Jasmonate-responsive transcription factors regulating plant secondary metabolism.

PubMed

Zhou, Meiliang; Memelink, Johan

2016-01-01

Plants produce a large variety of secondary metabolites including alkaloids, glucosinolates, terpenoids and phenylpropanoids. These compounds play key roles in plant-environment interactions and many of them have pharmacological activity in humans. Jasmonates (JAs) are plant hormones which induce biosynthesis of many secondary metabolites. JAs-responsive transcription factors (TFs) that regulate the JAs-induced accumulation of secondary metabolites belong to different families including AP2/ERF, bHLH, MYB and WRKY. Here, we give an overview of the types and functions of TFs that have been identified in JAs-induced secondary metabolite biosynthesis, and highlight their similarities and differences in regulating various biosynthetic pathways. We review major recent developments regarding JAs-responsive TFs mediating secondary metabolite biosynthesis, and provide suggestions for further studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Jasmonates: biosynthesis, perception, signal transduction and action in plant stress response, growth and development. An update to the 2007 review in Annals of Botany

PubMed Central

Wasternack, C.; Hause, B.

2013-01-01

Background Jasmonates are important regulators in plant responses to biotic and abiotic stresses as well as in development. Synthesized from lipid-constituents, the initially formed jasmonic acid is converted to different metabolites including the conjugate with isoleucine. Important new components of jasmonate signalling including its receptor were identified, providing deeper insight into the role of jasmonate signalling pathways in stress responses and development. Scope The present review is an update of the review on jasmonates published in this journal in 2007. New data of the last five years are described with emphasis on metabolites of jasmonates, on jasmonate perception and signalling, on cross-talk to other plant hormones and on jasmonate signalling in response to herbivores and pathogens, in symbiotic interactions, in flower development, in root growth and in light perception. Conclusions The last few years have seen breakthroughs in the identification of JASMONATE ZIM DOMAIN (JAZ) proteins and their interactors such as transcription factors and co-repressors, and the crystallization of the jasmonate receptor as well as of the enzyme conjugating jasmonate to amino acids. Now, the complex nature of networks of jasmonate signalling in stress responses and development including hormone cross-talk can be addressed. PMID:23558912

Functional Alignment of Metabolic Networks.

PubMed

Mazza, Arnon; Wagner, Allon; Ruppin, Eytan; Sharan, Roded

2016-05-01

Network alignment has become a standard tool in comparative biology, allowing the inference of protein function, interaction, and orthology. However, current alignment techniques are based on topological properties of networks and do not take into account their functional implications. Here we propose, for the first time, an algorithm to align two metabolic networks by taking advantage of their coupled metabolic models. These models allow us to assess the functional implications of genes or reactions, captured by the metabolic fluxes that are altered following their deletion from the network. Such implications may spread far beyond the region of the network where the gene or reaction lies. We apply our algorithm to align metabolic networks from various organisms, ranging from bacteria to humans, showing that our alignment can reveal functional orthology relations that are missed by conventional topological alignments.

VRML metabolic network visualizer.

PubMed

Rojdestvenski, Igor

2003-03-01

A successful date collection visualization should satisfy a set of many requirements: unification of diverse data formats, support for serendipity research, support of hierarchical structures, algorithmizability, vast information density, Internet-readiness, and other. Recently, virtual reality has made significant progress in engineering, architectural design, entertainment and communication. We experiment with the possibility of using the immersive abstract three-dimensional visualizations of the metabolic networks. We present the trial Metabolic Network Visualizer software, which produces graphical representation of a metabolic network as a VRML world from a formal description written in a simple SGML-type scripting language.

Rewiring of jasmonate and phytochrome B signalling uncouples plant growth-defense tradeoffs

PubMed Central

Campos, Marcelo L.; Yoshida, Yuki; Major, Ian T.; de Oliveira Ferreira, Dalton; Weraduwage, Sarathi M.; Froehlich, John E.; Johnson, Brendan F.; Kramer, David M.; Jander, Georg; Sharkey, Thomas D.; Howe, Gregg A.

2016-01-01

Plants resist infection and herbivory with innate immune responses that are often associated with reduced growth. Despite the importance of growth-defense tradeoffs in shaping plant productivity in natural and agricultural ecosystems, the molecular mechanisms that link growth and immunity are poorly understood. Here, we demonstrate that growth-defense tradeoffs mediated by the hormone jasmonate are uncoupled in an Arabidopsis mutant (jazQ phyB) lacking a quintet of Jasmonate ZIM-domain transcriptional repressors and the photoreceptor phyB. Analysis of epistatic interactions between jazQ and phyB reveal that growth inhibition associated with enhanced anti-insect resistance is likely not caused by diversion of photoassimilates from growth to defense but rather by a conserved transcriptional network that is hardwired to attenuate growth upon activation of jasmonate signalling. The ability to unlock growth-defense tradeoffs through relief of transcription repression provides an approach to assemble functional plant traits in new and potentially useful ways. PMID:27573094

Rewiring of jasmonate and phytochrome B signalling uncouples plant growth-defense tradeoffs

DOE PAGES

Campos, Marcelo L.; Yoshida, Yuki; Major, Ian T.; ...

