversion involves the cytosolic metabolism of maltose to hexose phosphates via an unusual, multidomain protein with 4-glucanotransferase activity, DPE2, believed to transfer glucosyl...

  17. SS-mPMG and SS-GA: tools for finding pathways and dynamic simulation of metabolic networks.

    Science.gov (United States)

    Katsuragi, Tetsuo; Ono, Naoaki; Yasumoto, Keiichi; Altaf-Ul-Amin, Md; Hirai, Masami Y; Sriyudthsak, Kansuporn; Sawada, Yuji; Yamashita, Yui; Chiba, Yukako; Onouchi, Hitoshi; Fujiwara, Toru; Naito, Satoshi; Shiraishi, Fumihide; Kanaya, Shigehiko

    2013-05-01

    Metabolomics analysis tools can provide quantitative information on the concentration of metabolites in an organism. In this paper, we propose the minimum pathway model generator tool for simulating the dynamics of metabolite concentrations (SS-mPMG) and a tool for parameter estimation by genetic algorithm (SS-GA). SS-mPMG can extract a subsystem of the metabolic network from the genome-scale pathway maps to reduce the complexity of the simulation model and automatically construct a dynamic simulator to evaluate the experimentally observed behavior of metabolites. Using this tool, we show that stochastic simulation can reproduce experimentally observed dynamics of amino acid biosynthesis in Arabidopsis thaliana. In this simulation, SS-mPMG extracts the metabolic network subsystem from published databases. The parameters needed for the simulation are determined using a genetic algorithm to fit the simulation results to the experimental data. We expect that SS-mPMG and SS-GA will help researchers to create relevant metabolic networks and carry out simulations of metabolic reactions derived from metabolomics data.

  18. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

    Science.gov (United States)

    Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. PMID:26970054

  19. Bacterial carbonatogenesis

    International Nuclear Information System (INIS)

    Several series of experiments in the laboratory as well as in natural conditions teach that the production of carbonate particles by heterotrophic bacteria follows different ways. The 'passive' carbonatogenesis is generated by modifications of the medium that lead to the accumulation of carbonate and bicarbonate ions and to the precipitation of solid particles. The 'active' carbonatogenesis is independent of the metabolic pathways. The carbonate particles are produced by ionic exchanges through the cell membrane following still poorly known mechanisms. Carbonatogenesis appears to be the response of heterotrophic bacterial communities to an enrichment of the milieu in organic matter. The active carbonatogenesis seems to start first. It is followed by the passive one which induces the growth of initially produced particles. The yield of heterotrophic bacterial carbonatogenesis and the amounts of solid carbonates production by bacteria are potentially very high as compared to autotrophic or chemical sedimentation from marine, paralic or continental waters. Furthermore, the bacterial processes are environmentally very ubiquitous; they just require organic matter enrichment. Thus, apart from purely evaporite and autotrophic ones, all Ca and/or Mg carbonates must be considered as from heterotrophic bacterial origin. By the way, the carbon of carbonates comes from primary organic matter. Such considerations ask questions about some interpretations from isotopic data on carbonates. Finally, bacterial heterotrophic carbonatogenesis appears as a fundamental phase in the relationships between atmosphere and lithosphere and in the geo-biological evolution of Earth. (author)

  20. Using co-metabolism to accelerate synthetic starch wastewater degradation and nutrient recovery in photosynthetic bacterial wastewater treatment technology.

    Science.gov (United States)

    Lu, Haifeng; Zhang, Guangming; Lu, Yufeng; Zhang, Yuanhui; Li, Baoming; Cao, Wei

    2016-01-01

    Starch wastewater is a type of nutrient-rich wastewater that contains numerous macromolecular polysaccharides. Using photosynthetic bacteria (PSB) to treat starch wastewater can reduce pollutants and enhance useful biomass production. However, PSB cannot directly degrade macromolecular polysaccharides, which weakens the starch degradation effect. Therefore, co-metabolism with primary substances was employed in PSB wastewater treatment to promote starch degradation. The results indicated that co-metabolism is a highly effective method in synthetic starch degradation by PSB. When malic acid was used as the optimal primary substrate, the chemical oxygen demand, total sugar, macromolecules removal and biomass yield were considerably higher than when primary substances were not used, respectively. Malic acid was the primary substrate that played a highly important role in starch degradation. It promoted the alpha-amylase activity to 46.8 U and the PSB activity, which induced the degradation of macromolecules. The products in the wastewater were ethanol, acetic acid and propionic acid. Ethanol was the primary product throughout the degradation process. The introduction of co-metabolism with malic acid to treat wastewater can accelerate macromolecules degradation and bioresource production and weaken the acidification effect. This method provides another pathway for bioresource recovery from wastewater. This approach is a sustainable and environmentally friendly wastewater treatment technology.

  1. Different biochemical mechanisms ensure network-wide balancing of reducing equivalents in microbial metabolism.

    Science.gov (United States)

    Fuhrer, Tobias; Sauer, Uwe

    2009-04-01

    To sustain growth, the catabolic formation of the redox equivalent NADPH must be balanced with the anabolic demand. The mechanisms that ensure such network-wide balancing, however, are presently not understood. Based on 13C-detected intracellular fluxes, metabolite concentrations, and cofactor specificities for all relevant central metabolic enzymes, we have quantified catabolic NADPH production in Agrobacterium tumefaciens, Bacillus subtilis, Escherichia coli, Paracoccus versutus, Pseudomonas fluorescens, Rhodobacter sphaeroides, Sinorhizobium meliloti, and Zymomonas mobilis. For six species, the estimated NADPH production from glucose catabolism exceeded the requirements for biomass synthesis. Exceptions were P. fluorescens, with balanced rates, and E. coli, with insufficient catabolic production, in which about one-third of the NADPH is supplied via the membrane-bound transhydrogenase PntAB. P. versutus and B. subtilis were the only species that appear to rely on transhydrogenases for balancing NADPH overproduction during growth on glucose. In the other four species, the main but not exclusive redox-balancing mechanism appears to be the dual cofactor specificities of several catabolic enzymes and/or the existence of isoenzymes with distinct cofactor specificities, in particular glucose 6-phosphate dehydrogenase. An unexpected key finding for all species, except E. coli and B. subtilis, was the lack of cofactor specificity in the oxidative pentose phosphate pathway, which contrasts with the textbook view of the pentose phosphate pathway dehydrogenases as being NADP+ dependent.

  2. Dissecting and engineering metabolic and regulatory networks of thermophilic bacteria for biofuel production.

    Science.gov (United States)

    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.

  3. Dissecting and engineering metabolic and regulatory networks of thermophilic bacteria for biofuel production.

    Science.gov (United States)

    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

  4. Systemic properties of metabolic networks lead to an epistasis-based model for heterosis.

    Science.gov (United States)

    Fiévet, Julie B; Dillmann, Christine; de Vienne, Dominique

    2010-01-01

    The genetic and molecular approaches to heterosis usually do not rely on any model of the genotype-phenotype relationship. From the generalization of Kacser and Burns' biochemical model for dominance and epistasis to networks with several variable enzymes, we hypothesized that metabolic heterosis could be observed because the response of the flux towards enzyme activities and/or concentrations follows a multi-dimensional hyperbolic-like relationship. To corroborate this, we used the values of systemic parameters accounting for the kinetic behaviour of four enzymes of the upstream part of glycolysis, and simulated genetic variability by varying in silico enzyme concentrations. Then we "crossed" virtual parents to get 1,000 hybrids, and showed that best-parent heterosis was frequently observed. The decomposition of the flux value into genetic effects, with the help of a novel multilocus epistasis index, revealed that antagonistic additive-by-additive epistasis effects play the major role in this framework of the genotype-phenotype relationship. This result is consistent with various observations in quantitative and evolutionary genetics, and provides a model unifying the genetic effects underlying heterosis. PMID:19916003

  5. Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

    OpenAIRE

    PitkÀnen, Esa

    2010-01-01

    Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the ...

  6. LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni.

    Science.gov (United States)

    Patel, Priyanka; Mandlik, Vineetha; Singh, Shailza

    2016-03-01

    A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database) is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level.

  7. Strain Dependent Genetic Networks for Antibiotic-Sensitivity in a Bacterial Pathogen with a Large Pan-Genome.

    Science.gov (United States)

    van Opijnen, Tim; Dedrick, Sandra; Bento, José

    2016-09-01

    The interaction between an antibiotic and bacterium is not merely restricted to the drug and its direct target, rather antibiotic induced stress seems to resonate through the bacterium, creating selective pressures that drive the emergence of adaptive mutations not only in the direct target, but in genes involved in many different fundamental processes as well. Surprisingly, it has been shown that adaptive mutations do not necessarily have the same effect in all species, indicating that the genetic background influences how phenotypes are manifested. However, to what extent the genetic background affects the manner in which a bacterium experiences antibiotic stress, and how this stress is processed is unclear. Here we employ the genome-wide tool Tn-Seq to construct daptomycin-sensitivity profiles for two strains of the bacterial pathogen Streptococcus pneumoniae. Remarkably, over half of the genes that are important for dealing with antibiotic-induced stress in one strain are dispensable in another. By confirming over 100 genotype-phenotype relationships, probing potassium-loss, employing genetic interaction mapping as well as temporal gene-expression experiments we reveal genome-wide conditionally important/essential genes, we discover roles for genes with unknown function, and uncover parts of the antibiotic's mode-of-action. Moreover, by mapping the underlying genomic network for two query genes we encounter little conservation in network connectivity between strains as well as profound differences in regulatory relationships. Our approach uniquely enables genome-wide fitness comparisons across strains, facilitating the discovery that antibiotic responses are complex events that can vary widely between strains, which suggests that in some cases the emergence of resistance could be strain specific and at least for species with a large pan-genome less predictable. PMID:27607357

  8. An arginine-aspartate network in the active site of bacterial TruB is critical for catalyzing pseudouridine formation.

    Science.gov (United States)

    Friedt, Jenna; Leavens, Fern M V; Mercier, Evan; Wieden, Hans-Joachim; Kothe, Ute

    2014-04-01

    Pseudouridine synthases introduce the most common RNA modification and likely use the same catalytic mechanism. Besides a catalytic aspartate residue, the contributions of other residues for catalysis of pseudouridine formation are poorly understood. Here, we have tested the role of a conserved basic residue in the active site for catalysis using the bacterial pseudouridine synthase TruB targeting U55 in tRNAs. Substitution of arginine 181 with lysine results in a 2500-fold reduction of TruB's catalytic rate without affecting tRNA binding. Furthermore, we analyzed the function of a second-shell aspartate residue (D90) that is conserved in all TruB enzymes and interacts with C56 of tRNA. Site-directed mutagenesis, biochemical and kinetic studies reveal that this residue is not critical for substrate binding but influences catalysis significantly as replacement of D90 with glutamate or asparagine reduces the catalytic rate 30- and 50-fold, respectively. In agreement with molecular dynamics simulations of TruB wild type and TruB D90N, we propose an electrostatic network composed of the catalytic aspartate (D48), R181 and D90 that is important for catalysis by fine-tuning the D48-R181 interaction. Conserved, negatively charged residues similar to D90 are found in a number of pseudouridine synthases, suggesting that this might be a general mechanism.

  9. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2010-05-01

    Full Text Available Abstract Background Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. Results Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and metabolic regulatory signal transduction pathways (STP operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes and for all the interactions between them (edges. The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. Conclusions The reported fully annotated interaction model serves as a platform for integrated systems biology studies of nutrient sensing and regulation in S. cerevisiae. Furthermore, we propose this annotated reconstruction as a first step towards generation of an extensive annotated protein-protein interaction network of signal transduction and metabolic regulation in this yeast.

  10. Bacterial diversity exploration in hydrocarbon polluted soil: metabolic potential and degrader community evolution revealed by isotope labeling

    International Nuclear Information System (INIS)

    Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous compounds produced by incomplete combustion of organic matter. They are a source of environmental pollution, especially associated to oil product exploitation, and represent a threat for living organisms including human beings because of their toxicity. Many bacteria capable of degrading PAHs have been isolated and studied. However, since less than 5% of soil bacteria can be cultivated in the laboratory, bacterial species able to degrade PAHs in situ have been poorly studied. The first goal of this study was to identify bacteria that degrade PAHs in soil using culture-independent molecular methods. To this end, a strategy known a stable isotope probing has been implemented based on the use of phenanthrene, a three rings PAH, in which the natural isotope of carbon was replaced by 13C. This molecule has been introduced as a tracer in microcosms containing soil from a constructed wetlands collecting contaminated water from highway runoff. Bacteria having incorporated the 13C were then identified by 16S rRNA gene sequence analysis after PCR amplification from labeled genomic DNA extracted from soil. The results show that so far little studied Betaproteobacteria, belonging to the genera Acidovorax, Rhodoferax, Hydrogenophaga and Thiobacillus, as well as Rhodocyclaceae, were the key players in phenanthrene degradation. Predominance of Betaproteobacteries was established thanks to quantitative PCR measurements. A dynamic analysis of bacterial diversity also showed that the community structure of degraders depended on phenanthrene bioavailability. In addition, the phylogenetic diversity of ring-hydroxylating di-oxygenases, enzymes involved in the first step of PAH degradation, has been explored. We detected new sequences, mostly related to di-oxygenases from Sphingomonadales and Burkholderiales. For the first time, we were able to associate a catalytic activity for oxidation of PAHs to partial gene sequences amplified

  11. Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.

    Science.gov (United States)

    Bordron, Philippe; Latorre, Mauricio; Cortés, Maria-Paz; González, Mauricio; Thiele, Sven; Siegel, Anne; Maass, Alejandro; Eveillard, Damien

    2016-02-01

    Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways. PMID:26677108

  12. Transient exposure to low levels of insecticide affects metabolic networks of honeybee larvae.

    Science.gov (United States)

    Derecka, Kamila; Blythe, Martin J; Malla, Sunir; Genereux, Diane P; Guffanti, Alessandro; Pavan, Paolo; Moles, Anna; Snart, Charles; Ryder, Thomas; Ortori, Catharine A; Barrett, David A; Schuster, Eugene; Stöger, Reinhard

    2013-01-01

    The survival of a species depends on its capacity to adjust to changing environmental conditions, and new stressors. Such new, anthropogenic stressors include the neonicotinoid class of crop-protecting agents, which have been implicated in the population declines of pollinating insects, including honeybees (Apis mellifera). The low-dose effects of these compounds on larval development and physiological responses have remained largely unknown. Over a period of 15 days, we provided syrup tainted with low levels (2 µg/L(-1)) of the neonicotinoid insecticide imidacloprid to beehives located in the field. We measured transcript levels by RNA sequencing and established lipid profiles using liquid chromatography coupled with mass spectrometry from worker-bee larvae of imidacloprid-exposed (IE) and unexposed, control (C) hives. Within a catalogue of 300 differentially expressed transcripts in larvae from IE hives, we detect significant enrichment of genes functioning in lipid-carbohydrate-mitochondrial metabolic networks. Myc-involved transcriptional response to exposure of this neonicotinoid is indicated by overrepresentation of E-box elements in the promoter regions of genes with altered expression. RNA levels for a cluster of genes encoding detoxifying P450 enzymes are elevated, with coordinated downregulation of genes in glycolytic and sugar-metabolising pathways. Expression of the environmentally responsive Hsp90 gene is also reduced, suggesting diminished buffering and stability of the developmental program. The multifaceted, physiological response described here may be of importance to our general understanding of pollinator health. Muscles, for instance, work at high glycolytic rates and flight performance could be impacted should low levels of this evolutionarily novel stressor likewise induce downregulation of energy metabolising genes in adult pollinators. PMID:23844170

  13. Complexity and robustness in hypernetwork models of metabolism.

    Science.gov (United States)

    Pearcy, Nicole; Chuzhanova, Nadia; Crofts, Jonathan J

    2016-10-01

    Metabolic reaction data is commonly modelled using a complex network approach, whereby nodes represent the chemical species present within the organism of interest, and connections are formed between those nodes participating in the same chemical reaction. Unfortunately, such an approach provides an inadequate description of the metabolic process in general, as a typical chemical reaction will involve more than two nodes, thus risking oversimplification of the system of interest in a potentially significant way. In this paper, we employ a complex hypernetwork formalism to investigate the robustness of bacterial metabolic hypernetworks by extending the concept of a percolation process to hypernetworks. Importantly, this provides a novel method for determining the robustness of these systems and thus for quantifying their resilience to random attacks/errors. Moreover, we performed a site percolation analysis on a large cohort of bacterial metabolic networks and found that hypernetworks that evolved in more variable environments displayed increased levels of robustness and topological complexity. PMID:27354314

  14. Combinational risk factors of metabolic syndrome identified by fuzzy neural network analysis of health-check data

    Directory of Open Access Journals (Sweden)

    Ushida Yasunori

    2012-08-01

    Full Text Available Abstract Background Lifestyle-related diseases represented by metabolic syndrome develop as results of complex interaction. By using health check-up data from two large studies collected during a long-term follow-up, we searched for risk factors associated with the development of metabolic syndrome. Methods In our original study, we selected 77 case subjects who developed metabolic syndrome during the follow-up and 152 healthy control subjects who were free of lifestyle-related risk components from among 1803 Japanese male employees. In a replication study, we selected 2196 case subjects and 2196 healthy control subjects from among 31343 other Japanese male employees. By means of a bioinformatics approach using a fuzzy neural network (FNN, we searched any significant combinations that are associated with MetS. To ensure that the risk combination selected by FNN analysis was statistically reliable, we performed logistic regression analysis including adjustment. Results We selected a combination of an elevated level of γ-glutamyltranspeptidase (γ-GTP and an elevated white blood cell (WBC count as the most significant combination of risk factors for the development of metabolic syndrome. The FNN also identified the same tendency in a replication study. The clinical characteristics of γ-GTP level and WBC count were statistically significant even after adjustment, confirming that the results obtained from the fuzzy neural network are reasonable. Correlation ratio showed that an elevated level of γ-GTP is associated with habitual drinking of alcohol and a high WBC count is associated with habitual smoking. Conclusions This result obtained by fuzzy neural network analysis of health check-up data from large long-term studies can be useful in providing a personalized novel diagnostic and therapeutic method involving the γ-GTP level and the WBC count.

  15. PPARγ isoforms differentially regulate metabolic networks to mediate mouse prostatic epithelial differentiation

    OpenAIRE

    Strand, D.W.; Jiang, M; Murphy, T A; Yi, Y.; Konvinse, K C; Franco, O E; Wang, Y.; Young, J D; Hayward, S.W.

    2012-01-01

    Recent observations indicate prostatic diseases are comorbidities of systemic metabolic dysfunction. These discoveries revealed fundamental questions regarding the nature of prostate metabolism. We previously showed that prostate-specific ablation of PPARγ in mice resulted in tumorigenesis and active autophagy. Here, we demonstrate control of overlapping and distinct aspects of prostate epithelial metabolism by ectopic expression of individual PPARγ isoforms in PPARγ knockout prostate epithel...

  16. Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks.

    Directory of Open Access Journals (Sweden)

    Tao Huang

    Full Text Available The metabolic stability is a very important idiosyncracy of proteins that is related to their global flexibility, intramolecular fluctuations, various internal dynamic processes, as well as many marvelous biological functions. Determination of protein's metabolic stability would provide us with useful information for in-depth understanding of the dynamic action mechanisms of proteins. Although several experimental methods have been developed to measure protein's metabolic stability, they are time-consuming and more expensive. Reported in this paper is a computational method, which is featured by (1 integrating various properties of proteins, such as biochemical and physicochemical properties, subcellular locations, network properties and protein complex property, (2 using the mRMR (Maximum Relevance & Minimum Redundancy principle and the IFS (Incremental Feature Selection procedure to optimize the prediction engine, and (3 being able to identify proteins among the four types: "short", "medium", "long", and "extra-long" half-life spans. It was revealed through our analysis that the following seven characters played major roles in determining the stability of proteins: (1 KEGG enrichment scores of the protein and its neighbors in network, (2 subcellular locations, (3 polarity, (4 amino acids composition, (5 hydrophobicity, (6 secondary structure propensity, and (7 the number of protein complexes the protein involved. It was observed that there was an intriguing correlation between the predicted metabolic stability of some proteins and the real half-life of the drugs designed to target them. These findings might provide useful insights for designing protein-stability-relevant drugs. The computational method can also be used as a large-scale tool for annotating the metabolic stability for the avalanche of protein sequences generated in the post-genomic age.

  17. Metabolic engineering of potato carotenoid content through tuber-specific overexpression of a bacterial mini-pathway.

    Directory of Open Access Journals (Sweden)

    Gianfranco Diretto

    Full Text Available BACKGROUND: Since the creation of "Golden Rice", biofortification of plant-derived foods is a promising strategy for the alleviation of nutritional deficiencies. Potato is the most important staple food for mankind after the cereals rice, wheat and maize, and is extremely poor in provitamin A carotenoids. METHODOLOGY: We transformed potato with a mini-pathway of bacterial origin, driving the synthesis of beta-carotene (Provitamin A from geranylgeranyl diphosphate. Three genes, encoding phytoene synthase (CrtB, phytoene desaturase (CrtI and lycopene beta-cyclase (CrtY from Erwinia, under tuber-specific or constitutive promoter control, were used. 86 independent transgenic lines, containing six different promoter/gene combinations, were produced and analyzed. Extensive regulatory effects on the expression of endogenous genes for carotenoid biosynthesis are observed in transgenic lines. Constitutive expression of the CrtY and/or CrtI genes interferes with the establishment of transgenosis and with the accumulation of leaf carotenoids. Expression of all three genes, under tuber-specific promoter control, results in tubers with a deep yellow ("golden" phenotype without any adverse leaf phenotypes. In these tubers, carotenoids increase approx. 20-fold, to 114 mcg/g dry weight and beta-carotene 3600-fold, to 47 mcg/g dry weight. CONCLUSIONS: This is the highest carotenoid and beta-carotene content reported for biofortified potato as well as for any of the four major staple foods (the next best event being "Golden Rice 2", with 31 mcg/g dry weight beta-carotene. Assuming a beta-carotene to retinol conversion of 6ratio1, this is sufficient to provide 50% of the Recommended Daily Allowance of Vitamin A with 250 gms (fresh weight of "golden" potatoes.

