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Sample records for bacterial metabolic networks

  1. Structural correlations in bacterial metabolic networks

    OpenAIRE

    Lizana Ludvig; Gerlee Philip; Bernhardsson Sebastian

    2011-01-01

    Abstract Background Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution. Results We consider t...

  2. On the accessibility of adaptive phenotypes of a bacterial metabolic network.

    Directory of Open Access Journals (Sweden)

    Wilfred Ndifon

    2009-08-01

    Full Text Available The mechanisms by which adaptive phenotypes spread within an evolving population after their emergence are understood fairly well. Much less is known about the factors that influence the evolutionary accessibility of such phenotypes, a pre-requisite for their emergence in a population. Here, we investigate the influence of environmental quality on the accessibility of adaptive phenotypes of Escherichia coli's central metabolic network. We used an established flux-balance model of metabolism as the basis for a genotype-phenotype map (GPM. We quantified the effects of seven qualitatively different environments (corresponding to both carbohydrate and gluconeogenic metabolic substrates on the structure of this GPM. We found that the GPM has a more rugged structure in qualitatively poorer environments, suggesting that adaptive phenotypes could be intrinsically less accessible in such environments. Nevertheless, on average approximately 74% of the genotype can be altered by neutral drift, in the environment where the GPM is most rugged; this could allow evolving populations to circumvent such ruggedness. Furthermore, we found that the normalized mutual information (NMI of genotype differences relative to phenotype differences, which measures the GPM's capacity to transmit information about phenotype differences, is positively correlated with (simulation-based estimates of the accessibility of adaptive phenotypes in different environments. These results are consistent with the predictions of a simple analytic theory that makes explicit the relationship between the NMI and the speed of adaptation. The results suggest an intuitive information-theoretic principle for evolutionary adaptation; adaptation could be faster in environments where the GPM has a greater capacity to transmit information about phenotype differences. More generally, our results provide insight into fundamental environment-specific differences in the accessibility of adaptive

  3. 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.

  4. 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.

  5. The role of metabolism in bacterial persistence

    Directory of Open Access Journals (Sweden)

    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.

  6. 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...

  7. 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.

  8. Evolution of metabolic network organization

    Directory of Open Access Journals (Sweden)

    Bonchev Danail

    2010-05-01

    Full Text Available Abstract Background Comparison of metabolic networks across species is a key to understanding how evolutionary pressures shape these networks. By selecting taxa representative of different lineages or lifestyles and using a comprehensive set of descriptors of the structure and complexity of their metabolic networks, one can highlight both qualitative and quantitative differences in the metabolic organization of species subject to distinct evolutionary paths or environmental constraints. Results We used a novel representation of metabolic networks, termed network of interacting pathways or NIP, to focus on the modular, high-level organization of the metabolic capabilities of the cell. Using machine learning techniques we identified the most relevant aspects of cellular organization that change under evolutionary pressures. We considered the transitions from prokarya to eukarya (with a focus on the transitions among the archaea, bacteria and eukarya, from unicellular to multicellular eukarya, from free living to host-associated bacteria, from anaerobic to aerobic, as well as the acquisition of cell motility or growth in an environment of various levels of salinity or temperature. Intuitively, we expect organisms with more complex lifestyles to have more complex and robust metabolic networks. Here we demonstrate for the first time that such organisms are not only characterized by larger, denser networks of metabolic pathways but also have more efficiently organized cross communications, as revealed by subtle changes in network topology. These changes are unevenly distributed among metabolic pathways, with specific categories of pathways being promoted to more central locations as an answer to environmental constraints. Conclusions Combining methods from graph theory and machine learning, we have shown here that evolutionary pressures not only affects gene and protein sequences, but also specific details of the complex wiring of functional modules

  9. 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.

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

    OpenAIRE

    Xueying Chen; Min Zhao; Hong Qu

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pall...

  11. Metabolic Responses of Bacterial Cells to Immobilization.

    Science.gov (United States)

    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

  12. Metabolic Responses of Bacterial Cells to Immobilization

    Directory of Open Access Journals (Sweden)

    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.

  13. Flux networks in metabolic graphs

    International Nuclear Information System (INIS)

    A metabolic model can be represented as a bipartite graph comprising linked reaction and metabolite nodes. Here it is shown how a network of conserved fluxes can be assigned to the edges of such a graph by combining the reaction fluxes with a conserved metabolite property such as molecular weight. A similar flux network can be constructed by combining the primal and dual solutions to the linear programming problem that typically arises in constraint-based modelling. Such constructions may help with the visualization of flux distributions in complex metabolic networks. The analysis also explains the strong correlation observed between metabolite shadow prices (the dual linear programming variables) and conserved metabolite properties. The methods were applied to recent metabolic models for Escherichia coli, Saccharomyces cerevisiae and Methanosarcina barkeri. Detailed results are reported for E. coli; similar results were found for other organisms

  14. Noise effect in metabolic networks

    International Nuclear Information System (INIS)

    Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states. (cross-disciplinary physics and related areas of science and technology)

  15. Algebraic comparison of metabolic networks, phylogenetic inference, and metabolic innovation

    Directory of Open Access Journals (Sweden)

    Hofacker Ivo L

    2006-02-01

    Full Text Available Abstract Background Comparison of metabolic networks is typically performed based on the organisms' enzyme contents. This approach disregards functional replacements as well as orthologies that are misannotated. Direct comparison of the structure of metabolic networks can circumvent these problems. Results Metabolic networks are naturally represented as directed hypergraphs in such a way that metabolites are nodes and enzyme-catalyzed reactions form (hyperedges. The familiar operations from set algebra (union, intersection, and difference form a natural basis for both the pairwise comparison of networks and identification of distinct metabolic features of a set of algorithms. We report here on an implementation of this approach and its application to the procaryotes. Conclusion We demonstrate that metabolic networks contain valuable phylogenetic information by comparing phylogenies obtained from network comparisons with 16S RNA phylogenies. The algebraic approach to metabolic networks is suitable to study metabolic innovations in two sets of organisms, free living microbes and Pyrococci, as well as obligate intracellular pathogens.

  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. 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...

  18. Predicting metabolic pathways from metabolic networks with limited biological knowledge

    OpenAIRE

    Leung, HCM; Yiu, SM; Chin, FYL; Leung, SY; Xiang, CL

    2010-01-01

    Understanding the metabolism of new species (e.g. endophytic fungi that produce fuel) have tremendous impact on human lives. Based on predicted proteins and existing reaction databases, one can construct the metabolic network for the species. Next is to identify critical metabolic pathways from the network. Existing computational techniques identify conserved pathways based on multiple networks of related species, but have the following drawbacks. Some do not rely on additional information, s...

  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. Uncovering transcriptional regulation of metabolism by using metabolic network topology

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Nielsen, Jens

    2005-01-01

    Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional...... changes induced by complex regulatory mechanisms coordinating the activity of different metabolic pathways. It is difficult to map such global transcriptional responses by using traditional methods, because many genes in the metabolic network have relatively small changes at their transcription level. We...... therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns in...

  1. Size Dependent Growth in Metabolic Networks

    CERN Document Server

    Dorrian, Henry; borresen, Jon

    2012-01-01

    Accurately determining and classifying the structure of complex networks is the focus of much current research. One class of network of particular interest are metabolic pathways, which have previously been studied from a graph theoretical viewpoint in a number of ways. Metabolic networks describe the chemical reactions within cells and are thus of prime importance from a biological perspective. Here we analyse metabolic networks from a section of microorganisms, using a range of metrics and attempt to address anomalies between the observed metrics and current descriptions of the graphical structure. We propose that the growth of the network may in some way be regulated by network size and attempt to reproduce networks with similar metrics to the metabolic pathways using a generative approach. We provide some hypotheses as to why biological networks may evolve according to these model criteria.

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

    Science.gov (United States)

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

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

  3. A network perspective on metabolic inconsistency

    Directory of Open Access Journals (Sweden)

    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

  4. Bacterial colony counting by Convolutional Neural Networks.

    Science.gov (United States)

    Ferrari, Alessandro; Lombardi, Stefano; Signoroni, Alberto

    2015-08-01

    Counting bacterial colonies on microbiological culture plates is a time-consuming, error-prone, nevertheless fundamental task in microbiology. Computer vision based approaches can increase the efficiency and the reliability of the process, but accurate counting is challenging, due to the high degree of variability of agglomerated colonies. In this paper, we propose a solution which adopts Convolutional Neural Networks (CNN) for counting the number of colonies contained in confluent agglomerates, that scored an overall accuracy of the 92.8% on a large challenging dataset. The proposed CNN-based technique for estimating the cardinality of colony aggregates outperforms traditional image processing approaches, becoming a promising approach to many related applications. PMID:26738016

  5. Computational Methods for Modification of Metabolic Networks

    Directory of Open Access Journals (Sweden)

    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.

  6. 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...

  7. 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.

  8. Phenotype prediction in regulated metabolic networks

    Directory of Open Access Journals (Sweden)

    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

  9. High resolution deuterium NMR studies of bacterial metabolism

    International Nuclear Information System (INIS)

    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

  10. High resolution deuterium NMR studies of bacterial metabolism

    Energy Technology Data Exchange (ETDEWEB)

    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. 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.

  12. Dispersal networks for enhancing bacterial degradation in heterogeneous environments

    International Nuclear Information System (INIS)

    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.

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

    Science.gov (United States)

    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

  14. 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.

  15. 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...

  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. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.; Palsson, B.O.; Nielsen, Jens

    2003-01-01

    The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments and the...... containing 1175 metabolic reactions and 584 metabolites. The number of gene functions included in the reconstructed network corresponds to similar to16% of all characterized ORFs in S. cerevisiae. Using the reconstructed network, the metabolic capabilities of S. cerevisiae were calculated and compared with...

  4. 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.

  5. 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...

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

    DEFF Research Database (Denmark)

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

    2003-01-01

    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...... 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....

  7. 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.

  8. 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. PMID:20298776

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

    Science.gov (United States)

    Vidal, Luciana O.; Abril, Gwenäel; Artigas, Luiz F.; Melo, Michaela L.; Bernardes, Marcelo C.; Lobão, Lúcia M.; Reis, Mariana C.; Moreira-Turcq, Patrícia; Benedetti, Marc; Tornisielo, Valdemar L.; Roland, Fabio

    2015-01-01

    We evaluated in situ rates of bacterial carbon processing in Amazonian floodplain lakes and mainstems, during both high water (HW) and low water (LW) phases (p < 0.05). Our results showed that bacterial production (BP) was lower and more variable than bacterial respiration, determined as total respiration. Bacterial carbon demand was mostly accounted by BR and presented the same pattern that BR in both water phases. Bacterial growth efficiency (BGE) showed a wide range (0.2–23%) and low mean value of 3 and 6%, (in HW and LW, respectively) suggesting that dissolved organic carbon was mostly allocated to catabolic metabolism. However, BGE was regulated by BP in LW 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 LW. Multiple correlation analyses revealed that indexes of organic matter (OM) quality (chlorophyll-a, N stable isotopes and C/N ratios) were the strongest seasonal drivers of bacterial carbon metabolism. Our work indicated that: (i) the bacterial metabolism was mostly driven by respiration in Amazonian aquatic ecosystems resulting in low BGE in either high or LW phase; (ii) the hydrological pulse regulated the bacterial heterotrophic metabolism between Amazonian mainstems and floodplain lakes mostly driven by OM quality. PMID:26483776

  10. 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

  11. 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

  12. 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

  13. Metabolic robustness and network modularity: A model study

    OpenAIRE

    Holme, Petter

    2010-01-01

    [Background] Several studies have mentioned network modularity -- that a network can easily be decomposed into subgraphs that are densely connected within and weakly connected between each other -- as a factor affecting metabolic robustness. In this paper we measure the relation between network modularity and several aspects of robustness directly in a model system of metabolism. [Methodology/Principal Findings] By using a model for generating chemical reaction systems where one can tune the ...

  14. Shuffling bacterial metabolomes

    OpenAIRE

    Thomason, Brendan; Read, Timothy D.

    2006-01-01

    Horizontal gene transfer (HGT) has a far more significant role than gene duplication in bacterial evolution. This has recently been illustrated by work demonstrating the importance of HGT in the emergence of bacterial metabolic networks, with horizontally acquired genes being placed in peripheral pathways at the outer branches of the networks.

  15. 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

  16. Interferon production by Shigella flexneri-infected fibroblasts depends upon intracellular bacterial metabolism.

    OpenAIRE

    Hess, C. B.; Niesel, D W; Holmgren, J.; Jonson, G; Klimpel, G R

    1990-01-01

    The role of bacterial invasion and subsequent intracellular metabolism or replication, or both, in the induction of interferon (IFN) production in primary cultures of murine embryo fibroblasts (MEFs) was examined. IFN production appeared to be dependent upon bacterial invasion. MEFs that were challenged with Shigella flexneri cultured at 30 degrees C to inhibit the temperature-dependent virulence gene expression that is essential for invasion failed to produce IFN. Furthermore, inhibition of ...

  17. 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.

  18. 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

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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, the ...... to attenuate unwanted side effects resulting from oxygen limitation during industrial fermentations with A. niger.......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, the...... 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...

  4. 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.

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

    OpenAIRE

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

    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 diseas...

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

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen; Ülgen, Kutlu Özergin; Kirdar, Betül; Nielsen, Jens

    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...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

  7. Metabolism of bacterial cells bound to solid carriers

    International Nuclear Information System (INIS)

    Escherichia coli 2260 cells bound to solid carriers (iodo-and bromoacetyl cellulose) were incubated in the Davis mineral medium and changes in respiratory activity, ATP level, 14C-valine and 14C-adenine incorporation and the number of bacteria able to multiply were investigated. As compared with suspended cells, no significant changes in the rate and capacity of the metabolic processes studied were recorded. Iodoacetyl cellulose had the smallest effect on the rates of nucleic acids and protein syntheses. (author). 3 figs., 2 tabs., 11 refs

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

    OpenAIRE

    Vitkin, Edward; Shlomi, Tomer

    2012-01-01

    Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for ...

  9. Metabolic robustness and network modularity: a model study.

    Directory of Open Access Journals (Sweden)

    Petter Holme

    Full Text Available BACKGROUND: Several studies have mentioned network modularity-that a network can easily be decomposed into subgraphs that are densely connected within and weakly connected between each other-as a factor affecting metabolic robustness. In this paper we measure the relation between network modularity and several aspects of robustness directly in a model system of metabolism. METHODOLOGY/PRINCIPAL FINDINGS: By using a model for generating chemical reaction systems where one can tune the network modularity, we find that robustness increases with modularity for changes in the concentrations of metabolites, whereas it decreases with changes in the expression of enzymes. The same modularity scaling is true for the speed of relaxation after the perturbations. CONCLUSIONS/SIGNIFICANCE: Modularity is not a general principle for making metabolism either more or less robust; this question needs to be addressed specifically for different types of perturbations of the system.

  10. 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.

  11. 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.

  12. A Strategy to Calculate the Patterns of Nutrient Consumption by Microorganisms Applying a Two-Level Optimisation Principle to Reconstructed Metabolic Networks

    OpenAIRE

    Ponce de León, Miguel; Cancela, Héctor; Acerenza, Luis

    2008-01-01

    Bacterial responses to environmental changes rely on a complex network of biochemical reactions. The properties of the metabolic network determining these responses can be divided into two groups: the stoichiometric properties, given by the stoichiometry matrix, and the kinetic/thermodynamic properties, given by the rate equations of the reaction steps. The stoichiometry matrix represents the maximal metabolic capabilities of the organism, and the regulatory mechanisms based on the rate laws ...

  13. 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

  14. Preferential attachment in the evolution of metabolic networks

    Directory of Open Access Journals (Sweden)

    Elofsson Arne

    2005-11-01

    Full Text Available Abstract Background Many biological networks show some characteristics of scale-free networks. Scale-free networks can evolve through preferential attachment where new nodes are preferentially attached to well connected nodes. In networks which have evolved through preferential attachment older nodes should have a higher average connectivity than younger nodes. Here we have investigated preferential attachment in the context of metabolic networks. Results The connectivities of the enzymes in the metabolic network of Escherichia coli were determined and representatives for these enzymes were located in 11 eukaryotes, 17 archaea and 46 bacteria. E. coli enzymes which have representatives in eukaryotes have a higher average connectivity while enzymes which are represented only in the prokaryotes, and especially the enzymes only present in βγ-proteobacteria, have lower connectivities than expected by chance. Interestingly, the enzymes which have been proposed as candidates for horizontal gene transfer have a higher average connectivity than the other enzymes. Furthermore, It was found that new edges are added to the highly connected enzymes at a faster rate than to enzymes with low connectivities which is consistent with preferential attachment. Conclusion Here, we have found indications of preferential attachment in the metabolic network of E. coli. A possible biological explanation for preferential attachment growth of metabolic networks is that novel enzymes created through gene duplication maintain some of the compounds involved in the original reaction, throughout its future evolution. In addition, we found that enzymes which are candidates for horizontal gene transfer have a higher average connectivity than other enzymes. This indicates that while new enzymes are attached preferentially to highly connected enzymes, these highly connected enzymes have sometimes been introduced into the E. coli genome by horizontal gene transfer. We speculate

  15. 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.

  16. Metabolic Coevolution in the Bacterial Symbiosis of Whiteflies and Related Plant Sap-Feeding Insects.

    Science.gov (United States)

    Luan, Jun-Bo; Chen, Wenbo; Hasegawa, Daniel K; Simmons, Alvin M; Wintermantel, William M; Ling, Kai-Shu; Fei, Zhangjun; Liu, Shu-Sheng; Douglas, Angela E

    2015-09-01

    Genomic decay is a common feature of intracellular bacteria that have entered into symbiosis with plant sap-feeding insects. This study of the whitefly Bemisia tabaci and two bacteria (Portiera aleyrodidarum and Hamiltonella defensa) cohoused in each host cell investigated whether the decay of Portiera metabolism genes is complemented by host and Hamiltonella genes, and compared the metabolic traits of the whitefly symbiosis with other sap-feeding insects (aphids, psyllids, and mealybugs). Parallel genomic and transcriptomic analysis revealed that the host genome contributes multiple metabolic reactions that complement or duplicate Portiera function, and that Hamiltonella may contribute multiple cofactors and one essential amino acid, lysine. Homologs of the Bemisia metabolism genes of insect origin have also been implicated in essential amino acid synthesis in other sap-feeding insect hosts, indicative of parallel coevolution of shared metabolic pathways across multiple symbioses. Further metabolism genes coded in the Bemisia genome are of bacterial origin, but phylogenetically distinct from Portiera, Hamiltonella and horizontally transferred genes identified in other sap-feeding insects. Overall, 75% of the metabolism genes of bacterial origin are functionally unique to one symbiosis, indicating that the evolutionary history of metabolic integration in these symbioses is strongly contingent on the pattern of horizontally acquired genes. Our analysis, further, shows that bacteria with genomic decay enable host acquisition of complex metabolic pathways by multiple independent horizontal gene transfers from exogenous bacteria. Specifically, each horizontally acquired gene can function with other genes in the pathway coded by the symbiont, while facilitating the decay of the symbiont gene coding the same reaction. PMID:26377567

  17. Marine bacterial, archaeal and protistan association networks reveal ecological linkages.

    Science.gov (United States)

    Steele, Joshua A; Countway, Peter D; Xia, Li; Vigil, Patrick D; Beman, J Michael; Kim, Diane Y; Chow, Cheryl-Emiliane T; Sachdeva, Rohan; Jones, Adriane C; Schwalbach, Michael S; Rose, Julie M; Hewson, Ian; Patel, Anand; Sun, Fengzhu; Caron, David A; Fuhrman, Jed A

    2011-09-01

    Microbes have central roles in ocean food webs and global biogeochemical processes, yet specific ecological relationships among these taxa are largely unknown. This is in part due to the dilute, microscopic nature of the planktonic microbial community, which prevents direct observation of their interactions. Here, we use a holistic (that is, microbial system-wide) approach to investigate time-dependent variations among taxa from all three domains of life in a marine microbial community. We investigated the community composition of bacteria, archaea and protists through cultivation-independent methods, along with total bacterial and viral abundance, and physico-chemical observations. Samples and observations were collected monthly over 3 years at a well-described ocean time-series site of southern California. To find associations among these organisms, we calculated time-dependent rank correlations (that is, local similarity correlations) among relative abundances of bacteria, archaea, protists, total abundance of bacteria and viruses and physico-chemical parameters. We used a network generated from these statistical correlations to visualize and identify time-dependent associations among ecologically important taxa, for example, the SAR11 cluster, stramenopiles, alveolates, cyanobacteria and ammonia-oxidizing archaea. Negative correlations, perhaps suggesting competition or predation, were also common. The analysis revealed a progression of microbial communities through time, and also a group of unknown eukaryotes that were highly correlated with dinoflagellates, indicating possible symbioses or parasitism. Possible 'keystone' species were evident. The network has statistical features similar to previously described ecological networks, and in network parlance has non-random, small world properties (that is, highly interconnected nodes). This approach provides new insights into the natural history of microbes. PMID:21430787

  18. 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

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

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej

    domains of life. Nowadays, metabolism has 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...... targets for therapeutic agents and future clinical 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...