2016-08-30

Plants resist infection and herbivory with innate immune responses that are often associated with reduced growth. Despite the importance of growth-defense tradeoffs in shaping plant productivity in natural and agricultural ecosystems, the molecular mechanisms that link growth and immunity are poorly understood. Here, we demonstrate that growth-defense tradeoffs mediated by the hormone jasmonate are uncoupled in an Arabidopsis mutant ( jazQ phyB) lacking a quintet of Jasmonate ZIM-domain transcriptional repressors and the photoreceptor phyB. Analysis of epistatic interactions between jazQ and phyB reveal that growth inhibition associated with enhanced anti-insect resistance is likely not caused by diversion of photoassimilates frommore » growth to defense but rather by a conserved transcriptional network that is hardwired to attenuate growth upon activation of jasmonate signalling. Furthermore, the ability to unlock growth-defense tradeoffs through relief of transcription repression provides an approach to assemble functional plant traits in new and potentially useful ways.« less

Rewiring of jasmonate and phytochrome B signalling uncouples plant growth-defense tradeoffs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campos, Marcelo L.; Yoshida, Yuki; Major, Ian T.

Plants resist infection and herbivory with innate immune responses that are often associated with reduced growth. Despite the importance of growth-defense tradeoffs in shaping plant productivity in natural and agricultural ecosystems, the molecular mechanisms that link growth and immunity are poorly understood. Here, we demonstrate that growth-defense tradeoffs mediated by the hormone jasmonate are uncoupled in an Arabidopsis mutant ( jazQ phyB) lacking a quintet of Jasmonate ZIM-domain transcriptional repressors and the photoreceptor phyB. Analysis of epistatic interactions between jazQ and phyB reveal that growth inhibition associated with enhanced anti-insect resistance is likely not caused by diversion of photoassimilates frommore » growth to defense but rather by a conserved transcriptional network that is hardwired to attenuate growth upon activation of jasmonate signalling. Furthermore, the ability to unlock growth-defense tradeoffs through relief of transcription repression provides an approach to assemble functional plant traits in new and potentially useful ways.« less

Elicitor-induced transcription factors for metabolic reprogramming of secondary metabolism in Medicago truncatula

PubMed Central

Naoumkina, Marina A; He, XianZhi; Dixon, Richard A

2008-01-01

Background Exposure of Medicago truncatula cell suspension cultures to pathogen or wound signals leads to accumulation of various classes of flavonoid and/or triterpene defense molecules, orchestrated via a complex signalling network in which transcription factors (TFs) are essential components. Results In this study, we analyzed TFs responding to yeast elicitor (YE) or methyl jasmonate (MJ). From 502 differentially expressed TFs, WRKY and AP2/EREBP gene families were over-represented among YE-induced genes whereas Basic Helix-Loop-Helix (bHLH) family members were more over-represented among the MJ-induced genes. Jasmonate ZIM-domain (JAZ) transcriptional regulators were highly induced by MJ treatment. To investigate potential involvement of WRKY TFs in signalling, we expressed four Medicago WRKY genes in tobacco. Levels of soluble and wall bound phenolic compounds and lignin were increased in all cases. WRKY W109669 also induced tobacco endo-1,3-β-glucanase (NtPR2) and enhanced the systemic defense response to tobacco mosaic virus in transgenic tobacco plants. Conclusion These results confirm that Medicago WRKY TFs have broad roles in orchestrating metabolic responses to biotic stress, and that they also represent potentially valuable reagents for engineering metabolic changes that impact pathogen resistance. PMID:19102779

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

PubMed Central

2011-01-01

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

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

PubMed

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

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

Distinct Roles of Jasmonates and Aldehydes in Plant-Defense Responses

PubMed Central

Chehab, E. Wassim; Kaspi, Roy; Savchenko, Tatyana; Rowe, Heather; Negre-Zakharov, Florence; Kliebenstein, Dan; Dehesh, Katayoon

2008-01-01

-herbivore-natural enemy) interactions. Significance The data suggest that jasmonates and hexenyl acetate play distinct roles in mediating direct and indirect plant-defense responses. The potential advantage of this “division of labor” is to ensure the most effective defense strategy that minimizes incurred damages at a reduced metabolic cost. PMID:18382679

Jasmonoyl-l-Isoleucine Coordinates Metabolic Networks Required for Anthesis and Floral Attractant Emission in Wild Tobacco (Nicotiana attenuata)[C][W][OPEN

PubMed Central

Stitz, Michael; Hartl, Markus; Baldwin, Ian T.; Gaquerel, Emmanuel

2014-01-01

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

Methyl jasmonate deficiency alters cellular metabolome including the aminome of tomato (Solanum lycopersicum L.) fruit

USDA-ARS?s Scientific Manuscript database

Lipoxygenase (LOX) catalyzes oxidation of C-13 atom of C:18 polyunsaturated fatty acids and produces jasmonic acid and other oxylipins that have important biological relevance. However, the role of these important molecules in cellular metabolism is barely understood. We have used a transgenic appro...

Plastic Transcriptomes Stabilize Immunity to Pathogen Diversity: The Jasmonic Acid and Salicylic Acid Networks within the Arabidopsis/Botrytis Pathosystem.