  18. Loss of variation of state detected in soybean metabolic and human myelomonocytic leukaemia cell transcriptional networks under external stimuli

    KAUST Repository

    Sakata, Katsumi

    2016-10-24

    Soybean (Glycine max) is sensitive to flooding stress, and flood damage at the seedling stage is a barrier to growth. We constructed two mathematical models of the soybean metabolic network, a control model and a flooded model, from metabolic profiles in soybean plants. We simulated the metabolic profiles with perturbations before and after the flooding stimulus using the two models. We measured the variation of state that the system could maintain from a state–space description of the simulated profiles. The results showed a loss of variation of state during the flooding response in the soybean plants. Loss of variation of state was also observed in a human myelomonocytic leukaemia cell transcriptional network in response to a phorbol-ester stimulus. Thus, we detected a loss of variation of state under external stimuli in two biological systems, regardless of the regulation and stimulus types. Our results suggest that a loss of robustness may occur concurrently with the loss of variation of state in biological systems. We describe the possible applications of the quantity of variation of state in plant genetic engineering and cell biology. Finally, we present a hypothetical “external stimulus-induced information loss” model of biological systems.

  19. Regulatory network of secondary metabolism in Brassica rapa : insight into the glucosinolate pathway

    NARCIS (Netherlands)

    Pino Del Carpio, Dunia; Basnet, Ram Kumar; Arends, Danny; Lin, Ke; De Vos, Ric C H; Muth, Dorota; Kodde, Jan; Boutilier, Kim; Bucher, Johan; Wang, Xiaowu; Jansen, Ritsert; Bonnema, Guusje

    2014-01-01

    Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomic

  20. In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

    NARCIS (Netherlands)

    Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

    2005-01-01

    A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all pro

  1. Designer labels for plant metabolism: statistical design of isotope labeling experiments for improved quantification of flux in complex plant metabolic networks.

    Science.gov (United States)

    Nargund, Shilpa; Sriram, Ganesh

    2013-01-27

    Metabolic fluxes are powerful indicators of cell physiology and can be estimated by isotope-assisted metabolic flux analysis (MFA). The complexity of the compartmented metabolic networks of plants has constrained the application of isotope-assisted MFA to them, principally because of poor identifiability of fluxes from the measured isotope labeling patterns. However, flux identifiability can be significantly improved by a priori design of isotope labeling experiments (ILEs). This computational design involves evaluating the effect of different isotope label and isotopomer measurement combinations on flux identifiability, and thereby identifying optimal labels and measurements toward evaluating the fluxes of interest with the highest confidence. This article reports ILE designs for two major, compartmented plant metabolic pathways - the pentose phosphate pathway (PPP) and γ-aminobutyric acid (GABA) shunt. Together, these pathways represent common motifs in plant metabolism including duplication of pathways in different subcellular compartments, reversible reactions and cyclic carbon flow. To compare various ILE designs, we employed statistical A- and D-optimality criteria. Our computations showed that 1,2-(13)C Glc is a powerful and robust label for the plant PPPs, given currently popular isotopomer measurement techniques (single quadrupole mass spectrometry [MS] and 2-D nuclear magnetic resonance [NMR]). Further analysis revealed that this label can estimate several PPP fluxes better than the popular label 1-(13)C Glc. Furthermore, the concurrent measurement of the isotopomers of hexose and pentose moieties synthesized exclusively in the cytosol or the plastid compartments (measurable through intracellular glucose or sucrose, starch, RNA ribose and histidine) considerably improves the identifiability of PPP fluxes in the individual compartments. Additionally, MS-derived isotopomer measurements outperform NMR-derived measurements in identifying PPP fluxes. The

  2. Using isotopic tracers to assess the impact of tillage and straw management on the microbial metabolic network in soil

    Science.gov (United States)

    Van Groenigen, K.; Forristal, D.; Jones, M. B.; Schwartz, E.; Hungate, B. A.; Dijkstra, P.

    2013-12-01

    By decomposing soil organic matter, microbes gain energy and building blocks for biosynthesis and release CO2 to the atmosphere. Therefore, insight into the effect of management practices on microbial metabolic pathways and C use efficiency (CUE; microbial C produced per substrate C utilized) may help to predict long term changes in soil C stocks. We studied the effects of reduced (RT) and conventional tillage (CT) on the microbial central C metabolic network, using soil samples from a 12-year-old field experiment in an Irish winter wheat cropping system. Each year after harvest, straw was removed from half of the RT and CT plots or incorporated into the soil in the other half, resulting in four treatment combinations. We added 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose as metabolic tracer isotopomers to composite soil samples taken at two depths (0-15 cm and 15-30 cm) from each treatment and used the rate of position-specific respired 13CO2 to parameterize a metabolic model. Model outcomes were then used to calculate CUE of the microbial community. We found that the composite samples differed in CUE, but the changes were small, with values ranging between 0.757-0.783 across treatments and soil depth. Increases in CUE were associated with a decrease in tricarboxylic acid cycle and reductive pentose phosphate pathway activity and increased consumption of metabolic intermediates for biosynthesis. Our results indicate that RT and straw incorporation promote soil C storage without substantially changing CUE or any of the microbial metabolic pathways. This suggests that at our site, RT and straw incorporation promote soil C storage mostly through direct effects such as increased soil C input and physical protection from decomposition, rather than by feedback responses of the microbial community.

  3. The deleterious metabolic and genotoxic effects of the bacterial metabolite p-cresol on colonic epithelial cells.

    Science.gov (United States)

    Andriamihaja, Mireille; Lan, Annaïg; Beaumont, Martin; Audebert, Marc; Wong, Ximena; Yamada, Kana; Yin, Yulong; Tomé, Daniel; Carrasco-Pozo, Catalina; Gotteland, Martin; Kong, Xiangfeng; Blachier, François

    2015-08-01

    p-Cresol that is produced by the intestinal microbiota from the amino acid tyrosine is found at millimolar concentrations in the human feces. The effects of this metabolite on colonic epithelial cells were tested in this study. Using the human colonic epithelial HT-29 Glc(-/+) cell line, we found that 0.8mM p-cresol inhibits cell proliferation, an effect concomitant with an accumulation of the cells in the S phase and with a slight increase of cell detachment without necrotic effect. At this concentration, p-cresol inhibited oxygen consumption in HT-29 Glc(-/+) cells. In rat normal colonocytes, p-cresol also inhibited respiration. Pretreatment of HT-29 Glc(-/+) cells with 0.8mM p-cresol for 1 day resulted in an increase of the state 3 oxygen consumption and of the cell maximal respiratory capacity with concomitant increased anion superoxide production. At higher concentrations (1.6 and 3.2mM), p-cresol showed similar effects but additionally increased after 1 day the proton leak through the inner mitochondrial membrane, decreasing the mitochondrial bioenergetic activity. At these concentrations, p-cresol was found to be genotoxic toward HT-29 Glc(-/+) and also LS-174T intestinal cells. Lastly, a decreased ATP intracellular content was observed after 3 days treatment. p-Cresol at 0.8mM concentration inhibits colonocyte respiration and proliferation. In response, cells can mobilize their "respiratory reserve." At higher concentrations, p-cresol pretreatment uncouples cell respiration and ATP synthesis, increases DNA damage, and finally decreases the ATP cell content. Thus, we have identified p-cresol as a metabolic troublemaker and as a genotoxic agent toward colonocytes. PMID:25881551

  4. Integrating chemical and genetic silencing strategies to identify host kinase-phosphatase inhibitor networks that control bacterial infection

    NARCIS (Netherlands)

    Albers, Harald M H G; Kuijl, Coenraad; Bakker, Jeroen; Hendrickx, Loes; Wekker, Sharida; Farhou, Nadha; Liu, Nora; Blasco-Moreno, Bernat; Scanu, Tiziana; den Hertog, Jeroen; Celie, Patrick; Ovaa, Huib; Neefjes, Jacques

    2014-01-01

    Every year three million people die as a result of bacterial infections, and this number may further increase due to resistance to current antibiotics. These antibiotics target almost all essential bacterial processes, leaving only a few new targets for manipulation. The host proteome has many more

  5. Shotgun proteome analysis of Bordetella pertussis reveals a distinct influence of iron availability on the bacterial metabolism, virulence, and defense response.

    Science.gov (United States)

    Alvarez Hayes, Jimena; Lamberti, Yanina; Surmann, Kristin; Schmidt, Frank; Völker, Uwe; Rodriguez, Maria Eugenia

    2015-07-01

    One of the mechanisms involved in host immunity is the limitation of iron accessibility to pathogens, which in turn provokes the corresponding physiological adaptation of pathogens. This study reports a gel-free nanoLC-MS/MS-based comparative proteome analysis of Bordetella pertussis grown under iron-excess and iron-depleted conditions. Out of the 926 proteins covered 98 displayed a shift in their abundance in response to low iron availability. Forty-seven of them were found to be increased in level while 58 were found with decreased protein levels under iron starvation. In addition to proteins previously reported to be influenced by iron in B. pertussis, we observed changes in metabolic proteins involved in fatty acid utilization and poly-hydroxybutyrate production. Additionally, many bacterial virulence factors regulated by the BvgAS two-component system were found at decreased levels in response to iron limitation. These results, together with the increased production of proteins potentially involved in oxidative stress resistance, seem to indicate that iron starvation provokes changes in B. pertussis phenotype that might shape host-pathogen interaction.

  6. HRGRN: A Graph Search-Empowered Integrative Database of Arabidopsis Signaling Transduction, Metabolism and Gene Regulation Networks.

    Science.gov (United States)

    Dai, Xinbin; Li, Jun; Liu, Tingsong; Zhao, Patrick Xuechun

    2016-01-01

    The biological networks controlling plant signal transduction, metabolism and gene regulation are composed of not only tens of thousands of genes, compounds, proteins and RNAs but also the complicated interactions and co-ordination among them. These networks play critical roles in many fundamental mechanisms, such as plant growth, development and environmental response. Although much is known about these complex interactions, the knowledge and data are currently scattered throughout the published literature, publicly available high-throughput data sets and third-party databases. Many 'unknown' yet important interactions among genes need to be mined and established through extensive computational analysis. However, exploring these complex biological interactions at the network level from existing heterogeneous resources remains challenging and time-consuming for biologists. Here, we introduce HRGRN, a graph search-empowered integrative database of Arabidopsis signal transduction, metabolism and gene regulatory networks. HRGRN utilizes Neo4j, which is a highly scalable graph database management system, to host large-scale biological interactions among genes, proteins, compounds and small RNAs that were either validated experimentally or predicted computationally. The associated biological pathway information was also specially marked for the interactions that are involved in the pathway to facilitate the investigation of cross-talk between pathways. Furthermore, HRGRN integrates a series of graph path search algorithms to discover novel relationships among genes, compounds, RNAs and even pathways from heterogeneous biological interaction data that could be missed by traditional SQL database search methods. Users can also build subnetworks based on known interactions. The outcomes are visualized with rich text, figures and interactive network graphs on web pages. The HRGRN database is freely available at http://plantgrn.noble.org/hrgrn/. PMID:26657893

  7. Hybrid dynamic modeling of Escherichia coli central metabolic network combining Michaelis–Menten and approximate kinetic equations

    DEFF Research Database (Denmark)

    Costa, Rafael S.; Machado, Daniel; Rocha, Isabel;

    2010-01-01

    The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters...... using the hybrid model composed of Michaelis–Menten and the approximate lin-log kinetics indicate that this is a possible suitable approach to model complex large-scale networks where the exact rate laws are unknown.......The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters......, represent nowadays the limiting factor in the construction of such models. In this study, we compare four alternative modeling approaches based on Michaelis–Menten kinetics for the bi-molecular reactions and different types of simplified rate equations for the remaining reactions (generalized mass action...

  8. Identification of altered metabolic pathways of γ-irradiated rice mutant via network-based transcriptome analysis.

    Science.gov (United States)

    Hwang, Sun-Goo; Kim, Dong Sub; Hwang, Jung Eun; Park, Hyeon Mi; Jang, Cheol Seong

    2015-12-01

    In order to develop rice mutants for crop improvement, we applied γ-irradiation mutagenesis and selected a rice seed color mutant (MT) in the M14 targeting-induced local lesions in genome lines. This mutant exhibited differences in germination rate, plant height, and root length in seedlings compared to the wild-type plants. We found 1645 different expressed probes of MT by microarray hybridization. To identify the modified metabolic pathways, we conducted integrated genomic analysis such as weighted correlation network analysis with a module detection method of differentially expressed genes (DEGs) in MT on the basis of large-scale microarray transcriptional profiling. These modules are largely divided into three subnetworks and mainly exhibit overrepresented gene ontology functions such as oxidation-related function, ion-binding, and kinase activity (phosphorylation), and the expressional coherences of module genes mainly exhibited in vegetative and maturation stages. Through a metabolic pathway analysis, we detected the significant DEGs involved in the major carbohydrate metabolism (starch degradation), protein degradation (aspartate protease), and signaling in sugars and nutrients. Furthermore, the accumulation of amino acids (asparagine and glutamic acid), sucrose, and starch in MT were affected by gamma rays. Our results provide an effective approach for identification of metabolic pathways associated with useful agronomic traits in mutation breeding. PMID:26361777

  9. Identification of altered metabolic pathways of γ-irradiated rice mutant via network-based transcriptome analysis.

    Science.gov (United States)

    Hwang, Sun-Goo; Kim, Dong Sub; Hwang, Jung Eun; Park, Hyeon Mi; Jang, Cheol Seong

    2015-12-01

    In order to develop rice mutants for crop improvement, we applied γ-irradiation mutagenesis and selected a rice seed color mutant (MT) in the M14 targeting-induced local lesions in genome lines. This mutant exhibited differences in germination rate, plant height, and root length in seedlings compared to the wild-type plants. We found 1645 different expressed probes of MT by microarray hybridization. To identify the modified metabolic pathways, we conducted integrated genomic analysis such as weighted correlation network analysis with a module detection method of differentially expressed genes (DEGs) in MT on the basis of large-scale microarray transcriptional profiling. These modules are largely divided into three subnetworks and mainly exhibit overrepresented gene ontology functions such as oxidation-related function, ion-binding, and kinase activity (phosphorylation), and the expressional coherences of module genes mainly exhibited in vegetative and maturation stages. Through a metabolic pathway analysis, we detected the significant DEGs involved in the major carbohydrate metabolism (starch degradation), protein degradation (aspartate protease), and signaling in sugars and nutrients. Furthermore, the accumulation of amino acids (asparagine and glutamic acid), sucrose, and starch in MT were affected by gamma rays. Our results provide an effective approach for identification of metabolic pathways associated with useful agronomic traits in mutation breeding.

  10. Comparison of Metabolic Network between Muscle and Intramuscular Adipose Tissues in Hanwoo Beef Cattle Using a Systems Biology Approach.

    Science.gov (United States)

    Lee, Hyun-Jeong; Park, Hye-Sun; Kim, Woonsu; Yoon, Duhak; Seo, Seongwon

    2014-01-01

    The interrelationship between muscle and adipose tissues plays a major role in determining the quality of carcass traits. The objective of this study was to compare metabolic differences between muscle and intramuscular adipose (IMA) tissues in the longissimus dorsi (LD) of Hanwoo (Bos taurus coreanae) using the RNA-seq technology and a systems biology approach. The LD sections between the 6th and 7th ribs were removed from nine (each of three cows, steers, and bulls) Hanwoo beef cattle (carcass weight of 430.2 ± 40.66 kg) immediately after slaughter. The total mRNA from muscle, IMA, and subcutaneous adipose and omental adipose tissues were isolated and sequenced. The reads that passed quality control were mapped onto the bovine reference genome (build bosTau6), and differentially expressed genes across tissues were identified. The KEGG pathway enrichment tests revealed the opposite direction of metabolic regulation between muscle and IMA. Metabolic gene network analysis clearly indicated that oxidative metabolism was upregulated in muscle and downregulated in IMA. Interestingly, pathways for regulating cell adhesion, structure, and integrity and chemokine signaling pathway were upregulated in IMA and downregulated in muscle. It is thus inferred that IMA may play an important role in the regulation of development and structure of the LD tissues and muscle/adipose communication.

  11. QTLs of factors of the metabolic syndrome and echocardiographic phenotypes: the hypertension genetic epidemiology network study

    Directory of Open Access Journals (Sweden)

    de Simone Giovanni

    2008-11-01

    Full Text Available Abstract Background In a previous study of the Hypertension Genetic Epidemiology Network (HyperGEN we have shown that metabolic syndrome (MetS risk factors were moderately and significantly associated with echocardiographic (ECHO left ventricular (LV phenotypes. Methods The study included 1,393 African Americans and 1,133 whites, stratified by type 2 diabetes mellitus (DM status. Heritabilities of seven factor scores based on the analysis of 15 traits were sufficiently high to pursue QTL discovery in this follow-up study. Results Three of the QTLs discovered relate to combined MetS-ECHO factors of "blood pressure (BP-LV wall thickness" on chromosome 3 at 225 cM with a 2.8 LOD score, on chromosome 20 at 2.1 cM with a 2.6 LOD score; and for "LV wall thickness" factor on chromosome 16 at 113.5 with a 2.6 LOD score in whites. The remaining QTLs include one for a "body mass index-insulin (BMI-INS" factor with a LOD score of 3.9 on chromosome 2 located at 64.8 cM; one for the same factor on chromosome 12 at 91.4 cM with a 3.3 LOD score; one for a "BP" factor on chromosome 19 located at 67.8 cM with a 3.0 LOD score. A suggestive linkage was also found for "Lipids-INS" with a 2.7 LOD score located on chromosome 11 at 113.1 cM in African Americans. Of the above QTLs, the one on chromosome 12 for "BMI-INS" is replicated in both ethnicities, (with highest LOD scores in African Americans. In addition, the QTL for "LV wall thickness" on chromosome 16q24.2-q24.3 reached its local maximum LOD score at marker D16S402, which is positioned within the 5th intron of the cadherin 13 gene, implicated in heart and vascular remodeling. Conclusion Our previous study and this follow-up suggest gene loci for some crucial MetS and cardiac geometry risk factors that contribute to the risk of developing heart disease.

  12. The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes.

    Directory of Open Access Journals (Sweden)

    Valentina Baldazzi

    2010-06-01

    Full Text Available Gene regulatory networks consist of direct interactions but also include indirect interactions mediated by metabolites and signaling molecules. We describe how these indirect interactions can be derived from a model of the underlying biochemical reaction network, using weak time-scale assumptions in combination with sensitivity criteria from metabolic control analysis. We apply this approach to a model of the carbon assimilation network in Escherichia coli. Our results show that the derived gene regulatory network is densely connected, contrary to what is usually assumed. Moreover, the network is largely sign-determined, meaning that the signs of the indirect interactions are fixed by the flux directions of biochemical reactions, independently of specific parameter values and rate laws. An inversion of the fluxes following a change in growth conditions may affect the signs of the indirect interactions though. This leads to a feedback structure that is at the same time robust to changes in the kinetic properties of enzymes and that has the flexibility to accommodate radical changes in the environment.

  13. Comparative analysis of false discovery rate methods in constructing metabolic association networks.

    Science.gov (United States)

    Koo, Imhoi; Yao, Sen; Zhang, Xiang; Kim, Seongho

    2014-08-01

    Gaussian graphical model (GGM)-based method, a key approach to reverse engineering biological networks, uses partial correlation to measure conditional dependence between two variables by controlling the contribution from other variables. After estimating partial correlation coefficients, one of the most critical processes in network construction is to control the false discovery rate (FDR) to assess the significant associations among variables. Various FDR methods have been proposed mainly for biomarker discovery, but it still remains unclear which FDR method performs better for network construction. Furthermore, there is no study to see the effect of the network structure on network construction. We selected the six FDR methods, the linear step-up procedure (BH95), the adaptive linear step-up procedure (BH00), Efron's local FDR (LFDR), Benjamini-Yekutieli's step-up procedure (BY01), Storey's q-value procedure (Storey01), and Storey-Taylor-Siegmund's adaptive step-up procedure (STS04), to evaluate their performances on network construction. We further considered two network structures, random and scale-free networks, to investigate their influence on network construction. Both simulated data and real experimental data suggest that STS04 provides the highest true positive rate (TPR) or F1 score, while BY01 has the highest positive predictive value (PPV) in network construction. In addition, no significant effect of the network structure is found on FDR methods.

  14. Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

    Directory of Open Access Journals (Sweden)

    Vishveshwara Saraswathi

    2009-02-01

    Full Text Available Abstract Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS. This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the

  15. [Bacterial vaginosis].