  20. 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, a...... ventilation strategy guided by jugular bulb oximetry and/or repeated CBF measurements may be more optimal in terms of cerebral oxygenation than a strategy aiming at identical levels of P(a)CO(2) for all patients....

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

    Science.gov (United States)

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

    2000-03-01

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

  2. Dual-label radioisotope method for simultaneously measuring bacterial production and metabolism in natural waters

    International Nuclear Information System (INIS)

    Bacterial production and amino acid metabolism in aquatic systems can be estimated by simultaneous incubation of water samples with both tritiated methyl-thymidine and 14C-labeled amino acids. This dual-label method not only saves time, labor, and materials, but also allows determination of these two parameters in the same microbial subcommunity. Both organic carbon incorporation and respiration can be estimated. The method is particularly suitable for large-scale field programs and has been used successfully with eutrophic estuarine samples as well as with oligotrophic oceanic water. In the mesohaline portion of Chesapeake Bay, thymidine incorporation ranged seasonally from 2 to 635 pmol liter-1 h-1 and amino acid turnover rates ranged from 0.01 to 28.4% h-1. Comparison of thymidine incorporation with amino acid turnover measurements made at a deep, midbay station in 1985 suggested a close coupling between bacterial production and amino acid metabolism during most of the year. However, production-specific amino acid turnover rates increased dramatically in deep bay waters during the spring phytoplankton bloom, indicating transient decoupling of bacterial production from metabolism. Ecological features such as this are readily detectable with the dual-label method

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

    Science.gov (United States)

    Özcan, Emrah; Çakır, Tunahan

    2016-01-01

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

  4. 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.

  5. 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

  6. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Bernhardsson, Sebastian; Minnhagen, Petter, E-mail: sebbeb@tp.umu.s [IceLab, Department of Physics, Umeaa University, 901 87 Umeaa (Sweden)

    2010-10-15

    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.

  8. 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.

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G. [Massachusetts Inst. of Tech., Cambridge, MA (United States). Dept. of Chemical Engineering

    1998-04-20

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

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. Metabolite coupling in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard Ø

    2006-03-01

    Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

  16. 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.

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

    Science.gov (United States)

    Vitkin, Edward; Shlomi, Tomer

    2012-01-01

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

  18. 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

  19. 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...

  20. 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......% (D2), 4% D4), and 6% BPM (D6), BPM providing up to 20% of total dietary N. Five balance experiments were conducted when the chickens were 3-7, 10-14, 17-21, 23-27, and 30-34 days old. During the same periods, 22-h respiration experiments (indirect calorimetry) were performed with troups of 6 chickens...... 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....

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803.

    Directory of Open Access Journals (Sweden)

    Henning Knoop

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

  6. 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.

  7. Early-life exercise may promote lasting brain and metabolic health through gut bacterial metabolites.

    Science.gov (United States)

    Mika, Agnieszka; Fleshner, Monika

    2016-02-01

    The 100 trillion microorganisms residing within our intestines contribute roughly 5 million additional genes to our genetic gestalt, thus posing the potential to influence many aspects of our physiology. Microbial colonization of the gut shortly after birth is vital for the proper development of immune, neural and metabolic systems, while sustaining a balanced, diverse gut flora populated with beneficial bacteria is necessary for maintaining optimal function of these systems. Although symbiotic host-microbial interactions are important throughout the lifespan, these interactions can have greater and longer lasting impacts during certain critical developmental periods. A better understanding of these sensitive periods is necessary to improve the impact and effectiveness of health-promoting interventions that target the microbial ecosystem. We have recently reported that exercise initiated in early life increases gut bacterial species involved in promoting psychological and metabolic health. In this review, we emphasize the ability of exercise during this developmentally receptive time to promote optimal brain and metabolic function across the lifespan through microbial signals. PMID:26647967

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

    Science.gov (United States)

    Schellenberger, Jan; Palsson, Bernhard Ø

    2009-02-27

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

  9. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health

    OpenAIRE

    Wei, Zhong; Yang, Tianjie; Friman, Ville-Petri; Xu, Yangchun; Shen, Qirong; Jousset, Alexandre

    2015-01-01

    Host-associated bacterial communities can function as an important line of defence against pathogens in animals and plants. Empirical evidence and theoretical predictions suggest that species-rich communities are more resistant to pathogen invasions. Yet, the underlying mechanisms are unclear. Here, we experimentally test how the underlying resource competition networks of resident bacterial communities affect invasion resistance to the plant pathogen Ralstonia solanacearum in microcosms and ...

  10. 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

  11. 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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    known transcription regulation network. Interactions across multiple levels of regulation were involved in adaptive changes that could also be achieved by controlling single genes. Our analysis suggests that global trade-offs and evolutionary constraints provide incentives to favor complex control......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...... model-based data analyses of dynamic transcript, protein, and metabolite abundances and promoter activities. Adaptation to malate was rapid and primarily controlled posttranscriptionally compared with the slow, mainly transcriptionally controlled adaptation to glucose that entailed nearly half of the...

  13. 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.

  14. 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

  15. 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...

  16. 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.

  17. Incremental parameter estimation of kinetic metabolic network models

    Directory of Open Access Journals (Sweden)

    Jia Gengjie

    2012-11-01

    Full Text Available Abstract Background An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE. Most of the existing estimation methods involve finding the global minimum of data fitting residuals over the entire parameter space simultaneously. Unfortunately, the associated computational requirement often becomes prohibitively high due to the large number of parameters and the lack of complete parameter identifiability (i.e. not all parameters can be uniquely identified. Results In this work, an incremental approach was applied to the parameter estimation of ODE models from concentration time profiles. Particularly, the method was developed to address a commonly encountered circumstance in the modeling of metabolic networks, where the number of metabolic fluxes (reaction rates exceeds that of metabolites (chemical species. Here, the minimization of model residuals was performed over a subset of the parameter space that is associated with the degrees of freedom in the dynamic flux estimation from the concentration time-slopes. The efficacy of this method was demonstrated using two generalized mass action (GMA models, where the method significantly outperformed single-step estimations. In addition, an extension of the estimation method to handle missing data is also presented. Conclusions The proposed incremental estimation method is able to tackle the issue on the lack of complete parameter identifiability and to significantly reduce the computational efforts in estimating model parameters, which will facilitate kinetic modeling of genome-scale cellular metabolism in the future.

  18. 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

  19. 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.

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

    OpenAIRE

    Chang Maw-Shang; Wang Feng-Sheng; Wu Wu-Hsiung

    2011-01-01

    Abstract Background Improving the synthesis rate of desired metabolites in metabolic systems is one of the main tasks in metabolic engineering. In the last decade, metabolic engineering approaches based on the mathematical optimization have been used extensively for the analysis and manipulation of metabolic networks. Experimental evidence shows that mutants reflect resilience phenomena against gene alterations. Although researchers have published many studies on the design of metabolic syste...

  1. Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria

    Directory of Open Access Journals (Sweden)

    Hou Jing

    2006-04-01

    Full Text Available Abstract Background Chloroplasts descended from cyanobacteria and have a drastically reduced genome following an endosymbiotic event. Many genes of the ancestral cyanobacterial genome have been transferred to the plant nuclear genome by horizontal gene transfer. However, a selective set of metabolism pathways is maintained in chloroplasts using both chloroplast genome encoded and nuclear genome encoded enzymes. As an organelle specialized for carrying out photosynthesis, does the chloroplast metabolic network have properties adapted for higher efficiency of photosynthesis? We compared metabolic network properties of chloroplasts and prokaryotic photosynthetic organisms, mostly cyanobacteria, based on metabolic maps derived from genome data to identify features of chloroplast network properties that are different from cyanobacteria and to analyze possible functional significance of those features. Results The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. Results showed that the whole metabolic networks in chloroplast and cyanobacteria both possess small-world network properties. Although the number of compounds and reactions in chloroplasts is less than that in cyanobacteria, the chloroplast's metabolic network has longer average path length, a larger diameter, and is Calvin Cycle -centered, indicating an overall less-dense network structure with specific and local high density areas in chloroplasts. Moreover, chloroplast metabolic network exhibits a better modular organization than cyanobacterial ones. Enzymes involved in the same metabolic processes tend to cluster into the same module in chloroplasts. Conclusion In summary, the differences in metabolic network properties may reflect the evolutionary changes during endosymbiosis that led to the improvement of the photosynthesis efficiency in higher plants. Our

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

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    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.

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

    Science.gov (United States)

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

    2016-05-01

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

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

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    Frank Diederichs

    2010-08-01

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

  5. 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.

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

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    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

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

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    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.

  8. 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

  9. Automated refinement and inference of analytical models for metabolic networks

    Science.gov (United States)

    Schmidt, Michael D.; Vallabhajosyula, Ravishankar R.; Jenkins, Jerry W.; Hood, Jonathan E.; Soni, Abhishek S.; Wikswo, John P.; Lipson, Hod

    2011-10-01

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model--suggesting nonlinear terms and structural modifications--or even constructing a new model that agrees with the system's time series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real time.

  10. Automated refinement and inference of analytical models for metabolic networks

    International Nuclear Information System (INIS)

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model-–suggesting nonlinear terms and structural modifications–-or even constructing a new model that agrees with the system's time series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real time

  11. 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.

  12. Feedback control architecture and the bacterial chemotaxis network.

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    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.

  13. 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.

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

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    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

  15. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks

    Science.gov (United States)

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities. PMID:26909353

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

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    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.

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

    Science.gov (United States)

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

    2008-01-01

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

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

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    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.

  19. Metabolic networking in Brunfelsia calycina petals after flower opening.

    Science.gov (United States)

    Bar-Akiva, Ayelet; Ovadia, Rinat; Rogachev, Ilana; Bar-Or, Carmiya; Bar, Einat; Freiman, Zohar; Nissim-Levi, Ada; Gollop, Natan; Lewinsohn, Efraim; Aharoni, Asaph; Weiss, David; Koltai, Hinanit; Oren-Shamir, Michal

    2010-03-01

    Brunfelsia calycina flowers change colour from purple to white due to anthocyanin degradation, parallel to an increase in fragrance and petal size. Here it was tested whether the production of the fragrant benzenoids is dependent on induction of the shikimate pathway, or if they are formed from the anthocyanin degradation products. An extensive characterization of the events taking place in Brunfelsia flowers is presented. Anthocyanin characterization was performed using ultraperfomance liquid chromatography-quadrupole time of flight-tandem mass specrometry (UPLC-QTOF-MS/MS). Volatiles emitted were identified by headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Accumulated proteins were identified by 2D gel electrophoresis. Transcription profiles were characterized by cross-species hybridization of Brunfelsia cDNAs to potato cDNA microarrays. Identification of accumulated metabolites was performed by UPLC-QTOF-MS non-targeted metabolite analysis. The results include characterization of the nine main anthocyanins in Brunfelsia flowers. In addition, 146 up-regulated genes, 19 volatiles, seven proteins, and 17 metabolites that increased during anthocyanin degradation were identified. A multilevel analysis suggests induction of the shikimate pathway. This pathway is the most probable source of the phenolic acids, which in turn are precursors of both the benzenoid and lignin production pathways. The knowledge obtained is valuable for future studies on degradation of anthocyanins, formation of volatiles, and the network of secondary metabolism in Brunfelsia and related species. PMID:20202996

  20. Effective Young's modulus of bacterial and microfibrillated cellulose fibrils in fibrous networks.

    Science.gov (United States)

    Tanpichai, Supachok; Quero, Franck; Nogi, Masaya; Yano, Hiroyuki; Young, Robert J; Lindström, Tom; Sampson, William W; Eichhorn, Stephen J

    2012-05-14

    The deformation micromechanics of bacterial cellulose (BC) and microfibrillated cellulose (MFC) networks have been investigated using Raman spectroscopy. The Raman spectra of both BC and MFC networks exhibit a band initially located at ≈ 1095 cm(-1). We have used the intensity of this band as a function of rotation angle of the specimens to study the cellulose fibril orientation in BC and MFC networks. We have also used the change in this peak's wavenumber position with applied tensile deformation to probe the stress-transfer behavior of these cellulosic materials. The intensity of this Raman band did not change significantly with rotation angle, indicating an in-plane 2D network of fibrils with uniform random orientation; conversely, a highly oriented flax fiber exhibited a marked change in intensity with rotation angle. Experimental data and theoretical analysis shows that the Raman band shift rate arising from deformation of networks under tension is dependent on the angles between the axis of fibrils, the strain axis, the incident laser polarization direction, and the back scattered polarization configurations. From this analysis, the effective moduli of single fibrils of BC and MFC in the networks were estimated to be in the ranges of 79-88 and 29-36 GPa, respectively. It is shown also that for the model to fit the data it is necessary to use a negative Poisson's ratio for MFC networks and BC networks. Discussion of this in-plane "auxetic" behavior is given. PMID:22423896

  1. 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...

  2. Limited Influence of Oxygen on the Evolution of Chemical Diversity in Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Kazuhiro Takemoto

    2013-10-01

    Full Text Available Oxygen is thought to promote species and biomolecule diversity. Previous studies have suggested that oxygen expands metabolic networks by acquiring metabolites with different chemical properties (higher hydrophobicity, for example. However, such conclusions are typically based on biased evaluation, and are therefore non-conclusive. Thus, we re-investigated the effect of oxygen on metabolic evolution using a phylogenetic comparative method and metadata analysis to reduce the bias as much as possible. Notably, we found no difference in metabolic network expansion between aerobes and anaerobes when evaluating phylogenetic relationships. Furthermore, we showed that previous studies have overestimated or underestimated the degrees of differences in the chemical properties (e.g., hydrophobicity between oxic and anoxic metabolites in metabolic networks of unicellular organisms; however, such overestimation was not observed when considering the metabolic networks of multicellular organisms. These findings indicate that the contribution of oxygen to increased chemical diversity in metabolic networks is lower than previously thought; rather, phylogenetic signals and cell-cell communication result in increased chemical diversity. However, this conclusion does not contradict the effect of oxygen on metabolic evolution; instead, it provides a deeper understanding of how oxygen contributes to metabolic evolution despite several limitations in data analysis methods.

  3. 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

  4. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    Science.gov (United States)

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. PMID:26576489

  5. Enzyme allocation problems in kinetic metabolic networks: optimal solutions are elementary flux modes.

    Science.gov (United States)

    Müller, Stefan; Regensburger, Georg; Steuer, Ralf

    2014-04-21

    The survival and proliferation of cells and organisms require a highly coordinated allocation of cellular resources to ensure the efficient synthesis of cellular components. In particular, the total enzymatic capacity for cellular metabolism is limited by finite resources that are shared between all enzymes, such as cytosolic space, energy expenditure for amino-acid synthesis, or micro-nutrients. While extensive work has been done to study constrained optimization problems based only on stoichiometric information, mathematical results that characterize the optimal flux in kinetic metabolic networks are still scarce. Here, we study constrained enzyme allocation problems with general kinetics, using the theory of oriented matroids. We give a rigorous proof for the fact that optimal solutions of the non-linear optimization problem are elementary flux modes. This finding has significant consequences for our understanding of optimality in metabolic networks as well as for the identification of metabolic switches and the computation of optimal flux distributions in kinetic metabolic networks. PMID:24295962

  6. 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

  7. 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.

  8. Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks

    Science.gov (United States)

    Bardoscia, Marco; Marsili, Matteo; Samal, Areejit

    2015-07-01

    System-level properties of metabolic networks may be the direct product of natural selection or arise as a by-product of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov chain Monte Carlo (MCMC) sampling based on flux balance analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks.

  9. Estimation of Ammonia-Nitrogen (Nh3-N Using an Artificial Neural Networks Under Bacterial Technology

    Directory of Open Access Journals (Sweden)

    Gebdang Biangbalbe Ruben

    2016-03-01

    Full Text Available An Artificial Neural Network (ANN was developed to estimate the NH3-N under the bacterial technology in Xuxi River, China. Eight water quality variables such as Dissolved Oxygen (DO, Chemical Oxygen Demand (COD, Total Nitrogen (TN, Total Phosphorus (TP, Suspended Sediment (SS, Temperature, Transparency, and Ammonia Nitrogen (NH3-N were used as inputs for the network. The observed and the predicted NH3-N of the trained networks showed a good fit after the training with a coefficient of correlation (r and a root mean square error (RMSE of 0.91 and 2.61 respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable; TN, Transparency, DO, and TP have proven to be the most effective inputs. Their training’s results showed a coefficient of correlation (r = 0.9295 and a (RMSE = 1.2081 which is more accurate than the prediction with eight inputs variables.

  10. FluxSimulator: An R package to simulate isotopomer distributions in metabolic networks

    OpenAIRE

    Binsl, Thomas W; Mullen, Katharine M.; Ivo H. M. van Stokkum; Jaap Heringa; van Beek, Johannes H G M

    2007-01-01

    The representation of biochemical knowledge in terms of fluxes (transformation rates) in a metabolic network is often a crucial step in the development of new drugs and efficient bioreactors. Mass spectroscopy (MS) and nuclear magnetic resonance spectroscopy (NMRS) in combination with 13C labeled substrates are experimental techniques resulting in data that may be used to quantify fluxes in the metabolic network underlying a process. The massive amount of data generated by spectroscopic exper...

  11. Bidirectionality and Compartmentation of Metabolic Fluxes Are Revealed in the Dynamics of Isotopomer Networks

    OpenAIRE

    Marko Vendelin; Pearu Peterson; Toomas Paalme; Schryer, David W

    2009-01-01

    Isotope labeling is one of the few methods of revealing the in vivo bidirectionality and compartmentalization of metabolic fluxes within metabolic networks. We argue that a shift from steady state to dynamic isotopomer analysis is required to deal with these cellular complexities and provide a review of dynamic studies of compartmentalized energy fluxes in eukaryotic cells including cardiac muscle, plants, and astrocytes. Knowledge of complex metabolic behaviour on a molecular level is prereq...