PubMed

Zhang, Wei; Corwin, Jason A; Copeland, Daniel; Feusier, Julie; Eshbaugh, Robert; Chen, Fang; Atwell, Susana; Kliebenstein, Daniel J

2017-11-01

To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis thaliana - Botrytis cinerea pathosystem to test how the host's defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA- and SA-signaling mutants, coi1-1 and npr1-1 , individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene coexpression networks and two vectors of defense variation triggered by genetic variation in B. cinerea This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen. © 2017 American Society of Plant Biologists. All rights reserved.

Jasmonate is essential for insect defense in Arabidopsis.

PubMed

McConn, M; Creelman, R A; Bell, E; Mullet, J E; Browse, J

1997-05-13

The signaling pathways that allow plants to mount defenses against chewing insects are known to be complex. To investigate the role of jasmonate in wound signaling in Arabidopsis and to test whether parallel or redundant pathways exist for insect defense, we have studied a mutant (fad3-2 fad7-2 fad8) that is deficient in the jasmonate precursor linolenic acid. Mutant plants contained negligible levels of jasmonate and showed extremely high mortality ( approximately 80%) from attack by larvae of a common saprophagous fungal gnat, Bradysia impatiens (Diptera: Sciaridae), even though neighboring wild-type plants were largely unaffected. Application of exogenous methyl jasmonate substantially protected the mutant plants and reduced mortality to approximately 12%. These experiments precisely define the role of jasmonate as being essential for the induction of biologically effective defense in this plant-insect interaction. The transcripts of three wound-responsive genes were shown not to be induced by wounding of mutant plants but the same transcripts could be induced by application of methyl jasmonate. By contrast, measurements of transcript levels for a gene encoding glutathione S-transferase demonstrated that wound induction of this gene is independent of jasmonate synthesis. These results indicate that the mutant will be a good genetic model for testing the practical effectiveness of candidate defense genes.

Metabolic networks are almost nonfractal: a comprehensive evaluation.

PubMed

Takemoto, Kazuhiro

2014-08-01

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

Methyl jasmonate leads to necrosis and apoptosis in hepatocellular carcinoma cells via inhibition of glycolysis and represses tumor growth in mice.

PubMed

Li, Jingjing; Chen, Kan; Wang, Fan; Dai, Weiqi; Li, Sainan; Feng, Jiao; Wu, Liwei; Liu, Tong; Xu, Shizan; Xia, Yujing; Lu, Jie; Zhou, Yingqun; Xu, Ling; Guo, Chuanyong

2017-07-11

Methyl jasmonate has recently been found to have anti-cancer activity. Methyl jasmonate detached hexokinase 2 from a voltage dependent anion channel causing a reduction in mitochondrial transmembrane potential that led to the release of cytochrome C and apoptosis inducing factor resulting in intrinsic apoptosis. Blocked adenosine triphosphate synthesis caused by mitochondrial injury hampered oxidative phosphorylation and led to cell necrosis. The results were applied to the in vivo treatment of nude mice with a satisfactory effect. Collectively, our results suggest that methyl jasmonate may be an adjuvant therapy for liver tumors due to its mechanism in cancer cells compared to that in normal cells: The major function is to inhibit glycolysis instead of changing aerobic metabolism.

Methyl jasmonate leads to necrosis and apoptosis in hepatocellular carcinoma cells via inhibition of glycolysis and represses tumor growth in mice

PubMed Central

Li, Jingjing; Chen, Kan; Wang, Fan; Dai, Weiqi; Li, Sainan; Feng, Jiao; Wu, Liwei; Liu, Tong; Xu, Shizan; Xia, Yujing; Lu, Jie; Zhou, Yingqun; Xu, Ling; Guo, Chuanyong

2017-01-01

Methyl jasmonate has recently been found to have anti-cancer activity. Methyl jasmonate detached hexokinase 2 from a voltage dependent anion channel causing a reduction in mitochondrial transmembrane potential that led to the release of cytochrome C and apoptosis inducing factor resulting in intrinsic apoptosis. Blocked adenosine triphosphate synthesis caused by mitochondrial injury hampered oxidative phosphorylation and led to cell necrosis. The results were applied to the in vivo treatment of nude mice with a satisfactory effect. Collectively, our results suggest that methyl jasmonate may be an adjuvant therapy for liver tumors due to its mechanism in cancer cells compared to that in normal cells: The major function is to inhibit glycolysis instead of changing aerobic metabolism. PMID:28498814

Jasmonate is essential for insect defense in Arabidopsis

PubMed Central

McConn, Michele; Creelman, Robert A.; Bell, Erin; Mullet, John E.; Browse, John

1997-01-01

The signaling pathways that allow plants to mount defenses against chewing insects are known to be complex. To investigate the role of jasmonate in wound signaling in Arabidopsis and to test whether parallel or redundant pathways exist for insect defense, we have studied a mutant (fad3–2 fad7–2 fad8) that is deficient in the jasmonate precursor linolenic acid. Mutant plants contained negligible levels of jasmonate and showed extremely high mortality (≈80%) from attack by larvae of a common saprophagous fungal gnat, Bradysia impatiens (Diptera: Sciaridae), even though neighboring wild-type plants were largely unaffected. Application of exogenous methyl jasmonate substantially protected the mutant plants and reduced mortality to ≈12%. These experiments precisely define the role of jasmonate as being essential for the induction of biologically effective defense in this plant–insect interaction. The transcripts of three wound-responsive genes were shown not to be induced by wounding of mutant plants but the same transcripts could be induced by application of methyl jasmonate. By contrast, measurements of transcript levels for a gene encoding glutathione S-transferase demonstrated that wound induction of this gene is independent of jasmonate synthesis. These results indicate that the mutant will be a good genetic model for testing the practical effectiveness of candidate defense genes. PMID:11038546

Network motif frequency vectors reveal evolving metabolic network organisation.