    Science.gov (United States)

    Romero Herrero, Daniel; Andreu Domingo, Antonia

    2016-07-01

    Bacterial vaginosis (BV) is the main cause of vaginal dysbacteriosis in the women during the reproductive age. It is an entity in which many studies have focused for years and which is still open for discussion topics. This is due to the diversity of microorganisms that cause it and therefore, its difficult treatment. Bacterial vaginosis is probably the result of vaginal colonization by complex bacterial communities, many of them non-cultivable and with interdependent metabolism where anaerobic populations most likely play an important role in its pathogenesis. The main symptoms are an increase of vaginal discharge and the unpleasant smell of it. It can lead to serious consequences for women, such as an increased risk of contracting sexually transmitted infections including human immunodeficiency virus and upper genital tract and pregnancy complications. Gram stain is the gold standard for microbiological diagnosis of BV, but can also be diagnosed using the Amsel clinical criteria. It should not be considered a sexually transmitted disease but it is highly related to sex. Recurrence is the main problem of medical treatment. Apart from BV, there are other dysbacteriosis less characterized like aerobic vaginitis of which further studies are coming slowly but are achieving more attention and consensus among specialists. PMID:27474242

  16. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Directory of Open Access Journals (Sweden)

    Julián Triana

    2014-08-01

    Full Text Available The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

  17. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  18. Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria

    Directory of Open Access Journals (Sweden)

    Grammel Hartmut

    2011-09-01

    Full Text Available Abstract Background Purple nonsulfur bacteria (PNSB are facultative photosynthetic bacteria and exhibit an extremely versatile metabolism. A central focus of research on PNSB dealt with the elucidation of mechanisms by which they manage to balance cellular redox under diverse conditions, in particular under photoheterotrophic growth. Results Given the complexity of the central metabolism of PNSB, metabolic modeling becomes crucial for an integrated analysis of the accumulated biological knowledge. We reconstructed a stoichiometric model capturing the central metabolism of three important representatives of PNSB (Rhodospirillum rubrum, Rhodobacter sphaeroides and Rhodopseudomonas palustris. Using flux variability analysis, the model reveals key metabolic constraints related to redox homeostasis in these bacteria. With the help of the model we can (i give quantitative explanations for non-intuitive, partially species-specific phenomena of photoheterotrophic growth of PNSB, (ii reproduce various quantitative experimental data, and (iii formulate several new hypotheses. For example, model analysis of photoheterotrophic growth reveals that - despite a large number of utilizable catabolic pathways - substrate-specific biomass and CO2 yields are fixed constraints, irrespective of the assumption of optimal growth. Furthermore, our model explains quantitatively why a CO2 fixing pathway such as the Calvin cycle is required by PNSB for many substrates (even if CO2 is released. We also analyze the role of other pathways potentially involved in redox metabolism and how they affect quantitatively the required capacity of the Calvin cycle. Our model also enables us to discriminate between different acetate assimilation pathways that were proposed recently for R. sphaeroides and R. rubrum, both lacking the isocitrate lyase. Finally, we demonstrate the value of the metabolic model also for potential biotechnological applications: we examine the theoretical

  19. Challenges and Opportunities of Long-Term Continuous Stream Metabolism Measurements at the National Ecological Observatory Network

    Science.gov (United States)

    Goodman, K. J.; Lunch, C. K.; Baxter, C.; Hall, R.; Holtgrieve, G. W.; Roberts, B. J.; Marcarelli, A. M.; Tank, J. L.

    2013-12-01

    Recent advances in dissolved oxygen sensing and modeling have made continuous measurements of whole-stream metabolism relatively easy to make, allowing ecologists to quantify and evaluate stream ecosystem health at expanded temporal and spatial scales. Long-term monitoring of continuous stream metabolism will enable a better understanding of the integrated and complex effects of anthropogenic change (e.g., land-use, climate, atmospheric deposition, invasive species, etc.) on stream ecosystem function. In addition to their value in the particular streams measured, information derived from long-term data will improve the ability to extrapolate from shorter-term data. With the need to better understand drivers and responses of whole-stream metabolism come difficulties in interpreting the results. Long-term trends will encompass physical changes in stream morphology and flow regime (e.g., variable flow conditions and changes in channel structure) combined with changes in biota. Additionally long-term data sets will require an organized database structure, careful quantification of errors and uncertainties, as well as propagation of error as a result of the calculation of metabolism metrics. Parsing of continuous data and the choice of modeling approaches can also have a large influence on results and on error estimation. The two main modeling challenges include 1) obtaining unbiased, low-error daily estimates of gross primary production (GPP) and ecosystem respiration (ER), and 2) interpreting GPP and ER measurements over extended time periods. The National Ecological Observatory Network (NEON), in partnership with academic and government scientists, has begun to tackle several of these challenges as it prepares for the collection and calculation of 30 years of continuous whole-stream metabolism data. NEON is a national-scale research platform that will use consistent procedures and protocols to standardize measurements across the United States, providing long

  20. Regulatory Network of Secondary Metabolism in Brassica rapa: Insight into the Glucosinolate Pathway

    OpenAIRE

    Dunia Pino Del Carpio; Ram Kumar Basnet; Danny Arends; Ke Lin; Ric C H De Vos; Dorota Muth; Jan Kodde; Kim Boutilier; Johan Bucher; Xiaowu Wang; Ritsert Jansen; Guusje Bonnema

    2014-01-01

    Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leave...

  1. Pathway Processor: A Tool for Integrating Whole-Genome Expression Results into Metabolic Networks

    OpenAIRE

    Grosu, Paul; Townsend, Jeffrey P.; Hartl, Daniel L.; Cavalieri, Duccio

    2002-01-01

    We have developed a new tool to visualize expression data on metabolic pathways and to evaluate which metabolic pathways are most affected by transcriptional changes in whole-genome expression experiments. Using the Fisher Exact Test, the method scores biochemical pathways according to the probability that as many or more genes in a pathway would be significantly altered in a given experiment by chance alone. This method has been validated on diauxic shift experiments and reproduces well know...

  2. Organization of Enzyme Concentration across the Metabolic Network in Cancer Cells

    OpenAIRE

    Madhukar, Neel S.; Warmoes, Marc O; Locasale, Jason W.

    2015-01-01

    Rapid advances in mass spectrometry have allowed for estimates of absolute concentrations across entire proteomes, permitting the interrogation of many important biological questions. Here, we focus on a quantitative aspect of human cancer cell metabolism that has been limited by a paucity of available data on the abundance of metabolic enzymes. We integrate data from recent measurements of absolute protein concentration to analyze the statistics of protein abundance across the human metaboli...

  3. Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.

    Directory of Open Access Journals (Sweden)

    Fabio Coppedè

    Full Text Available Folate metabolism, also known as one-carbon metabolism, is required for several cellular processes including DNA synthesis, repair and methylation. Impairments of this pathway have been often linked to Alzheimer's disease (AD. In addition, increasing evidence from large scale case-control studies, genome-wide association studies, and meta-analyses of the literature suggest that polymorphisms of genes involved in one-carbon metabolism influence the levels of folate, homocysteine and vitamin B12, and might be among AD risk factors. We analyzed a dataset of 30 genetic and biochemical variables (folate, homocysteine, vitamin B12, and 27 genotypes generated by nine common biallelic polymorphisms of genes involved in folate metabolism obtained from 40 late-onset AD patients and 40 matched controls to assess the predictive capacity of Artificial Neural Networks (ANNs in distinguish consistently these two different conditions and to identify the variables expressing the maximal amount of relevant information to the condition of being affected by dementia of Alzheimer's type. Moreover, we constructed a semantic connectivity map to offer some insight regarding the complex biological connections among the studied variables and the two conditions (being AD or control. TWIST system, an evolutionary algorithm able to remove redundant and noisy information from complex data sets, selected 16 variables that allowed specialized ANNs to discriminate between AD and control subjects with over 90% accuracy. The semantic connectivity map provided important information on the complex biological connections among one-carbon metabolic variables highlighting those most closely linked to the AD condition.

  4. Protein design in systems metabolic engineering for industrial strain development.

    Science.gov (United States)

    Chen, Zhen; Zeng, An-Ping

    2013-05-01

    Accelerating the process of industrial bacterial host strain development, aimed at increasing productivity, generating new bio-products or utilizing alternative feedstocks, requires the integration of complementary approaches to manipulate cellular metabolism and regulatory networks. Systems metabolic engineering extends the concept of classical metabolic engineering to the systems level by incorporating the techniques used in systems biology and synthetic biology, and offers a framework for the development of the next generation of industrial strains. As one of the most useful tools of systems metabolic engineering, protein design allows us to design and optimize cellular metabolism at a molecular level. Here, we review the current strategies of protein design for engineering cellular synthetic pathways, metabolic control systems and signaling pathways, and highlight the challenges of this subfield within the context of systems metabolic engineering.

  5. Ecological network analysis of an urban metabolic system based on input-output tables: model development and case study for Beijing.

    Science.gov (United States)

    Zhang, Yan; Zheng, Hongmei; Fath, Brian D; Liu, Hong; Yang, Zhifeng; Liu, Gengyuan; Su, Meirong

    2014-01-15

    If cities are considered as "superorganisms", then disorders of their metabolic processes cause something analogous to an "urban disease". It is therefore helpful to identify the causes of such disorders by analyzing the inner mechanisms that control urban metabolic processes. Combining input-output analysis with ecological network analysis lets researchers study the functional relationships and hierarchy of the urban metabolic processes, thereby providing direct support for the analysis of urban disease. In this paper, using Beijing as an example, we develop a model of an urban metabolic system that accounts for the intensity of the embodied ecological elements using monetary input-output tables from 1997, 2000, 2002, 2005, and 2007, and use this data to compile the corresponding physical input-output tables. This approach described the various flows of ecological elements through urban metabolic processes and let us build an ecological network model with 32 components. Then, using two methods from ecological network analysis (flow analysis and utility analysis), we quantitatively analyzed the physical input-output relationships among urban components, determined the ecological hierarchy of the components of the metabolic system, and determined the distribution of advantage-dominated and disadvantage-dominated relationships, thereby providing scientific support to guide restructuring of the urban metabolic system in an effort to prevent or cure urban "diseases".

  6. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  7. Systems biology study of mucopolysaccharidosis using a human metabolic reconstruction network.

    Science.gov (United States)

    Salazar, Diego A; Rodríguez-López, Alexander; Herreño, Angélica; Barbosa, Hector; Herrera, Juliana; Ardila, Andrea; Barreto, George E; González, Janneth; Alméciga-Díaz, Carlos J

    2016-02-01

    Mucopolysaccharidosis (MPS) is a group of lysosomal storage diseases (LSD), characterized by the deficiency of a lysosomal enzyme responsible for the degradation of glycosaminoglycans (GAG). This deficiency leads to the lysosomal accumulation of partially degraded GAG. Nevertheless, deficiency of a single lysosomal enzyme has been associated with impairment in other cell mechanism, such as apoptosis and redox balance. Although GAG analysis represents the main biomarker for MPS diagnosis, it has several limitations that can lead to a misdiagnosis, whereby the identification of new biomarkers represents an important issue for MPS. In this study, we used a system biology approach, through the use of a genome-scale human metabolic reconstruction to understand the effect of metabolism alterations in cell homeostasis and to identify potential new biomarkers in MPS. In-silico MPS models were generated by silencing of MPS-related enzymes, and were analyzed through a flux balance and variability analysis. We found that MPS models used approximately 2286 reactions to satisfy the objective function. Impaired reactions were mainly involved in cellular respiration, mitochondrial process, amino acid and lipid metabolism, and ion exchange. Metabolic changes were similar for MPS I and II, and MPS III A to C; while the remaining MPS showed unique metabolic profiles. Eight and thirteen potential high-confidence biomarkers were identified for MPS IVB and VII, respectively, which were associated with the secondary pathologic process of LSD. In vivo evaluation of predicted intermediate confidence biomarkers (β-hexosaminidase and β-glucoronidase) for MPS IVA and VI correlated with the in-silico prediction. These results show the potential of a computational human metabolic reconstruction to understand the molecular mechanisms this group of diseases, which can be used to identify new biomarkers for MPS. PMID:26276570

  8. Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease

    Directory of Open Access Journals (Sweden)

    Chavali Arvind K

    2012-04-01

    Full Text Available Abstract Background Systems biology holds promise as a new approach to drug target identification and drug discovery against neglected tropical diseases. Genome-scale metabolic reconstructions, assembled from annotated genomes and a vast array of bioinformatics/biochemical resources, provide a framework for the interrogation of human pathogens and serve as a platform for generation of future experimental hypotheses. In this article, with the application of selection criteria for both Leishmania major targets (e.g. in silico gene lethality and drugs (e.g. toxicity, a method (MetDP to rationally focus on a subset of low-toxic Food and Drug Administration (FDA-approved drugs is introduced. Results This metabolic network-driven approach identified 15 L. major genes as high-priority targets, 8 high-priority synthetic lethal targets, and 254 FDA-approved drugs. Results were compared to previous literature findings and existing high-throughput screens. Halofantrine, an antimalarial agent that was prioritized using MetDP, showed noticeable antileishmanial activity when experimentally evaluated in vitro against L. major promastigotes. Furthermore, synthetic lethality predictions also aided in the prediction of superadditive drug combinations. For proof-of-concept, double-drug combinations were evaluated in vitro against L. major and four combinations involving the drug disulfiram that showed superadditivity are presented. Conclusions A direct metabolic network-driven method that incorporates single gene essentiality and synthetic lethality predictions is proposed that generates a set of high-priority L. major targets, which are in turn associated with a select number of FDA-approved drugs that are candidate antileishmanials. Additionally, selection of high-priority double-drug combinations might provide for an attractive and alternative avenue for drug discovery against leishmaniasis.

  9. Bistability in a Metabolic Network Underpins the De Novo Evolution of Colony Switching in Pseudomonas fluorescens

    DEFF Research Database (Denmark)

    Gallie, Jenna; Libby, Eric; Bertels, Frederic;

    2015-01-01

    levels favour nucleotide metabolism (capsule OFF), while cells with lower pyrimidine levels divert resources towards polymer biosynthesis (capsule ON). This decision point is present and functional in the wild-type strain. Finally, we present a simple mathematical model demonstrating that the molecular...... in central metabolism (carB) generates such a striking phenotype. We show that colony switching is underpinned by ON/OFF expression of capsules consisting of a colanic acid-like polymer. We use molecular genetics, biochemical analyses, and experimental evolution to establish that capsule switching results...

  10. Proteome- and transcriptome-driven reconstruction of the human myocyte metabolic network and its use for identification of markers for diabetes

    DEFF Research Database (Denmark)

    Väremo, Leif; Scheele, Camilla; Broholm, Christa;

    2015-01-01

    -analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism......Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome......-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta...

  11. The topology of the bacterial co-conserved protein network and its implications for predicting protein function

    Directory of Open Access Journals (Sweden)

    Leach Sonia M

    2008-06-01

    Full Text Available Abstract Background Protein-protein interactions networks are most often generated from physical protein-protein interaction data. Co-conservation, also known as phylogenetic profiles, is an alternative source of information for generating protein interaction networks. Co-conservation methods generate interaction networks among proteins that are gained or lost together through evolution. Co-conservation is a particularly useful technique in the compact bacteria genomes. Prior studies in yeast suggest that the topology of protein-protein interaction networks generated from physical interaction assays can offer important insight into protein function. Here, we hypothesize that in bacteria, the topology of protein interaction networks derived via co-conservation information could similarly improve methods for predicting protein function. Since the topology of bacteria co-conservation protein-protein interaction networks has not previously been studied in depth, we first perform such an analysis for co-conservation networks in E. coli K12. Next, we demonstrate one way in which network connectivity measures and global and local function distribution can be exploited to predict protein function for previously uncharacterized proteins. Results Our results showed, like most biological networks, our bacteria co-conserved protein-protein interaction networks had scale-free topologies. Our results indicated that some properties of the physical yeast interaction network hold in our bacteria co-conservation networks, such as high connectivity for essential proteins. However, the high connectivity among protein complexes in the yeast physical network was not seen in the co-conservation network which uses all bacteria as the reference set. We found that the distribution of node connectivity varied by functional category and could be informative for function prediction. By integrating of functional information from different annotation sources and using the

  12. Lack of evolvability in self-sustaining autocatalytic networks constraints metabolism-first scenarios for the origin of life.

    Science.gov (United States)

    Vasas, Vera; Szathmáry, Eörs; Santos, Mauro

    2010-01-26

    A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first "living" systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where self-reproducing and evolving proto-metabolic networks are assumed to have predated self-replicating genes. Recent theoretical work shows that "compositional genomes" (i.e., the counts of different molecular species in an assembly) are able to propagate compositional information and can provide a setup on which natural selection acts. Accordingly, if we stick to the notion of replicator as an entity that passes on its structure largely intact in successive replications, those macromolecular aggregates could be dubbed "ensemble replicators" (composomes) and quite different from the more familiar genes and memes. In sharp contrast with template-dependent replication dynamics, we demonstrate here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and, therefore, the system lacks evolvability (i.e., it cannot substantially depart from the asymptotic steady-state solution already built-in in the dynamical equations). We conclude that this fundamental limitation of ensemble replicators cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.

  13. An Experimentally-Supported Genome-Scale Metabolic Network Reconstruction for Yersinia pestis CO92

    Energy Technology Data Exchange (ETDEWEB)

    Charusanti, Pep; Chauhan, Sadhana; Mcateer, Kathleen; Lerman, Joshua A.; Hyduke, Daniel R.; Motin, Vladimir L.; Ansong, Charles; Adkins, Joshua N.; Palsson, Bernhard O.

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, thus provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  14. An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92

    Directory of Open Access Journals (Sweden)

    Motin Vladimir L

    2011-10-01

    Full Text Available Abstract Background Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Results Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Conclusions Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  15. Network-level architecture and the evolutionary potential of underground metabolism

    NARCIS (Netherlands)

    Notebaart, R.A.; Szappanos, B.; Kintses, B.; Pal, F; Gyorkei, A.; Bogos, B.; Lazar, V.; Spohn, R.; Csorgo, B.; Wagner, A.; Ruppin, E.; Pal, C.; Papp, B.

    2014-01-01

    A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remaine

  16. Metabolic ecology.

    Science.gov (United States)

    Humphries, Murray M; McCann, Kevin S

    2014-01-01

    Ecological theory that is grounded in metabolic currencies and constraints offers the potential to link ecological outcomes to biophysical processes across multiple scales of organization. The metabolic theory of ecology (MTE) has emphasized the potential for metabolism to serve as a unified theory of ecology, while focusing primarily on the size and temperature dependence of whole-organism metabolic rates. Generalizing metabolic ecology requires extending beyond prediction and application of standardized metabolic rates to theory focused on how energy moves through ecological systems. A bibliometric and network analysis of recent metabolic ecology literature reveals a research network characterized by major clusters focused on MTE, foraging theory, bioenergetics, trophic status, and generalized patterns and predictions. This generalized research network, which we refer to as metabolic ecology, can be considered to include the scaling, temperature and stoichiometric models forming the core of MTE, as well as bioenergetic equations, foraging theory, life-history allocation models, consumer-resource equations, food web theory and energy-based macroecology models that are frequently employed in ecological literature. We conclude with six points we believe to be important to the advancement and integration of metabolic ecology, including nomination of a second fundamental equation, complementary to the first fundamental equation offered by the MTE. PMID:24028511

  17. Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

    OpenAIRE

    He, Fei; Murabito, Ettore; Westerhoff, Hans V

    2016-01-01

    Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased...

  18. Symmetry in the Language of Gene Expression: A Survey of Gene Promoter Networks in Multiple Bacterial Species and Non-σ Regulons

    Directory of Open Access Journals (Sweden)

    Stefan M. Turcic

    2011-11-01

    Full Text Available The language of gene expression displays topological symmetry. An important step during gene expression is the binding of transcriptional proteins to DNA promoters adjacent to a gene. Some proteins bind to many promoters in a genome, defining a regulon of genes wherein each promoter might vary in DNA sequence relative to the average consensus. Here we examine the linguistic organization of gene promoter networks, wherein each node in the network represents a promoter and links between nodes represent the extent of base pair-sharing. Prior work revealed a fractal nucleus in several σ-factor regulons from Escherichia coli. We extend these findings to show fractal nuclei in gene promoter networks from three bacterial species, E. coli, Bacillus subtilis, and Pseudomonas aeruginosa. We surveyed several non-σ transcription factors from these species and found that many contain a nucleus that is both visually and numerically fractal. Promoter footprint size scaled as a negative power-law with both information entropy and fractal dimension, while the latter two parameters scaled positively and linearly. The fractal dimension of the diffuse networks (dB = ~1.7 was close to that expected of a diffusion limited aggregation process, confirming prior predictions as to a possible mechanism for development of this structure.

  19. Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism incorporating different states of hydroxylation.

    Science.gov (United States)

    Kavun Ozbayraktar, Fatma Betul; Ulgen, Kutlu O

    2011-04-01

    The first elaborate metabolic model of Saccharomyces cerevisiae sphingolipid metabolism was reconstructed in silico. The model considers five different states of sphingolipid hydroxylation, rendering it unique among other models. It is aimed to clarify the significance of hydroxylation on sphingolipids and hence to interpret the preferences of the cell between different metabolic pathway branches under different stress conditions. The newly constructed model was validated by single, double and triple gene deletions with experimentally verified phenotypes. Calcium sensitivity and deletion mutations that may suppress calcium sensitivity were examined by CSG1 and CSG2 related deletions. The model enabled the analysis of complex sphingolipid content of the plasma membrane coupled with diacylglycerol and phosphatidic acid biosynthesis and ATP consumption in in silico cell. The flux data belonging to these critically important key metabolites are integrated with the fact of phytoceramide induced cell death to propose novel potential drug targets for cancer therapeutics. In conclusion, we propose that IPT1, GDA1, CSG and AUR1 gene deletions may be novel candidates of drug targets for cancer therapy according to the results of flux balance and variability analyses coupled with robustness analysis.