  12. A Dynamic State Metabolic Journey: From Mass Spectrometry to Network Analysis via Estimation of Kinetic Parameters

    OpenAIRE

    Dhanasekaran, Arockia R.

    2011-01-01

    In the post-genomic era, there is a dire need for tools to perform metabolic analyses that include the structural, functional, and regulatory analysis of metabolic networks. This need arose because of the lag between the two phases of metabolic engineering, namely, synthesis and analysis. Molecular biological tools for synthesis like recombinant DNA technology and genetic engineering have advanced a lot farther than tools for systemic analysis. Consequently, bioinformatics is poised to play ...

  13. 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

  14. 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

  15. 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

  16. Effect of an acute necrotic bacterial gill infection and feed deprivation on the metabolic rate of Atlantic salmon Salmo salar.

    Science.gov (United States)

    Jones, M A; Powell, M D; Becker, J A; Carter, C G

    2007-10-31

    In this study, experiments were conducted to examine the effect of an acute necrotic bacterial gill infection on the metabolic rate (M(O2)) of Atlantic salmon Salmo salar. Fed and unfed Atlantic salmon smolts were exposed to a high concentration (5 x 10(12) CFU ml(-1)) of the bacteria Tenacibaculum maritimum, their routine and maximum metabolic rates (M(O2rout) and M(O2max), respectively) were measured, and relative metabolic scope determined. A significant decrease in metabolic scope was found for both fed and unfed infected groups. Fed infected fish had a mean +/- standard error of the mean (SEM) decrease of 2.21 +/- 0.97 microM O2 g(-1) h(-1), whilst unfed fish a mean +/- SEM decrease of 3.16 +/- 1.29 microM O2 g(-1) h(-1). The decrease in metabolic scope was a result of significantly increased M(O2rout) of both fed and unfed infected salmon. Fed infected fish had a mean +/- SEM increase in M(O2rout) of 1.86 +/- 0.66 microM O2 g(-1) h(-1), whilst unfed infected fish had a mean +/- SEM increase of 2.16 +/- 0.72 microM O2 g(-1) h(-1). Interestingly, all groups maintained M(O2max) regardless of infection status. Increases in M(O2rout) corresponded to a significant increase in blood plasma osmolality. A decrease in metabolic scope has implications for how individuals allocate energy; fish with smaller metabolic scope will have less energy to allocate to functions such as growth, reproduction and immune response, which may adversely affect the efficiency of fish growth. PMID:18159670

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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; Jelsbak, Lars

    2013-01-01

    The genetic basis of bacterial adaptation to a natural environment has been investigated in a highly successful Pseudomonas aeruginosa lineage (DK2) that evolved within the airways of patients with cystic fibrosis (CF) for more than 35 y. During evolution in the CF airways, the DK2 lineage underw...... unexpected phenotypes. Our results suggest that adaptation to a highly selective environment, such as the CF airways, is a highly dynamic and complex process, which involves continuous optimization of existing regulatory networks to match the fluctuations in the environment....

  5. 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

  6. 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...

  7. Bidirectionality and compartmentation of metabolic fluxes are revealed in the dynamics of isotopomer networks.

    Science.gov (United States)

    Schryer, David W; Peterson, Pearu; Paalme, Toomas; Vendelin, Marko

    2009-04-01

    Isotope labeling is one of the few methods of revealing the in vivo bidirectionality and compartmentalization of metabolic fluxes within metabolic networks. We argue that a shift from steady state to dynamic isotopomer analysis is required to deal with these cellular complexities and provide a review of dynamic studies of compartmentalized energy fluxes in eukaryotic cells including cardiac muscle, plants, and astrocytes. Knowledge of complex metabolic behaviour on a molecular level is prerequisite for the intelligent design of genetically modified organisms able to realize their potential of revolutionizing food, energy, and pharmaceutical production. We describe techniques to explore the bidirectionality and compartmentalization of metabolic fluxes using information contained in the isotopic transient, and discuss the integration of kinetic models with MFA. The flux parameters of an example metabolic network were optimized to examine the compartmentalization of metabolites and and the bidirectionality of fluxes in the TCA cycle of Saccharomyces uvarum for steady-state respiratory growth. PMID:19468334

  8. Bidirectionality and Compartmentation of Metabolic Fluxes Are Revealed in the Dynamics of Isotopomer Networks

    Directory of Open Access Journals (Sweden)

    Marko Vendelin

    2009-04-01

    Full Text Available Isotope labeling is one of the few methods of revealing the in vivo bidirectionality and compartmentalization of metabolic fluxes within metabolic networks. We argue that a shift from steady state to dynamic isotopomer analysis is required to deal with these cellular complexities and provide a review of dynamic studies of compartmentalized energy fluxes in eukaryotic cells including cardiac muscle, plants, and astrocytes. Knowledge of complex metabolic behaviour on a molecular level is prerequisite for the intelligent design of genetically modified organisms able to realize their potential of revolutionizing food, energy, and pharmaceutical production. We describe techniques to explore the bidirectionality and compartmentalization of metabolic fluxes using information contained in the isotopic transient, and discuss the integration of kinetic models with MFA. The flux parameters of an example metabolic network were optimized to examine the compartmentalization of metabolites and and the bidirectionality of fluxes in the TCA cycle of Saccharomyces uvarum for steady-state respiratory growth.

  9. 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

  10. 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-...

  11. 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.

  12. 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 ...

  13. 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.

  14. 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

  15. 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.

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

    OpenAIRE

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

    2013-01-01

    Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototro...

  17. 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

  18. 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

    to increase with increasing specific growth rate but at a much lower level than previously reported for Bacillus subtilis. Two futile cycles in the pyruvate metabolism were included in the metabolic network. A substantial flux in the futile cycle involving malic enzyme was estimated, whereas only a...... very small 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...... partly taken up 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....

  19. Deciphering metabolic networks by blue native polyacrylamide gel electrophoresis: A functional proteomic exploration

    Directory of Open Access Journals (Sweden)

    Christopher Auger

    2015-06-01

    Full Text Available Metabolism is the consortium of reactions within a cell which directs a variety of processes including energy synthesis, signalling and the behaviour of a biological system. Metabolic networks, and more specifically the activity of enzymes within them, provide an accurate status of how cellular information is being executed. The performance of these networks and their ability to siphon metabolites in a number of directions may be the difference between a healthy and diseased state. Blue native polyacrylamide gel electrophoresis (BN-PAGE, owing to its simplicity and wide-ranging applications, permits the inspection of these nodules. The separation of proteins and enzyme complexes in their native format enables the exploration of enzymatic activity in metabolic networks via in-gel assays. These are quick, specific, and amenable to further studies. This electrophoretic technology not only enables the visualization of enzymatic efficacy but reveals the crosstalk among enzymes and their interactions with other organellar partners.

  20. 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

  1. 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...

  2. 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...

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

    OpenAIRE

    Karp Peter D; Latendresse Mario

    2011-01-01

    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 search...

  4. 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...

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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....

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

    OpenAIRE

    Petit, Elsa; LaTouf, W. Greg; Coppi, Maddalena V.; Warnick, Thomas A; Currie, Devin; Romashko, Igor; Deshpande, Supriya; Haas, Kelly; Alvelo-Maurosa, Jesús G; Wardman, Colin; 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. W...

  11. Modeling suggests that gene circuit architecture controls phenotypic variability in a bacterial persistence network

    Directory of Open Access Journals (Sweden)

    Koh Rachel S

    2012-05-01

    Full Text Available Abstract Background Bacterial persistence is a non-inherited bet-hedging mechanism where a subpopulation of cells enters a dormant state, allowing those cells to survive environmental stress such as treatment with antibiotics. Persister cells are not mutants; they are formed by natural stochastic variation in gene expression. Understanding how regulatory architecture influences the level of phenotypic variability can help us explain how the frequency of persistence events can be tuned. Results We present a model of the regulatory network controlling the HipBA toxin-antitoxin system from Escherichia coli. Using a biologically realistic model we first determine that the persistence phenotype is not the result of bistability within the network. Next, we develop a stochastic model and show that cells can enter persistence due to random fluctuations in transcription, translation, degradation, and complex formation. We then examine alternative gene circuit architectures for controlling hipBA expression and show that networks with more noise (more persisters and less noise (fewer persisters are straightforward to achieve. Thus, we propose that the gene circuit architecture can be used to tune the frequency of persistence, a trait that can be selected for by evolution. Conclusions We develop deterministic and stochastic models describing how the regulation of toxin and antitoxin expression influences phenotypic variation within a population. Persistence events are the result of stochastic fluctuations in toxin levels that cross a threshold, and their frequency is controlled by the regulatory topology governing gene expression.

  12. A probabilistic neural network approach for modeling and classification of bacterial growth/no-growth data.

    Science.gov (United States)

    Hajmeer, M; Basheer, I

    2002-10-01

    In this paper, we propose to use probabilistic neural networks (PNNs) for classification of bacterial growth/no-growth data and modeling the probability of growth. The PNN approach combines both Bayes theorem of conditional probability and Parzen's method for estimating the probability density functions of the random variables. Unlike other neural network training paradigms, PNNs are characterized by high training speed and their ability to produce confidence levels for their classification decision. As a practical application of the proposed approach, PNNs were investigated for their ability in classification of growth/no-growth state of a pathogenic Escherichia coli R31 in response to temperature and water activity. A comparison with the most frequently used traditional statistical method based on logistic regression and multilayer feedforward artificial neural network (MFANN) trained by error backpropagation was also carried out. The PNN-based models were found to outperform linear and nonlinear logistic regression and MFANN in both the classification accuracy and ease by which PNN-based models are developed. PMID:12133614

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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 transi...

  19. 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.

  20. 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

    time with immunomagnetic beads was not critical for optimal target cell recovery, but samples needed to be washed at least 5¿times during the immunomagnetic separation to reduce unspecific binding of the indigenous soil bacteria to the magnetic beads. Soil absorption of the polyclonal antibody further......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. The...... method was optimized using Pseudomonas putida KT2440¿:¿:Tc+/TOL::gfp inoculated into soil microcosms. Inoculated soil samples were incubated with [3H]-Leu followed by an immunomagnetic separation to recover the target bacteria. Radiolabel incorporated by the target bacteria was then measured. Incubation...

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

    Czech Academy of Sciences Publication Activity Database

    Knoop, H.; Gründel, M.; Zilliges, Y.; Lehmann, R.; Hoffmann, S.; Lockau, W.; Steuer, Ralf

    2013-01-01

    Roč. 9, č. 6 (2013), e1003081-e1003081. ISSN 1553-7358 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : SP STRAIN PCC-6803 * SP ATCC 51142 * photoautotrophic metabolism * anacystis-nidulans * reconstructions * pathway * plants * models * growth Subject RIV: EI - Biotechnology ; Bionics Impact factor: 4.829, year: 2013

  2. 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

  3. 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.

  4. 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

    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 <70 µmol L(-1). Non-ischemic mitochondrial dysfunction was defined...... 5 patients classified as non-ischemic mitochondrial dysfunction, and in 2 patients (3 catheters) classified as ischemia. CONCLUSIONS: In patients with severe community-acquired meningitis, compromised cerebral energy metabolism occurs frequently and was diagnosed in 7 out of 15 cases. A biochemical...

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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. PMID:27219048

  10. 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.

  11. 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

  12. 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

  13. Changes in bacterial community metabolism and composition during the degradation of dissolved organic matter from the jellyfish Aurelia aurita in a Mediterranean coastal lagoon.

    Science.gov (United States)

    Blanchet, Marine; Pringault, Olivier; Bouvy, Marc; Catala, Philippe; Oriol, Louise; Caparros, Jocelyne; Ortega-Retuerta, Eva; Intertaglia, Laurent; West, Nyree; Agis, Martin; Got, Patrice; Joux, Fabien

    2015-09-01

    Spatial increases and temporal shifts in outbreaks of gelatinous plankton have been observed over the past several decades in many estuarine and coastal ecosystems. The effects of these blooms on marine ecosystem functioning and particularly on the dynamics of the heterotrophic bacteria are still unclear. The response of the bacterial community from a Mediterranean coastal lagoon to the addition of dissolved organic matter (DOM) from the jellyfish Aurelia aurita, corresponding to an enrichment of dissolved organic carbon (DOC) by 1.4, was assessed for 22 days in microcosms (8 l). The high bioavailability of this material led to (i) a rapid mineralization of the DOC and dissolved organic nitrogen from the jellyfish and (ii) the accumulation of high concentrations of ammonium and orthophosphate in the water column. DOM from jellyfish greatly stimulated heterotrophic prokaryotic production and respiration rates during the first 2 days; then, these activities showed a continuous decay until reaching those measured in the control microcosms (lagoon water only) at the end of the experiment. Bacterial growth efficiency remained below 20%, indicating that most of the DOM was respired and a minor part was channeled to biomass production. Changes in bacterial diversity were assessed by tag pyrosequencing of partial bacterial 16S rRNA genes, DNA fingerprints, and a cultivation approach. While bacterial diversity in control microcosms showed little changes during the experiment, the addition of DOM from the jellyfish induced a rapid growth of Pseudoalteromonas and Vibrio species that were isolated. After 9 days, the bacterial community was dominated by Bacteroidetes, which appeared more adapted to metabolize high-molecular-weight DOM. At the end of the experiment, the bacterial community shifted toward a higher proportion of Alphaproteobacteria. Resilience of the bacterial community after the addition of DOM from the jellyfish was higher for metabolic functions than diversity

  14. 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...

  15. 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 w...

  16. Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

    Science.gov (United States)

    Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

    2016-01-01

    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 interactions can

  17. 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

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

    Science.gov (United States)

    Robaina-Estévez, Semidán; Nikoloski, Zoran

    2016-01-01

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

  19. MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.

    Science.gov (United States)

    Cottret, Ludovic; Wildridge, David; Vinson, Florence; Barrett, Michael P; Charles, Hubert; Sagot, Marie-France; Jourdan, Fabien

    2010-07-01

    High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr. PMID:20444866

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

    Science.gov (United States)

    Robaina-Estévez, Semidán; Nikoloski, Zoran

    2016-05-01

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

  1. Studying the Relationship between Robustness against Mutations in Metabolic Networks and Lifestyle of Organisms

    Directory of Open Access Journals (Sweden)

    Sayed-Amir Marashi

    2013-01-01

    Full Text Available Robustness is the key feature of biological networks that enables living organisms to keep their homeostatic state and to survive against external and internal perturbations. Variations in environmental conditions or nutrients and intracellular changes such as genetic mutations have the potential to change stability and efficiency of an organism. Structural robustness helps biological systems to choose alternative routes of adaptation to varying conditions. In this study, in order to estimate the structural robustness in metabolic networks we presented a novel flux balance-based approach inspired by bond percolation theory. Fourteen in silico metabolic models were studied in this work in order to examine the possible relationship between the lifestyle of organisms and their metabolic robustness. The results of this study confirm that in organisms which are highly adapted to their environment robustness to mutations may decrease compared to other organisms.

  2. 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.

  3. 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.

  4. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Imam, S; Schauble, S; Brooks, AN; Baliga, NS; Price, ND

    2015-05-05

    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.

  6. 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.

  7. 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

  8. 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

  9. 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. PMID:26701126

  10. Growth states of catalytic reaction networks exhibiting energy metabolism

    Science.gov (United States)

    Kondo, Yohei; Kaneko, Kunihiko

    2011-07-01

    All cells derive nutrition by absorbing some chemical and energy resources from the environment; these resources are used by the cells to reproduce the chemicals within them, which in turn leads to an increase in their volume. In this study we introduce a protocell model exhibiting catalytic reaction dynamics, energy metabolism, and cell growth. Results of extensive simulations of this model show the existence of four phases with regard to the rates of both the influx of resources and cell growth. These phases include an active phase with high influx and high growth rates, an inefficient phase with high influx but low growth rates, a quasistatic phase with low influx and low growth rates, and a death phase with negative growth rate. A mean field model well explains the transition among these phases as bifurcations. The statistical distribution of the active phase is characterized by a power law, and that of the inefficient phase is characterized by a nearly equilibrium distribution. We also discuss the relevance of the results of this study to distinct states in the existing cells.

  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. 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

  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. 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.

  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. 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

  17. 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

  18. 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.

  19. 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 ...

  20. 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

  1. Evaluate the potential toxicity of quantum dots on bacterial metabolism by microcalorimetry

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Qi [College of Chemistry and Life Science, Guangxi Teachers Education University, Nanning 530001 (China); State Key Laboratory of Virology, College of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430072 (China); Huang, Shan, E-mail: huangs@whu.edu.cn [College of Chemistry and Life Science, Guangxi Teachers Education University, Nanning 530001 (China); State Key Laboratory of Virology, College of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430072 (China); Su, Wei [College of Chemistry and Life Science, Guangxi Teachers Education University, Nanning 530001 (China); Li, Peiyuan [College of Pharmacy, Guangxi Traditional Chinese Medical University, Nanning 530001 (China); Liu, Yi, E-mail: prof.liuyi@263.net [State Key Laboratory of Virology, College of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430072 (China)

    2013-01-20

    Highlights: Black-Right-Pointing-Pointer Microcalorimeter was applied for the investigations of the toxic effects of QDs on bacteria. Black-Right-Pointing-Pointer The results indicate that the toxicity of these QDs may come from the toxic Cd{sup 2+} released. Black-Right-Pointing-Pointer The results indicate electrostatic interaction is the main force between bacteria and QDs. Black-Right-Pointing-Pointer The toxicity of these QDs can be varied efficiently by modifying with different ligands. - Abstract: Herein, we evaluated the toxic effects of mercaptoacetic acid (MAA)-CdSe quantum dots (QDs), MAA-CdSe/ZnS QDs and cysteamine (CA)-CdSe/ZnS QDs on the growth of both Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by microcalorimetry. Thermogenic curves of bacteria were recorded and bioeffects of QDs on bacteria were investigated. The results suggested that both MAA-CdSe QDs and MAA-CdSe/ZnS QDs inhibited the E. coli growth but stimulated the S. aureus growth with dose-dependent type. The inhibition or stimulation efficiency of QDs on E. coli or S. aureus growth all decreased dramatically after UV irradiation, which was due to the liberation of more toxic Cd{sup 2+}. In addition, MAA-CdSe/ZnS QDs and CA-CdSe/ZnS QDs affected the growth of E. coli and S. aureus differently. MAA-CdSe/ZnS QDs could not affect the growth of bacteria, while CA-CdSe/ZnS QDs inhibited the bacterial growth dramatically, which resulted from the negative charge on the surface of these bacteria.