PubMed

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

2015-01-01

At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

Plastic Transcriptomes Stabilize Immunity to Pathogen Diversity: The Jasmonic Acid and Salicylic Acid Networks within the Arabidopsis/Botrytis Pathosystem[OPEN

PubMed Central

Eshbaugh, Robert; Chen, Fang; Atwell, Susana

2017-01-01

To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem to test how the host’s defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA- and SA-signaling mutants, coi1-1 and npr1-1, individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene coexpression networks and two vectors of defense variation triggered by genetic variation in B. cinerea. This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen. PMID:29042403

Benefits of jasmonate-dependent defenses against vertebrate herbivores in nature.

PubMed

Machado, Ricardo Ar; McClure, Mark; Hervé, Maxime R; Baldwin, Ian T; Erb, Matthias

2016-06-29

Endogenous jasmonates are important regulators of plant defenses. If and how they enable plants to maintain their reproductive output when facing community-level herbivory under natural conditions, however, remains unknown. We demonstrate that jasmonate-deficient Nicotiana attenuata plants suffer more damage by arthropod and vertebrate herbivores than jasmonate-producing plants in nature. However, only damage by vertebrate herbivores translates into a significant reduction in flower production. Vertebrate stem peeling has the strongest negative impact on plant flower production. Stems are defended by jasmonate-dependent nicotine, and the native cottontail rabbit Sylvilagus nuttallii avoids jasmonate-producing N. attenuata shoots because of their high levels of nicotine. Thus, endogenous jasmonates enable plants to resist different types of herbivores in nature, and jasmonate-dependent defenses are important for plants to maintain their reproductive potential when facing vertebrate herbivory. Ecological and evolutionary models on plant defense signaling should aim at integrating arthropod and vertebrate herbivory at the community level.

Benefits of jasmonate-dependent defenses against vertebrate herbivores in nature

PubMed Central

Machado, Ricardo AR; McClure, Mark; Hervé, Maxime R; Baldwin, Ian T; Erb, Matthias

2016-01-01

Endogenous jasmonates are important regulators of plant defenses. If and how they enable plants to maintain their reproductive output when facing community-level herbivory under natural conditions, however, remains unknown. We demonstrate that jasmonate-deficient Nicotiana attenuata plants suffer more damage by arthropod and vertebrate herbivores than jasmonate-producing plants in nature. However, only damage by vertebrate herbivores translates into a significant reduction in flower production. Vertebrate stem peeling has the strongest negative impact on plant flower production. Stems are defended by jasmonate-dependent nicotine, and the native cottontail rabbit Sylvilagus nuttallii avoids jasmonate-producing N. attenuata shoots because of their high levels of nicotine. Thus, endogenous jasmonates enable plants to resist different types of herbivores in nature, and jasmonate-dependent defenses are important for plants to maintain their reproductive potential when facing vertebrate herbivory. Ecological and evolutionary models on plant defense signaling should aim at integrating arthropod and vertebrate herbivory at the community level. DOI: http://dx.doi.org/10.7554/eLife.13720.001 PMID:27352734

Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction: COMMUNITY DATA-DRIVEN METABOLIC NETWORK MODELING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henry, Christopher S.; Bernstein, Hans C.; Weisenhorn, Pamela

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 networkmore » 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.« less

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

PubMed

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

2010-06-01

The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level. Copyright 2010 Elsevier Inc. All rights reserved.

Emerging roles in plant defense for cis-jasmone-induced cytochrome P450 CYP81D11.

PubMed

Matthes, Michaela; Bruce, Toby; Chamberlain, Keith; Pickett, John; Napier, Johnathan

2011-04-01

cis-Jasmone is a volatile organic compound emitted constitutively by flowers or leaves of several plant species where it acts as an attractant for pollinators and as a chemical cue for host localisation (or avoidance) for insects. ( 1-3) It is also released by some plant species after feeding damage inflicted by herbivorous insects and in this case might serve as a chemical cue for parasitoids to guide them to their prey (so called "indirect defense"). ( 4,5) Moreover, we have recently shown that plants can perceive cis-jasmone and that it acts as a signaling molecule in A. thaliana, inducing a discrete and distinctive suite of genes, of which a large subset is putatively involved in metabolism and defense responses. ( 6) Cytochrome P450s feature prominently in these functional subsets and of these the highest fold change upon cis-jasmone treatment occurred with the cytochrome CYP81D11 (At3g28740). ( 6) Hence this gene was chosen for a more thorough analysis of the potential biological relevance of the cis-jasmone induced defense response. Although the precise function of CYP81D11 remains to be determined, we could previously demonstrate its involvement in the indirect defense response in Arabidopsis, as plants exposed to cis-jasmone ceased to be attractive to the aphid parasitoid Aphidius ervi when this P450 was inactivated by T-DNA insertion mutagenesis. ( 6) Here we report additional experiments which give further support to a role of CYP81D11 in the direct or indirect defense response of A. thaliana.