  20. Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks.

    Science.gov (United States)

    Simão, Daniel; Terrasso, Ana P; Teixeira, Ana P; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M

    2016-01-01

    The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-(13)C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells. PMID:27619889

  1. Enhancing Carbon Fixation by Metabolic Engineering: A Model System of Complex Network Modulation

    Energy Technology Data Exchange (ETDEWEB)

    Dr. Gregory Stephanopoulos

    2008-04-10

    In the first two years of this research we focused on the development of a DNA microarray for transcriptional studies in the photosynthetic organism Synechocystis and the elucidation of the metabolic pathway for biopolymer synthesis in this organism. In addition we also advanced the molecular biological tools for metabolic engineering of biopolymer synthesis in Synechocystis and initiated a series of physiological studies for the elucidation of the carbon fixing pathways and basic central carbon metabolism of these organisms. During the last two-year period we focused our attention on the continuation and completion of the last task, namely, the development of tools for basic investigations of the physiology of these cells through, primarily, the determination of their metabolic fluxes. The reason for this decision lies in the importance of fluxes as key indicators of physiology and the high level of information content they carry in terms of identifying rate limiting steps in a metabolic pathway. While flux determination is a well-advanced subject for heterotrophic organisms, for the case of autotrophic bacteria, like Synechocystis, some special challenges had to be overcome. These challenges stem mostly from the fact that if one uses {sup 13}C labeled CO{sub 2} for flux determination, the {sup 13}C label will mark, at steady state, all carbon atoms of all cellular metabolites, thus eliminating the necessary differentiation required for flux determination. This peculiarity of autotrophic organisms makes it imperative to carry out flux determination under transient conditions, something that had not been accomplished before. We are pleased to report that we have solved this problem and we are now able to determine fluxes in photosynthetic organisms from stable isotope labeling experiments followed by measurements of label enrichment in cellular metabolites using Gas Chromatography-Mass Spectrometry. We have conducted extensive simulations to test the method and

  2. Modulation of glutamine metabolism by the PI(3)K-PKB-FOXO network regulates autophagy

    NARCIS (Netherlands)

    van der Vos, Kristan E.; Eliasson, Pernilla; Proikas-Cezanne, Tassula; Vervoort, Stephin J.; van Boxtel, Ruben; Putker, Marrit; van Zutphen, Iris J.; Mauthe, Mario; Zellmer, Sebastian; Pals, Cornelieke; Verhagen, Liesbeth P.; Koerkamp, Marian J. A. Groot; Braat, A. Koen; Dansen, Tobias B.; Holstege, Frank C.; Gebhardt, Rolf; Burgering, Boudewijn M.; Coffer, Paul J.

    2012-01-01

    The PI(3)K-PKB-FOXO signalling network provides a major intracellular hub for the regulation of cell proliferation, survival and stress resistance. Here we report an unexpected role for FOXO transcription factors inregulating autophagy by modulating intracellular glutamine levels. To identify transc

  3. Change in network connectivity during fictive-gasping generation in hypoxia: Prevention by a metabolic intermediate

    Directory of Open Access Journals (Sweden)

    Andrés eNieto-Posadas

    2014-07-01

    Full Text Available The neuronal circuit in charge of generating the respiratory rhythms, localized in the pre-Bötzinger complex (preBötC, is configured to produce fictive-eupnea during normoxia and reconfigures to produce fictive-gasping during hypoxic conditions in vitro. The mechanisms involved in such reconfiguration have been extensively investigated by cell-focused studies, but the actual changes at the network level remain elusive. Since a failure to generate gasping has been linked to Sudden Infant Death Syndrome, the study of gasping generation and pharmacological approaches to promote it may have clinical relevance. Here, we study the changes in network dynamics and circuit reconfiguration that occur during the transition to fictive-gasping generation in the brainstem slice preparation by recording the preBötC with multi-electrode arrays and assessing correlated firing among respiratory neurons or clusters of respiratory neurons (multiunits. We studied whether the respiratory network reconfiguration in hypoxia involves changes in either the number of active respiratory elements, the number of functional connections among elements, or the strength of these connections. Moreover, we tested the influence of isocitrate, a Krebs cycle intermediate that has recently been shown to promote breathing, on the configuration of the preBötC circuit during normoxia and on its reconfiguration during hypoxia. We found that, in contrast to previous suggestions based on cell-focused studies, the number and the overall activity of respiratory neurons change only slightly during hypoxia. However, hypoxia induces a reduction in the strength of functional connectivity within the circuit without reducing the number of connections. Isocitrate prevented this reduction during hypoxia while increasing the strength of network connectivity. In conclusion, we provide an overview of the configuration of the respiratory network under control conditions and how it is reconfigured

  4. Biochemical characterization of human gluconokinase and the proposed metabolic impact of gluconic Acid as determined by constraint based metabolic network analysis

    DEFF Research Database (Denmark)

    Rohatgi, Neha; Nielsen, Tine Kragh; Bjørn, Sara Petersen;

    2014-01-01

    The metabolism of gluconate is well characterized in prokaryotes where it is known to be degraded following phosphorylation by gluconokinase. Less is known of gluconate metabolism in humans. Human gluconokinase activity was recently identified proposing questions about the metabolic role of gluco......, the results highlight that little is known of the mechanism of gluconate metabolism in humans despite its widespread use in medicine and consumer products.......The metabolism of gluconate is well characterized in prokaryotes where it is known to be degraded following phosphorylation by gluconokinase. Less is known of gluconate metabolism in humans. Human gluconokinase activity was recently identified proposing questions about the metabolic role...... of gluconate in humans. Here we report the recombinant expression, purification and biochemical characterization of isoform I of human gluconokinase alongside substrate specificity and kinetic assays of the enzyme catalyzed reaction. The enzyme, shown to be a dimer, had ATP dependent phosphorylation activity...

  5. A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics

    Directory of Open Access Journals (Sweden)

    van Gulik Walter M

    2006-12-01

    Full Text Available Abstract Background Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (disfunctioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog format have been proposed as a suitable alternative with fewer parameters. Results In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC simulations. Conclusion The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only

  6. Astragaloside IV improves lipid metabolism in obese mice by alleviation of leptin resistance and regulation of thermogenic network

    Science.gov (United States)

    Wu, Hui; Gao, Yan; Shi, Hai-Lian; Qin, Li-Yue; Huang, Fei; Lan, Yun-Yi; Zhang, Bei-Bei; Hu, Zhi-Bi; Wu, Xiao-Jun

    2016-01-01

    Obesity is a worldwide threat to public health in modern society, which may result from leptin resistance and disorder of thermogenesis. The present study investigated whether astragaloside IV (ASI) could prevent obesity in high-fat diet (HFD)-fed and db/db mice. In HFD-fed mice, ASI prevented body weight gain, lowered serum triglyceride and total cholesterol levels, mitigated liver lipid accumulation, reduced fat tissues and decreased the enlargement of adipose cells. In metabolic chambers, ASI lessened appetite of the mice, decreased their respiratory exchange ratio and elevated VCO2 and VO2 without altering circadian motor activity. Moreover, ASI modulated thermogenesis associated gene expressions in liver and brawn fat tissues, as well as leptin resistance evidenced by altered expressions of leptin, leptin receptor (ObR) or appetite associated genes. In SH-SY5Y cells, ASI enhanced leptin signaling transduction. However, in db/db mice, ASI did not change body weight gain and appetite associated genes. But it decreased serum triglyceride and total cholesterol levels as well as liver triglyceride. Meanwhile, it significantly modulated gene expressions of PPARα, PGC1-α, UCP2, ACC, SCD1, LPL, AP2, CD36 and SREBP-1c. Collectively, our study suggested that ASI could efficiently improve lipid metabolism in obese mice probably through enhancing leptin sensitivity and modulating thermogenic network. PMID:27444146

  7. Astragaloside IV improves lipid metabolism in obese mice by alleviation of leptin resistance and regulation of thermogenic network.

    Science.gov (United States)

    Wu, Hui; Gao, Yan; Shi, Hai-Lian; Qin, Li-Yue; Huang, Fei; Lan, Yun-Yi; Zhang, Bei-Bei; Hu, Zhi-Bi; Wu, Xiao-Jun

    2016-01-01

    Obesity is a worldwide threat to public health in modern society, which may result from leptin resistance and disorder of thermogenesis. The present study investigated whether astragaloside IV (ASI) could prevent obesity in high-fat diet (HFD)-fed and db/db mice. In HFD-fed mice, ASI prevented body weight gain, lowered serum triglyceride and total cholesterol levels, mitigated liver lipid accumulation, reduced fat tissues and decreased the enlargement of adipose cells. In metabolic chambers, ASI lessened appetite of the mice, decreased their respiratory exchange ratio and elevated VCO2 and VO2 without altering circadian motor activity. Moreover, ASI modulated thermogenesis associated gene expressions in liver and brawn fat tissues, as well as leptin resistance evidenced by altered expressions of leptin, leptin receptor (ObR) or appetite associated genes. In SH-SY5Y cells, ASI enhanced leptin signaling transduction. However, in db/db mice, ASI did not change body weight gain and appetite associated genes. But it decreased serum triglyceride and total cholesterol levels as well as liver triglyceride. Meanwhile, it significantly modulated gene expressions of PPARα, PGC1-α, UCP2, ACC, SCD1, LPL, AP2, CD36 and SREBP-1c. Collectively, our study suggested that ASI could efficiently improve lipid metabolism in obese mice probably through enhancing leptin sensitivity and modulating thermogenic network. PMID:27444146

  8. Effects of chlorinated drinking water on the xenobiotic metabolism in Cyprinus carpio treated with samples from two Italian municipal networks.

    Science.gov (United States)

    Cirillo, Silvia; Canistro, Donatella; Vivarelli, Fabio; Paolini, Moreno

    2016-09-01

    Drinking water (DW) disinfection represents a milestone of the past century, thanks to its efficacy in the reduction of risks of epidemic forms by water micro-organisms. Nevertheless, such process generates disinfection by-products (DBPs), some of which are genotoxic both in animals and in humans and carcinogenic in animals. At present, chlorination is one of the most employed strategies but the toxicological effects of several classes of DBPs are unknown. In this investigation, a multidisciplinary approach foreseeing the chemical analysis of chlorinated DW samples and the study of its effects on mixed function oxidases (MFOs) belonging to the superfamily of cytochrome P450-linked monooxygenases of Cyprinus carpio hepatopancreas, was employed. The experimental samples derived from aquifers of two Italian towns (plant 1, river water and plant 2, spring water) were obtained immediately after the disinfection (A) and along the network (R1). Animals treated with plant 1 DW-processed fractions showed a general CYP-associated MFO induction. By contrast, in plant 2, a complex modulation pattern was achieved, with a general up-regulation for the point A and a marked MFO inactivation in the R1 group, particularly for the testosterone metabolism. Together, the toxicity and co-carcinogenicity (i.e. unremitting over-generation of free radicals and increased bioactivation capability) of DW linked to the recorded metabolic manipulation, suggests that a prolonged exposure to chlorine-derived disinfectants may produce adverse health effects.

  9. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  10. Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays

    Science.gov (United States)

    To investigate the natural variability of leaf metabolism and enzymatic activity in a maize inbred population, statistical and network analyses were employed on metabolite and enzyme profiles. The test of coefficient of variation showed that sugars and amino acids displayed opposite trends in their ...

  11. To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

    Directory of Open Access Journals (Sweden)

    Christopher D Nogiec

    Full Text Available Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation's effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation's effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology.

  12. To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

    Science.gov (United States)

    Nogiec, Christopher D; Kasif, Simon

    2013-01-01

    Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation's effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation's effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology. PMID:23967053

  13. Screening of potential targets in Plasmodium falciparum using stage-specific metabolic network analysis.

    Science.gov (United States)

    Dholakia, Neel; Dhandhukia, Pinakin; Roy, Nilanjan

    2015-11-01

    The Apicomplexa parasite Plasmodium is a major cause of death in developing countries which are less equipped to bring new medicines to the market. Currently available drugs used for treatment of malaria are limited either by inadequate efficacy, toxicity and/or increased resistance. Availability of the genome sequence, microarray data and metabolic profile of Plasmodium parasite offers an opportunity for the identification of stage-specific genes important to the organism's lifecycle. In this study, microarray data were analysed for differential expression and overlapped onto metabolic pathways to identify differentially regulated pathways essential for transition to successive erythrocytic stages. The results obtained indicate that S-adenosylmethionine decarboxylase/ornithine decarboxylase, a bifunctional enzyme required for polyamine synthesis, is important for the Plasmodium cell growth in the absence of exogenous polyamines. S-adenosylmethionine decarboxylase/ornithine decarboxylase is a valuable target for designing therapeutically useful inhibitors. One such inhibitor, [Formula: see text]-difluoromethyl ornithine, is currently in use for the treatment of African sleeping sickness caused by Trypanosoma brucei. Structural studies of ornithine decarboxylase along with known inhibitors and their analogues were carried out to screen drug databases for more effective and less toxic compounds. PMID:26303382

  14. Identifying genes and gene networks involved in chromium metabolism and detoxification in Crambe abyssinica

    Energy Technology Data Exchange (ETDEWEB)

    Zulfiqar, Asma, E-mail: asmazulfiqar08@yahoo.com [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Paulose, Bibin, E-mail: bpaulose@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Chhikara, Sudesh, E-mail: sudesh@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Dhankher, Om Parkash, E-mail: parkash@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States)

    2011-10-15

    Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: > Molecular mechanism of Cr uptake and detoxification in plants is not well known. > We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. > 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. > Pathways linked to stress, ion transport, and sulfur assimilation were affected. > This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.

  15. Screening of potential targets in Plasmodium falciparum using stage-specific metabolic network analysis.

    Science.gov (United States)

    Dholakia, Neel; Dhandhukia, Pinakin; Roy, Nilanjan

    2015-11-01

    The Apicomplexa parasite Plasmodium is a major cause of death in developing countries which are less equipped to bring new medicines to the market. Currently available drugs used for treatment of malaria are limited either by inadequate efficacy, toxicity and/or increased resistance. Availability of the genome sequence, microarray data and metabolic profile of Plasmodium parasite offers an opportunity for the identification of stage-specific genes important to the organism's lifecycle. In this study, microarray data were analysed for differential expression and overlapped onto metabolic pathways to identify differentially regulated pathways essential for transition to successive erythrocytic stages. The results obtained indicate that S-adenosylmethionine decarboxylase/ornithine decarboxylase, a bifunctional enzyme required for polyamine synthesis, is important for the Plasmodium cell growth in the absence of exogenous polyamines. S-adenosylmethionine decarboxylase/ornithine decarboxylase is a valuable target for designing therapeutically useful inhibitors. One such inhibitor, [Formula: see text]-difluoromethyl ornithine, is currently in use for the treatment of African sleeping sickness caused by Trypanosoma brucei. Structural studies of ornithine decarboxylase along with known inhibitors and their analogues were carried out to screen drug databases for more effective and less toxic compounds.

  16. In vitro reconstruction and analysis of evolutionary variation of the tomato acylsucrose metabolic network

    OpenAIRE

    Fan, Pengxiang; Miller, Abigail M.; Schilmiller, Anthony L.; Liu, Xiaoxiao; Ofner, Itai; Jones, A. Daniel; Zamir, Dani; Last, Robert L.

    2015-01-01

    Throughout the course of human history, plant-derived natural products have been used in medicines, in cooking, as pest control agents, and in rituals of cultural importance. Plants produce rapidly diversifying specialized metabolites as protective agents and to mediate interactions with beneficial organisms. In vitro reconstruction of the cultivated tomato insect protective acylsucrose biosynthetic network showed that four acyltransferase enzymes are sufficient to produce the full set of nat...

  17. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    Science.gov (United States)

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

  18. Evolution of the metabolic and regulatory networks associated with oxygen availability in two phytopathogenic enterobacteria

    Directory of Open Access Journals (Sweden)

    Babujee Lavanya

    2012-03-01

    Full Text Available Abstract Background Dickeya dadantii and Pectobacterium atrosepticum are phytopathogenic enterobacteria capable of facultative anaerobic growth in a wide range of O2 concentrations found in plant and natural environments. The transcriptional response to O2 remains under-explored for these and other phytopathogenic enterobacteria although it has been well characterized for animal-associated genera including Escherichia coli and Salmonella enterica. Knowledge of the extent of conservation of the transcriptional response across orthologous genes in more distantly related species is useful to identify rates and patterns of regulon evolution. Evolutionary events such as loss and acquisition of genes by lateral transfer events along each evolutionary branch results in lineage-specific genes, some of which may have been subsequently incorporated into the O2-responsive stimulon. Here we present a comparison of transcriptional profiles measured using densely tiled oligonucleotide arrays for two phytopathogens, Dickeya dadantii 3937 and Pectobacterium atrosepticum SCRI1043, grown to mid-log phase in MOPS minimal medium (0.1% glucose with and without O2. Results More than 7% of the genes of each phytopathogen are differentially expressed with greater than 3-fold changes under anaerobic conditions. In addition to anaerobic metabolism genes, the O2 responsive stimulon includes a variety of virulence and pathogenicity-genes. Few of these genes overlap with orthologous genes in the anaerobic stimulon of E. coli. We define these as the conserved core, in which the transcriptional pattern as well as genetic architecture are well preserved. This conserved core includes previously described anaerobic metabolic pathways such as fermentation. Other components of the anaerobic stimulon show variation in genetic content, genome architecture and regulation. Notably formate metabolism, nitrate/nitrite metabolism, and fermentative butanediol production, differ between E

  19. Reconstructing a hydrogen-driven microbial metabolic network in Opalinus Clay rock

    Science.gov (United States)

    Bagnoud, Alexandre; Chourey, Karuna; Hettich, Robert L.; de Bruijn, Ino; Andersson, Anders F.; Leupin, Olivier X.; Schwyn, Bernhard; Bernier-Latmani, Rizlan

    2016-01-01

    The Opalinus Clay formation will host geological nuclear waste repositories in Switzerland. It is expected that gas pressure will build-up due to hydrogen production from steel corrosion, jeopardizing the integrity of the engineered barriers. In an in situ experiment located in the Mont Terri Underground Rock Laboratory, we demonstrate that hydrogen is consumed by microorganisms, fuelling a microbial community. Metagenomic binning and metaproteomic analysis of this deep subsurface community reveals a carbon cycle driven by autotrophic hydrogen oxidizers belonging to novel genera. Necromass is then processed by fermenters, followed by complete oxidation to carbon dioxide by heterotrophic sulfate-reducing bacteria, which closes the cycle. This microbial metabolic web can be integrated in the design of geological repositories to reduce pressure build-up. This study shows that Opalinus Clay harbours the potential for chemolithoautotrophic-based system, and provides a model of microbial carbon cycle in deep subsurface environments where hydrogen and sulfate are present. PMID:27739431

  20. Reconstructing a hydrogen-driven microbial metabolic network in Opalinus Clay rock

    Science.gov (United States)

    Bagnoud, Alexandre; Chourey, Karuna; Hettich, Robert L.; de Bruijn, Ino; Andersson, Anders F.; Leupin, Olivier X.; Schwyn, Bernhard; Bernier-Latmani, Rizlan

    2016-10-01

    The Opalinus Clay formation will host geological nuclear waste repositories in Switzerland. It is expected that gas pressure will build-up due to hydrogen production from steel corrosion, jeopardizing the integrity of the engineered barriers. In an in situ experiment located in the Mont Terri Underground Rock Laboratory, we demonstrate that hydrogen is consumed by microorganisms, fuelling a microbial community. Metagenomic binning and metaproteomic analysis of this deep subsurface community reveals a carbon cycle driven by autotrophic hydrogen oxidizers belonging to novel genera. Necromass is then processed by fermenters, followed by complete oxidation to carbon dioxide by heterotrophic sulfate-reducing bacteria, which closes the cycle. This microbial metabolic web can be integrated in the design of geological repositories to reduce pressure build-up. This study shows that Opalinus Clay harbours the potential for chemolithoautotrophic-based system, and provides a model of microbial carbon cycle in deep subsurface environments where hydrogen and sulfate are present.

  1. Identifying genes and gene networks involved in chromium metabolism and detoxification in Crambe abyssinica

    International Nuclear Information System (INIS)

    Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: → Molecular mechanism of Cr uptake and detoxification in plants is not well known. → We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. → 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. → Pathways linked to stress, ion transport, and sulfur assimilation were affected. → This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.

  2. Composition and Metabolic Activities of the Bacterial Community in Shrimp Sauce at the Flavor-Forming Stage of Fermentation As Revealed by Metatranscriptome and 16S rRNA Gene Sequencings.