  2. Bacterial metabolism of methylated amines and identification of novel methylotrophs in Movile Cave.

    Science.gov (United States)

    Wischer, Daniela; Kumaresan, Deepak; Johnston, Antonia; El Khawand, Myriam; Stephenson, Jason; Hillebrand-Voiculescu, Alexandra M; Chen, Yin; Colin Murrell, J

    2015-01-01

    Movile Cave, Romania, is an unusual underground ecosystem that has been sealed off from the outside world for several million years and is sustained by non-phototrophic carbon fixation. Methane and sulfur-oxidising bacteria are the main primary producers, supporting a complex food web that includes bacteria, fungi and cave-adapted invertebrates. A range of methylotrophic bacteria in Movile Cave grow on one-carbon compounds including methylated amines, which are produced via decomposition of organic-rich microbial mats. The role of methylated amines as a carbon and nitrogen source for bacteria in Movile Cave was investigated using a combination of cultivation studies and DNA stable isotope probing (DNA-SIP) using (13)C-monomethylamine (MMA). Two newly developed primer sets targeting the gene for gamma-glutamylmethylamide synthetase (gmaS), the first enzyme of the recently-discovered indirect MMA-oxidation pathway, were applied in functional gene probing. SIP experiments revealed that the obligate methylotroph Methylotenera mobilis is one of the dominant MMA utilisers in the cave. DNA-SIP experiments also showed that a new facultative methylotroph isolated in this study, Catellibacterium sp. LW-1 is probably one of the most active MMA utilisers in Movile Cave. Methylated amines were also used as a nitrogen source by a wide range of non-methylotrophic bacteria in Movile Cave. PCR-based screening of bacterial isolates suggested that the indirect MMA-oxidation pathway involving GMA and N-methylglutamate is widespread among both methylotrophic and non-methylotrophic MMA utilisers from the cave. PMID:25050523

  3. Evaluate the potential toxicity of quantum dots on bacterial metabolism by microcalorimetry

    International Nuclear Information System (INIS)

    Highlights: ► Microcalorimeter was applied for the investigations of the toxic effects of QDs on bacteria. ► The results indicate that the toxicity of these QDs may come from the toxic Cd2+ released. ► The results indicate electrostatic interaction is the main force between bacteria and QDs. ► The toxicity of these QDs can be varied efficiently by modifying with different ligands. - Abstract: Herein, we evaluated the toxic effects of mercaptoacetic acid (MAA)-CdSe quantum dots (QDs), MAA-CdSe/ZnS QDs and cysteamine (CA)-CdSe/ZnS QDs on the growth of both Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by microcalorimetry. Thermogenic curves of bacteria were recorded and bioeffects of QDs on bacteria were investigated. The results suggested that both MAA-CdSe QDs and MAA-CdSe/ZnS QDs inhibited the E. coli growth but stimulated the S. aureus growth with dose-dependent type. The inhibition or stimulation efficiency of QDs on E. coli or S. aureus growth all decreased dramatically after UV irradiation, which was due to the liberation of more toxic Cd2+. In addition, MAA-CdSe/ZnS QDs and CA-CdSe/ZnS QDs affected the growth of E. coli and S. aureus differently. MAA-CdSe/ZnS QDs could not affect the growth of bacteria, while CA-CdSe/ZnS QDs inhibited the bacterial growth dramatically, which resulted from the negative charge on the surface of these bacteria.

  4. 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

  5. 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.

  6. 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.

  7. Effects of photochemical Transformations of Dissolved Organic Matter on Bacterial Metabolism and Diversity in Three Contrasting Coastal Sites in the Northwestern Mediterranean Sea during Summer

    International Nuclear Information System (INIS)

    The effects of photo transformation of dissolved organic matter (DOM) on bacterial growth, production, respiration, growth efficiency, and diversity were investigated during summer in two lagoons and one oligo trophic coastal water samples from the Northwestern Mediterranean Sea, differing widely in DOM and chromophoric DOM concentrations. Exposure of 0.2μm filtered waters to full sun radiation for 1 d resulted in small changes in optical properties and concentrations of DOM, and no changes in nitrate, nitrite, and phosphate concentrations. After exposure to sunlight or dark (control) treatments, the water samples were inoculated with the original bacterial com community. Photo transformation of DOM had contrasting effects on bacterial production and respiration, depending on the water's origin, resulting in an increase of bacterial growth efficiency for the oligo trophic coastal water sample (120%) and a decrease for the lagoon waters (20 to 40%) relative to that observed in dark treatments. We also observed that bacterial growth on DOM irradiated by full sun resulted in changes in community structure of total and metabolically active bacterial cells for the three locations studied when compared to the bacteria growing on unirradiated DOM, and that changes were mainly caused by photo transformation of DOM by UV radiation for the eutrophic lagoon and the oligo trophic coastal water and by photosynthetically active radiation (PAR) for the meso eutrophic lagoon. These initial results indicate that photo transformation of DOM significantly alters both bacterial metabolism and community structure in surface water for a variety of coastal ecosystems in the Mediterranean Sea. Further studies will be necessary to elucidate a more detailed appreciation of potential temporal and spatial variations of the effects measured. (author)

  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. 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.

  10. Plasticity of metabolic networks and the evolution of C4 photosynthesis

    Science.gov (United States)

    Bogart, Eli; Myers, Chris

    2012-02-01

    Over 50 groups of plants have independently developed a common mechanism (C4 photosynthesis) for increasing the efficiency of photosynthetic carbon dioxide assimilation. Understanding the high degree of evolvability of the C4 system could offer useful guidance for attempts to introduce it artificially to other plants. Previously, the nonlinear relationship between carbon dioxide levels and rates of carbon assimilation and photorespiration has prevented the application of genome-scale metabolic models to the problem of the evolution of the pathway. We apply a nonlinear optimization method to find feasible flux distributions in a plant metabolic model, allowing us to explore the plasticity of the metabolic network and characterize the fitness landscape of the transition from C3 to C4 photosynthesis.

  11. 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.

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

    International Nuclear Information System (INIS)

    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

  13. Bacterial degradation of recalcitrant PAHs: metabolic studies and application to pyrene degradation in a freshwater sediment

    Energy Technology Data Exchange (ETDEWEB)

    Jouanneau, Y.; Demaneche, S.; Meyer, Ch.; Willison, J.C. [CEA-Grenoble, UMR 5092 CNRS-CEA-UJF, 38 - Grenoble (France)

    2005-07-01

    Cost-effective bio-remediation strategies have been proposed to remove toxic chemicals, including polycyclic aromatic hydrocarbons (PAHs), from contaminated sites. However, the efficiency of these strategies is often limited, due to the resistance of certain chemicals to microbial degradation. Our studies deal with the biodegradation of four-ring PAHs using two recently isolated bacteria, Mycobacterium strain 6PY1, which can mineralize pyrene and phenanthrene, and Sphingomonas strain CHY-1, which mineralizes chrysene and various three-ring PAHs. The metabolic pathways for the biodegradation of PAHs have been investigated using GC-MS to identify and assay metabolites. Also, several enzymes involved in PAH catabolism have been identified by a combination of proteomic and genetic approaches. In Mycobacterium 6PY1, two ring-hydroxylating di-oxygenases which catalyze the initial attack of PAHs have been overproduced in E. coli, isolated and characterized. The selectivity of the two enzymes showed marked differences, since one di-oxygenase preferentially oxidized 2- or 3- ring PAHs whereas the other attacked pyrene and 3-ring PAHs exclusively. In Sphingomonas CHY-1, a single di-oxygenase, called PhnI, was found to convert seven PAHs, including chrysene, to the corresponding dihydro-diols. It is the first enzyme to be described which is able to attack the four-ring PAHs chrysene and benz[a]anthracene.. The fate of pyrene was examined in a sediment taken from a freshwater lake of the French Alps. Experiments were carried out in microcosms containing a layer of sediment which was spiked with {sup 14}C-pyrene. Pyrene mineralization was monitored over 61 days by measuring the {sup 14}CO{sub 2} evolved from the microcosms. Some microcosms were planted with young reeds (Phragmites australis), while other were inoculated with Mycobacterium 6PY1. P. australis reeds promoted a significant increase of pyrene degradation, which most likely resulted from a root-mediated increase of

  14. Bacterial degradation of recalcitrant PAHs: metabolic studies and application to pyrene degradation in a freshwater sediment

    International Nuclear Information System (INIS)

    Cost-effective bio-remediation strategies have been proposed to remove toxic chemicals, including polycyclic aromatic hydrocarbons (PAHs), from contaminated sites. However, the efficiency of these strategies is often limited, due to the resistance of certain chemicals to microbial degradation. Our studies deal with the biodegradation of four-ring PAHs using two recently isolated bacteria, Mycobacterium strain 6PY1, which can mineralize pyrene and phenanthrene, and Sphingomonas strain CHY-1, which mineralizes chrysene and various three-ring PAHs. The metabolic pathways for the biodegradation of PAHs have been investigated using GC-MS to identify and assay metabolites. Also, several enzymes involved in PAH catabolism have been identified by a combination of proteomic and genetic approaches. In Mycobacterium 6PY1, two ring-hydroxylating di-oxygenases which catalyze the initial attack of PAHs have been overproduced in E. coli, isolated and characterized. The selectivity of the two enzymes showed marked differences, since one di-oxygenase preferentially oxidized 2- or 3- ring PAHs whereas the other attacked pyrene and 3-ring PAHs exclusively. In Sphingomonas CHY-1, a single di-oxygenase, called PhnI, was found to convert seven PAHs, including chrysene, to the corresponding dihydro-diols. It is the first enzyme to be described which is able to attack the four-ring PAHs chrysene and benz[a]anthracene.. The fate of pyrene was examined in a sediment taken from a freshwater lake of the French Alps. Experiments were carried out in microcosms containing a layer of sediment which was spiked with 14C-pyrene. Pyrene mineralization was monitored over 61 days by measuring the 14CO2 evolved from the microcosms. Some microcosms were planted with young reeds (Phragmites australis), while other were inoculated with Mycobacterium 6PY1. P. australis reeds promoted a significant increase of pyrene degradation, which most likely resulted from a root-mediated increase of oxygen diffusion

  15. Visualization and quantification of archaeal and bacterial metabolically active cells in soil using fluorescence in situ hybridization method

    Science.gov (United States)

    Semenov, Mikhail; Manucharova, Natalia; Stepanov, Alexey

    2015-04-01

    The method of in situ hybridization using fluorescent labeled 16S rRNA-targeted oligonucleotide probes (FISH - fluorescence in situ hybridization) combines identification and quantification of groups of microorganisms at different phylogenetic levels, from domain to species. The FISH method enables to study the soil microbial community in situ, avoiding plating on nutrient media, and allows to identify and quantify living, metabolically active cells of Bacteria and Archaea. The full procedure consists of the following steps: desorption of the cells from the soil particles, fixation of cells, coating a fixed sample on the glass slide, hybridization with the specific probes and, finally, microscopic observation and cell counting. For the FISH analysis of Bacteria and Archaea, the paraformaldehyde-fixed samples were hybridized with Cy3-labeled Archaea-specific probe(Arc915) and 6-carboxyfluorescein (FAM)-labeled Bacteria-specific probe(EUB338). When a molecular probe is incorporated into a cell, it can hybridize solely with a complementary rRNA sequence. The hybridization can be visualized under the fluorescent microscope and counted. The application of FISH will be demonstrated by the abundance of metabolically active cells of Archaea and Bacteria depending on soil properties, depth and land use. The research was carried out at field and natural ecosystems of European part of Russia. Samples were collected within the soil profiles (3-6 horizons) of Chernozem and Kastanozem with distinct land use. Quantification of metabolically active cells in virgin and arable Chernozem revealed that the abundance of Archaea in topsoil of virgin Chernozem was doubled as compared with arable soil, but it leveled off in the deeper horizons. Plowing of Chernozem decreased an amount of archaeal and bacterial active cells simultaneously, however, Bacteria were more resistant to agrogenic impact than Archaea. In Kastanozem, a significant change in the abundance of metabolically active

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

    Science.gov (United States)

    Verma-Gaur, Jiyoti; Qu, Yue; Harrison, Paul F; Lo, Tricia L; Quenault, Tara; Dagley, Michael J; Bellousoff, Matthew; Powell, David R; Beilharz, Traude H; Traven, Ana

    2015-10-01

    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. PMID:26474309

  17. 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.

  18. 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...

  19. 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

  20. Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis

    Directory of Open Access Journals (Sweden)

    Huthmacher Carola

    2010-08-01

    Full Text Available Abstract Background Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed. Results Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predicted life cycle stage specific metabolism with the help of a flux balance approach that integrates gene expression data. Predicted metabolite exchanges between parasite and host were found to be in good accordance with experimental findings when the parasite's metabolic network was embedded into that of its host (erythrocyte. Knock-out simulations identified 307 indispensable metabolic reactions within the parasite. 35 out of 57 experimentally demonstrated essential enzymes were recovered and another 16 enzymes, if additionally the assumption was made that nutrient uptake from the host cell is limited and all reactions catalyzed by the inhibited enzyme are blocked. This predicted set of putative drug targets, shown to be enriched with true targets by a factor of at least 2.75, was further analyzed with respect to homology to human enzymes, functional similarity to therapeutic targets in other organisms and their predicted potency for prophylaxis and disease treatment. Conclusions The results suggest that the set of essential enzymes predicted by our flux balance approach represents a promising starting point for further drug development.

  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. 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

  7. 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.

  8. Network environ perspective for urban metabolism and carbon emissions: a case study of Vienna, Austria.

    Science.gov (United States)

    Chen, Shaoqing; Chen, Bin

    2012-04-17

    Cities are considered major contributors to global warming, where carbon emissions are highly embedded in the overall urban metabolism. To examine urban metabolic processes and emission trajectories we developed a carbon flux model based on Network Environ Analysis (NEA). The mutual interactions and control situation within the urban ecosystem of Vienna were examined, and the system-level properties of the city's carbon metabolism were assessed. Regulatory strategies to minimize carbon emissions were identified through the tracking of the possible pathways that affect these emission trajectories. Our findings suggest that indirect flows have a strong bearing on the mutual and control relationships between urban sectors. The metabolism of a city is considered self-mutualistic and sustainable only when the local and distal environments are embraced. Energy production and construction were found to be two factors with a major impact on carbon emissions, and whose regulation is only effective via ad-hoc pathways. In comparison with the original life-cycle tracking, the application of NEA was better at revealing details from a mechanistic aspect, which is crucial for informed sustainable urban management. PMID:22424579

  9. 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.

  10. 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.

  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. 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 ...

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. iRsp1095: A genome-scale reconstruction of the Rhodobacter sphaeroides metabolic network

    Directory of Open Access Journals (Sweden)

    Gorzalski Alexander S

    2011-07-01

    Full Text Available Abstract Background Rhodobacter sphaeroides is one of the best studied purple non-sulfur photosynthetic bacteria and serves as an excellent model for the study of photosynthesis and the metabolic capabilities of this and related facultative organisms. The ability of R. sphaeroides to produce hydrogen (H2, polyhydroxybutyrate (PHB or other hydrocarbons, as well as its ability to utilize atmospheric carbon dioxide (CO2 as a carbon source under defined conditions, make it an excellent candidate for use in a wide variety of biotechnological applications. A genome-level understanding of its metabolic capabilities should help realize this biotechnological potential. Results Here we present a genome-scale metabolic network model for R. sphaeroides strain 2.4.1, designated iRsp1095, consisting of 1,095 genes, 796 metabolites and 1158 reactions, including R. sphaeroides-specific biomass reactions developed in this study. Constraint-based analysis showed that iRsp1095 agreed well with experimental observations when modeling growth under respiratory and phototrophic conditions. Genes essential for phototrophic growth were predicted by single gene deletion analysis. During pathway-level analyses of R. sphaeroides metabolism, an alternative route for CO2 assimilation was identified. Evaluation of photoheterotrophic H2 production using iRsp1095 indicated that maximal yield would be obtained from growing cells, with this predicted maximum ~50% higher than that observed experimentally from wild type cells. Competing pathways that might prevent the achievement of this theoretical maximum were identified to guide future genetic studies. Conclusions iRsp1095 provides a robust framework for future metabolic engineering efforts to optimize the solar- and nutrient-powered production of biofuels and other valuable products by R. sphaeroides and closely related organisms.

  18. In vivo metabolism of 2,2'-diaminopimelic acid from gram-positive and gram-negative bacterial cells by ruminal microorganisms and ruminants and its use as a marker of bacterial biomass

    International Nuclear Information System (INIS)

    Cells of Bacillus megaterium GW1 and Escherichia coli W7-M5 were specifically radiolabeled with 2,2'-diamino [G-3H] pimelic acid ([3H]DAP) as models of gram-positive and gram-negative bacteria, respectively. Two experiments were conducted to study the in vivo metabolism of 2,2'-diaminopimelic acid (DAP) in sheep. In experiment 1, cells of [3H]DAP-labeled B. megaterium GW1 were infused into the rumen of one sheep and the radiolabel was traced within microbial samples, digesta, and the whole animal. Bacterially bound [3H]DAP was extensively metabolized, primarily (up to 70% after 8 h) via decarboxylation to [3H]lysine by both ruminal protozoa and ruminal bacteria. Recovery of infused radiolabel in urine and feces was low (42% after 96 h) and perhaps indicative of further metabolism by the host animal. In experiment 2, [3H]DAP-labeled B. megaterium GW1 was infused into the rumens of three sheep and [3H]DAP-labeled E. coli W7-W5 was infused into the rumen of another sheep. The radioactivity contents of these mutant bacteria were insufficient to use as tracers, but the metabolism of DAP was monitored in the total, free, and peptidyl forms. Free DAP, as a proportion of total DPA in duodenal digesta, varied from 0 to 9.5%, whereas peptidyl DAP accounted for 8.3 to 99.2%

  19. 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/.

  20. Genome-scale reconstruction and system level investigation of the metabolic network of Methylobacterium extorquens AM1

    Directory of Open Access Journals (Sweden)

    Peyraud Rémi

    2011-11-01

    Full Text Available Abstract Background Methylotrophic microorganisms are playing a key role in biogeochemical processes - especially the global carbon cycle - and have gained interest for biotechnological purposes. Significant progress was made in the recent years in the biochemistry, genetics, genomics, and physiology of methylotrophic bacteria, showing that methylotrophy is much more widespread and versatile than initially assumed. Despite such progress, system-level description of the methylotrophic metabolism is currently lacking, and much remains to understand regarding the network-scale organization and properties of methylotrophy, and how the methylotrophic capacity emerges from this organization, especially in facultative organisms. Results In this work, we report on the integrated, system-level investigation of the metabolic network of the facultative methylotroph Methylobacterium extorquens AM1, a valuable model of methylotrophic bacteria. The genome-scale metabolic network of the bacterium was reconstructed and contains 1139 reactions and 977 metabolites. The sub-network operating upon methylotrophic growth was identified from both in silico and experimental investigations, and 13C-fluxomics was applied to measure the distribution of metabolic fluxes under such conditions. The core metabolism has a highly unusual topology, in which the unique enzymes that catalyse the key steps of C1 assimilation are tightly connected by several, large metabolic cycles (serine cycle, ethylmalonyl-CoA pathway, TCA cycle, anaplerotic processes. The entire set of reactions must operate as a unique process to achieve C1 assimilation, but was shown to be structurally fragile based on network analysis. This observation suggests that in nature a strong pressure of selection must exist to maintain the methylotrophic capability. Nevertheless, substantial substrate cycling could be measured within C2/C3/C4 inter-conversions, indicating that the metabolic network is highly

  1. 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...... identified 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...