CYP94-mediated jasmonoyl-isoleucine hormone oxidation shapes jasmonate profiles and attenuates defence responses to Botrytis cinerea infection

PubMed Central

Aubert, Yann; Widemann, Emilie; Miesch, Laurence; Pinot, Franck; Heitz, Thierry

2015-01-01

Induced resistance to the necrotrophic pathogen Botrytis cinerea depends on jasmonate metabolism and signalling in Arabidopsis. We have presented here extensive jasmonate profiling in this pathosystem and investigated the impact of the recently reported jasmonoyl-isoleucine (JA-Ile) catabolic pathway mediated by cytochrome P450 (CYP94) enzymes. Using a series of mutant and overexpressing (OE) plant lines, we showed that CYP94B3 and CYP94C1 are integral components of the fungus-induced jasmonate metabolic pathway and control the abundance of oxidized conjugated but also some unconjugated derivatives, such as sulfated 12-HSO4-JA. Despite causing JA-Ile overaccumulation due to impaired oxidation, CYP94 deficiency had negligible impacts on resistance, associated with enhanced JAZ repressor transcript levels. In contrast, plants overexpressing (OE) CYP94B3 or CYP94C1 were enriched in 12-OH-JA-Ile or 12-COOH-JA-Ile respectively. This shift towards oxidized JA-Ile derivatives was concomitant with strongly impaired defence gene induction and reduced disease resistance. CYP94B3-OE, but unexpectedly not CYP94C1-OE, plants displayed reduced JA-Ile levels compared with the wild type, suggesting that increased susceptibility in CYP94C1-OE plants may result from changes in the hormone oxidation ratio rather than absolute changes in JA-Ile levels. Consistently, while feeding JA-Ile to seedlings triggered strong induction of JA pathway genes, induction was largely reduced or abolished after feeding with the CYP94 products 12-OH-JA-Ile and 12-COOH-JA-Ile, respectively. This trend paralleled in vitro pull-down assays where 12-COOH-JA-Ile was unable to promote COI1–JAZ9 co-receptor assembly. Our results highlight the dual function of CYP94B3/C1 in antimicrobial defence: by controlling hormone oxidation status for signal attenuation, these enzymes also define JA-Ile as a metabolic hub directing jasmonate profile complexity. PMID:25903915

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong

2014-12-10

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Jasmonates act positively in adventitious root formation in petunia cuttings.

PubMed

Lischweski, Sandra; Muchow, Anne; Guthörl, Daniela; Hause, Bettina

2015-09-22

Petunia is a model to study the process of adventitious root (AR) formation on leafy cuttings. Excision of cuttings leads to a transient increase in jasmonates, which is regarded as an early, transient and critical event for rooting. Here, the role of jasmonates in AR formation on petunia cuttings has been studied by a reverse genetic approach. To reduce the endogenous levels of jasmonates, transgenic plants were generated expressing a Petunia hybrida ALLENE OXIDE CYCLASE (PhAOC)-RNAi construct. The transgenic plants exhibited strongly reduced PhAOC transcript and protein levels as well as diminished accumulation of cis-12-oxo-phytodienoic acid, jasmonic acid and jasmonoyl-isoleucine after wounding in comparison to wild type and empty vector expressing plants. Reduced levels of endogenous jasmonates resulted in formation of lower numbers of ARs. However, this effect was not accompanied by altered levels of auxin and aminocyclopropane carboxylate (ACC, precursor of ethylene) or by impaired auxin and ethylene-induced gene expression. Neither activity of cell-wall invertases nor accumulation of soluble sugars was altered by jasmonate deficiency. Diminished numbers of AR in JA-deficient cuttings suggest that jasmonates act as positive regulators of AR formation in petunia wild type. However, wound-induced rise in jasmonate levels in petunia wild type cuttings seems not to be causal for increased auxin and ethylene levels and for sink establishment.

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

PubMed Central

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

2011-01-01

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

Inference and Prediction of Metabolic Network Fluxes

PubMed Central

Nikoloski, Zoran; Perez-Storey, Richard; Sweetlove, Lee J.

2015-01-01

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping. PMID:26392262

Environmental versatility promotes modularity in genome-scale metabolic networks.

PubMed

Samal, Areejit; Wagner, Andreas; Martin, Olivier C

2011-08-24

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. 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. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple

Polyphenolic responses of grapevine berries to light, temperature, oxidative stress, abscisic acid and jasmonic acid show specific developmental-dependent degrees of metabolic resilience to perturbation.

PubMed

Degu, Asfaw; Ayenew, Biruk; Cramer, Grant R; Fait, Aaron

2016-12-01

Grape-berries are exposed to a plethora of abiotic and biotic stimuli during their development. The developmental and temporal regulation of grape berry polyphenol metabolism in response to various cues was investigated using LC-QTOF-MS based metabolite profiling. High light (2500μmolm(-2)s(-1)), high temperature (40°C), jasmonic acid (200μM), menadione (120μM) and abscisic acid (3.026mM) treatments were applied to detached berries. Greater magnitudes of metabolite fluctuations characterize the pre-veraison berries than the veraison stage in response to the treatments. Furthermore, a tighter co-response of metabolic processes was shown at veraison, likely supporting the resilience to change in response to stress. High temperature and ABA treatments led to greater magnitudes of change during the course of the experiment. The present study demonstrates the occurrence of differential patterns of metabolic responses specific to individual cues and berry developmental stage, which in the field are commonly associated and thus hardly discernable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolic network modeling with model organisms.