    Science.gov (United States)

    Duan, Shan; Hu, Xiaoxi; Li, Mengru; Miao, Jianyin; Du, Jinghe; Wu, Rongli

    2016-03-30

    The bacterial community and the metabolic activities involved at the flavor-forming stage during the fermentation of shrimp sauce were investigated using metatranscriptome and 16S rRNA gene sequencings. Results showed that the abundance of Tetragenococcus was 95.1%. Tetragenococcus halophilus was identified in 520 of 588 transcripts annotated in the Nr database. Activation of the citrate cycle and oxidative phosphorylation, along with the absence of lactate dehydrogenase gene expression, in T. halophilus suggests that T. halophilus probably underwent aerobic metabolism during shrimp sauce fermentation. The metabolism of amino acids, production of peptidase, and degradation of limonene and pinene were very active in T. halophilus. Carnobacterium, Pseudomonas, Escherichia, Staphylococcus, Bacillus, and Clostridium were also metabolically active, although present in very small populations. Enterococcus, Abiotrophia, Streptococcus, and Lactobacillus were detected in metatranscriptome sequencing, but not in 16S rRNA gene sequencing. Many minor taxa showed no gene expression, suggesting that they were in dormant status. PMID:26978261

  3. Metabolic mapping reveals sex-dependent involvement of default mode and salience network in alexithymia.

    Science.gov (United States)

    Colic, L; Demenescu, L R; Li, M; Kaufmann, J; Krause, A L; Metzger, C; Walter, M

    2016-02-01

    Alexithymia, a personality construct marked by difficulties in processing one's emotions, has been linked to the altered activity in the anterior cingulate cortex (ACC). Although longitudinal studies reported sex differences in alexithymia, what mediates them is not known. To investigate sex-specific associations of alexithymia and neuronal markers, we mapped metabolites in four brain regions involved differentially in emotion processing using a point-resolved spectroscopy MRS sequence in 3 Tesla. Both sexes showed negative correlations between alexithymia and N-acetylaspartate (NAA) in pregenual ACC (pgACC). Women showed a robust negative correlation of the joint measure of glutamate and glutamine (Glx) to NAA in posterior cingulate cortex (PCC), whereas men showed a weak positive association of Glx to NAA in dorsal ACC (dACC). Our results suggest that lowered neuronal integrity in pgACC, a region of the default mode network (DMN), might primarily account for the general difficulties in emotional processing in alexithymia. Association of alexithymia in women extends to another region in the DMN-PCC, while in men a region in the salience network (SN) was involved. These observations could be representative of sex specific regulation strategies that include diminished internal evaluation of feelings in women and cognitive emotion suppression in men. PMID:26341904

  4. Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

    OpenAIRE

    Vishveshwara Saraswathi; Bhattacharyya Moitrayee

    2009-01-01

    Abstract Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this stud...

  5. Tracing bacterial metabolism using multi-nuclear (1H, 2H, and 13C) Solid State NMR: Realizing an Idea Initiated by James Scott

    Science.gov (United States)

    Cody, G.; Fogel, M. L.; Jin, K.; Griffen, P.; Steele, A.; Wang, Y.

    2011-12-01

    Approximately 6 years ago, while at the Geophysical Laboratory, James Scott became interested in the application of Solid State Nuclear Magnetic Resonance Spectroscopy to study bacterial metabolism. As often happens, other experiments intervened and the NMR experiments were not pursued. We have revisited Jame's question and find that using a multi-nuclear approach (1H, 2H, and 13C Solid State NMR) on laboratory cell culture has some distinct advantages. Our experiments involved batch cultures of E. coli (MG1655) harvested at stationary phase. In all experiments the growth medium consisted of MOPS medium for enterobacteria, where the substrate is glucose. In one set of experiments, 10 % of the water was D2O; in another 10 % of the glucose was per-deuterated. The control experiment used both water and glucose at natural isotopic abundance. A kill control of dead E. coli immersed in pure D2O for an extended period exhibited no deuterium incorporation. In both deuterium enriched experiments, considerable incorporation of deuterium into E. coli's biomolecular constituents was detected via 2H Solid State NMR. In the case of the D2O enriched experiment, 58 % of the incorporated deuterium is observed in a sharp peak at a frequency of 0.31 ppm, consistent with D incorporation in the cell membrane lipids, the remainder is observed in a broad peak at a higher frequency (centered at 5.4 ppm, but spanning out to beyond 10 ppm) that is consistent with D incorporation into predominantly DNA and RNA. In the case of the D-glucose experiments, 61 % of the deuterium is observed in a sharp resonance peak at 0.34 ppm, also consistent with D incorporation into membrane lipids, the remainder of the D is observed at a broad resonance peak centered at 4.3 ppm, consistent with D enrichment in glycogen. Deuterium abundance in the E. coli cells grown in 10 % D2O is nearly 2X greater than that grown with 10 % D-glucose. Very subtle differences are observed in both the 1H and 13C solid

  6. In vitro reconstruction and analysis of evolutionary variation of the tomato acylsucrose metabolic network.

    Science.gov (United States)

    Fan, Pengxiang; Miller, Abigail M; Schilmiller, Anthony L; Liu, Xiaoxiao; Ofner, Itai; Jones, A Daniel; Zamir, Dani; Last, Robert L

    2016-01-12

    Plant glandular secreting trichomes are epidermal protuberances that produce structurally diverse specialized metabolites, including medically important compounds. Trichomes of many plants in the nightshade family (Solanaceae) produce O-acylsugars, and in cultivated and wild tomatoes these are mixtures of aliphatic esters of sucrose and glucose of varying structures and quantities documented to contribute to insect defense. We characterized the first two enzymes of acylsucrose biosynthesis in the cultivated tomato Solanum lycopersicum. These are type I/IV trichome-expressed BAHD acyltransferases encoded by Solyc12g006330--or S. lycopersicum acylsucrose acyltransferase 1 (Sl-ASAT1)--and Solyc04g012020 (Sl-ASAT2). These enzymes were used--in concert with two previously identified BAHD acyltransferases--to reconstruct the entire cultivated tomato acylsucrose biosynthetic pathway in vitro using sucrose and acyl-CoA substrates. Comparative genomics and biochemical analysis of ASAT enzymes were combined with in vitro mutagenesis to identify amino acids that influence CoA ester substrate specificity and contribute to differences in types of acylsucroses that accumulate in cultivated and wild tomato species. This work demonstrates the feasibility of the metabolic engineering of these insecticidal metabolites in plants and microbes. PMID:26715757

  7. Characterization of the periplasmic redox network that sustains the versatile anaerobic metabolism of Shewanella oneidensis MR-1

    Directory of Open Access Journals (Sweden)

    Mónica N. Alves

    2015-06-01

    Full Text Available The versatile anaerobic metabolism of the Gram-negative bacterium Shewanella oneidensis MR-1 (SOMR-1 relies on a multitude of redox proteins found in its periplasm. Most are multiheme cytochromes that carry electrons to terminal reductases of insoluble electron acceptors located at the cell surface, or bona fide terminal reductases of soluble electron acceptors. In this study, the interaction network of several multiheme cytochromes was explored by a combination of NMR spectroscopy, activity assays followed by UV-visible spectroscopy and comparison of surface electrostatic potentials. From these data the small tetraheme cytochrome (STC emerges as the main periplasmic redox shuttle in SOMR-1. It accepts electrons from CymA and distributes them to a number of terminal oxidoreductases involved in the respiration of various compounds. STC is also involved in the electron transfer pathway to reduce nitrite by interaction with the octaheme tetrathionate reductase (OTR, but not with cytochrome c nitrite reductase (ccNiR. In the main pathway leading the metal respiration STC pairs with flavocytochrome c (FccA, the other major periplasmic cytochrome, which provides redundancy in this important pathway. The data reveals that the two proteins compete for the binding site at the surface of MtrA, the decaheme cytochrome inserted on the periplasmic side of the MtrCAB-OmcA outer-membrane complex. However, this is not observed for the MtrA homologues. Indeed, neither STC nor FccA interact with MtrD, the best replacement for MtrA, and only STC is able to interact with the decaheme cytochrome DmsE of the outer-membrane complex DmsEFABGH. Overall, these results shown that STC plays a central role in the anaerobic respiratory metabolism of SOMR-1. Nonetheless, the trans-periplasmic electron transfer chain is functionally resilient as a consequence of redundancies that arise from the presence of alternative pathways that bypass/compete with STC.

  8. Expression profiling of Crambe abyssinica under arsenate stress identifies genes and gene networks involved in arsenic metabolism and detoxification

    Directory of Open Access Journals (Sweden)

    Kandasamy Suganthi

    2010-06-01

    Full Text Available Abstract Background Arsenic contamination is widespread throughout the world and this toxic metalloid is known to cause cancers of organs such as liver, kidney, skin, and lung in human. In spite of a recent surge in arsenic related studies, we are still far from a comprehensive understanding of arsenic uptake, detoxification, and sequestration in plants. Crambe abyssinica, commonly known as 'abyssinian mustard', is a non-food, high biomass oil seed crop that is naturally tolerant to heavy metals. Moreover, it accumulates significantly higher levels of arsenic as compared to other species of the Brassicaceae family. Thus, C. abyssinica has great potential to be utilized as an ideal inedible crop for phytoremediation of heavy metals and metalloids. However, the mechanism of arsenic metabolism in higher plants, including C. abyssinica, remains elusive. Results To identify the differentially expressed transcripts and the pathways involved in arsenic metabolism and detoxification, C. abyssinica plants were subjected to arsenate stress and a PCR-Select Suppression Subtraction Hybridization (SSH approach was employed. A total of 105 differentially expressed subtracted cDNAs were sequenced which were found to represent 38 genes. Those genes encode proteins functioning as antioxidants, metal transporters, reductases, enzymes involved in the protein degradation pathway, and several novel uncharacterized proteins. The transcripts corresponding to the subtracted cDNAs showed strong upregulation by arsenate stress as confirmed by the semi-quantitative RT-PCR. Conclusions Our study revealed novel insights into the plant defense mechanisms and the regulation of genes and gene networks in response to arsenate toxicity. The differential expression of transcripts encoding glutathione-S-transferases, antioxidants, sulfur metabolism, heat-shock proteins, metal transporters, and enzymes in the ubiquitination pathway of protein degradation as well as several unknown

  9. Investigation of Archaeal and Bacterial community structure of five different small drinking water networks with special regard to the nitrifying microorganisms.

    Science.gov (United States)

    Nagymáté, Zsuzsanna; Homonnay, Zalán G; Márialigeti, Károly

    2016-01-01

    Total microbial community structure, and particularly nitrifying communities inhabiting five different small drinking water networks characterized with different water physical and chemical parameters was investigated, using cultivation-based methods and sequence aided Terminal Restriction Fragment Length Polymorphism (T-RFLP) analysis. Ammonium ion, originated from well water, was only partially oxidized via nitrite to nitrate in the drinking water distribution systems. Nitrification occurred at low ammonium ion concentration (27-46μM), relatively high pH (7.6-8.2) and over a wide range of dissolved oxygen concentrations (0.4-9.0mgL(-1)). The nitrifying communities of the distribution systems were characterized by variable most probable numbers (2×10(2)-7.1×10(4) MPN L(-1)) and probably originated from the non-treated well water. The sequence aided T-RFLP method revealed that ammonia-oxidizing microorganisms and nitrite-oxidizing Bacteria (Nitrosomonas oligotropha, Nitrosopumilus maritimus, and Nitrospira moscoviensis, 'Candidatus Nitrospira defluvii') were present in different ratios in the total microbial communities of the distinct parts of the water network systems. The nitrate generated by nitrification was partly utilized by nitrate-reducing (and denitrifying) Bacteria, present in low MPN and characterized by sequence aided T-RFLP as Comamonas sp. and Pseudomonas spp. Different environmental factors, like pH, chemical oxygen demand, calculated total inorganic nitrogen content (moreover nitrite and nitrate concentration), temperature had important effect on the total bacterial and archaeal community distribution. PMID:27296965

  10. Two isoforms of TALDO1 generated by alternative translational initiation show differential nucleocytoplasmic distribution to regulate the global metabolic network

    Science.gov (United States)

    Moriyama, Tetsuji; Tanaka, Shu; Nakayama, Yasumune; Fukumoto, Masahiro; Tsujimura, Kenji; Yamada, Kohji; Bamba, Takeshi; Yoneda, Yoshihiro; Fukusaki, Eiichiro; Oka, Masahiro

    2016-01-01

    Transaldolase 1 (TALDO1) is a rate-limiting enzyme involved in the pentose phosphate pathway, which is traditionally thought to occur in the cytoplasm. In this study, we found that the gene TALDO1 has two translational initiation sites, generating two isoforms that differ by the presence of the first 10 N-terminal amino acids. Notably, the long and short isoforms were differentially localised to the cell nucleus and cytoplasm, respectively. Pull-down and in vitro transport assays showed that the long isoform, unlike the short one, binds to importin α and is actively transported into the nucleus in an importin α/β-dependent manner, demonstrating that the 10 N-terminal amino acids are essential for its nuclear localisation. Additionally, we found that these two isoforms can form homo- and/or hetero-dimers with different localisation dynamics. A metabolite analysis revealed that the subcellular localisation of TALDO1 is not crucial for its activity in the pentose phosphate pathway. However, the expression of these two isoforms differentially affected the levels of various metabolites, including components of the tricarboxylic acid cycle, nucleotides, and sugars. These results demonstrate that the nucleocytoplasmic distribution of TALDO1, modulated via alternative translational initiation and dimer formation, plays an important role in a wide range of metabolic networks. PMID:27703206

  11. Towards a systems-level understanding of gene regulatory, protein interaction, and metabolic networks in cyanobacteria

    Directory of Open Access Journals (Sweden)

    Miguel Angel Hernández-Prieto

    2014-07-01

    Full Text Available Cyanobacteria are essential primary producers in marine ecosystems, playing an important role in both carbon and nitrogen cycles. In the last decade, various genome sequencing and metagenomic projects have generated large amounts of genetic data for cyanobacteria. This wealth of data provides researchers with a new basis for the study of molecular adaptation, ecology and evolution of cyanobacteria, as well as for developing biotechnological applications. It also facilitates the use of multiplex techniques, i.e., expression profiling by high-throughput technologies such as microarrays, RNA-seq, and proteomics. However, exploration and analysis of these data is challenging, and often requires advanced computational methods. Also, they need to be integrated into our existing framework of knowledge to use them to draw reliable biological conclusions. Here, systems biology provides important tools. Especially, the construction and analysis of molecular networks has emerged as a powerful systems-level framework, with which to integrate such data, and to better understand biological relevant processes in these organisms.In this review, we provide an overview of the advances and experimental approaches undertaken using multiplex data from genomic, transcriptomic, proteomic, and metabolomic studies in cyanobacteria. Furthermore, we summarize currently available web-based tools dedicated to cyanobacteria, i.e., CyanoBase, CyanoEXpress, ProPortal, Cyanorak, CyanoBIKE, and CINPER. Finally, we present a case study for the freshwater model cyanobacteria, Synechocystis sp. PCC6803, to show the power of meta-analysis, and the potential to extrapolate acquired knowledge to the ecologically important marine cyanobacteria genus, Prochlorococcus.

  12. Transcriptional-metabolic networks in beta-carotene-enriched potato tubers: the long and winding road to the Golden phenotype.

    Science.gov (United States)

    Diretto, Gianfranco; Al-Babili, Salim; Tavazza, Raffaela; Scossa, Federico; Papacchioli, Velia; Migliore, Melania; Beyer, Peter; Giuliano, Giovanni

    2010-10-01

    Vitamin A deficiency is a public health problem in a large number of countries. Biofortification of major staple crops (wheat [Triticum aestivum], rice [Oryza sativa], maize [Zea mays], and potato [Solanum tuberosum]) with β-carotene has the potential to alleviate this nutritional problem. Previously, we engineered transgenic "Golden" potato tubers overexpressing three bacterial genes for β-carotene synthesis (CrtB, CrtI, and CrtY, encoding phytoene synthase, phytoene desaturase, and lycopene β-cyclase, respectively) and accumulating the highest amount of β-carotene in the four aforementioned crops. Here, we report the systematic quantitation of carotenoid metabolites and transcripts in 24 lines carrying six different transgene combinations under the control of the 35S and Patatin (Pat) promoters. Low levels of B-I expression are sufficient for interfering with leaf carotenogenesis, but not for β-carotene accumulation in tubers and calli, which requires high expression levels of all three genes under the control of the Pat promoter. Tubers expressing the B-I transgenes show large perturbations in the transcription of endogenous carotenoid genes, with only minor changes in carotenoid content, while the opposite phenotype (low levels of transcriptional perturbation and high carotenoid levels) is observed in Golden (Y-B-I) tubers. We used hierarchical clustering and pairwise correlation analysis, together with a new method for network correlation analysis, developed for this purpose, to assess the perturbations in transcript and metabolite levels in transgenic leaves and tubers. Through a "guilt-by-profiling" approach, we identified several endogenous genes for carotenoid biosynthesis likely to play a key regulatory role in Golden tubers, which are candidates for manipulations aimed at the further optimization of tuber carotenoid content. PMID:20671108

  13. Extraction of elementary rate constants from global network analysis of E. coli central metabolism

    Directory of Open Access Journals (Sweden)

    Broderick Gordon

    2008-05-01

    Full Text Available Abstract Background As computational performance steadily increases, so does interest in extending one-particle-per-molecule models to larger physiological problems. Such models however require elementary rate constants to calculate time-dependent rate coefficients under physiological conditions. Unfortunately, even when in vivo kinetic data is available, it is often in the form of aggregated rate laws (ARL that do not specify the required elementary rate constants corresponding to mass-action rate laws (MRL. There is therefore a need to develop a method which is capable of automatically transforming ARL kinetic information into more detailed MRL rate constants. Results By incorporating proteomic data related to enzyme abundance into an MRL modelling framework, here we present an efficient method operating at a global network level for extracting elementary rate constants from experiment-based aggregated rate law (ARL models. The method combines two techniques that can be used to overcome the difficult properties in parameterization. The first, a hybrid MRL/ARL modelling technique, is used to divide the parameter estimation problem into sub-problems, so that the parameters of the mass action rate laws for each enzyme are estimated in separate steps. This reduces the number of parameters that have to be optimized simultaneously. The second, a hybrid algebraic-numerical simulation and optimization approach, is used to render some rate constants identifiable, as well as to greatly narrow the bounds of the other rate constants that remain unidentifiable. This is done by incorporating equality constraints derived from the King-Altman and Cleland method into the simulated annealing algorithm. We apply these two techniques to estimate the rate constants of a model of E. coli glycolytic pathways. The simulation and statistical results show that our innovative method performs well in dealing with the issues of high computation cost, stiffness, local

  14. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  15. Mountain Pine Beetles Colonizing Historical and Naïve Host Trees Are Associated with a Bacterial Community Highly Enriched in Genes Contributing to Terpene Metabolism

    OpenAIRE

    Adams, Aaron S.; Aylward, Frank O.; Adams, Sandye M; Erbilgin, Nadir; Aukema, Brian H.; Currie, Cameron R; Suen, Garret; Raffa, Kenneth F.

    2013-01-01

    The mountain pine beetle, Dendroctonus ponderosae, is a subcortical herbivore native to western North America that can kill healthy conifers by overcoming host tree defenses, which consist largely of high terpene concentrations. The mechanisms by which these beetles contend with toxic compounds are not well understood. Here, we explore a component of the hypothesis that beetle-associated bacterial symbionts contribute to the ability of D. ponderosae to overcome tree defenses by assisting with...

  16. NMR study of the 1-{sup 13}C glucose colon bacterial metabolism; Etude du metabolisme bacterien colique du 1-{sup 13}C glucose par RMN

    Energy Technology Data Exchange (ETDEWEB)

    Briet, F.; Flourie, B.; Pochart, P.; Rambaud, J.C.; Desjeux, J.F. [Hopital Saint-Lazare, 75 - Paris (France); Dallery, L. [Conservatoire National des Arts et Metiers (CNAM), 75 - Paris (France); Grivet, J.P. [Centre National de la Recherche Scientifique (CNRS), 45 - Orleans-la-Source (France)

    1994-12-31

    The aim of the study is to examine in-vitro and by nuclear magnetic resonance the biological pathways for the fermentation of the 1-{sup 13}C labelled glucose (99 atoms percent) by human colon bacteria. The preparation of the bacterial suspension and the glucose degradation kinetics are presented; the NMR analysis sensitivity and quantification features are discussed and results are presented. 2 figs., 1 ref.

  17. Mountain pine beetles colonizing historical and naive host trees are associated with a bacterial community highly enriched in genes contributing to terpene metabolism.

    Science.gov (United States)

    Adams, Aaron S; Aylward, Frank O; Adams, Sandye M; Erbilgin, Nadir; Aukema, Brian H; Currie, Cameron R; Suen, Garret; Raffa, Kenneth F

    2013-06-01

    The mountain pine beetle, Dendroctonus ponderosae, is a subcortical herbivore native to western North America that can kill healthy conifers by overcoming host tree defenses, which consist largely of high terpene concentrations. The mechanisms by which these beetles contend with toxic compounds are not well understood. Here, we explore a component of the hypothesis that beetle-associated bacterial symbionts contribute to the ability of D. ponderosae to overcome tree defenses by assisting with terpene detoxification. Such symbionts may facilitate host tree transitions during range expansions currently being driven by climate change. For example, this insect has recently breached the historical geophysical barrier of the Canadian Rocky Mountains, providing access to näive tree hosts and unprecedented connectivity to eastern forests. We use culture-independent techniques to describe the bacterial community associated with D. ponderosae beetles and their galleries from their historical host, Pinus contorta, and their more recent host, hybrid P. contorta-Pinus banksiana. We show that these communities are enriched with genes involved in terpene degradation compared with other plant biomass-processing microbial communities. These pine beetle microbial communities are dominated by members of the genera Pseudomonas, Rahnella, Serratia, and Burkholderia, and the majority of genes involved in terpene degradation belong to these genera. Our work provides the first metagenome of bacterial communities associated with a bark beetle and is consistent with a potential microbial contribution to detoxification of tree defenses needed to survive the subcortical environment. PMID:23542624

  18. Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

    Science.gov (United States)

    Schabort, Du Toit W P; Letebele, Precious K; Steyn, Laurinda; Kilian, Stephanus G; du Preez, James C

    2016-01-01

    We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus. PMID:27315089

  19. Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

    Directory of Open Access Journals (Sweden)

    Du Toit W P Schabort

    Full Text Available We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus.