  2. Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard O

    2006-03-01

    Full Text Available Abstract Background Extreme pathways (ExPas have been shown to be valuable for studying the functions and capabilities of metabolic networks through characterization of the null space of the stoichiometric matrix (S. Singular value decomposition (SVD of the ExPa matrix P has previously been used to characterize the metabolic regulatory problem in the human red blood cell (hRBC from a network perspective. The calculation of ExPas is NP-hard, and for genome-scale networks the computation of ExPas has proven to be infeasible. Therefore an alternative approach is needed to reveal regulatory properties of steady state solution spaces of genome-scale stoichiometric matrices. Results We show that the SVD of a matrix (W formed of random samples from the steady-state solution space of the hRBC metabolic network gives similar insights into the regulatory properties of the network as was obtained with SVD of P. This new approach has two main advantages. First, it works with a direct representation of the shape of the metabolic solution space without the confounding factor of a non-uniform distribution of the extreme pathways and second, the SVD procedure can be applied to a very large number of samples, such as will be produced from genome-scale networks. Conclusion These results show that we are now in a position to study the network aspects of the regulatory problem in genome-scale metabolic networks through the use of random sampling. Contact: palsson@ucsd.edu

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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

  10. Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

    OpenAIRE

    Wittmann, Christoph; Heinzle, Elmar

    2002-01-01

    A comprehensive approach of metabolite balancing, 13C tracer studies, gas chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and isotopomer modeling was applied for comparative metabolic network analysis of a genealogy of five successive generations of lysine-producing Corynebacterium glutamicum. The five strains examined (C. glutamicum ATCC 13032, 13287, 21253, 21526, and 21543) were previously obtained by random mutagenesis and se...

  11. Use of metabolic inhibitors to estimate protozooplankton grazing and bacterial production in a monomictic eutrophic lake with an anaerobic hypolimnion

    International Nuclear Information System (INIS)

    Inhibitors of eucaryotes (cycloheximide and amphotericin B) and procaryotes (penicillin and chloramphenical) were used to estimate bacterivory and bacterial production in a eutrophic lake. Bacterial production appeared to be slightly greater than protozoan grazing in the aerobic waters of Lake Oglethorpe. Use of penicillin and cycloheximide yielded inconsistent results in anaerobic water and in aerobic water when bacterial production was low. Production measured by inhibiting eucaryotes with cycloheximide did not always agree with [3H]thymidine estimates or differential filtration methods. Laboratory experiments showed that several common freshwater protozoans continued to swim and ingest bacterium-size latex beads in the presence of the eucaryote inhibitor. Penicillin also affected grazing rates of some ciliates. The authors recommended that caution and a corroborating method be used when estimating ecologically important parameters with specific inhibitors

  12. 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...

  13. 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...

  14. 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; Almstrup, Kristian; Petri, Andreas; Barrett, Amy; Travers, Mary; Rayner, Nigel W; Mägi, Reedik; Pettersson, Fredrik H; Broxholme, John; Neville, Matt J; Wills, Quin F; Cheeseman, Jane; Allen, Maxine; Holmes, Chris C; Spector, Tim D; Fleckner, Jan; McCarthy, Mark I; Karpe, Fredrik; Lindgren, Cecilia M; Zondervan, Krina T

    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, ...... interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations....

  15. 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 ...

  16. A network-based approach for resistance transmission in bacterial populations.

    Science.gov (United States)

    Gehring, Ronette; Schumm, Phillip; Youssef, Mina; Scoglio, Caterina

    2010-01-01

    Horizontal transfer of mobile genetic elements (conjugation) is an important mechanism whereby resistance is spread through bacterial populations. The aim of our work is to develop a mathematical model that quantitatively describes this process, and to use this model to optimize antimicrobial dosage regimens to minimize resistance development. The bacterial population is conceptualized as a compartmental mathematical model to describe changes in susceptible, resistant, and transconjugant bacteria over time. This model is combined with a compartmental pharmacokinetic model to explore the effect of different plasma drug concentration profiles. An agent-based simulation tool is used to account for resistance transfer occurring when two bacteria are adjacent or in close proximity. In addition, a non-linear programming optimal control problem is introduced to minimize bacterial populations as well as the drug dose. Simulation and optimization results suggest that the rapid death of susceptible individuals in the population is pivotal in minimizing the number of transconjugants in a population. This supports the use of potent antimicrobials that rapidly kill susceptible individuals and development of dosage regimens that maintain effective antimicrobial drug concentrations for as long as needed to kill off the susceptible population. Suggestions are made for experiments to test the hypotheses generated by these simulations. PMID:19747924

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Dysregulated expression of arginine metabolic enzymes in human intestinal tissues of necrotizing enterocolitis and response of CaCO2 cells to bacterial components.

    Science.gov (United States)

    Leung, Kam Tong; Chan, Kathy Yuen Yee; Ma, Terence Ping Yuen; Yu, Jasmine Wai Sum; Tong, Joanna Hung Man; Tam, Yuk Him; Cheung, Hon Ming; To, Ka Fai; Lam, Hugh Simon; Lee, Kim Hung; Li, Karen; Ng, Pak Cheung

    2016-03-01

    The small intestine is the exclusive site of arginine synthesis in neonates. Low levels of circulating arginine have been associated with the occurrence of necrotizing enterocolitis (NEC) but the mechanism of arginine dysregulation has not been fully elucidated. We aimed to investigate (i) expressional changes of arginine synthesizing and catabolic enzymes in human intestinal tissues of NEC, spontaneous intestinal perforation (SIP) and noninflammatory surgical conditions (Surg-CTL) and to investigate the (ii) mechanisms of arginine dysregulation and enterocyte proliferation upon stimulation by bacterial components, arginine depletion, ARG1 overexpression and nitric oxide (NO) supplementation. Our results showed that expressions of arginine synthesizing enzymes ALDH18A1, ASL, ASS1, CPS1, GLS, OAT and PRODH were significantly decreased in NEC compared with Surg-CTL or SIP tissues. Catabolic enzyme ARG1 was increased (>100-fold) in NEC tissues and histologically demonstrated to be expressed by infiltrating neutrophils. No change in arginine metabolic enzymes was observed between SIP and Surg-CTL tissues. In CaCO2 cells, arginine metabolic enzymes were differentially dysregulated by lipopolysaccharide or lipoteichoic acid. Depletion of arginine reduced cell proliferation and this phenomenon could be partially rescued by NO. Overexpression of ARG1 also reduced enterocyte proliferation. We provided the first expressional profile of arginine metabolic enzymes at the tissue level of NEC. Our findings suggested that arginine homeostasis was severely disturbed and could be triggered by inflammatory responses of enterocytes and infiltrating neutrophils as well as bacterial components. Such reactions could reduce arginine and NO, resulting in mucosal damage. The benefit of arginine supplementation for NEC prophylaxis merits further clinical evaluation. PMID:26895666

  6. 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.

    Howard EC, Henriksen JR, Buchan A, Reisch CR, Burgmann H, Welsh R, Ye W, Gonzalez JM, Mace K, Joye SB, Kiene RP, Whitman WB, Moran MA (2006) Bacterial taxa that limit sulfur flux from the ocean. Science 314(5799): 649–652 Howard EC, Sun S, Biers EJ...

  7. A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

    Science.gov (United States)

    Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

  8. 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.

  9. 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...

  10. 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...

  11. 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 ...

  12. Comparative Analysis of the Effects of Two Probiotic Bacterial Strains on Metabolism and Innate Immunity in the RAW 264.7 Murine Macrophage Cell Line.

    Science.gov (United States)

    Pradhan, Biswaranjan; Guha, Dipanjan; Ray, Pratikshya; Das, Debashmita; Aich, Palok

    2016-06-01

    Probiotic and potential probiotic bacterial strains are routinely prescribed and used as supplementary therapy for a variety infectious diseases, including enteric disorders among a wide range of individuals. While there are an increasing number of studies defining the possible mechanisms of probiotic activity, a great deal remains unknown regarding the diverse modes of action attributed to these therapeutic agents. More precise information is required to support the appropriate application of probiotics. To address this objective, we selected two probiotics strains, Lactobacillus acidophilus MTCC-10307 (LA) and Bacillus clausii MTCC-8326 (BC) that are frequently prescribed for the treatment of intestinal disorders and investigated their effects on the RAW 264.7 murine macrophage cell line. Our results reveal that LA and BC are potent activators of both metabolic activity and innate immune responses in these cells. We also observed that LA and BC possessed similar activity in preventing infection simulated in vitro in murine macrophages by Salmonella typhimurium serovar enterica. PMID:27038159

  13. Complex metabolic network of 1,3-propanediol transport mechanisms and its system identification via biological robustness.

    Science.gov (United States)

    Guo, Yanjie; Feng, Enmin; Wang, Lei; Xiu, Zhilong

    2014-04-01

    The bioconversion of glycerol to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae) can be characterized by an intricate metabolic network of interactions among biochemical fluxes, metabolic compounds, key enzymes and genetic regulation. Since there are some uncertain factors in the fermentation, especially the transport mechanisms of 1,3-PD across cell membrane, the metabolic network contains multiple possible metabolic systems. Considering the genetic regulation of dha regulon and inhibition of 3-hydroxypropionaldehyde to the growth of cells, we establish a 14-dimensional nonlinear hybrid dynamical system aiming to determine the most possible metabolic system and the corresponding optimal parameter. The existence, uniqueness and continuity of solutions are discussed. Taking the robustness index of the intracellular substances together as a performance index, a system identification model is proposed, in which 1,395 continuous variables and 90 discrete variables are involved. The identification problem is decomposed into two subproblems and a parallel particle swarm optimization procedure is constructed to solve them. Numerical results show that it is most possible that 1,3-PD passes the cell membrane by active transport coupled with passive diffusion. PMID:24002752

  14. 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

  15. Automatic reconstruction of a bacterial regulatory network using Natural Language Processing

    OpenAIRE

    Collado-Vides Julio; Martínez-Flores Irma; Salgado Heladia; Rodríguez-Penagos Carlos

    2007-01-01

    Abstract Background Manual curation of biological databases, an expensive and labor-intensive process, is essential for high quality integrated data. In this paper we report the implementation of a state-of-the-art Natural Language Processing system that creates computer-readable networks of regulatory interactions directly from different collections of abstracts and full-text papers. Our major aim is to understand how automatic annotation using Text-Mining techniques can complement manual cu...

  16. Intestinal concentrations of free and encapsulated dietary medium-chain fatty acids and effects on gastric microbial ecology and bacterial metabolic products in the digestive tract of piglets.

    Science.gov (United States)

    Zentek, Jürgen; Buchheit-Renko, Susanne; Männer, Klaus; Pieper, Robert; Vahjen, Wilfried

    2012-02-01

    The influence of low dietary levels of free and encapsulated medium-chain fatty acids on their concentrations in the digesta, the gastric microbial ecology and bacterial metabolic products in the gastrointestinal tract (GIT) in weaned piglets was studied. Starting after weaning, 36 piglets were fed a diet without (Control) or with medium-chain fatty acids uncoated (MCFA) or coated with vegetable fat and lecithin (MCFAc). After 4 weeks, the animals were killed, and digesta from the stomach and different sections of the GIT were collected. The concentrations of caprylic (p Lactobacillus johnsonii (p Lactobacillus amylovorus (p = 0.001) in gastric contents. A similar trend was seen with diet MCFA. Relative concentrations of short-chain fatty acids were characterised by lower propionic acid levels (p = 0.045), numerically (p < 0.1) higher acetic, lower n-butyric and i-valeric acid concentrations in the small intestine. Lactic acid concentrations were not significantly changed in the GIT, but ammonia concentrations increased (p < 0.001) in the distal small intestine in the MCFA and MCFAc groups. In conclusion, medium-chain fatty acids affected microbial ecology parameters in the gastric contents and bacterial metabolites in the small intestine. At low dietary levels, medium-chain fatty acids may be regarded as modulators of the gastric microbiota in weaned piglets. PMID:22397093

  17. 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

    Carotenoid production by micro organisms, as opposed to chemical synthesis, could fulfill an ever-increasing demand for 'all natural' products. The yeast Phaffia rhodozyma has received considerable attention because it produces the red pigment astaxanthin, commonly used as an animal feed supplement....... In order to have a better understanding of its metabolism, labeling experiments with [1-C-13]glucose were conducted with the wildtype strain (CBS5905T) and a hyper-producing carotenoid strain (J4-3) in order to determine their metabolic network structure and estimate intracellular fluxes. Amino acid...

  18. 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)

  19. Glucose Metabolism in Legionella pneumophila: Dependence on the Entner-Doudoroff Pathway and Connection with Intracellular Bacterial Growth† ▿

    OpenAIRE

    Harada, Eiji; Iida, Ken-ichiro; Shiota, Susumu; Nakayama, Hiroaki; Yoshida, Shin-ichi

    2010-01-01

    Glucose metabolism in Legionella pneumophila was studied by focusing on the Entner-Doudoroff (ED) pathway with a combined genetic and biochemical approach. The bacterium utilized exogenous glucose for synthesis of acid-insoluble cell components but manifested no discernible increase in the growth rate. Assays with permeabilized cell preparations revealed the activities of three enzymes involved in the pathway, i.e., glucokinase, phosphogluconate dehydratase, and 2-dehydro-3-deoxy-phosphogluco...

  20. 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

  1. 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

  2. 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 ...

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

    OpenAIRE

    Verma-Gaur, Jiyoti; Qu, Yue; Harrison, Paul F.; Lo, Tricia L.; Quenault, Tara; Dagley, Michael J.; Bellousoff, Matthew; Powell, David R; Beilharz, Traude H.; Traven, Ana

    2015-01-01

    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 change...

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

    Directory of Open Access Journals (Sweden)

    Priyanka Patel

    2016-03-01

    Full Text Available 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.

  5. 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

  6. 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.

  7. 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

  8. Modeling the bacterial flagellum by an elastic network of rigid bodies

    Science.gov (United States)

    Speier, C.; Vogel, R.; Stark, H.

    2011-08-01

    Bacteria such as Escherichia coli propel themselves by rotating a bundle of helical filaments, each driven by a rotary motor embedded in the cell membrane. Each filament is an assembly of thousands of copies of the protein flagellin which assumes two different states. We model the filament by an elastic network of rigid bodies that form bonds with one another according to a scheme suggested by Namba and Vondervistz (1997 Q. Rev. Biophys. 30 1-65) and add additional binding sites at the inner part of the rigid body. Our model reproduces the helical parameters of the 12 possible polymorphic configurations very well. We demonstrate that its energetical ground state corresponds to the normal helical form, usually observed in nature, only when inner and outer binding sites of the rigid body have a large axial displacement. This finding correlates directly to the elongated shape of the flagellin molecule. An Ising Hamiltonian in our model directly addresses the two states of the flagellin protein. It contains an external field that represents external parameters which allow us to alter the ground state of the filament.

  9. 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

  10. Possible mechanism for preterm labor associated with bacterial infection. I. Stimulation of phosphoinositide metabolism by endotoxin in endometrial fibroblasts

    International Nuclear Information System (INIS)

    Growing evidence suggests an association between intra-amniotic infection and premature initiation of parturition. We recently demonstrated that some factor(s) including endotoxin produced by the organism stimulates endogenous phospholipase A2 resulting in liberation of arachidonic acid and prostaglandin formation. The studies presented in this report were designated to evaluate the mechanism for endotoxin to stimulate phospholipase A2 using human endometrial fibroblasts. Exposure of the fibroblasts to endotoxin from Escherichia coli in the presence of [32P] phosphate increased 32P-labeling of phosphatidic acid (PA) and phosphatidyl-inositol (PI) in a dose-dependent and a time-dependent manners. The PA labeling occurred without a measurable lag time. These findings demonstrate that the endotoxin stimulates phosphoinositide metabolism in human endometrial fibroblasts by a receptor-mediated mechanism. Membrane phosphoinositide turnover stimulated by endotoxin results in cytosolic Ca2+ increment, liberation of arachidonic acid, which may be involved in the initiation of parturition

  11. Linked gene networks involved in nitrogen and carbon metabolism and levels of water-soluble carbohydrate accumulation in wheat stems.

    Science.gov (United States)

    McIntyre, C Lynne; Casu, Rosanne E; Rattey, Allan; Dreccer, M Fernanda; Kam, Jason W; van Herwaarden, Anthony F; Shorter, Ray; Xue, Gang Ping

    2011-12-01

    High levels of water-soluble carbohydrates (WSC) provide an important source of stored assimilate for grain filling in wheat. To better understand the interaction between carbohydrate metabolism and other metabolic processes associated with the WSC trait, a genome-wide expression analysis was performed using eight field-grown lines from the high and low phenotypic tails of a wheat population segregating for WSC and the Affymetrix wheat genome array. The 259 differentially expressed probe sets could be assigned to 26 functional category bins, as defined using MapMan software. There were major differences in the categories to which the differentially expressed probe sets were assigned; for example, probe sets upregulated in high relative to low WSC lines were assigned to category bins such as amino acid metabolism, protein degradation and transport and to be involved in starch synthesis-related processes (carbohydrate metabolism bin), whereas downregulated probe sets were assigned to cell wall-related bins, amino acid synthesis and stress and were involved in sucrose breakdown. Using the set of differentially expressed genes as input, chemical-protein network analyses demonstrated a linkage between starch and N metabolism via pyridoxal phosphate. Twelve C and N metabolism-related genes were selected for analysis of their expression response to varying N and water treatments in the field in the four high and four low WSC progeny lines; the two nitrogen/amino acid metabolism genes demonstrated a consistent negative association between their level of expression and level of WSC. Our results suggest that the assimilation of nitrogen into amino acids is an important factor that influences the levels of WSC in the stems of field-grown wheat. PMID:21789636

  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. 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

    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...

  14. 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...

  15. 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.

  16. 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.

  17. Possible mechanism for preterm labor associated with bacterial infection. I. Stimulation of phosphoinositide metabolism by endotoxin in endometrial fibroblasts

    Energy Technology Data Exchange (ETDEWEB)

    Khan, A.A.; Imai, A.; Tamaya, T. (Gifu Univ. School of Medicine (Japan))

    1990-07-01

    Growing evidence suggests an association between intra-amniotic infection and premature initiation of parturition. We recently demonstrated that some factor(s) including endotoxin produced by the organism stimulates endogenous phospholipase A2 resulting in liberation of arachidonic acid and prostaglandin formation. The studies presented in this report were designated to evaluate the mechanism for endotoxin to stimulate phospholipase A2 using human endometrial fibroblasts. Exposure of the fibroblasts to endotoxin from Escherichia coli in the presence of ({sup 32}P) phosphate increased {sup 32}P-labeling of phosphatidic acid (PA) and phosphatidyl-inositol (PI) in a dose-dependent and a time-dependent manners. The PA labeling occurred without a measurable lag time. These findings demonstrate that the endotoxin stimulates phosphoinositide metabolism in human endometrial fibroblasts by a receptor-mediated mechanism. Membrane phosphoinositide turnover stimulated by endotoxin results in cytosolic Ca{sup 2+} increment, liberation of arachidonic acid, which may be involved in the initiation of parturition.

  18. 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

  19. 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

  20. Enrichment of carotenoids in flaxseed (Linum usitatissimum) by metabolic engineering with introduction of bacterial phytoene synthase gene crtB.