PubMed

Yilmaz, L Safak; Walhout, Albertha Jm

2017-02-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. Published by Elsevier Ltd.

Metabolic network modeling with model organisms

PubMed Central

Yilmaz, L. Safak; Walhout, Albertha J.M.

2017-01-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. PMID:28088694

Metabolic brain networks in aging and preclinical Alzheimer's disease.

PubMed

Arnemann, Katelyn L; Stöber, Franziska; Narayan, Sharada; Rabinovici, Gil D; Jagust, William J

2018-01-01

Metabolic brain networks can provide insight into the network processes underlying progression from healthy aging to Alzheimer's disease. We explore the effect of two Alzheimer's disease risk factors, amyloid-β and ApoE ε4 genotype, on metabolic brain networks in cognitively normal older adults (N = 64, ages 69-89) compared to young adults (N = 17, ages 20-30) and patients with Alzheimer's disease (N = 22, ages 69-89). Subjects underwent MRI and PET imaging of metabolism (FDG) and amyloid-β (PIB). Normal older adults were divided into four subgroups based on amyloid-β and ApoE genotype. Metabolic brain networks were constructed cross-sectionally by computing pairwise correlations of metabolism across subjects within each group for 80 regions of interest. We found widespread elevated metabolic correlations and desegregation of metabolic brain networks in normal aging compared to youth and Alzheimer's disease, suggesting that normal aging leads to widespread loss of independent metabolic function across the brain. Amyloid-β and the combination of ApoE ε4 led to less extensive elevated metabolic correlations compared to other normal older adults, as well as a metabolic brain network more similar to youth and Alzheimer's disease. This could reflect early progression towards Alzheimer's disease in these individuals. Altered metabolic brain networks of older adults and those at the highest risk for progression to Alzheimer's disease open up novel lines of inquiry into the metabolic and network processes that underlie normal aging and Alzheimer's disease.

Detecting breakdown points in metabolic networks.

PubMed

Tagore, Somnath; De, Rajat K

2011-12-14

A complex network of biochemical reactions present in an organism generates various biological moieties necessary for its survival. It is seen that biological systems are robust to genetic and environmental changes at all levels of organization. Functions of various organisms are sustained against mutational changes by using alternative pathways. It is also seen that if any one of the paths for production of the same metabolite is hampered, an alternate path tries to overcome this defect and helps in combating the damage. Certain physical, chemical or genetic change in any of the precursor substrate of a biochemical reaction may damage the production of the ultimate product. We employ a quantitative approach for simulating this phenomena of causing a physical change in the biochemical reactions by performing external perturbations to 12 metabolic pathways under carbohydrate metabolism in Saccharomyces cerevisae as well as 14 metabolic pathways under carbohydrate metabolism in Homo sapiens. Here, we investigate the relationship between structure and degree of compatibility of metabolites against external perturbations, i.e., robustness. Robustness can also be further used to identify the extent to which a metabolic pathway can resist a mutation event. Biological networks with a certain connectivity distribution may be very resilient to a particular attack but not to another. The goal of this work is to determine the exact boundary of network breakdown due to both random and targeted attack, thereby analyzing its robustness. We also find that compared to various non-standard models, metabolic networks are exceptionally robust. Here, we report the use of a 'Resilience-based' score for enumerating the concept of 'network-breakdown'. We also use this approach for analyzing metabolite essentiality providing insight into cellular robustness that can be further used for future drug development. We have investigated the behavior of metabolic pathways under carbohydrate

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

PubMed

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

2009-12-01

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

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks.

PubMed

Filho, Humberto A; Machicao, Jeaneth; Bruno, Odemir M

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks

PubMed Central

Filho, Humberto A.; Machicao, Jeaneth

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology. PMID:29734359

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

PubMed

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

2016-01-01

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

Steady states and stability in metabolic networks without regulation.

PubMed

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

2016-07-21

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

Deficiencies in Jasmonate-Mediated Plant Defense Reveal Quantitative Variation in Botrytis cinerea Pathogenesis

PubMed Central

Rowe, Heather C.; Walley, Justin W.; Corwin, Jason; Chan, Eva K.-F.; Dehesh, Katayoon; Kliebenstein, Daniel J.