  20. Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population.

    Science.gov (United States)

    Wen, Weiwei; Li, Kun; Alseekh, Saleh; Omranian, Nooshin; Zhao, Lijun; Zhou, Yang; Xiao, Yingjie; Jin, Min; Yang, Ning; Liu, Haijun; Florian, Alexandra; Li, Wenqiang; Pan, Qingchun; Nikoloski, Zoran; Yan, Jianbing; Fernie, Alisdair R

    2015-07-01

    Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R(2) = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R(2) >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement. PMID:26187921

  1. Structural and Functional Analysis of Giant Strong Component of Bacillus thuringiensis Metabolic Network Análise estrutural de funcional do GSC (Giant Strong Component) da rede metabólica de Bacillus thurigiensis

    OpenAIRE

    Ding, D.W.; Ding, Y.R.; Li, L N; Y.J. Cai; W.B. Xu

    2009-01-01

    The purpose of this work was to study the giant strong component (GSC) of B. thuringiensis metabolic network by structural and functional analysis. Based on so-called "bow tie" structure, we extracted and studied GSC with its functional significance. Global structural properties such as degree distribution and average path length were computed and indicated that the GSC is also a small-world and scale-free network. Furthermore, the GSC was decomposed and functional significant for metabolism ...

  2. 溶藻细菌L7对水华鱼腥藻氮代谢的影响%Effects of the algicidal bacterial strain L7 on nitrogen metabolism of Anabaena flos-aquae

    Institute of Scientific and Technical Information of China (English)

    张涵之; 潘伟斌; 陈宝华

    2012-01-01

    [目的]进一步探明藻菌关系,研究溶藻细菌对藻类氮代谢的影响及其作用机制.[方法]将水华鱼腥藻和溶藻细菌L7按两种比例接种入BG11培养液中,在室内进行共培养(藻细胞初始密度为1.21×108 cells/L;溶藻细菌L7初始密度分别为1.75×107、1.75×108 CFU/mL).连续7d测定藻细胞数、异形胞频率和藻细胞内的硝酸还原酶(NR)活性、谷氨酰胺合成酶(GS)活性、谷氨酸合成酶(GOGAT)活性、蛋白质含量、丙二醛(MDA)含量.[结果]低密度溶藻细菌L7能够促进藻生长(第7天藻细胞密度是对照组的1.58倍),增加异形胞频率(第7天高于对照组66.67%);高密度则会抑制藻生长(第7天藻细胞密度相比对照组下降98.84%),降低异形胞频率(第7天为0).在藻细胞内氮代谢关键酶活性方面,接种后2-5 d,两处理组中藻细胞内NR和GOGAT活性均极显著高于对照组(P<0.01);接种后0-5 d,高密度处理组的GS活性极显著高于对照组(P<0.01),而低密度处理组的则在大部分时间内极显著低于对照组(P<0.01).在整个实验期内,低密度处理组中藻细胞内蛋白质含量一直极显著高于对照组(P<0.01);而在高密度处理组中,除第5天外,细胞内蛋白质含量则全部极显著低于对照组(P<0.01).接种后2-4 d,高密度处理组中藻细胞内MDA含量呈现上升趋势,并极显著高于其余两组(P<0.01).[结论]低密度溶藻细菌L7能够提高水华鱼腥藻对氮源的需求,加速蛋白质合成,促进氮代谢;而高密度溶藻细菌L7会对藻细胞产生过氧化伤害,阻碍蛋白质合成和氮代谢过程.%[Objective] The influence mechanism of the algicidal bacterial strain L7 on nitrogen metabolism of Anabaena flos-aquae were investigated to understand the interaction of cyanobacteria-bacteria.[Methods] The algicidal bacterial strain L7 and Anabaena flos-aquae with different ratio were inoculated into BG11 liquid medium.The initial

  3. A high-throughput metabolomic approach to explore the regulatory effect of mangiferin on metabolic network disturbances of hyperlipidemia rats.

    Science.gov (United States)

    Zhou, Chengyan; Li, Gang; Li, Yanchuan; Gong, Liya; Huang, Yifan; Shi, Zhiping; Du, Shanshan; Li, Ying; Wang, Maoqing; Yin, Jun; Sun, Changhao

    2015-02-01

    This paper was designed to study metabolomic characters of the high-fat diet (HFD)-induced hyperlipidemia and the intervention effects of Mangiferin (MG). In this study, we aimed to investigate the intervention of MG on rats with hyperlipidemia induced by HFD and explore the possible mechanisms of hyperlipidemia. Urine metabolic profiles were analyzed using ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC-ESI-QTOF-MS) coupled with the principal component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) models, Heatmap and metabolism pathway analysis. PCA was applied to study the trajectory of the urinary metabolic phenotype of hyperlipidemia rat after administration of MG. The VIP-plot of orthogonal PLS-DA was used for discovering potential biomarkers to clarify the mechanism of MG. Biochemical analyses indicate that MG can alleviate the hyperlipidemia damage. Twenty significantly changed metabolites (potential biomarkers) were found to be reasonable in explaining the action mechanism of MG. The effectiveness of MG on hyperlipidemia is proved using the established metabolomic method and the regulated metabolic pathways involve the TCA cycle, taurine and hypotaurine metabolism, glyoxylate and dicarboxylate metabolism, glycine and serine and threonine metabolism, glycerophospholipid metabolism, primary bile acid biosynthesis etc. The results indicated that MG has a favourable protective effect on HFD-induced hyperlipidemia by adjusting the metabolic disorders. It also suggests that the metabolomic technology is a powerful approach for elucidation of the action mechanisms of MG.

  4. Alcohol metabolism in human cells causes DNA damage and activates the Fanconi anemia – breast cancer susceptibility (FA-BRCA) DNA damage response network

    Science.gov (United States)

    Abraham, Jessy; Balbo, Silvia; Crabb, David; Brooks, P.J.

    2011-01-01

    Background We recently reported that exposure of human cells in vitro to acetaldehyde resulted in activation of the Fanconi anemia-breast cancer associated (FA-BRCA) DNA damage response network. Methods To determine whether intracellular generation of acetaldehyde from ethanol metabolism can cause DNA damage and activate the FA-BRCA network, we engineered HeLa cells to metabolize alcohol by expression of human alcohol dehydrogenase 1B. Results Incubation of HeLa-ADH1B cells with ethanol (20 mM) resulted in acetaldehyde accumulation in the media which was prevented by co-incubation with 4-methyl pyrazole (4-MP), a specific inhibitor of ADH. Ethanol treatment of HeLa-ADH1B cells produced a 4-fold increase in the acetaldehyde-DNA adduct, N2-ethylidene-dGuo, and also resulted in activation of the Fanconi anemia -breast cancer susceptibility (FA-BRCA) DNA damage response network, as indicated by a monoubiquitination of FANCD2, and phosphorylation of BRCA1. Ser 1524 was identified as one site of BRCA1 phosphorylation. The increased levels of DNA adducts, FANCD2 monoubiquitination, and BRCA1 phosphorylation were all blocked by 4-MP, indicating that acetaldehyde, rather than ethanol itself, was responsible for all three responses. Importantly, the ethanol concentration we used is within the range that can be attained in the human body during social drinking. Conclusions Our results indicate that intracellular metabolism of ethanol to acetaldehyde results in DNA damage which activates the FA-BRCA DNA damage response network. PMID:21919919

  5. 天冬氨酸家族主要氨基酸高产菌株的选育策略%Metabolic Engineering Strategies of Bacterial Strains for Overproduction of L-Threonine and L-Lysine

    Institute of Scientific and Technical Information of China (English)

    吴瑶瑶; 裘娟萍

    2012-01-01

    L-Threonine and L-lysine, two of the L-aspartate family amino acids (AFAAs) , have attracted great attention because of their wide application in industries of food, animal feeding and cosmetics. Metabolic engineering of bacterial strains significantly improved the production of L-threonine and L-lysine. Here, biosynthetic pathways and regulations of L-threonine and L-lysine are summarized. The strategies of metabolic engineering for the development of L-threonine and L-lysine overproducers are also discussed.%L-苏氨酸与L-赖氨酸是L-天冬氨酸家族氨基酸(AFAAs)中的重要成员,近年来由于其在食品、化妆晶、动物饲料添加剂等方面的广泛应用而备受关注,市场需求逐年上升.运用代谢工程手段构建高产菌,可有效地提高L-苏氨酸和L-赖氨酸的生产水平.本文详述了 L-苏氨酸与L-赖氨酸的合成途径、调控机制以及两种氨基酸高产菌株的构建策略.

  6. Research on metabolic network of extremely halophilic archaea%极端嗜盐古菌代谢网络研究

    Institute of Scientific and Technical Information of China (English)

    丁德武

    2012-01-01

    Extremely halophilic archaea belonging to the euryarchaeota halobium branch, it is a typical population in archaea, and very important to microbial resources. In this article, we mainly study the structure and function of metabolic network about one extremely halophilic archaea: Halobacterium salinarum Rl. We obtain a list of all metabolic reactions in Halobacterium salinarum Rl from published high-quality metabolic models, and represent it with metabolite graph. We analyze functional modules and hubs of the network, and discussed their biological signification.%极端嗜盐古菌(extremely thermophilic archaea)属于广域古菌界盐杆菌科,是古菌域中的典型生理类群,也是重要的极端微生物资源.文章主要对一种极端嗜盐古菌——盐沼盐杆菌(Halobacterium salinarum R1)——代谢网络的结构与功能进行了分析.对高质量盐沼盐杆菌代谢网络数据进行整理,构建了其中所有的代谢反应列表,并用代谢物图来表示.分析了该网络的功能模块和关键节点,并讨论了它们的生物学功能意义.

  7. Modeling the Differences in Biochemical Capabilities of Pseudomonas Species by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

    Directory of Open Access Journals (Sweden)

    Parizad Babaei

    2014-01-01

    Full Text Available To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

  8. Ecological network analysis for carbon metabolism of eco-industrial parks: a case study of a typical eco-industrial park in Beijing.

    Science.gov (United States)

    Lu, Yi; Chen, Bin; Feng, Kuishuang; Hubacek, Klaus

    2015-06-16

    Energy production and industrial processes are crucial economic sectors accounting for about 62% of greenhouse gas (GHG) emissions globally in 2012. Eco-industrial parks are practical attempts to mitigate GHG emissions through cooperation among businesses and the local community in order to reduce waste and pollution, efficiently share resources, and help with the pursuit of sustainable development. This work developed a framework based on ecological network analysis to trace carbon metabolic processes in eco-industrial parks and applied it to a typical eco-industrial park in Beijing. Our findings show that the entire metabolic system is dominated by supply of primary goods from the external environment and final demand. The more carbon flows through a sector, the more influence it would exert upon the whole system. External environment and energy providers are the most active and dominating part of the carbon metabolic system, which should be the first target to mitigate emissions by increasing efficiencies. The carbon metabolism of the eco-industrial park can be seen as an evolutionary system with high levels of efficiency, but this may come at the expense of larger levels of resilience. This work may provide a useful modeling framework for low-carbon design and management of industrial parks.

  9. Bacterial Protein-Tyrosine Kinases

    DEFF Research Database (Denmark)

    Shi, Lei; Kobir, Ahasanul; Jers, Carsten;

    2010-01-01

    in exopolysaccharide production, virulence, DNA metabolism, stress response and other key functions of the bacterial cell. BY-kinases act through autophosphorylation (mainly in exopolysaccharide production) and phosphorylation of other proteins, which have in most cases been shown to be activated by tyrosine......Bacteria and Eukarya share essentially the same family of protein-serine/threonine kinases, also known as the Hanks-type kinases. However, when it comes to protein-tyrosine phosphorylation, bacteria seem to have gone their own way. Bacterial protein-tyrosine kinases (BY-kinases) are bacterial...... and highlighted their importance in bacterial physiology. Having no orthologues in Eukarya, BY-kinases are receiving a growing attention from the biomedical field, since they represent a particularly promising target for anti-bacterial drug design....

  10. Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803

    DEFF Research Database (Denmark)

    Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio;

    2011-01-01

    activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling......Synechocystis sp. PCC6803 is a model cyanobacterium capable of producing biofuels with CO2 as carbon source and with its metabolism fueled by light, for which it stands as a potential production platform of socio-economic importance. Compilation and characterization of Synechocystis genome......-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux...

  11. Correlation-Based Network Analysis of Metabolite and Enzyme Profiles Reveals a Role of Citrate Biosynthesis in Modulating N and C Metabolism in Zea mays.

    Science.gov (United States)

    Toubiana, David; Xue, Wentao; Zhang, Nengyi; Kremling, Karl; Gur, Amit; Pilosof, Shai; Gibon, Yves; Stitt, Mark; Buckler, Edward S; Fernie, Alisdair R; Fait, Aaron

    2016-01-01

    To investigate the natural variability of leaf metabolism and enzymatic activity in a maize inbred population, statistical and network analyses were employed on metabolite and enzyme profiles. The test of coefficient of variation showed that sugars and amino acids displayed opposite trends in their variance within the population, consistently with their related enzymes. The overall higher CV values for metabolites as compared to the tested enzymes are indicative for their greater phenotypic plasticity. H(2) tests revealed galactinol (1) and asparagine (0.91) as the highest scorers among metabolites and nitrate reductase (0.73), NAD-glutamate dehydrogenase (0.52), and phosphoglucomutase (0.51) among enzymes. The overall low H(2) scores for metabolites and enzymes are suggestive for a great environmental impact or gene-environment interaction. Correlation-based network generation followed by community detection analysis, partitioned the network into three main communities and one dyad, (i) reflecting the different levels of phenotypic plasticity of the two molecular classes as observed for the CV values and (ii) highlighting the concerted changes between classes of chemically related metabolites. Community 1 is composed mainly of enzymes and specialized metabolites, community 2' is enriched in N-containing compounds and phosphorylated-intermediates. The third community contains mainly organic acids and sugars. Cross-community linkages are supported by aspartate, by the photorespiration amino acids glycine and serine, by the metabolically related GABA and putrescine, and by citrate. The latter displayed the strongest node-betweenness value (185.25) of all nodes highlighting its fundamental structural role in the connectivity of the network by linking between different communities and to the also strongly connected enzyme aldolase. PMID:27462343

  12. Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.

    Directory of Open Access Journals (Sweden)

    Ahmad A Mannan

    Full Text Available An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-'omics' steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population.

  13. Primary productivity, heterotrophy, metabolic indicators of stress and interactions in algal-bacterial mat communities affected by a fluctuating thermal regime

    International Nuclear Information System (INIS)

    Thermal habitats in effluent cooling waters from production nuclear reactors at the Savannah River Plant are unlike natural thermal habitats in that reactor operations are periodically halted, exposing the organisms growing in these thermal habitats to ambient temperatures for unpredictable lengths of time. Rates of primary production, glucose heterotrophy, and the composition of algal-bacterial mat communities growing along a thermal gradient from about 50 to 350C during periods of reactor operation were studied. Cyanobacteria were the only photoautotrophs in mat communities above 400C while cyanobacteria and eucaryotic algae comprised the photoautotrophic component of mat communities below 400C. The heterotrophic component of these communities above 400C was made up of stenothermic and eurythermic thermophilic bacteria while both eurythermic thermophiles and mesophilic bacteria were found in communities below 400C. Net CO2-fixation rates during thermal conditions dropped after initial exposure to ambient temperatures. After prolonged exposure of the thermal communities to ambient temperatures, adaptation and colonization by mesophilic algae occurred. Rates of glucose utilization under varying degrees of thermal influence suggested that the heterotrophic component may not have been optimally adapted to thermal conditions. During periods of changing thermal conditions, an increase in the percentage extracellular release of photosynthetically fixed 14CO2 by cyanobacteria and algae and an increase in the percentage of glucose mineralized (respired) by the heterotrophic component of the mat communities was observed. Results of temperature shift experiments indicated that the short-term response of the photoautotrophic component of these communities to thermal stress was an increase in the percentage of photosynthate released extracellularly

  14. Transcriptional and metabolic signatures of Arabidopsis responses to chewing damage by an insect herbivore and bacterial infection and the consequences of their interaction

    Directory of Open Access Journals (Sweden)

    Heidi M Appel

    2014-09-01

    Full Text Available Plants use multiple interacting signaling systems to identify and respond to biotic stresses. Although it is often assumed that there is specificity in signaling responses to specific pests, this is rarely examined outside of the gene-for-gene relationships of plant-pathogen interactions. In this study, we first compared early events in gene expression and later events in metabolite profiles of Arabidopsis thaliana following attack by either the caterpillar Spodoptera exigua or avirulent (DC3000 avrRpm1 Pseudomonas syringae pv. tomato at three time points. Transcriptional responses of the plant to caterpillar feeding were rapid, occurring within 1 h of feeding, and then decreased at 6 h and 24 h. In contrast, plant response to the pathogen was undetectable at 1 h but grew larger and more significant at 6 h and 24 h. There was a surprisingly large amount of overlap in jasmonate and salicylate signaling in responses to the insect and pathogen, including levels of gene expression and individual hormones. The caterpillar and pathogen treatments induced different patterns of expression of glucosinolate biosynthesis genes and levels of glucosinolates. This suggests that when specific responses develop, their regulation is complex and best understood by characterizing expression of many genes and metabolites. We then examined the effect of feeding by the caterpillar Spodoptera exigua on Arabidopsis susceptibility to virulent (DC3000 and avirulent (DC3000 avrRpm1 P. syringae pv. tomato, and found that caterpillar feeding enhanced Arabidopsis resistance to the avirulent pathogen and lowered resistance to the virulent strain. We conclude that efforts to improve plant resistance to bacterial pathogens are likely to influence resistance to insects and vice versa. Studies explicitly comparing plant responses to multiple stresses, including the role of elicitors at early time points, are critical to understanding how plants organize responses in natural

  15. Bacterial Vaginosis

    Science.gov (United States)

    ... 586. Related Content STDs during Pregnancy Fact Sheet Pregnancy and HIV, Viral Hepatitis, and STD Prevention Pelvic Inflammatory Disease ( ... Bacterial Vaginosis (BV) Chlamydia Gonorrhea Genital Herpes Hepatitis HIV/AIDS & STDs Human Papillomavirus ... STDs See Also Pregnancy Reproductive ...

  16. Bacterial Meningitis

    Science.gov (United States)

    ... Schedules Preteen & Teen Vaccines Meningococcal Disease Sepsis Bacterial Meningitis Recommend on Facebook Tweet Share Compartir On this ... serious disease. Laboratory Methods for the Diagnosis of Meningitis This manual summarizes laboratory methods used to isolate, ...

  17. Proteomic Dissection of Endosperm Starch Granule Associated Proteins Reveals a Network Coordinating Starch Biosynthesis and Amino Acid Metabolism and Glycolysis in Rice Endosperms

    Science.gov (United States)

    Yu, Huatao; Wang, Tai

    2016-01-01

    Starch biosynthesis and starch granule packaging in cereal endosperms involve a coordinated action of starch biosynthesis enzymes and coordination with other metabolisms. Because directly binding to starch granules, starch granule-associated proteins (SGAPs) are essential to understand the underlying mechanisms, however the information on SGAPs remains largely unknown. Here, we dissected developmentally changed SGAPs from developing rice endosperms from 10 to 20 days after flowering (DAF). Starch granule packaging was not completed at 10 DAF, and was finished in the central endosperm at 15 DAF and in the whole endosperm at 20 DAF. Proteomic analysis with two-dimensional differential in-gel electrophoresis and mass spectrometry revealed 115 developmentally changed SGAPs, representing 37 unique proteins. 65% of the unique proteins had isoforms. 39% of the identified SGAPs were involved in starch biosynthesis with main functions in polyglucan elongation and granule structure trimming. Almost all proteins involved in starch biosynthesis, amino acid biosynthesis, glycolysis, protein folding, and PPDK pathways increased abundance as the endosperm developed, and were predicted in an interaction network. The network represents an important mechanism to orchestrate carbon partitioning among starch biosynthesis, amino acid biosynthesis and glycolysis for efficient starch and protein storage. These results provide novel insights into mechanisms of starch biosynthesis and its coordination with amino acid metabolisms and glycolysis in cereal endosperms. PMID:27252723

  18. The transcriptional regulatory network of Corynebacterium jeikeium K411 and its interaction with metabolic routes contributing to human body odor formation.

    Science.gov (United States)

    Barzantny, Helena; Schröder, Jasmin; Strotmeier, Jasmin; Fredrich, Eugenie; Brune, Iris; Tauch, Andreas

    2012-06-15

    Lipophilic corynebacteria are involved in the generation of volatile odorous products in the process of human body odor formation by degrading skin lipids and specific odor precursors. Therefore, these bacteria represent appropriate model systems for the cosmetic industry to examine axillary malodor formation on the molecular level. To understand the transcriptional control of metabolic pathways involved in this process, the transcriptional regulatory network of the lipophilic axilla isolate Corynebacterium jeikeium K411 was reconstructed from the complete genome sequence. This bioinformatic approach detected a gene-regulatory repertoire of 83 candidate proteins, including 56 DNA-binding transcriptional regulators, nine two-component systems, nine sigma factors, and nine regulators with diverse physiological functions. Furthermore, a cross-genome comparison among selected corynebacterial species of the taxonomic cluster 3 revealed a common gene-regulatory repertoire of 44 transcriptional regulators, including the MarR-like regulator Jk0257, which is exclusively encoded in the genomes of this taxonomical subline. The current network reconstruction comprises 48 transcriptional regulators and 674 gene-regulatory interactions that were assigned to five interconnected functional modules. Most genes involved in lipid degradation are under the combined control of the global cAMP-sensing transcriptional regulator GlxR and the LuxR-family regulator RamA, probably reflecting the essential role of lipid degradation in C. jeikeium. This study provides the first genome-scale in silico analysis of the transcriptional regulation of metabolism in a lipophilic bacterium involved in the formation of human body odor.