    Science.gov (United States)

    Fujisawa, Masaki; Watanabe, Mio; Choi, Song-Kang; Teramoto, Maki; Ohyama, Kanji; Misawa, Norihiko

    2008-06-01

    Linseed flax (Linum usitatissimum L.) is an industrially important oil crop, which includes large amounts of alpha-linolenic acid (18:3) and lignan in its seed oil. We report here the metabolic engineering of flax plants to increase carotenoid amount in seeds. Agrobacterium-mediated transformation of flax was performed to express the phytoene synthase gene (crtB) derived from the soil bacterium Pantoea ananatis (formerly called Erwinia uredovora 20D3) under the control of the cauliflower mosaic virus (CaMV) 35S constitutive promoter or the Arabidopsis thaliana fatty acid elongase 1 gene (FAE1) seed-specific promoter. As a result, eight transgenic flax plants were generated. They formed orange seeds (embryos), in which phytoene, alpha-carotene, and beta-carotene were newly accumulated in addition to increased amounts of lutein, while untransformed flax plants formed light-yellow seeds, in which only lutein was detected. Interestingly, despite the control of the CaMV 35S promoter, the expression of crtB was not observed in the leaves but in the seeds in the transgenic flax plants. Total carotenoid amounts in these seeds were 65.4-156.3 microg/g fresh weight, which corresponded to 7.8- to 18.6-fold increase, compared with those of untransformed controls. These results suggest that the flux of phytoene synthesis from geranylgeranyl diphosphate was first promoted by the expressed crtB gene product (CrtB), and then phytoene was consecutively decomposed to the downstream metabolites alpha-carotene, beta-carotene, and lutein, as catalyzed by endogenous carotenoid biosynthetic enzymes in seeds. The transgenic flaxseeds enriched with the carotenoids could be valuable as nutritional sources for human health. PMID:18640603

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Hyun-Seob Song

    2015-03-01

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

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

    Science.gov (United States)

    Weston, David J; Pelletier, Dale A; Morrell-Falvey, Jennifer L; Tschaplinski, Timothy J; Jawdy, Sara S; Lu, Tse-Yuan; Allen, Sara M; Melton, Sarah J; Martin, Madhavi Z; Schadt, Christopher W; Karve, Abhijit A; Chen, Jin-Gui; Yang, Xiaohan; Doktycz, Mitchel J; Tuskan, Gerald A

    2012-06-01

    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. PMID:22375709

  4. 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...

  5. 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

  6. 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.

  7. 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.

  8. Bacterial gastroenteritis

    Science.gov (United States)

    Infectious diarrhea - bacterial gastroenteritis; Acute gastroenteritis; Gastroenteritis - bacterial ... Bacterial gastroenteritis can affect 1 person or a group of people who all ate the same food. It is ...

  9. [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

  10. 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.

  11. 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.

  12. 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

  13. Reconstruction of the genome-scale metabolic network of Kluyveromyces lactis

    OpenAIRE

    Dias, Oscar

    2013-01-01

    System Biology proposes to study biological components, as well as the interactions between them, to understand and predict systems’ behaviour through the use of mathematical models. Under this scope, Genome-Scale Metabolic Models (GSMMs) can be regarded as mathematical representations of the intrinsic metabolic capabilities of a given organism, encoded in its genome, and can be used in a variety of applications like predicting the phenotypical behaviour of a given organism in ...

  14. 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...

  15. 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...

  16. 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...

  17. 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

  18. 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.

  19. Reconstruction and analysis of a genome-scale metabolic network of Corynebacterium glutamicum S9114.

    Science.gov (United States)

    Mei, Jie; Xu, Nan; Ye, Chao; Liu, Liming; Wu, Jianrong

    2016-01-10

    Corynebacterium glutamicum S9114 is commonly used for industrial glutamate production. Therefore, a comprehensive understanding of the physiological and metabolic characteristics of C. glutamicum is important for developing its potential for industrial production. A genome-scale metabolic model, iJM658, was reconstructed based on genome annotation and literature mining. The model consists of 658 genes, 984 metabolites and 1065 reactions. The model quantitatively predicted C. glutamicum growth on different carbon and nitrogen sources and determined 129 genes to be essential for cell growth. The iJM658 model predicted that C. glutamicum had two glutamate biosynthesis pathways and lacked eight key genes in biotin synthesis. Robustness analysis indicated a relative low oxygen level (1.21mmol/gDW/h) would improve glutamate production rate. Potential metabolic engineering targets for improving γ-aminobutyrate and isoleucine production rate were predicted by in silico deletion or overexpression of some genes. The iJM658 model is a useful tool for understanding and optimizing the metabolism of C. glutamicum and a valuable resource for future metabolic and physiological research. PMID:26392034

  20. 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.

  1. 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

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

    DEFF Research Database (Denmark)

    Brochado, Ana Rita

    A holistic view of the cell is fundamental for gaining insights into genotype to phenotype relationships. Systems Biology is a discipline within Biology, which uses such holistic approach by focusing on the development and application of tools for studying the structure and dynamics of cellular...... processes. Metabolism is an extensively studied and characterised subcellular system, for which several modeling approaches have been proposed over the last 20 years. Nowadays, stoichiometric modeling of metabolism is done at the genome scale and it has diverse applications, many of them for helping at...

  3. 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.

  4. 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

  5. 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. PMID:20080693

  6. A disease-specific metabolic brain network associated with corticobasal degeneration

    OpenAIRE

    Niethammer, Martin; Tang, Chris C.; Feigin, Andrew; Allen, Patricia J.; Heinen, Lisette; Hellwig, Sabine; Amtage, Florian; Hanspal, Era; Vonsattel, Jean Paul; Poston, Kathleen L.; Meyer, Philipp T.; Leenders, Klaus L; Eidelberg, David

    2014-01-01

    Niethammer et al. aim to improve the differential diagnosis of corticobasal degeneration by identifying a metabolic covariance pattern associated with the disorder, and validating it in independent patient and control populations. They develop an automated logistic algorithm to discriminate between corticobasal degeneration and related syndromes on a prospective single-case basis.

  7. 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

    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...

  8. Enzyme allocation problems in kinetic metabolic networks: Optimal solutions are elementary flux modes

    Czech Academy of Sciences Publication Activity Database

    Müller, Stefan; Regensburger, G.; Steuer, Ralf

    2014-01-01

    Roč. 347, APR 2014 (2014), s. 182-190. ISSN 0022-5193 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : metabolic optimization * enzyme kinetics * oriented matroid * elementary vector * conformal sum Subject RIV: EI - Biotechnology ; Bionics Impact factor: 2.116, year: 2014

  9. 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

  10. 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

  11. Activation of a metabolic gene regulatory network downstream of mTOR complex 1

    OpenAIRE

    Düvel, Katrin; Yecies, Jessica L.; Menon, Suchithra; Raman, Pichai; Lipovsky, Alex I.; Souza, Amanda L.; Triantafellow, Ellen; Ma, Qicheng; Gorski, Regina; Cleaver, Stephen; Heiden, Matthew G. Vander; MacKeigan, Jeffrey P.; Finan, Peter M.; Clish, Clary B; Murphy, Leon O.

    2010-01-01

    Aberrant activation of the mammalian target of rapamycin complex 1 (mTORC1) is a common molecular event in a variety of pathological settings, including genetic tumor syndromes, cancer, and obesity. However, the cell intrinsic consequences of mTORC1 activation remain poorly defined. Through a combination of unbiased genomic, metabolomic, and bioinformatic approaches, we demonstrate that mTORC1 activation is sufficient to stimulate specific metabolic pathways, including glycolysis, the oxidati...

  12. 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...

  13. Conservation of lipid metabolic gene transcriptional regulatory networks in fish and mammals.

    Science.gov (United States)

    Carmona-Antoñanzas, Greta; Tocher, Douglas R; Martinez-Rubio, Laura; Leaver, Michael J

    2014-01-15

    Lipid content and composition in aquafeeds have changed rapidly as a result of the recent drive to replace ecologically limited marine ingredients, fishmeal and fish oil (FO). Terrestrial plant products are the most economic and sustainable alternative; however, plant meals and oils are devoid of physiologically important cholesterol and long-chain polyunsaturated fatty acids (LC-PUFA), eicosapentaenoic (EPA), docosahexaenoic (DHA) and arachidonic (ARA) acids. Although replacement of dietary FO with vegetable oil (VO) has little effect on growth in Atlantic salmon (Salmo salar), several studies have shown major effects on the activity and expression of genes involved in lipid homeostasis. In vertebrates, sterols and LC-PUFA play crucial roles in lipid metabolism by direct interaction with lipid-sensing transcription factors (TFs) and consequent regulation of target genes. The primary aim of the present study was to elucidate the role of key TFs in the transcriptional regulation of lipid metabolism in fish by transfection and overexpression of TFs. The results show that the expression of genes of LC-PUFA biosynthesis (elovl and fads2) and cholesterol metabolism (abca1) are regulated by Lxr and Srebp TFs in salmon, indicating highly conserved regulatory mechanism across vertebrates. In addition, srebp1 and srebp2 mRNA respond to replacement of dietary FO with VO. Thus, Atlantic salmon adjust lipid metabolism in response to dietary lipid composition through the transcriptional regulation of gene expression. It may be possible to further increase efficient and effective use of sustainable alternatives to marine products in aquaculture by considering these important molecular interactions when formulating diets. PMID:24177230

  14. Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

    Science.gov (United States)

    He, Fei; Murabito, Ettore; Westerhoff, Hans V

    2016-04-01

    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 throughin silicotheoretical studies with the aim to guide and complement furtherin vitroandin vivoexperimental efforts. Clearly, what counts is the resultin vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. PMID:27075000

  15. 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

  16. 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.

  17. Modules in the metabolic network of E.coli with regulatory interactions

    Czech Academy of Sciences Publication Activity Database

    Geryk, J.; Slanina, František

    2013-01-01

    Roč. 8, č. 2 (2013), s. 188-202. ISSN 1748-5673 R&D Projects: GA MŠk OC09078 Institutional support: RVO:68378271 Keywords : networks * modularity * biophysics Subject RIV: BO - Biophysics Impact factor: 0.655, year: 2013 http://www.inderscience.com/info/inarticle.php?artid=55500

  18. 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

  19. Regulatory and metabolic networks for the adaptation of Pseudomonas aeruginosa biofilms to urinary tract-like conditions.

    Directory of Open Access Journals (Sweden)

    Petra Tielen

    Full Text Available Biofilms of the Gram-negative bacterium Pseudomonas aeruginosa are one of the major causes of complicated urinary tract infections with detrimental outcome. To develop novel therapeutic strategies the molecular adaption strategies of P. aeruginosa biofilms to the conditions of the urinary tract were investigated thoroughly at the systems level using transcriptome, proteome, metabolome and enzyme activity analyses. For this purpose biofilms were grown anaerobically in artificial urine medium (AUM. Obtained data were integrated bioinformatically into gene regulatory and metabolic networks. The dominating response at the transcriptome and proteome level was the adaptation to iron limitation via the broad Fur regulon including 19 sigma factors and up to 80 regulated target genes or operons. In agreement, reduction of the iron cofactor-dependent nitrate respiratory metabolism was detected. An adaptation of the central metabolism to lactate, citrate and amino acid as carbon sources with the induction of the glyoxylate bypass was observed, while other components of AUM like urea and creatinine were not used. Amino acid utilization pathways were found induced, while fatty acid biosynthesis was reduced. The high amounts of phosphate found in AUM explain the reduction of phosphate assimilation systems. Increased quorum sensing activity with the parallel reduction of chemotaxis and flagellum assembly underscored the importance of the biofilm life style. However, reduced formation of the extracellular polysaccharide alginate, typical for P. aeruginosa biofilms in lungs, indicated a different biofilm type for urinary tract infections. Furthermore, the obtained quorum sensing response results in an increased production of virulence factors like the extracellular lipase LipA and protease LasB and AprA explaining the harmful cause of these infections.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

    -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-analysis of...

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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...

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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

  15. Sexual Behavior and Network Characteristics and Their Association with Bacterial Sexually Transmitted Infections among Black Men Who Have Sex with Men in the United States.

    Directory of Open Access Journals (Sweden)

    Hyman M Scott

    Full Text Available Black men who have sex with men (MSM have a high prevalence of bacterial sexually transmitted infections (STIs, and individual risk behavior does not fully explain the higher prevalence when compared with other MSM. Using the social-ecological framework, we evaluated individual, social and sexual network, and structural factors and their association with prevalent STIs among Black MSM.The HIV Prevention Trials Network 061 was a multi-site cohort study designed to determine the feasibility and acceptability of a multi-component intervention for Black MSM in six US cities. Baseline assessments included demographics, risk behavior, and social and sexual network questions collected information about the size, nature and connectedness of their sexual network. Logistic regression was used to estimate the odds of having any prevalent sexually transmitted infection (gonorrhea, chlamydia, or syphilis.A total of 1,553 Black MSM were enrolled in this study. In multivariate analysis, older age (aOR = 0.57; 95% CI 0.49-0.66, p<0.001 was associated with a lower odds of having a prevalent STI. Compared with reporting one male sexual partner, having 2-3 partners (aOR = 1.74; 95% CI 1.08-2.81, p<0.024 or more than 4 partners (aOR = 2.29; 95% CI 1.43-3.66, p<0.001 was associated with prevalent STIs. Having both Black and non-Black sexual partners (aOR = 0.67; 95% CI 0.45-0.99, p = 0.042 was the only sexual network factor associated with prevalent STIs.Age and the number and racial composition of sexual partners were associated with prevalent STIs among Black MSM, while other sexual network factors were not. Further studies are needed to evaluate the effects of the individual, network, and structural factors on prevalent STIs among Black MSM to inform combination interventions to reduce STIs among these men.

  16. Sexual Behavior and Network Characteristics and Their Association with Bacterial Sexually Transmitted Infections among Black Men Who Have Sex with Men in the United States

    Science.gov (United States)

    Scott, Hyman M.; Irvin, Risha; Wilton, Leo; Van Tieu, Hong; Watson, Chauncey; Magnus, Manya; Chen, Iris; Gaydos, Charlotte; Hussen, Sophia A.; Mannheimer, Sharon; Mayer, Kenneth; Hessol, Nancy A.; Buchbinder, Susan

    2015-01-01

    Background Black men who have sex with men (MSM) have a high prevalence of bacterial sexually transmitted infections (STIs), and individual risk behavior does not fully explain the higher prevalence when compared with other MSM. Using the social-ecological framework, we evaluated individual, social and sexual network, and structural factors and their association with prevalent STIs among Black MSM. Methods The HIV Prevention Trials Network 061 was a multi-site cohort study designed to determine the feasibility and acceptability of a multi-component intervention for Black MSM in six US cities. Baseline assessments included demographics, risk behavior, and social and sexual network questions collected information about the size, nature and connectedness of their sexual network. Logistic regression was used to estimate the odds of having any prevalent sexually transmitted infection (gonorrhea, chlamydia, or syphilis). Results A total of 1,553 Black MSM were enrolled in this study. In multivariate analysis, older age (aOR = 0.57; 95% CI 0.49–0.66, p<0.001) was associated with a lower odds of having a prevalent STI. Compared with reporting one male sexual partner, having 2–3 partners (aOR = 1.74; 95% CI 1.08–2.81, p<0.024) or more than 4 partners (aOR = 2.29; 95% CI 1.43–3.66, p<0.001) was associated with prevalent STIs. Having both Black and non-Black sexual partners (aOR = 0.67; 95% CI 0.45–0.99, p = 0.042) was the only sexual network factor associated with prevalent STIs. Conclusions Age and the number and racial composition of sexual partners were associated with prevalent STIs among Black MSM, while other sexual network factors were not. Further studies are needed to evaluate the effects of the individual, network, and structural factors on prevalent STIs among Black MSM to inform combination interventions to reduce STIs among these men. PMID:26720332

  17. 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...

  18. 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

  19. 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.

  20. 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

  1. 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

  2. Metabolic brain networks in patients with Parkinson's disease based on 18F-FDG PET imaging

    International Nuclear Information System (INIS)

    Objective: To validate PD-related pattern (PDRP) network as a measure of PD by 18F-FDG PET imaging. Methods: Thirty-two PD patients with different severities and 32 healthy controls matched by age and gender were recruited in studies of resting-state brain 18F-FDG PET imaging. To obtain the PDRP, principal component analysis (PCA) was used. The correlations between PDRP expression and the severities of PD (classified by unified PD rating scale (UPDRS) motor scores and Hoehn and Yahr stages) were investigated. The two-sample t test and Pearson correlation analysis were used for statistical analysis. Results: PDRP was characterized by relative metabolic increases in the putamen, globus pallidus (GP), thalamus, pons, cerebellum and primary motor cortex, and was associated with decreases in the premotor and posterior parietal areas. The value of PDRP expression in PD group (1.605±0.655) was significantly higher than that of healthy controls (0.000±0.523; t=10.829, P<0.001). The value of PDRP expression also correlated significantly with UPDRS motor scores (r=0.760, P<0.001) and Hoehn and Yahr stages in PD group (r=0.736, P<0.001). Conclusion: The PDRP based on 18F-FDG PET imaging can be useful for identification of PD patients from healthy controls and correlates well with the severity of the disease. (authors)

  3. Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard

    2009-04-01

    Full Text Available Abstract Background Infections with Salmonella cause significant morbidity and mortality worldwide. Replication of Salmonella typhimurium inside its host cell is a model system for studying the pathogenesis of intracellular bacterial infections. Genome-scale modeling of bacterial metabolic networks provides a powerful tool to identify and analyze pathways required for successful intracellular replication during host-pathogen interaction. Results We have developed and validated a genome-scale metabolic network of Salmonella typhimurium LT2 (iRR1083. This model accounts for 1,083 genes that encode proteins catalyzing 1,087 unique metabolic and transport reactions in the bacterium. We employed flux balance analysis and in silico gene essentiality analysis to investigate growth under a wide range of conditions that mimic in vitro and host cell environments. Gene expression profiling of S. typhimurium isolated from macrophage cell lines was used to constrain the model to predict metabolic pathways that are likely to be operational during infection. Conclusion Our analysis suggests that there is a robust minimal set of metabolic pathways that is required for successful replication of Salmonella inside the host cell. This model also serves as platform for the integration of high-throughput data. Its computational power allows identification of networked metabolic pathways and generation of hypotheses about metabolism during infection, which might be used for the rational design of novel antibiotics or vaccine strains.

  4. Identification of Metabolic Pathways Essential for Fitness of Salmonella Typhimurium In Vivo

    DEFF Research Database (Denmark)

    Jelsbak, Lotte; Hartman, Hassan; Schroll, Casper; Rosenkrantz, Jesper Tjørnholt; Lemire, Sebastien; Wallrodt, Inke; Thomsen, Line Elnif; Poolman, Mark; Kilstrup, Mogens; Jensen, Peter Ruhdal; Olsen, John E.

    2014-01-01

    Bacterial infections remain a threat to human and animal health worldwide, and there is an urgent need to find novel targets for intervention. In the current study we used a computer model of the metabolic network of Salmonella enterica serovar Typhimurium and identified pairs of reactions (cut...

  5. 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

  6. 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

  7. 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

  8. 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...

  9. 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

  10. 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.

  11. 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 ...

  12. Metabolites related to gut bacterial metabolism, peroxisome proliferator-activated receptor-alpha activation, and insulin sensitivity are associated with physical function in functionally-limited older adults

    OpenAIRE

    Lustgarten, Michael S.; Price, Lori L; Chalé, Angela; FIELDING, ROGER A.

    2014-01-01

    Identification of mechanisms underlying physical function will be important for addressing the growing challenge that health care will face with physical disablement in the expanding aging population. Therefore, the goals of the current study were to use metabolic profiling to provide insight into biologic mechanisms that may underlie physical function by examining the association between baseline and the 6-month change in serum mass spectrometry-obtained amino acids, fatty acids, and acylcar...