2010-01-01

Despite the described central role of jasmonate signaling in plant defense against necrotrophic pathogens, the existence of intraspecific variation in pathogen capacity to activate or evade plant jasmonate-mediated defenses is rarely considered. Experimental infection of jasmonate-deficient and jasmonate-insensitive Arabidopsis thaliana with diverse isolates of the necrotrophic fungal pathogen Botrytis cinerea revealed pathogen variation for virulence inhibition by jasmonate-mediated plant defenses and induction of plant defense metabolites. Comparison of the transcriptional effects of infection by two distinct B. cinerea isolates showed only minor differences in transcriptional responses of wild-type plants, but notable isolate-specific transcript differences in jasmonate-insensitive plants. These transcriptional differences suggest B. cinerea activation of plant defenses that require plant jasmonate signaling for activity in response to only one of the two B. cinerea isolates tested. Thus, similar infection phenotypes observed in wild-type plants result from different signaling interactions with the plant that are likely integrated by jasmonate signaling. PMID:20419157

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

NASA Astrophysics Data System (ADS)

Almaas, Eivind

2008-03-01

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

A Jasmonate ZIM-Domain Protein NaJAZd Regulates Floral Jasmonic Acid Levels and Counteracts Flower Abscission in Nicotiana attenuata Plants

PubMed Central

Oh, Youngjoo; Baldwin, Ian T.; Galis, Ivan

2013-01-01

Jasmonic acid is an important regulator of plant growth, development and defense. The jasmonate-ZIM domain (JAZ) proteins are key regulators in jasmonate signaling ubiquitously present in flowering plants but their functional annotation remains largely incomplete. Recently, we identified 12 putative JAZ proteins in native tobacco, Nicotiana attenuata, and initiated systematic functional characterization of these proteins by reverse genetic approaches. In this report, Nicotiana attenuata plants silenced in the expression of NaJAZd (irJAZd) by RNA interference were used to characterize NaJAZd function. Although NaJAZd transcripts were strongly and transiently up-regulated in the rosette leaves by simulated herbivory treatment, we did not observe strong defense-related phenotypes, such as altered herbivore performance or the constitutive accumulation of defense-related secondary metabolites in irJAZd plants compared to wild type plants, both in the glasshouse and the native habitat of Nicotiana attenuata in the Great Basin Desert, Utah, USA. Interestingly, irJAZd plants produced fewer seed capsules than did wild type plants as a result of increased flower abscission in later stages of flower development. The early- and mid-developmental stages of irJAZd flowers had reduced levels of jasmonic acid and jasmonoyl-L-isoleucine, while fully open flowers had normal levels, but these were impaired in NaMYB305 transcript accumulations. Previously, NaMYB305-silenced plants were shown to have strong flower abscission phenotypes and contained lower NECTARIN 1 transcript levels, phenotypes which are copied in irJAZd plants. We propose that the NaJAZd protein is required to counteract flower abscission, possibly by regulating jasmonic acid and jasmonoyl-L-isoleucine levels and/or expression of NaMYB305 gene in Nicotiana attenuata flowers. This novel insight into the function of JAZ proteins in flower and seed development highlights the diversity of functions played by jasmonates

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

PubMed

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

2010-08-01

With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. Copyright © 2010 Elsevier Ltd. All rights reserved.

Chemical Approaches to Probe Metabolic Networks

PubMed Central

Medina-Cleghorn, Daniel; Nomura, Daniel K.

2013-01-01

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

Control of fluxes in metabolic networks

PubMed Central

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

2016-01-01

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

Control of fluxes in metabolic networks.

PubMed

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

2016-07-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. © 2016 Basler et al.; Published by Cold Spring Harbor Laboratory Press.

Beyond topology: coevolution of structure and flux in metabolic networks.

PubMed

Morrison, E S; Badyaev, A V

2017-10-01

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Fruit metabolite networks in engineered and non-engineered tomato genotypes reveal fluidity in a hormone and agroecosystem specific manner.

PubMed

Fatima, Tahira; Sobolev, Anatoly P; Teasdale, John R; Kramer, Matthew; Bunce, Jim; Handa, Avtar K; Mattoo, Autar K

Metabolomics provides a view of endogenous metabolic patterns not only during plant growth, development and senescence but also in response to genetic events, environment and disease. The effects of the field environment on plant hormone-specific metabolite profiles are largely unknown. Few studies have analyzed useful phenotypes generated by introducing single or multiple gene events alongside the non-engineered wild type control at field scale to determine the robustness of the genetic trait and its modulation in the metabolome as a function of specific agroecosystem environments. We evaluated the influence of genetic background (high polyamine lines; low methyl jasmonate line; low ethylene line; and isogenic genotypes carrying double transgenic events) and environments (hairy vetch, rye, plastic black mulch and bare soil mulching systems) on the metabolomic profile of isogenic reverse genetic mutations and selected mulch based cropping systems in tomato fruit. Net photosynthesis and fruit yield were also determined. NMR spectroscopy was used for quantifying metabolites that are central to primary metabolism. We analyzed both the first moment (means) of metabolic response to genotypes and agroecosystems by traditional univariate/multivariate methods, and the second moment (covariances) of responses by creating networks that depicted changes in correlations of paired metabolites. This particular approach is novel and was necessary because our experimental material yielded highly variable metabolic responses that could not be easily understood using the traditional analytical approaches for first moment statistics. High endogenous spermidine and spermine content exhibited strong effects on amino acids, Krebs cycle intermediates and energy molecules (ADP + ATP) in ripening fruits of plants grown under different agroecosystem environments. The metabolic response to high polyamine genotypes was similar to the response to hairy vetch cover crop mulch; supported by

The large-scale organization of metabolic networks

NASA Astrophysics Data System (ADS)

Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z. N.; Barabási, A.-L.