  19. Isoliquiritigenin induces growth inhibition and apoptosis through downregulating arachidonic acid metabolic network and the deactivation of PI3K/Akt in human breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Li, Ying; Zhao, Haixia [Department of Pharmacology, School of Medicine, Wuhan University, Wuhan 430071 (China); Wang, Yuzhong [Key Laboratory for Oral Biomedical Engineering of Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan 430079 (China); Zheng, Hao; Yu, Wei; Chai, Hongyan [Department of Pharmacology, School of Medicine, Wuhan University, Wuhan 430071 (China); Zhang, Jing [Animal Experimental Center of Wuhan University, Wuhan 430071 (China); Falck, John R. [Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390,USA (United States); Guo, Austin M. [Department of Pharmacology, School of Medicine, Wuhan University, Wuhan 430071 (China); Department of Pharmacology, New York Medical College, Valhalla, NY 10595 (United States); Yue, Jiang; Peng, Renxiu [Department of Pharmacology, School of Medicine, Wuhan University, Wuhan 430071 (China); Yang, Jing, E-mail: yangjingliu2013@163.com [Department of Pharmacology, School of Medicine, Wuhan University, Wuhan 430071 (China); Research Center of Food and Drug Evaluation, Wuhan University, Wuhan 430071 (China)

    2013-10-01

    Arachidonic acid (AA)-derived eicosanoids and its downstream pathways have been demonstrated to play crucial roles in growth control of breast cancer. Here, we demonstrate that isoliquiritigenin, a flavonoid phytoestrogen from licorice, induces growth inhibition and apoptosis through downregulating multiple key enzymes in AA metabolic network and the deactivation of PI3K/Akt in human breast cancer. Isoliquiritigenin diminished cell viability, 5-bromo-2′-deoxyuridine (BrdU) incorporation, and clonogenic ability in both MCF-7 and MDA-MB-231cells, and induced apoptosis as evidenced by an analysis of cytoplasmic histone-associated DNA fragmentation, flow cytometry and hoechst staining. Furthermore, isoliquiritigenin inhibited mRNA expression of multiple forms of AA-metabolizing enzymes, including phospholipase A2 (PLA2), cyclooxygenases (COX)-2 and cytochrome P450 (CYP) 4A, and decreased secretion of their products, including prostaglandin E{sub 2} (PGE{sub 2}) and 20-hydroxyeicosatetraenoic acid (20-HETE), without affecting COX-1, 5-lipoxygenase (5-LOX), 5-lipoxygenase activating protein (FLAP), and leukotriene B{sub 4} (LTB{sub 4}). In addition, it downregulated the levels of phospho-PI3K, phospho-PDK (Ser{sup 241}), phospho-Akt (Thr{sup 308}), phospho-Bad (Ser{sup 136}), and Bcl-x{sub L} expression, thereby activating caspase cascades and eventually cleaving poly(ADP-ribose) polymerase (PARP). Conversely, the addition of exogenous eicosanoids, including PGE{sub 2}, LTB{sub 4} and a 20-HETE analog (WIT003), and caspase inhibitors, or overexpression of constitutively active Akt reversed isoliquiritigenin-induced apoptosis. Notably, isoliquiritigenin induced growth inhibition and apoptosis of MDA-MB-231 human breast cancer xenografts in nude mice, together with decreased intratumoral levels of eicosanoids and phospho-Akt (Thr{sup 308}). Collectively, these data suggest that isoliquiritigenin induces growth inhibition and apoptosis through downregulating AA metabolic

  20. An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

    Science.gov (United States)

    Costa, Michael A.; Collins, R. Eric; Anterola, Aldwin M.; Cochrane, Fiona C.; Davin, Laurence B.; Lewis, Norman G.

    2003-01-01

    The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member

  1. Clarifying the regulation of NO/N2O production in Nitrosomonas europaea during anoxic-oxic transition via flux balance analysis of a metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Villas-Boas, Silas G; Swift, Simon; Chandran, Kartik; Singhal, Naresh

    2014-09-01

    The metabolic mechanism regulating the production of nitric and nitrous oxide (NO, N2O) in ammonia oxidizing bacteria (AOB) was characterized by flux balance analysis (FBA) of a stoichiometric metabolic network (SMN) model. The SMN model was created using 51 reactions and 44 metabolites of the energy metabolism in Nitrosomonas europaea, a widely studied AOB. FBA of model simulations provided estimates for reaction rates and yield ratios of intermediate metabolites, substrates, and products. These estimates matched well, deviating on average by 15% from values for 17 M yield ratios reported for non-limiting oxygen and ammonium concentrations. A sensitivity analysis indicated that the reactions catalysed by cytochromes aa3 and P460 principally regulate the pathways of NO and N2O production (hydroxylamine oxidoreductase mediated and nitrifier denitrification). FBA of simulated N. europaea exposure to oxic-anoxic-oxic transition indicated that NO and N2O production primarily resulted from an intracellular imbalance between the production and consumption of electron equivalents during NH3 oxidation, and that NO and N2O are emitted when the sum of their production rates is greater than half the rate of NO oxidation by cytochrome P460.

  2. Using Boolean Logic Modeling of Gene Regulatory Networks to Exploit the Links Between Cancer and Metabolism for Therapeutic Purposes.

    Science.gov (United States)

    Arshad, Osama A; Venkatasubramani, Priyadharshini S; Datta, Aniruddha; Venkatraj, Jijayanagaram

    2016-01-01

    The uncontrolled cell proliferation that is characteristically associated with cancer is usually accompanied by alterations in the genome and cell metabolism. Indeed, the phenomenon of cancer cells metabolizing glucose using a less efficient anaerobic process even in the presence of normal oxygen levels, termed the Warburg effect, is currently considered to be one of the hallmarks of cancer. Diabetes, much like cancer, is defined by significant metabolic changes. Recent epidemiological studies have shown that diabetes patients treated with the antidiabetic drug Metformin have significantly lowered risk of cancer as compared to patients treated with other antidiabetic drugs. We utilize a Boolean logic model of the pathways commonly mutated in cancer to not only investigate the efficacy of Metformin for cancer therapeutic purposes but also demonstrate how Metformin in concert with other cancer drugs could provide better and less toxic clinical outcomes as compared to using cancer drugs alone.

  3. Jasmonoyl-L-isoleucine coordinates metabolic networks required for anthesis and floral attractant emission in wild tobacco (Nicotiana attenuata).

    Science.gov (United States)

    Stitz, Michael; Hartl, Markus; Baldwin, Ian T; Gaquerel, Emmanuel

    2014-10-01

    Jasmonic acid and its derivatives (jasmonates [JAs]) play central roles in floral development and maturation. The binding of jasmonoyl-L-isoleucine (JA-Ile) to the F-box of CORONATINE INSENSITIVE1 (COI1) is required for many JA-dependent physiological responses, but its role in anthesis and pollinator attraction traits remains largely unexplored. Here, we used the wild tobacco Nicotiana attenuata, which develops sympetalous flowers with complex pollination biology, to examine the coordinating function of JA homeostasis in the distinct metabolic processes that underlie flower maturation, opening, and advertisement to pollinators. From combined transcriptomic, targeted metabolic, and allometric analyses of transgenic N. attenuata plants for which signaling deficiencies were complemented with methyl jasmonate, JA-Ile, and its functional homolog, coronatine (COR), we demonstrate that (1) JA-Ile/COR-based signaling regulates corolla limb opening and a JA-negative feedback loop; (2) production of floral volatiles (night emissions of benzylacetone) and nectar requires JA-Ile/COR perception through COI1; and (3) limb expansion involves JA-Ile-induced changes in limb fresh mass and carbohydrate metabolism. These findings demonstrate a master regulatory function of the JA-Ile/COI1 duet for the main function of a sympetalous corolla, that of advertising for and rewarding pollinator services. Flower opening, by contrast, requires JA-Ile signaling-dependent changes in primary metabolism, which are not compromised in the COI1-silenced RNA interference line used in this study. PMID:25326292

  4. Probing the metabolic network in bloodstream-form Trypanosoma brucei using untargeted metabolomics with stable isotope labelled glucose.

    Directory of Open Access Journals (Sweden)

    Darren J Creek

    2015-03-01

    Full Text Available Metabolomics coupled with heavy-atom isotope-labelled glucose has been used to probe the metabolic pathways active in cultured bloodstream form trypomastigotes of Trypanosoma brucei, a parasite responsible for human African trypanosomiasis. Glucose enters many branches of metabolism beyond glycolysis, which has been widely held to be the sole route of glucose metabolism. Whilst pyruvate is the major end-product of glucose catabolism, its transamination product, alanine, is also produced in significant quantities. The oxidative branch of the pentose phosphate pathway is operative, although the non-oxidative branch is not. Ribose 5-phosphate generated through this pathway distributes widely into nucleotide synthesis and other branches of metabolism. Acetate, derived from glucose, is found associated with a range of acetylated amino acids and, to a lesser extent, fatty acids; while labelled glycerol is found in many glycerophospholipids. Glucose also enters inositol and several sugar nucleotides that serve as precursors to macromolecule biosynthesis. Although a Krebs cycle is not operative, malate, fumarate and succinate, primarily labelled in three carbons, were present, indicating an origin from phosphoenolpyruvate via oxaloacetate. Interestingly, the enzyme responsible for conversion of phosphoenolpyruvate to oxaloacetate, phosphoenolpyruvate carboxykinase, was shown to be essential to the bloodstream form trypanosomes, as demonstrated by the lethal phenotype induced by RNAi-mediated downregulation of its expression. In addition, glucose derivatives enter pyrimidine biosynthesis via oxaloacetate as a precursor to aspartate and orotate.

  5. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; de Fries, Louise Skovlund

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social...

  6. Integrative metabolic engineering

    Directory of Open Access Journals (Sweden)

    George H McArthur IV

    2015-07-01

    Full Text Available Recent advances in experimental and computational synthetic biology are extremely useful for achieving metabolic engineering objectives. The integration of synthetic biology and metabolic engineering within an iterative design-build-test framework will improve the practice of metabolic engineering by relying more on efficient design strategies. Computational tools that aid in the design and in silico simulation of metabolic pathways are especially useful. However, software helpful for constructing, implementing, measuring and characterizing engineered pathways and networks should not be overlooked. In this review, we highlight computational synthetic biology tools relevant to metabolic engineering, organized in the context of the design-build-test cycle.

  7. Bacterial protein toxins : tools to study mammalian molecular cell biology

    NARCIS (Netherlands)

    Wüthrich, I.W.

    2014-01-01

    Bacterial protein toxins are genetically encoded proteinaceous macromolecules that upon exposure causes perturbation of cellular metabolism in a susceptible host. A bacterial toxin can work at a distance from the site of infection, and has direct and quantifiable actions. Bacterial protein toxins ca

  8. Metabolic model of Synechococcus sp. PCC 7002: Prediction of flux distribution and network modification for enhanced biofuel production.

    Science.gov (United States)

    Hendry, John I; Prasannan, Charulata B; Joshi, Aditi; Dasgupta, Santanu; Wangikar, Pramod P

    2016-08-01

    Flux Balance Analysis was performed with the Genome Scale Metabolic Model of a fast growing cyanobacterium Synechococcus sp. PCC 7002 to gain insights that would help in engineering the organism as a production host. Gene essentiality and synthetic lethality analysis revealed a reduced metabolic robustness under genetic perturbation compared to the heterotrophic bacteria Escherichia coli. Under glycerol heterotrophy the reducing equivalents were generated from tricarboxylic acid cycle rather than the oxidative pentose phosphate pathway. During mixotrophic growth in glycerol the photosynthetic electron transport chain was predominantly used for ATP synthesis with a photosystem I/photosystem II flux ratio higher than that observed under autotrophy. An exhaustive analysis of all possible double reaction knock outs was performed to reroute fixed carbon towards ethanol and butanol production. It was predicted that only ∼10% of fixed carbon could be diverted for ethanol and butanol production.

  9. Pathway Pioneer: A Web-Based Graphical Tool for the Organization and Flux Analysis of Metabolic Networks

    OpenAIRE

    Singh, Sumit Kumar

    2014-01-01

    As stoichiometric metabolic models increase in complexity and delity, design and reconstruction tools are urgently needed to increase the productivity of this time-consuming process. Engineers require software for the exploration, evaluation, and rapid analysis of model alternatives within an intuitive visualization and data management framework. This thesis introduces such a tool: Pathway Pioneer (www.pathwaypioneer.org), a web based system built as a front-end graphical user interface to th...

  10. Lack of evolvability in self-sustaining autocatalytic networks constraints metabolism-first scenarios for the origin of life

    OpenAIRE

    Vasas V.; Szathmary E.; Santos M

    2010-01-01

    A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first “living” systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where ...

  11. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......) and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

  12. Antibiotic efficacy is linked to bacterial cellular respiration

    OpenAIRE

    Lobritz, Michael A.; Belenky, Peter; Porter, Caroline B. M.; Gutierrez, Arnaud; Yang, Jason H.; Schwarz, Eric G.; Dwyer, Daniel J; Khalil, Ahmad S.; James J Collins

    2015-01-01

    The global burden of antibiotic resistance has created a demand to better understand the basic mechanisms of existing antibiotics. Of significant interest is how antibiotics may perturb bacterial metabolism, and how bacterial metabolism may influence antibiotic activity. Here, we study the interaction of bacteriostatic and bactericidal antibiotics, the two major phenotypic drug classes. Interestingly, the two classes differentially perturb bacterial cellular respiration, with major consequenc...

  13. Bacterial Adhesion & Blocking Bacterial Adhesion

    DEFF Research Database (Denmark)

    Vejborg, Rebecca Munk

    2008-01-01

    tract to the microbial flocs in waste water treatment facilities. Microbial biofilms may however also cause a wide range of industrial and medical problems, and have been implicated in a wide range of persistent infectious diseases, including implantassociated microbial infections. Bacterial adhesion...... is the first committing step in biofilm formation, and has therefore been intensely scrutinized. Much however, still remains elusive. Bacterial adhesion is a highly complex process, which is influenced by a variety of factors. In this thesis, a range of physico-chemical, molecular and environmental parameters......, which influence the transition from a planktonic lifestyle to a sessile lifestyle, have been studied. Protein conditioning film formation was found to influence bacterial adhesion and subsequent biofilm formation considerable, and an aqueous extract of fish muscle tissue was shown to significantly...

  14. Bacterial lipases

    NARCIS (Netherlands)

    Jaeger, Karl-Erich; Ransac, Stéphane; Dijkstra, Bauke W.; Colson, Charles; Heuvel, Margreet van; Misset, Onno

    1994-01-01

    Many different bacterial species produce lipases which hydrolyze esters of glycerol with preferably long-chain fatty acids. They act at the interface generated by a hydrophobic lipid substrate in a hydrophilic aqueous medium. A characteristic property of lipases is called interfacial activation, mea

  15. Evolutionary convergence and nitrogen metabolism in Blattabacterium strain Bge, primary endosymbiont of the cockroach Blattella germanica.

    Science.gov (United States)

    López-Sánchez, Maria J; Neef, Alexander; Peretó, Juli; Patiño-Navarrete, Rafael; Pignatelli, Miguel; Latorre, Amparo; Moya, Andrés

    2009-11-01

    Bacterial endosymbionts of insects play a central role in upgrading the diet of their hosts. In certain cases, such as aphids and tsetse flies, endosymbionts complement the metabolic capacity of hosts living on nutrient-deficient diets, while the bacteria harbored by omnivorous carpenter ants are involved in nitrogen recycling. In this study, we describe the genome sequence and inferred metabolism of Blattabacterium strain Bge, the primary Flavobacteria endosymbiont of the omnivorous German cockroach Blattella germanica. Through comparative genomics with other insect endosymbionts and free-living Flavobacteria we reveal that Blattabacterium strain Bge shares the same distribution of functional gene categories only with Blochmannia strains, the primary Gamma-Proteobacteria endosymbiont of carpenter ants. This is a remarkable example of evolutionary convergence during the symbiotic process, involving very distant phylogenetic bacterial taxa within hosts feeding on similar diets. Despite this similarity, different nitrogen economy strategies have emerged in each case. Both bacterial endosymbionts code for urease but display different metabolic functions: Blochmannia strains produce ammonia from dietary urea and then use it as a source of nitrogen, whereas Blattabacterium strain Bge codes for the complete urea cycle that, in combination with urease, produces ammonia as an end product. Not only does the cockroach endosymbiont play an essential role in nutrient supply to the host, but also in the catabolic use of amino acids and nitrogen excretion, as strongly suggested by the stoichiometric analysis of the inferred metabolic network. Here, we explain the metabolic reasons underlying the enigmatic return of cockroaches to the ancestral ammonotelic state.

  16. Pathways of Lipid Metabolism in Marine Algae, Co-Expression Network, Bottlenecks and Candidate Genes for Enhanced Production of EPA and DHA in Species of Chromista

    Directory of Open Access Journals (Sweden)

    Alice Mühlroth

    2013-11-01

    Full Text Available The importance of n-3 long chain polyunsaturated fatty acids (LC-PUFAs for human health has received more focus the last decades, and the global consumption of n-3 LC-PUFA has increased. Seafood, the natural n-3 LC-PUFA source, is harvested beyond a sustainable capacity, and it is therefore imperative to develop alternative n-3 LC-PUFA sources for both eicosapentaenoic acid (EPA, 20:5n-3 and docosahexaenoic acid (DHA, 22:6n-3. Genera of algae such as Nannochloropsis, Schizochytrium, Isochrysis and Phaedactylum within the kingdom Chromista have received attention due to their ability to produce n-3 LC-PUFAs. Knowledge of LC-PUFA synthesis and its regulation in algae at the molecular level is fragmentary and represents a bottleneck for attempts to enhance the n-3 LC-PUFA levels for industrial production. In the present review, Phaeodactylum tricornutum has been used to exemplify the synthesis and compartmentalization of n-3 LC-PUFAs. Based on recent transcriptome data a co-expression network of 106 genes involved in lipid metabolism has been created. Together with recent molecular biological and metabolic studies, a model pathway for n-3 LC-PUFA synthesis in P. tricornutum has been proposed, and is compared to industrialized species of Chromista. Limitations of the n-3 LC-PUFA synthesis by enzymes such as thioesterases, elongases, acyl-CoA synthetases and acyltransferases are discussed and metabolic bottlenecks are hypothesized such as the supply of the acetyl-CoA and NADPH. A future industrialization will depend on optimization of chemical compositions and increased biomass production, which can be achieved by exploitation of the physiological potential, by selective breeding and by genetic engineering.

  17. Virus-induced gene silencing of pea CHLI and CHLD affects tetrapyrrole biosynthesis, chloroplast development and the primary metabolic network.

    Science.gov (United States)

    Luo, Tao; Luo, Sha; Araújo, Wagner L; Schlicke, Hagen; Rothbart, Maxi; Yu, Jing; Fan, Tingting; Fernie, Alisdair R; Grimm, Bernhard; Luo, Meizhong

    2013-04-01

    The first committed and highly regulated step of chlorophyll biosynthesis is the insertion of Mg(2+) into protoporphyrin IX, which is catalyzed by Mg chelatase that consists of CHLH, CHLD and CHLI subunits. In this study, CHLI and CHLD genes were suppressed by virus-induced gene silencing (VIGS-CHLI and VIGS-CHLD) in pea (Pisum sativum), respectively. VIGS-CHLI and VIGS-CHLD plants both showed yellow leaf phenotypes with the reduced Mg chelatase activity and the inactivated synthesis of 5-aminolevulinic acid. The lower chlorophyll accumulation correlated with undeveloped thylakoid membranes, altered chloroplast nucleoid structure, malformed antenna complexes and compromised photosynthesis capacity in the yellow leaf tissues of the VIGS-CHLI and VIGS-CHLD plants. Non-enzymatic antioxidant contents and the activities of antioxidant enzymes were altered in response to enhanced accumulation of reactive oxygen species (ROS) in the chlorophyll deficient leaves of VIGS-CHLI and VIGS-CHLD plants. Furthermore, the results of metabolite profiling indicate a tight correlation between primary metabolic pathways and Mg chelatase activity. We also found that CHLD induces a feedback-regulated change of the transcription of photosynthesis-associated nuclear genes. CHLD and CHLI silencing resulted in a rapid reduction of photosynthetic proteins. Taken together, Mg chelatase is not only a key regulator of tetrapyrrole biosynthesis but its activity also correlates with ROS homeostasis, primary interorganellar metabolism and retrograde signaling in plant cells. PMID:23416492

  18. LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

    OpenAIRE

    Priyanka Patel; Vineetha Mandlik; Shailza Singh

    2015-01-01

    A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database) is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the ment...

  19. Bacterial Ecology

    DEFF Research Database (Denmark)

    Fenchel, Tom

    2011-01-01

    Bacterial ecology is concerned with the interactions between bacteria and their biological and nonbiological environments and with the role of bacteria in biogeochemical element cycling. Many fundamental properties of bacteria are consequences of their small size. Thus, they can efficiently exploit...... biogeochemical processes are carried exclusively by bacteria. * Bacteria play an important role in all types of habitats including some that cannot support eukaryotic life....