  13. Microbial dispersal in unsaturated porous media: Characteristics of motile bacterial cell motions in unsaturated angular pore networks

    Science.gov (United States)

    Ebrahimi, Ali N.; Or, Dani

    2014-09-01

    The dispersal rates of self-propelled microorganisms affect their spatial interactions and the ecological functioning of microbial communities. Microbial dispersal rates affect risk of contamination of water resources by soil-borne pathogens, the inoculation of plant roots, or the rates of spoilage of food products. In contrast with the wealth of information on microbial dispersal in water replete systems, very little is known about their dispersal rates in unsaturated porous media. The fragmented aqueous phase occupying complex soil pore spaces suppress motility and limits dispersal ranges in unsaturated soil. The primary objective of this study was to systematically evaluate key factors that shape microbial dispersal in model unsaturated porous media to quantify effects of saturation, pore space geometry, and chemotaxis on characteristics of principles that govern motile microbial dispersion in unsaturated soil. We constructed a novel 3-D angular pore network model (PNM) to mimic aqueous pathways in soil for different hydration conditions; within the PNM, we employed an individual-based model that considers physiological and biophysical properties of motile and chemotactic bacteria. The effects of hydration conditions on first passage times in different pore networks were studied showing that fragmentation of aquatic habitats under dry conditions sharply suppresses nutrient transport and microbial dispersal rates in good agreement with limited experimental data. Chemotactically biased mean travel speed of microbial cells across 9 mm saturated PNM was ˜3 mm/h decreasing exponentially to 0.45 mm/h for the PNM at matric potential of -15 kPa (for -35 kPa, dispersal practically ceases and the mean travel time to traverse the 9 mm PNM exceeds 1 year). Results indicate that chemotaxis enhances dispersal rates by orders of magnitude relative to random (diffusive) motions. Model predictions considering microbial cell sizes relative to available liquid pathways sizes were

  14. 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. PMID:25983044

  15. Skeletal muscle carnitine loading increases energy expenditure, modulates fuel metabolism gene networks and prevents body fat accumulation in humans

    OpenAIRE

    Stephens, Francis B; Wall, Benjamin T.; Marimuthu, Kanagaraj; Shannon, Chris E; Constantin-Teodosiu, Dumitru; Macdonald, Ian A.; Greenhaff, Paul L

    2013-01-01

    Twelve weeks of daily L-carnitine and carbohydrate feeding in humans increases skeletal muscle total carnitine content, and prevents body mass accrual associated with carbohydrate feeding alone. Here we determined the influence of L-carnitine and carbohydrate feeding on energy metabolism, body fat mass andmuscle expression of fuel metabolism genes. Twelve males exercised at 50% maximal oxygen consumption for 30 min once before and once after 12 weeks of twice daily feeding of 80 g carbohyd...

  16. 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.

  17. Dissecting lipid metabolism in meibomian glands of humans and mice: An integrative study reveals a network of metabolic reactions not duplicated in other tissues.

    Science.gov (United States)

    Butovich, Igor A; McMahon, Anne; Wojtowicz, Jadwiga C; Lin, Feng; Mancini, Ronald; Itani, Kamel

    2016-06-01

    Lipids comprise the bulk of the meibomian gland secretion (meibum) which is produced by meibocytes. Complex arrays of lipogenic reactions in meibomian glands, which we collectively call meibogenesis, have not been explored on a molecular level yet. Our goals were to elucidate the possible biosynthetic pathways that underlie the generation of meibum, reveal similarities in, and differences between, lipid metabolism in meibomian glands and other organs and tissues, and integrate meibomian gland studies into the field of general metabolomics. Specifically, we have conducted detailed analyses of human and mouse specimens using genomic, immunohistochemical, and lipidomic approaches. Among equally highly expressed genes found in meibomian glands of both species were those related to fatty acid elongation, branching, desaturation, esterification, reduction of fatty acids to alcohols, and cholesterol biosynthesis. Importantly, corresponding lipid products were detected in meibum of both species using lipidomic approaches. For the first time, a cohesive, unifying biosynthetic scheme that connects genomic, lipidomic, and immunohistochemical observations is outlined and discussed. PMID:27032494

  18. 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

  19. 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

  20. 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

  1. 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 ...

  2. 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, ...

  3. Prostatitis - bacterial

    Science.gov (United States)

    Any bacteria that can cause a urinary tract infection can cause acute bacterial prostatitis. Infections spread through sexual contact can cause prostatitis. These include chlamydia and gonorrhea . Sexually transmitted ...

  4. Bacterial Conjunctivitis

    OpenAIRE

    Köhle, Ülkü; Kükner, Şahap

    2003-01-01

    Conjunctivitis is an infection of the conjunctiva, generally characterized by irritation, itching, foreign body sensation, tearing and discharge. Bacterial conjunctivitis may be distinguished from other types of conjunctivitis by the presence of yellow–white mucopurulent discharge. It is the most common form of ocular infection all around the world. Staphylococcus species are the most common bacterial pathogenes, followed by Streptococcus pneumoniae and Haemophilus i...

  5. 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

  6. 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

  7. 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

  8. Isoliquiritigenin induces growth inhibition and apoptosis through downregulating arachidonic acid metabolic network and the deactivation of PI3K/Akt in human breast cancer

    International Nuclear Information System (INIS)

    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 E2 (PGE2) and 20-hydroxyeicosatetraenoic acid (20-HETE), without affecting COX-1, 5-lipoxygenase (5-LOX), 5-lipoxygenase activating protein (FLAP), and leukotriene B4 (LTB4). In addition, it downregulated the levels of phospho-PI3K, phospho-PDK (Ser241), phospho-Akt (Thr308), phospho-Bad (Ser136), and Bcl-xL expression, thereby activating caspase cascades and eventually cleaving poly(ADP-ribose) polymerase (PARP). Conversely, the addition of exogenous eicosanoids, including PGE2, LTB4 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 (Thr308). Collectively, these data suggest that isoliquiritigenin induces growth inhibition and apoptosis through downregulating AA metabolic network and the deactivation of PI3K/Akt in human breast cancer

  9. Polymorphisms in folate-metabolizing genes, chromosome damage, and risk of Down syndrome in Italian women: identification of key factors using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Migheli Francesca

    2010-09-01

    Full Text Available Abstract Background Studies in mothers of Down syndrome individuals (MDS point to a role for polymorphisms in folate metabolic genes in increasing chromosome damage and maternal risk for a Down syndrome (DS pregnancy, suggesting complex gene-gene interactions. This study aimed to analyze a dataset of genetic and cytogenetic data in an Italian group of MDS and mothers of healthy children (control mothers to assess the predictive capacity of artificial neural networks assembled in TWIST system in distinguish consistently these two different conditions and to identify the variables expressing the maximal amount of relevant information to the condition of being mother of a DS child. The dataset consisted of the following variables: the frequency of chromosome damage in peripheral lymphocytes (BNMN frequency and the genotype for 7 common polymorphisms in folate metabolic genes (MTHFR 677C>T and 1298A>C, MTRR 66A>G, MTR 2756A>G, RFC1 80G>A and TYMS 28bp repeats and 1494 6bp deletion. Data were analysed using TWIST system in combination with supervised artificial neural networks, and a semantic connectivity map. Results TWIST system selected 6 variables (BNMN frequency, MTHFR 677TT, RFC1 80AA, TYMS 1494 6bp +/+, TYMS 28bp 3R/3R and MTR 2756AA genotypes that were subsequently used to discriminate between MDS and control mothers with 90% accuracy. The semantic connectivity map provided important information on the complex biological connections between the studied variables and the two conditions (being MDS or control mother. Conclusions Overall, the study suggests a link between polymorphisms in folate metabolic genes and DS risk in Italian women.

  10. Human metabolic atlas: an online resource for human metabolism

    OpenAIRE

    Pornputtapong, Natapol; Nookaew, Intawat; Nielsen, Jens

    2015-01-01

    Human tissue-specific genome-scale metabolic models (GEMs) provide comprehensive understanding of human metabolism, which is of great value to the biomedical research community. To make this kind of data easily accessible to the public, we have designed and deployed the human metabolic atlas (HMA) website (http://www.metabolicatlas.org). This online resource provides comprehensive information about human metabolism, including the results of metabolic network analyses. We hope that it can also...

  11. 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.

  12. 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.

  13. 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

  14. 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

    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 ...

  15. Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism

    OpenAIRE

    Pérez-Delgado, Carmen M.; Moyano, Tomás C.; García-Calderón, Margarita; Canales, Javier; Gutiérrez, Rodrigo A; Márquez, Antonio J.; Betti, Marco

    2016-01-01

    Highlight A clear interconnection between photorespiration and primary nitrogen assimilation is established in Lotus japonicus, and key transcription factors connected to both routes are identified using transcriptomics and gene co-expression networks.

  16. Adaptive Calcified Matrix Response of Dental Pulp to Bacterial Invasion Is Associated with Establishment of a Network of Glial Fibrillary Acidic Protein+/Glutamine Synthetase+ Cells

    OpenAIRE

    Farahani, Ramin M.; Nguyen, Ky-Anh; Simonian, Mary; Hunter, Neil

    2010-01-01

    We report evidence for anatomical and functional changes of dental pulp in response to bacterial invasion through dentin that parallel responses to noxious stimuli reported in neural crest-derived sensory tissues. Sections of resin-embedded carious adult molar teeth were prepared for immunohistochemistry, in situ hybridization, ultrastructural analysis, and microdissection to extract mRNA for quantitative analyses. In odontoblasts adjacent to the leading edge of bacterial invasion in carious ...

  17. Comparative Pathway Analyzer--a web server for comparative analysis, clustering and visualization of metabolic networks in multiple organisms.

    Science.gov (United States)

    Oehm, Sebastian; Gilbert, David; Tauch, Andreas; Stoye, Jens; Goesmann, Alexander

    2008-07-01

    In order to understand the phenotype of any living system, it is essential to not only investigate its genes, but also the specific metabolic pathway variant of the organism of interest, ideally in comparison with other organisms. The Comparative Pathway Analyzer, CPA, calculates and displays the differences in metabolic reaction content between two sets of organisms. Because results are highly dependent on the distribution of organisms into these two sets and the appropriate definition of these sets often is not easy, we provide hierarchical clustering methods for the identification of significant groupings. CPA also visualizes the reaction content of several organisms simultaneously allowing easy comparison. Reaction annotation data and maps for visualizing the results are taken from the KEGG database. Additionally, users can upload their own annotation data. This website is free and open to all users and there is no login requirement. It is available at https://www.cebitec.uni-bielefeld.de/groups/brf/software/cpa/index.html. PMID:18539612

  18. 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...

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

    OpenAIRE

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

    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 (carc...

  20. 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...

  1. 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 ...

  2. Positive Emotionality is Associated with Baseline Metabolism in Orbitofrontal Cortex and in Regions of the Default Network

    OpenAIRE

    Volkow, Nora D.; Tomasi, Dardo; Wang, Gene-Jack; Fowler, Joanna S.; Telang, Frank; Goldstein, Rita Z.; Alia-Klein, Nelly; Woicik, Patricia; Wong, Christopher; Logan, Jean; Millard, Jayne; Alexoff, David

    2011-01-01

    Positive Emotionality (personality construct of well being, achievement/motivation, social and closeness) has been associated with striatal dopamine D2 receptor availability in healthy controls. Since striatal D2 receptors modulate activity in orbitofrontal cortex and cingulate (brain regions that process natural and drug rewards) we hypothesized that these regions underlie positive emotionality. To test this we assessed the correlation between baseline brain glucose metabolism (measured with...

  3. Discovery of Novel 15-Lipoxygenase Activators To Shift the Human Arachidonic Acid Metabolic Network toward Inflammation Resolution.

    Science.gov (United States)

    Meng, Hu; McClendon, Christopher L; Dai, Ziwei; Li, Kenan; Zhang, Xiaoling; He, Shan; Shang, Erchang; Liu, Ying; Lai, Luhua

    2016-05-12

    For disease network intervention, up-regulating enzyme activities is equally as important as down-regulating activities. However, the design of enzyme activators presents a challenging route for drug discovery. Previous studies have suggested that activating 15-lipoxygenase (15-LOX) is a promising strategy to intervene the arachidonic acid (AA) metabolite network and control inflammation. To prove this concept, we used a computational approach to discover a previously unknown allosteric site on 15-LOX. Both allosteric inhibitors and novel activators were discovered using this site. The influence of activating 15-LOX on the AA metabolite network was then investigated experimentally. The activator was found to increase levels of 15-LOX products and reduce production of pro-inflammatory mediators in human whole blood assays. These results demonstrate the promising therapeutic value of enzyme activators and aid in further development of activators of other proteins. PMID:26290290

  4. Bacterial Adhesion & Blocking Bacterial Adhesion

    DEFF Research Database (Denmark)

    Vejborg, Rebecca Munk

    2008-01-01

    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...... 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...

  5. 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

  6. 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...

  7. iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks

    OpenAIRE

    Andreozzi, Stefano; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2016-01-01

    Accurate determination of physiological states of cellular metabolism requires detailed information about metabolic fluxes, metabolite concentrations and distribution of enzyme states. Integration of fluxomics and metabolomics data, and thermodynamics-based metabolic flux analysis contribute to improved understanding of steady-state properties of metabolism. However, knowledge about kinetics and enzyme activities though essential for quantitative understanding of metabolic dynamics remains sc...

  8. Knock-out of SO1377 gene, which encodes the member of a conserved hypothetical bacterial protein family COG2268, results in alteration of iron metabolism, increased spontaneous mutation and hydrogen peroxide sensitivity in Shewanella oneidensis MR-1

    Directory of Open Access Journals (Sweden)

    Klingeman Dawn M

    2006-04-01

    Full Text Available Abstract Background Shewanella oneidensis MR-1 is a facultative, gram-negative bacterium capable of coupling the oxidation of organic carbon to a wide range of electron acceptors such as oxygen, nitrate and metals, and has potential for bioremediation of heavy metal contaminated sites. The complete 5-Mb genome of S. oneidensis MR-1 was sequenced and standard sequence-comparison methods revealed approximately 42% of the MR-1 genome encodes proteins of unknown function. Defining the functions of hypothetical proteins is a great challenge and may need a systems approach. In this study, by using integrated approaches including whole genomic microarray and proteomics, we examined knockout effects of the gene encoding SO1377 (gi24372955, a member of the conserved, hypothetical, bacterial protein family COG2268 (Clusters of Orthologous Group in bacterium Shewanella oneidensis MR-1, under various physiological conditions. Results Compared with the wild-type strain, growth assays showed that the deletion mutant had a decreased growth rate when cultured aerobically, but not affected under anaerobic conditions. Whole-genome expression (RNA and protein profiles revealed numerous gene and protein expression changes relative to the wild-type control, including some involved in iron metabolism, oxidative damage protection and respiratory electron transfer, e. g. complex IV of the respiration chain. Although total intracellular iron levels remained unchanged, whole-cell electron paramagnetic resonance (EPR demonstrated that the level of free iron in mutant cells was 3 times less than that of the wild-type strain. Siderophore excretion in the mutant also decreased in iron-depleted medium. The mutant was more sensitive to hydrogen peroxide and gave rise to 100 times more colonies resistant to gentamicin or kanamycin. Conclusion Our results showed that the knock-out of SO1377 gene had pleiotropic effects and suggested that SO1377 may play a role in iron

  9. Modeling bacterial chemotaxis inside a cell

    OpenAIRE

    Ouannes, Nesrine; Djedi, Noureddine; Luga, Hervé; Duthen, Yves

    2014-01-01

    This paper describes a bacterial system that reproduces a population of bacteria that behave by simulating the internal reactions of each bacterial cell. The chemotaxis network of a cell is modulated by a hybrid approach that uses an algebraic model for the receptor clusters activity and an ordinary differential equation for the adaptation dynamics. The experiments are defined in order to simulate bacterial growth in an environment where nutrients are regularly added to it. The results show a...

  10. 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.

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

    International Nuclear Information System (INIS)

    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 Ca2+-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 β (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: ► We performed brain proteomic analysis of rats exposed to the neurotoxicant, Aroclor 1254. ► Cerebellum and

  12. Positive emotionality is associated with baseline metabolism in orbitofrontal cortex and in regions of the default network.

    Science.gov (United States)

    Volkow, N D; Tomasi, D; Wang, G-J; Fowler, J S; Telang, F; Goldstein, R Z; Alia-Klein, N; Woicik, P; Wong, C; Logan, J; Millard, J; Alexoff, D

    2011-08-01

    Positive emotionality (PEM) (personality construct of well-being, achievement/motivation, social and closeness) has been associated with striatal dopamine D2 receptor availability in healthy controls. As striatal D2 receptors modulate activity in orbitofrontal cortex (OFC) and cingulate (brain regions that process natural and drug rewards), we hypothesized that these regions underlie PEM. To test this, we assessed the correlation between baseline brain glucose metabolism (measured with positron emission tomography and [(18)F]fluoro-deoxyglucose) and scores on PEM (obtained from the multidimensional personality questionnaire or MPQ) in healthy controls (n = 47). Statistical parametric mapping (SPM) analyses revealed that PEM was positively correlated (P(c)trait that protects against substance use disorders. As dysfunction of OFC and cingulate is a hallmark of addiction, these findings support a common neural basis underlying protective personality factors and brain dysfunction underlying substance use disorders. In addition, we also uncovered an association between PEM and baseline metabolism in regions from the DMN, which suggests that PEM may relate to global cortical processes that are active during resting conditions (introspection, mind wandering). PMID:21483434

  13. 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

  14. 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...

  15. 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...

  16. Metabolic profiling of Parkinson's disease: evidence of biomarker from gene expression analysis and rapid neural network detection

    Directory of Open Access Journals (Sweden)

    Kumar Suresh

    2009-07-01

    Full Text Available Abstract Background Parkinson's disease (PD is a neurodegenerative disorder. The diagnosis of Parkinsonism is challenging because currently none of the clinical tests have been proven to help in diagnosis. PD may produce characteristic perturbations in the metabolome and such variations can be used as the marker for detection of disease. To test this hypothesis, we used proton NMR and multivariate analysis followed by neural network pattern detection. Methods & Results 1H nuclear magnetic resonance spectroscopy analysis was carried out on plasma samples of 37 healthy controls and 43 drug-naive patients with PD. Focus on 22 targeted metabolites, 17 were decreased and 5 were elevated in PD patients (p PDHB and NPFF genes leading to increased pyruvate concentration in blood plasma. Moreover, the implementation of 1H- NMR spectral pattern in neural network algorithm shows 97.14% accuracy in the detection of disease progression. Conclusion The results increase the prospect of a robust molecular definition in detection of PD through the early symptomatic phase of the disease. This is an ultimate opening for therapeutic intervention. If validated in a genuinely prospective fashion in larger samples, the biomarker trajectories described here will go a long way to facilitate the development of useful therapies. Moreover, implementation of neural network will be a breakthrough in clinical screening and rapid detection of PD.

  17. 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

  18. 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

  19. 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

  20. 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...

  1. Bacterial Microcompartments

    OpenAIRE

    Kerfeld, Cheryl A.

    2010-01-01

    Bacterialmicrocompartments (BMCs) are organelles composed entirely of protein. They promote specific metabolic processes by encapsulating and colocalizing enzymes with their substrates and cofactors, by protecting vulnerable enzymes in a defined microenvironment, and by sequestering toxic or volatile intermediates. Prototypes of the BMCsare the carboxysomes of autotrophic bacteria. However, structures of similar polyhedral shape are being discovered in an ever-increasing number of heterotroph...

  2. Bacterial Protein-Tyrosine Kinases

    DEFF Research Database (Denmark)

    Shi, Lei; Kobir, Ahasanul; Jers, Carsten;

    2010-01-01

    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...... enzymes that are unique in exploiting the ATP/GTP-binding Walker motif to catalyze phosphorylation of protein tyrosine residues. Characterized for the first time only a decade ago, BY-kinases have now come to the fore. Important regulatory roles have been linked with these enzymes, via their involvement...... 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...

  3. Bacterial water quality and network hydraulic characteristics: a field study of a small, looped water distribution system using culture-independent molecular methods

    OpenAIRE

    R. Sekar; P. Deines; Machell, J.; A. M. Osborn; C. A. Biggs; J. B. Boxall

    2012-01-01

    Aims:  To determine the spatial and temporal variability in the abundance, structure and composition of planktonic bacterial assemblages sampled from a small, looped water distribution system and to interpret results with respect to hydraulic conditions. Methods and Results:  Water samples were collected from five sampling points, twice a day at 06:00 h and 09:00 h on a Monday (following low weekend demand) and a Wednesday (higher midweek demand). All samples were fully compliant with cur...

  4. 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.

  5. Engineering Cellular Metabolism

    DEFF Research Database (Denmark)

    Nielsen, Jens; Keasling, Jay

    2016-01-01

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

  6. 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.

  7. 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

  8. 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

  9. Oxidative Metabolism of Rye (Secale cereale L.) after Short Term Exposure to Aluminum: Uncovering the Glutathione–Ascorbate Redox Network

    Science.gov (United States)

    de Sousa, Alexandra; AbdElgawad, Hamada; Han, Asard; Teixeira, Jorge; Matos, Manuela; Fidalgo, Fernanda

    2016-01-01

    One of the major limitations to plant growth and yield in acidic soils is the prevalence of soluble aluminum ions (Al3+) in the soil solution, which can irreversible damage the root apex cells. Nonetheless, many Al-tolerant species overcome Al toxicity and are well-adapted to acidic soils, being able to complete their life cycle under such stressful conditions. At this point, the complex physiological and biochemical processes inherent to Al tolerance remain unclear, especially in what concerns the behavior of antioxidant enzymes and stress indicators at early plant development. Since rye (Secale cereale L.), is considered the most Al-tolerant cereal, in this study we resort to seedlings of two genotypes with different Al sensitivities in order to evaluate their oxidative metabolism after short term Al exposure. Al-induced toxicity and antioxidant responses were dependent on rye genotype, organ and exposure period. Al affected biomass production and membrane integrity in roots and leaves of the sensitive (RioDeva) genotype. Catalase was the primary enzyme involved in H2O2 detoxification in the tolerant (Beira) genotype, while in RioDeva this task was mainly performed by GPX and POX. Evaluation of the enzymatic and non-enzymatic components of the ascorbate–glutathione cycle, as well the oxalate content, revealed that Beira genotype coped with Al stress by converting DHA into oxalate and tartarate, which posteriorly may bind to Al forming non-toxic chelates. In contrast, RioDeva genotype used a much more ineffective strategy which passed through ascorbate regeneration. So, remarkable differences between MDHAR and DHAR activities appear to be the key for a higher Al tolerance. PMID:27252711

  10. 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

  11. Bacterial hydrodynamics

    CERN Document Server

    Lauga, Eric

    2015-01-01

    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 micron 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 framework, we review the biomechanics of bacterial motility and look ahead to future challenges.

  12. Gut microbiota and host metabolism in liver cirrhosis.

    Science.gov (United States)

    Usami, Makoto; Miyoshi, Makoto; Yamashita, Hayato

    2015-11-01

    The gut microbiota has the capacity to produce a diverse range of compounds that play a major role in regulating the activity of distal organs and the liver is strategically positioned downstream of the gut. Gut microbiota linked compounds such as short chain fatty acids, bile acids, choline metabolites, indole derivatives, vitamins, polyamines, lipids, neurotransmitters and neuroactive compounds, and hypothalamic-pituitary-adrenal axis hormones have many biological functions. This review focuses on the gut microbiota and host metabolism in liver cirrhosis. Dysbiosis in liver cirrhosis causes serious complications, such as bacteremia and hepatic encephalopathy, accompanied by small intestinal bacterial overgrowth and increased intestinal permeability. Gut dysbiosis in cirrhosis and intervention with probiotics and synbiotics in a clinical setting is reviewed and evaluated. Recent studies have revealed the relationship between gut microbiota and host metabolism in chronic metabolic liver disease, especially, non-alcoholic fatty liver disease, alcoholic liver disease, and with the gut microbiota metabolic interactions in dysbiosis related metabolic diseases such as diabetes and obesity. Recently, our understanding of the relationship between the gut and liver and how this regulates systemic metabolic changes in liver cirrhosis has increased. The serum lipid levels of phospholipids, free fatty acids, polyunsaturated fatty acids, especially, eicosapentaenoic acid, arachidonic acid, and docosahexaenoic acid have significant correlations with specific fecal flora in liver cirrhosis. Many clinical and experimental reports support the relationship between fatty acid metabolism and gut-microbiota. Various blood metabolome such as cytokines, amino acids, and vitamins are correlated with gut microbiota in probiotics-treated liver cirrhosis patients. The future evaluation of the gut-microbiota-liver metabolic network and the intervention of these relationships using probiotics

  13. Association of DNA Methylation at CPT1A Locus with Metabolic Syndrome in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN Study.

    Directory of Open Access Journals (Sweden)

    Mithun Das

    Full Text Available In this study, we conducted an epigenome-wide association study of metabolic syndrome (MetS among 846 participants of European descent in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN. DNA was isolated from CD4+ T cells and methylation at ~470,000 cytosine-phosphate-guanine dinucleotide (CpG pairs was assayed using the Illumina Infinium HumanMethylation450 BeadChip. We modeled the percentage methylation at individual CpGs as a function of MetS using linear mixed models. A Bonferroni-corrected P-value of 1.1 x 10(-7 was considered significant. Methylation at two CpG sites in CPT1A on chromosome 11 was significantly associated with MetS (P for cg00574958 = 2.6x10(-14 and P for cg17058475 = 1.2x10(-9. Significant associations were replicated in both European and African ancestry participants of the Bogalusa Heart Study. Our findings suggest that methylation in CPT1A is a promising epigenetic marker for MetS risk which could become useful as a treatment target in the future.

  14. Coregulation of host-adapted metabolism and virulence by pathogenic yersiniae

    Directory of Open Access Journals (Sweden)

    Ann Kathrin eHeroven

    2014-10-01

    Full Text Available Deciphering the principles how pathogenic bacteria adapt their metabolism to a specific host microenvironment is critical for understanding bacterial pathogenesis. The enteric pathogenic Yersinia species Y. pseudotuberculosis and Y. enterocolitica and the causative agent of plague, Y. pestis, are able to survive in a large variety of environmental reservoirs (e.g. soil, plants, insects as well as warm-blooded animals (e.g. rodents, pigs, humans with a particular preference for lymphatic tissues. In order to manage rapidly changing environmental conditions and inter-bacterial competition, Yersinia senses the nutritional composition during the course of an infection by special molecular devices, integrates this information and adapts its metabolism accordingly. In addition, nutrient availability has an impact on expression of virulence genes in response to C-sources, demonstrating a tight link between the pathogenicity of yersiniae and utilization of nutrients. Recent studies revealed that global regulatory factors such as the cAMP receptor protein (Crp and the carbon storage regulator (Csr system are part of a large network of transcriptional and posttranscriptional control strategies adjusting metabolic changes and virulence in response to temperature, ion and nutrient availability. Gained knowledge about the specific metabolic requirements and the correlation between metabolic and virulence gene expression that enable efficient host colonization led to the identification of new potential antimicrobial targets.

  15. Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

    Directory of Open Access Journals (Sweden)

    Oldiges Marco

    2009-01-01

    Full Text Available Abstract Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1 experimental measurement of participating molecules, (2 assignment of rate laws to each reaction, and (3 parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1 coarse-grained comparison of the algorithms on all models and (2 fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics

  16. Metabolic acidosis

    Science.gov (United States)

    Acidosis - metabolic ... Metabolic acidosis occurs when the body produces too much acid. It can also occur when the kidneys are not ... the body. There are several types of metabolic acidosis. Diabetic acidosis develops when acidic substances, known as ...

  17. 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 <1.5 ± 0.8 mg/L, NOB cells can oxidize the NO produced by AOB through reactions catalyzed by oxidative NirK. PMID:26551878

  18. Microbial minimalism: genome reduction in bacterial pathogens.

    Science.gov (United States)

    Moran, Nancy A

    2002-03-01

    When bacterial lineages make the transition from free-living or facultatively parasitic life cycles to permanent associations with hosts, they undergo a major loss of genes and DNA. Complete genome sequences are providing an understanding of how extreme genome reduction affects evolutionary directions and metabolic capabilities of obligate pathogens and symbionts. PMID:11893328

  19. The metabolic network of Clostridium acetobutylicum: Comparison of the approximate Bayesian computation via sequential Monte Carlo (ABC-SMC) and profile likelihood estimation (PLE) methods for determinability analysis.

    Science.gov (United States)

    Thorn, Graeme J; King, John R

    2016-01-01

    The Gram-positive bacterium Clostridium acetobutylicum is an anaerobic endospore-forming species which produces acetone, butanol and ethanol via the acetone-butanol (AB) fermentation process, leading to biofuels including butanol. In previous work we looked to estimate the parameters in an ordinary differential equation model of the glucose metabolism network using data from pH-controlled continuous culture experiments. Here we combine two approaches, namely the approximate Bayesian computation via an existing sequential Monte Carlo (ABC-SMC) method (to compute credible intervals for the parameters), and the profile likelihood estimation (PLE) (to improve the calculation of confidence intervals for the same parameters), the parameters in both cases being derived from experimental data from forward shift experiments. We also apply the ABC-SMC method to investigate which of the models introduced previously (one non-sporulation and four sporulation models) have the greatest strength of evidence. We find that the joint approximate posterior distribution of the parameters determines the same parameters as previously, including all of the basal and increased enzyme production rates and enzyme reaction activity parameters, as well as the Michaelis-Menten kinetic parameters for glucose ingestion, while other parameters are not as well-determined, particularly those connected with the internal metabolites acetyl-CoA, acetoacetyl-CoA and butyryl-CoA. We also find that the approximate posterior is strongly non-Gaussian, indicating that our previous assumption of elliptical contours of the distribution is not valid, which has the effect of reducing the numbers of pairs of parameters that are (linearly) correlated with each other. Calculations of confidence intervals using the PLE method back this up. Finally, we find that all five of our models are equally likely, given the data available at present. PMID:26561777

  20. The intrinsic resistome of bacterial pathogens

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    JoseLMartinez

    2013-04-01

    Full Text Available Intrinsically resistant bacteria have emerged as a relevant health problem in the last years. Those bacterial species, several of them with an environmental origin, present naturally a low-level susceptibility to several drugs. It has been proposed that intrinsic resistance is mainly the consequence of the impermeability of cellular envelopes, the activity of multidrug efflux pumps or the lack of appropriate targets for a given family of drugs. However, recently published articles indicate that the characteristic phenotype of susceptibility to antibiotics of a given bacterial species depends on the concerted activity of several elements, what has been named as intrinsic resistome. These determinants comprise not just classical resistance genes. Other elements, several of them involved in basic bacterial metabolic processes, are of relevance for the intrinsic resistance of bacterial pathogens. In the present review we analyse recent publications on the intrinsic resistomes of Escherichia coli and Pseudomonas aeruginosa. We present as well information on the role that global regulators of bacterial metabolism, as Crc from P. aeruginosa, may have on modulating bacterial susceptibility to antibiotics. Finally, we discuss the possibility of searching inhibitors of the intrinsic resistome in the aim of improving the activity of drugs currently in use for clinical practice.

  1. Final Report: Filling Knowledge Gaps in Biological Networks: Integrated Global Approaches to Understand H{sub 2} Metabolism in Chlamydomonas Reinhardtii

    Energy Technology Data Exchange (ETDEWEB)

    Grossman, Arthur

    2012-05-01

    The major goal of our part of this project has been to generate mutants in fermentation metabolism and begin to decipher how lesions in the pathways associated with fermentation metabolism impact both H{sub 2} production and the production of other metabolites that accumulate as cells become anoxic. We are also trying to understand how metabolic pathways are regulated as O{sub 2} in the environment becomes depleted.

  2. Formaldehyde stress responses in bacterial pathogens

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    Nathan Houqian Chen

    2016-03-01

    Full Text Available Formaldehyde is the simplest of all aldehydes and is highly cytotoxic. Its use and associated dangers from environmental exposure have been well documented. Detoxification systems for formaldehyde are found throughout the biological world and they are especially important in methylotrophic bacteria, which generate this compound as part of their metabolism of methanol. Formaldehyde metabolizing systems can be divided into those dependent upon pterin cofactors, sugar phosphates and those dependent upon glutathione. The more prevalent thiol-dependent formaldehyde detoxification system is found in many bacterial pathogens, almost all of which do not metabolize methane or methanol. This review describes the endogenous and exogenous sources of formaldehyde, its toxic effects and mechanisms of detoxification. The methods of formaldehyde sensing are also described with a focus on the formaldehyde responsive transcription factors HxlR, FrmR and NmlR. Finally, the physiological relevance of detoxification systems for formaldehyde in bacterial pathogens is discussed.

  3. Formaldehyde Stress Responses in Bacterial Pathogens.

    Science.gov (United States)

    Chen, Nathan H; Djoko, Karrera Y; Veyrier, Frédéric J; McEwan, Alastair G

    2016-01-01

    Formaldehyde is the simplest of all aldehydes and is highly cytotoxic. Its use and associated dangers from environmental exposure have been well documented. Detoxification systems for formaldehyde are found throughout the biological world and they are especially important in methylotrophic bacteria, which generate this compound as part of their metabolism of methanol. Formaldehyde metabolizing systems can be divided into those dependent upon pterin cofactors, sugar phosphates and those dependent upon glutathione. The more prevalent thiol-dependent formaldehyde detoxification system is found in many bacterial pathogens, almost all of which do not metabolize methane or methanol. This review describes the endogenous and exogenous sources of formaldehyde, its toxic effects and mechanisms of detoxification. The methods of formaldehyde sensing are also described with a focus on the formaldehyde responsive transcription factors HxlR, FrmR, and NmlR. Finally, the physiological relevance of detoxification systems for formaldehyde in bacterial pathogens is discussed. PMID:26973631

  4. 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

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    D.W. Ding

    2009-06-01

    Full Text Available 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 of these divisions were investigated by comparing to KEGG metabolic pathways.O objetivo deste trabalho foi realizar uma análise estrutural e funcional do GSC (Giant Strong Component da rede metabólica de Bacillus thurigiensis. Baseando-se na estrutura bow-tie, o GSC foi extraído e analisado quanto ao sue significado funcional. Propriedades estruturais globais tais como grau de distribuição e tamanho médio da via metabólica foram mensuradas, concluindo-se que o GSC é também uma rede small world e scalefree. Além disso, a rede GSC foi decomposta e as divisões com significância funcional no metabolismo foram comparadas às vias metabólicas KEGG.

  5. GLAMM: Genome-Linked Application for Metabolic Maps

    Energy Technology Data Exchange (ETDEWEB)

    Bates, John; Chivian, Dylan; Arkin, Adam

    2011-05-29

    The Genome-Linked Application for Metabolic Maps (GLAMM) is a unified web interface for visualizing metabolic networks, reconstructing metabolic networks from annotated genome data, visualizing experimental data in the context of metabolic networks, and investigating the construction of novel, transgenic pathways. This simple, user-friendly interface is tightly integrated with the comparative genomics tools of MicrobesOnline. GLAMM is available for free to the scientific community at glamm.lbl.gov.

  6. Metabolic Disorders

    Science.gov (United States)

    ... as your liver, muscles, and body fat. A metabolic disorder occurs when abnormal chemical reactions in your body ... that produce the energy. You can develop a metabolic disorder when some organs, such as your liver or ...

  7. Metabolic Syndrome

    Science.gov (United States)

    Metabolic syndrome is a group of conditions that put you at risk for heart disease and diabetes. These ... doctors agree on the definition or cause of metabolic syndrome. The cause might be insulin resistance. Insulin is ...

  8. Applying high resolution mass spectrometry and network analysis to assess exposure to a novel androgen, spironolactone, on metabolic pathways in fish

    Science.gov (United States)

    Although metabolomics can successfully detect effects from overall contaminant exposure, its ability to elucidate specific metabolic pathways impacted by those exposures can be hindered by bottlenecks in metabolite identification. However, improved analytical approaches that com...

  9. Bacterial Nail Infection (Paronychia)

    Science.gov (United States)

    ... of nail infection is often caused by a bacterial infection but may also be caused by herpes, a ... to a type of yeast called Candida , or bacterial infection, and this may lead to abnormal nail growth. ...

  10. iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.

    Science.gov (United States)

    Andreozzi, Stefano; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2016-01-01

    Accurate determination of physiological states of cellular metabolism requires detailed information about metabolic fluxes, metabolite concentrations and distribution of enzyme states. Integration of fluxomics and metabolomics data, and thermodynamics-based metabolic flux analysis contribute to improved understanding of steady-state properties of metabolism. However, knowledge about kinetics and enzyme activities though essential for quantitative understanding of metabolic dynamics remains scarce and involves uncertainty. Here, we present a computational methodology that allow us to determine and quantify the kinetic parameters that correspond to a certain physiology as it is described by a given metabolic flux profile and a given metabolite concentration vector. Though we initially determine kinetic parameters that involve a high degree of uncertainty, through the use of kinetic modeling and machine learning principles we are able to obtain more accurate ranges of kinetic parameters, and hence we are able to reduce the uncertainty in the model analysis. We computed the distribution of kinetic parameters for glucose-fed E. coli producing 1,4-butanediol and we discovered that the observed physiological state corresponds to a narrow range of kinetic parameters of only a few enzymes, whereas the kinetic parameters of other enzymes can vary widely. Furthermore, this analysis suggests which are the enzymes that should be manipulated in order to engineer the reference state of the cell in a desired way. The proposed approach also sets up the foundations of a novel type of approaches for efficient, non-asymptotic, uniform sampling of solution spaces. PMID:26474788

  11. Analog regulation of metabolic demand

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    Muskhelishvili Georgi

    2011-03-01

    Full Text Available Abstract Background The 3D structure of the chromosome of the model organism Escherichia coli is one key component of its gene regulatory machinery. This type of regulation mediated by topological transitions of the chromosomal DNA can be thought of as an analog control, complementing the digital control, i.e. the network of regulation mediated by dedicated transcription factors. It is known that alterations in the superhelical density of chromosomal DNA lead to a rich pattern of differential expressed genes. Using a network approach, we analyze these expression changes for wild type E. coli and mutants lacking nucleoid associated proteins (NAPs from a metabolic and transcriptional regulatory network perspective. Results We find a significantly higher correspondence between gene expression and metabolism for the wild type expression changes compared to mutants in NAPs, indicating that supercoiling induces meaningful metabolic adjustments. As soon as the underlying regulatory machinery is impeded (as for the NAP mutants, this coherence between expression changes and the metabolic network is substantially reduced. This effect is even more pronounced, when we compute a wild type metabolic flux distribution using flux balance analysis and restrict our analysis to active reactions. Furthermore, we are able to show that the regulatory control exhibited by DNA supercoiling is not mediated by the transcriptional regulatory network (TRN, as the consistency of the expression changes with the TRN logic of activation and suppression is strongly reduced in the wild type in comparison to the mutants. Conclusions So far, the rich patterns of gene expression changes induced by alterations of the superhelical density of chromosomal DNA have been difficult to interpret. Here we characterize the effective networks