  20. Flux-balance modelling of plant metabolism

    OpenAIRE

    Lee James Sweetlove; R. George eRatcliffe

    2011-01-01

    Flux-balance modelling of plant metabolic networks provides an important complement to 13C-based metabolic flux analysis. Flux-balance modelling is a constraints-based approach in which steady-state fluxes in a metabolic network are predicted by using optimisation algorithms within an experimentally bounded solution space. In the last two years several flux-balance models of plant metabolism have been published including genome-scale models of Arabidopsis metabolism. In this review we conside...

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

    Energy Technology Data Exchange (ETDEWEB)

    Kodavanti, Prasada Rao S., E-mail: kodavanti.prasada@epa.gov [Neurotoxicology Branch, NHEERL, ORD, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina (United States); Osorio, Cristina [Systems Proteomics Center, University of North Carolina at Chapel Hill, North Carolina (United States); Program on Molecular Biology and Biotechnology, University of North Carolina at Chapel Hill, North Carolina (United States); Royland, Joyce E.; Ramabhadran, Ram [Genetic and Cellular Toxicology Branch, NHEERL, ORD, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina (United States); Alzate, Oscar [Department of Cellular and Developmental Biology, University of North Carolina at Chapel Hill, North Carolina (United States); Systems Proteomics Center, University of North Carolina at Chapel Hill, North Carolina (United States); Program on Molecular Biology and Biotechnology, University of North Carolina at Chapel Hill, North Carolina (United States)

    2011-11-15

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

  2. Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

    Directory of Open Access Journals (Sweden)

    Kim Pan-Jun

    2011-08-01

    Full Text Available Abstract Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis. Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925 for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test

  3. Expression of microRNA-34a in Alzheimer's disease brain targets genes linked to synaptic plasticity, energy metabolism, and resting state network activity.

    Science.gov (United States)

    Sarkar, S; Jun, S; Rellick, S; Quintana, D D; Cavendish, J Z; Simpkins, J W

    2016-09-01

    Polygenetic risk factors and reduced expression of many genes in late-onset Alzheimer's disease (AD) impedes identification of a target(s) for disease-modifying therapies. We identified a single microRNA, miR-34a that is over expressed in specific brain regions of AD patients as well as in the 3xTg-AD mouse model. Specifically, increased miR-34a expression in the temporal cortex region compared to age matched healthy control correlates with severity of AD pathology. miR-34a over expression in patient's tissue and forced expression in primary neuronal culture correlates with concurrent repression of its target genes involved in synaptic plasticity, oxidative phosphorylation and glycolysis. The repression of oxidative phosphorylation and glycolysis related proteins correlates with reduced ATP production and glycolytic capacity, respectively. We also found that miR-34a overexpressed neurons secrete miR-34a containing exosomes that are taken up by neighboring neurons. Furthermore, miR-34a targets dozens of genes whose expressions are known to be correlated with synchronous activity in resting state functional networks. Our analysis of human genomic sequences from the tentative promoter of miR-34a gene shows the presence of NFκB, STAT1, c-Fos, CREB and p53 response elements. Together, our results raise the possibilities that pathophysiology-induced activation of specific transcription factor may lead to increased expression of miR-34a gene and miR-34a mediated concurrent repression of its target genes in neural networks may result in dysfunction of synaptic plasticity, energy metabolism, and resting state network activity. Thus, our results provide insights into polygenetic AD mechanisms and disclose miR-34a as a potential therapeutic target for AD. PMID:27235866

  4. Information and Metabolism in Bacterial Chemotaxis

    OpenAIRE

    Gennaro Auletta

    2013-01-01

    One of the most important issues in theoretical biology is to understand how control mechanisms are deployed by organisms to maintain their homeostasis and ensure their survival. A crucial issue is how organisms deal with environmental information in a way that ensures appropriate exchanges with the environment — even in the most basic of life forms (namely, bacteria). In this paper, I present an information theoretic formulation of how Escherichia coli responds to environmental inf...

  5. Social behavior and decision making in bacterial conjugation.

    Science.gov (United States)

    Koraimann, Günther; Wagner, Maria A

    2014-01-01

    Bacteria frequently acquire novel genes by horizontal gene transfer (HGT). HGT through the process of bacterial conjugation is highly efficient and depends on the presence of conjugative plasmids (CPs) or integrated conjugative elements (ICEs) that provide the necessary genes for DNA transmission. This review focuses on recent advancements in our understanding of ssDNA transfer systems and regulatory networks ensuring timely and spatially controlled DNA transfer (tra) gene expression. As will become obvious by comparing different systems, by default, tra genes are shut off in cells in which conjugative elements are present. Only when conditions are optimal, donor cells-through epigenetic alleviation of negatively acting roadblocks and direct stimulation of DNA transfer genes-become transfer competent. These transfer competent cells have developmentally transformed into specialized cells capable of secreting ssDNA via a T4S (type IV secretion) complex directly into recipient cells. Intriguingly, even under optimal conditions, only a fraction of the population undergoes this transition, a finding that indicates specialization and cooperative, social behavior. Thereby, at the population level, the metabolic burden and other negative consequences of tra gene expression are greatly reduced without compromising the ability to horizontally transfer genes to novel bacterial hosts. This undoubtedly intelligent strategy may explain why conjugative elements-CPs and ICEs-have been successfully kept in and evolved with bacteria to constitute a major driving force of bacterial evolution.

  6. Antibiotic resistance of bacterial biofilms

    DEFF Research Database (Denmark)

    Hoiby, N.; Bjarnsholt, T.; Givskov, M.;

    2010-01-01

    A biofilm is a structured consortium of bacteria embedded in a self-produced polymer matrix consisting of polysaccharide, protein and DNA. Bacterial biofilms cause chronic infections because they show increased tolerance to antibiotics and disinfectant chemicals as well as resisting phagocytosis...... and other components of the body's defence system. The persistence of, for example, staphylococcal infections related to foreign bodies is due to biofilm formation. Likewise, chronic Pseudomonas aeruginosa lung infection in cystic fibrosis patients is caused by biofilm-growing mucoid strains....... Characteristically, gradients of nutrients and oxygen exist from the top to the bottom of biofilms and these gradients are associated with decreased bacterial metabolic activity and increased doubling times of the bacterial cells; it is these more or less dormant cells that are responsible for some of the tolerance...

  7. Bacterial regulatory networks—from self-organizing molecules to cell shape and patterns in bacterial communities

    OpenAIRE

    Hengge, Regine; Sourjik, Victor

    2013-01-01

    The ESF–EMBO Conference on ‘Bacterial Networks' was held in March, 2013. It brought together molecular microbiologists, bacteral systems biologists and synthetic biologists to discuss the architecture, function and dynamics of regulatory networks in bacteria.

  8. 基于模糊均值的细菌群体趋药性复杂网络社团结构发现%Identification of Community Structure in Complex Networks Using Bacterial Colony Chemotaxis with Fuzzy Means Algorithm

    Institute of Scientific and Technical Information of China (English)

    李艳灵; 刘先省

    2015-01-01

    复杂网络的社团发现问题是网络数据挖掘中的重要问题之一。利用基于模糊 C 均值的细菌群体趋药性算法最大化网络的模块度,算法中模糊 C 均值的初始值由群体细菌取药性算法获得。模糊 C 均值算法在此基础上发现复杂网络的社团结构。其创新点在于最佳模块度的寻找。实验结果表明:该算法具有对现实世界网络社团划分的可行性和有效性。%Identification of communities in a complex network is one of the important problems in data min‐ing of network data .The bacterial colony chemotaxis (BCC) strategy with fuzzy C‐means (FCM ) algorithm was used to maximize the modularity of a network .In the new algorithm ,the initial cluster center of FCM algorithm was obtained by BCC algorithm .Then ,the FCM algorithm was used for detecting communities in a complex network .The proposed algorithm outperformed most the existing methods in the literature as regards the opti‐mal modularity found .Experimental results for real‐word networks confirmed the feasibility and effectiveness of the proposed algorithm .

  9. Bacterial Microcompartments

    Energy Technology Data Exchange (ETDEWEB)

    Kerfeld, Cheryl A.; Heinhorst, Sabine; Cannon, Gordon C.

    2010-06-05

    Bacterialmicrocompartments (BMCs) are organelles composed entirely of protein. They promote specific metabolic processes by encapsulatingand colocalizing enzymes with their substrates and cofactors, by protecting vulnerable enzymes in a defined microenvironment, and bysequestering toxic or volatile intermediates. Prototypes of the BMCsare the carboxysomes of autotrophic bacteria. However, structures of similarpolyhedral shape are being discovered in an ever-increasing number of heterotrophic bacteria, where they participate in the utilization ofspecialty carbon and energy sources.Comparative genomics reveals that the potential for this type of compartmentalization is widespread acrossbacterial phyla and suggests that genetic modules encoding BMCs are frequently laterally transferred among bacteria. The diverse functionsof these BMCs suggest that they contribute to metabolic innovation in bacteria in a broad range of environments.

  10. Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism.

    Science.gov (United States)

    Pérez-Delgado, Carmen M; Moyano, Tomás C; García-Calderón, Margarita; Canales, Javier; Gutiérrez, Rodrigo A; Márquez, Antonio J; Betti, Marco

    2016-05-01

    Nitrogen is one of the most important nutrients for plants and, in natural soils, its availability is often a major limiting factor for plant growth. Here we examine the effect of different forms of nitrogen nutrition and of photorespiration on gene expression in the model legume Lotus japonicus with the aim of identifying regulatory candidate genes co-ordinating primary nitrogen assimilation and photorespiration. The transcriptomic changes produced by the use of different nitrogen sources in leaves of L. japonicus plants combined with the transcriptomic changes produced in the same tissue by different photorespiratory conditions were examined. The results obtained provide novel information on the possible role of plastidic glutamine synthetase in the response to different nitrogen sources and in the C/N balance of L. japonicus plants. The use of gene co-expression networks establishes a clear relationship between photorespiration and primary nitrogen assimilation and identifies possible transcription factors connected to the genes of both routes. PMID:27117340

  11. Microscopy and Bioinformatic Analyses of Lipid Metabolism Implicate a Sporophytic Signaling Network Supporting Pollen Development in Arabidopsis

    Institute of Scientific and Technical Information of China (English)

    Yixing Wang; Hong Wu; Ming Yang

    2008-01-01

    The Arabidopsis sporophytic tapetum undergoes a programmed degeneration process to secrete lipid and other materials to support pollen development.However,the molecular mechanism regulating the degeneration process is unknown.To gain insight into this molecular mechanism,we first determined that the most critical period for tapetal secretion to support pollen development iS from the vacuolate microspore stage to the early binucleate pollen stage.We then analyzed the expression of enzymes responsible for lipid biosynthesis and degradation with available in-silico data.The genes for these enzymes that are expressed in the stamen but not in the concurrent uninucleate microspore and binucleate pollen are of particular interest,as they presumably hold the clues to unique molecular processes in the sporophytic tissues compared to the gametophytic tissue.No gene for lipid biosynthesis but a single gene encoding a patatin-like protein likely for lipid mobilization was identified based on the selection criterion.A search for genes co-expressed with this gene identified additional genes encoding typical signal transduction components such as a leucine-rich repeat receptor kinase,an extra-large G-protein,other protein kinases,and transcription factors.In addition,proteases,cell wall degradation enzymes,and other proteins were also identified.These proteins thus may be components of a signaling network leading to degradation of a broad range of cellular components.Since a broad range of degradation activities is expected to occur only in the tapetal degeneration process at this stage in the stamen,it iS further hypothesized that the signaling network acts in the tapetal degeneration process.

  12. Assessment of nitric oxide (NO) redox reactions contribution to nitrous oxide (N2 O) formation during nitrification using a multispecies metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Chandran, Kartik; Villas-Boas, Silas G; Singhal, Naresh

    2016-05-01

    Over the coming decades nitrous oxide (N2O) is expected to become a dominant greenhouse gas and atmospheric ozone depleting substance. In wastewater treatment systems, N2O is majorly produced by nitrifying microbes through biochemical reduction of nitrite (NO2(-)) and nitric oxide (NO). However it is unknown if the amount of N2O formed is affected by alternative NO redox reactions catalyzed by oxidative nitrite oxidoreductase (NirK), cytochromes (i.e., P460 [CytP460] and 554 [Cyt554 ]) and flavohemoglobins (Hmp) in ammonia- and nitrite-oxidizing bacteria (AOB and NOB, respectively). In this study, a mathematical model is developed to assess how N2O formation is affected by such alternative nitrogen redox transformations. The developed multispecies metabolic network model captures the nitrogen respiratory pathways inferred from genomes of eight AOB and NOB species. The performance of model variants, obtained as different combinations of active NO redox reactions, was assessed against nine experimental datasets for nitrifying cultures producing N2O at different concentration of electron donor and acceptor. Model predicted metabolic fluxes show that only variants that included NO oxidation to NO2(-) by CytP460 and Hmp in AOB gave statistically similar estimates to observed production rates of N2O, NO, NO2(-) and nitrate (NO3(-)), together with fractions of AOB and NOB species in biomass. Simulations showed that NO oxidation to NO2(-) decreased N2O formation by 60% without changing culture's NO2(-) production rate. Model variants including NO reduction to N2O by Cyt554 and cNor in NOB did not improve the accuracy of experimental datasets estimates, suggesting null N2O production by NOB during nitrification. Finally, the analysis shows that in nitrifying cultures transitioning from dissolved oxygen levels above 3.8 ± 0.38 to oxidize the NO produced by AOB through reactions catalyzed by oxidative NirK. PMID:26551878

  13. Metabolic Network for the Biosynthesis of Intra- and Extracellular α-Glucans Required for Virulence of Mycobacterium tuberculosis

    Science.gov (United States)

    van de Weerd, Robert; Chandra, Govind; Appelmelk, Ben; Alber, Marina; Ioerger, Thomas R.; Jacobs, William R.; Geurtsen, Jeroen; Bornemann, Stephen

    2016-01-01

    Mycobacterium tuberculosis synthesizes intra- and extracellular α-glucans that were believed to originate from separate pathways. The extracellular glucose polymer is the main constituent of the mycobacterial capsule that is thought to be involved in immune evasion and virulence. However, the role of the α-glucan capsule in pathogenesis has remained enigmatic due to an incomplete understanding of α-glucan biosynthetic pathways preventing the generation of capsule-deficient mutants. Three separate and potentially redundant pathways had been implicated in α-glucan biosynthesis in mycobacteria: the GlgC-GlgA, the Rv3032 and the TreS-Pep2-GlgE pathways. We now show that α-glucan in mycobacteria is exclusively assembled intracellularly utilizing the building block α-maltose-1-phosphate as the substrate for the maltosyltransferase GlgE, with subsequent branching of the polymer by the branching enzyme GlgB. Some α-glucan is exported to form the α-glucan capsule. There is an unexpected convergence of the TreS-Pep2 and GlgC-GlgA pathways that both generate α-maltose-1-phosphate. While the TreS-Pep2 route from trehalose was already known, we have now established that GlgA forms this phosphosugar from ADP-glucose and glucose 1-phosphate 1000-fold more efficiently than its hitherto described glycogen synthase activity. The two routes are connected by the common precursor ADP-glucose, allowing compensatory flux from one route to the other. Having elucidated this unexpected configuration of the metabolic pathways underlying α-glucan biosynthesis in mycobacteria, an M. tuberculosis double mutant devoid of α-glucan could be constructed, showing a direct link between the GlgE pathway, α-glucan biosynthesis and virulence in a mouse infection model. PMID:27513637

  14. The NADPH metabolic network regulates human αB-crystallin cardiomyopathy and reductive stress in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Heng B Xie

    2013-06-01

    Full Text Available Dominant mutations in the alpha-B crystallin (CryAB gene are responsible for a number of inherited human disorders, including cardiomyopathy, skeletal muscle myopathy, and cataracts. The cellular mechanisms of disease pathology for these disorders are not well understood. Among recent advances is that the disease state can be linked to a disturbance in the oxidation/reduction environment of the cell. In a mouse model, cardiomyopathy caused by the dominant CryAB(R120G missense mutation was suppressed by mutation of the gene that encodes glucose 6-phosphate dehydrogenase (G6PD, one of the cell's primary sources of reducing equivalents in the form of NADPH. Here, we report the development of a Drosophila model for cellular dysfunction caused by this CryAB mutation. With this model, we confirmed the link between G6PD and mutant CryAB pathology by finding that reduction of G6PD expression suppressed the phenotype while overexpression enhanced it. Moreover, we find that expression of mutant CryAB in the Drosophila heart impaired cardiac function and increased heart tube dimensions, similar to the effects produced in mice and humans, and that reduction of G6PD ameliorated these effects. Finally, to determine whether CryAB pathology responds generally to NADPH levels we tested mutants or RNAi-mediated knockdowns of phosphogluconate dehydrogenase (PGD, isocitrate dehydrogenase (IDH, and malic enzyme (MEN, the other major enzymatic sources of NADPH, and we found that all are capable of suppressing CryAB(R120G pathology, confirming the link between NADP/H metabolism and CryAB.

  15. The NADPH metabolic network regulates human αB-crystallin cardiomyopathy and reductive stress in Drosophila melanogaster.

    Science.gov (United States)

    Xie, Heng B; Cammarato, Anthony; Rajasekaran, Namakkal S; Zhang, Huali; Suggs, Jennifer A; Lin, Ho-Chen; Bernstein, Sanford I; Benjamin, Ivor J; Golic, Kent G

    2013-06-01

    Dominant mutations in the alpha-B crystallin (CryAB) gene are responsible for a number of inherited human disorders, including cardiomyopathy, skeletal muscle myopathy, and cataracts. The cellular mechanisms of disease pathology for these disorders are not well understood. Among recent advances is that the disease state can be linked to a disturbance in the oxidation/reduction environment of the cell. In a mouse model, cardiomyopathy caused by the dominant CryAB(R120G) missense mutation was suppressed by mutation of the gene that encodes glucose 6-phosphate dehydrogenase (G6PD), one of the cell's primary sources of reducing equivalents in the form of NADPH. Here, we report the development of a Drosophila model for cellular dysfunction caused by this CryAB mutation. With this model, we confirmed the link between G6PD and mutant CryAB pathology by finding that reduction of G6PD expression suppressed the phenotype while overexpression enhanced it. Moreover, we find that expression of mutant CryAB in the Drosophila heart impaired cardiac function and increased heart tube dimensions, similar to the effects produced in mice and humans, and that reduction of G6PD ameliorated these effects. Finally, to determine whether CryAB pathology responds generally to NADPH levels we tested mutants or RNAi-mediated knockdowns of phosphogluconate dehydrogenase (PGD), isocitrate dehydrogenase (IDH), and malic enzyme (MEN), the other major enzymatic sources of NADPH, and we found that all are capable of suppressing CryAB(R120G) pathology, confirming the link between NADP/H metabolism and CryAB.

  16. Filling Knowledge Gaps in Biological Networks: integrating global approaches to understand H2 metabolism in Chlamydomonas reinhardtii - Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Posewitz, Matthew C

    2011-06-30

    The green alga Chlamydomonas reinhardtii (Chlamydomonas) has numerous genes encoding enzymes that function in fermentative pathways. Among these genes, are the [FeFe]-hydrogenases, pyruvate formate lyase, pyruvate ferredoxin oxidoreductase, acetate kinase, and phosphotransacetylase. We have systematically undertaken a series of targeted mutagenesis approaches to disrupt each of these key genes and omics techniques to characterize alterations in metabolic flux. Funds from DE-FG02-07ER64423 were specifically leveraged to generate mutants with disruptions in the genes encoding the [FeFe]-hydrogenases HYDA1 and HYDA2, pyruvate formate lyase (PFL1), and in bifunctional alcohol/aldehyde alcohol dehydrogenase (ADH1). Additionally funds were used to conduct global transcript profiling experiments of wildtype Chlamydomonas cells, as well as of the hydEF-1 mutant, which is unable to make H2 due to a lesion in the [FeFe]-hydrogenase biosynthetic pathway. In the wildtype cells, formate, acetate and ethanol are the dominant fermentation products with traces of CO2 and H2 also being produced. In the hydEF-1 mutant, succinate production is increased to offset the loss of protons as a terminal electron acceptor. In the pfl-1 mutant, lactate offsets the loss of formate production, and in the adh1-1 mutant glycerol is made instead of ethanol. To further probe the system, we generated a double mutant (pfl1-1 adh1) that is unable to synthesize both formate and ethanol. This strain, like the pfl1 mutants, secreted lactate, but also exhibited a significant increase in the levels of extracellular glycerol, acetate, and intracellular reduced sugars, and a decline in dark, fermentative H2 production. Whereas wild-type Chlamydomonas fermentation primarily produces formate and ethanol, the double mutant performs a complete rerouting of the glycolytic carbon to lactate and glycerol. Lastly, transcriptome data have been analysed for both the wildtype and hydEF-1, that correlate with our

  17. Bacterial Hydrodynamics

    Science.gov (United States)

    Lauga, Eric

    2016-01-01

    Bacteria predate plants and animals by billions of years. Today, they are the world's smallest cells, yet they represent the bulk of the world's biomass and the main reservoir of nutrients for higher organisms. Most bacteria can move on their own, and the majority of motile bacteria are able to swim in viscous fluids using slender helical appendages called flagella. Low-Reynolds number hydrodynamics is at the heart of the ability of flagella to generate propulsion at the micrometer scale. In fact, fluid dynamic forces impact many aspects of bacteriology, ranging from the ability of cells to reorient and search their surroundings to their interactions within mechanically and chemically complex environments. Using hydrodynamics as an organizing fr