2000-10-01

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

Jasmonate perception by inositol-phosphate-potentiated COI1-JAZ co-receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheard, Laura B; Tan, Xu; Mao, Haibin

2011-11-07

Jasmonates are a family of plant hormones that regulate plant growth, development and responses to stress. The F-box protein CORONATINE INSENSITIVE 1 (COI1) mediates jasmonate signalling by promoting hormone-dependent ubiquitylation and degradation of transcriptional repressor JAZ proteins. Despite its importance, the mechanism of jasmonate perception remains unclear. Here we present structural and pharmacological data to show that the true Arabidopsis jasmonate receptor is a complex of both COI1 and JAZ. COI1 contains an open pocket that recognizes the bioactive hormone (3R,7S)-jasmonoyl-l-isoleucine (JA-Ile) with high specificity. High-affinity hormone binding requires a bipartite JAZ degron sequence consisting of a conserved {alpha}-helix formore » COI1 docking and a loop region to trap the hormone in its binding pocket. In addition, we identify a third critical component of the jasmonate co-receptor complex, inositol pentakisphosphate, which interacts with both COI1 and JAZ adjacent to the ligand. Our results unravel the mechanism of jasmonate perception and highlight the ability of F-box proteins to evolve as multi-component signalling hubs.« less

FCDECOMP: decomposition of metabolic networks based on flux coupling relations.

PubMed

Rezvan, Abolfazl; Marashi, Sayed-Amir; Eslahchi, Changiz

2014-10-01

A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.

Jasmonic acid/methyl jasmonate accumulate in wounded soybean hypocotyls and modulate wound gene expression.

PubMed

Creelman, R A; Tierney, M L; Mullet, J E

1992-06-01

Jasmonic acid (JA) and its methyl ester, methyl jasmonate (MeJA), are plant lipid derivatives that resemble mammalian eicosanoids in structure and biosynthesis. These compounds are proposed to play a role in plant wound and pathogen responses. Here we report the quantitative determination of JA/MeJA in planta by a procedure based on the use of [13C,2H3]MeJA as an internal standard. Wounded soybean (Glycine max [L] Merr. cv. Williams) stems rapidly accumulated MeJA and JA. Addition of MeJA to soybean suspension cultures also increased mRNA levels for three wound-responsive genes (chalcone synthase, vegetative storage protein, and proline-rich cell wall protein) suggesting a role for MeJA/JA in the mediation of several changes in gene expression associated with the plants' response to wounding.

Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis

PubMed Central

Li, Dapeng; Baldwin, Ian T.; Gaquerel, Emmanuel

2015-01-01

Natural variation can be extremely useful in unraveling the determinants of phenotypic trait evolution but has rarely been analyzed with unbiased metabolic profiling to understand how its effects are organized at the level of biochemical pathways. Native populations of Nicotiana attenuata, a wild tobacco species, have been shown to be highly genetically diverse for traits important for their interactions with insects. To resolve the chemodiversity existing in these populations, we developed a metabolomics and computational pipeline to annotate leaf metabolic responses to Manduca sexta herbivory. We selected seeds from 43 accessions of different populations from the southwestern United States—including the well-characterized Utah 30th generation inbred accession—and grew 183 plants in the glasshouse for standardized herbivory elicitation. Metabolic profiles were generated from elicited leaves of each plant using a high-throughput ultra HPLC (UHPLC)-quadrupole TOFMS (qTOFMS) method, processed to systematically infer covariation patterns among biochemically related metabolites, as well as unknown ones, and finally assembled to map natural variation. Navigating this map revealed metabolic branch-specific variations that surprisingly only partly overlapped with jasmonate accumulation polymorphisms and deviated from canonical jasmonate signaling. Fragmentation analysis via indiscriminant tandem mass spectrometry (idMS/MS) was conducted with 10 accessions that spanned a large proportion of the variance found in the complete accession dataset, and compound spectra were computationally assembled into spectral similarity networks. The biological information captured by this networking approach facilitates the mining of the mass spectral data of unknowns with high natural variation, as demonstrated by the annotation of a strongly herbivory-inducible phenolic derivative, and can guide pathway analysis. PMID:26170304

Continuous exposure to the deterrents cis-jasmone and methyl jasmonate does not alter the behavioural responses of Frankliniella occidentalis.

PubMed

Egger, Barbara; Spangl, Bernhard; Koschier, Elisabeth Helene

2016-01-01

Behavioural responses of Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), a generalist, cell sap-feeding insect species with piercing-sucking mouthparts, after continuous exposure to two deterrent secondary plant compounds are investigated. We compared in choice assays on bean leaf discs, the settling, feeding, and oviposition preferences of F. occidentalis females that had no experience with the two fatty acid derivatives methyl jasmonate and cis -jasmone before testing (naïve thrips) vs. females that had been exposed to the deterrent compounds before testing (experienced thrips). The thrips were exposed to the deterrents at low or high concentrations for varied time periods and subsequently tested on bean leaf discs treated with the respective deterrent at either a low or a high concentration. Frankliniella occidentalis females avoided settling on the deterrent-treated bean leaf discs for an observation period of 6 h, independent of their previous experience. Our results demonstrate that feeding and oviposition deterrence of the jasmonates to the thrips were not altered by continuous exposure of the thrips to the jasmonates. Habituation was not induced, neither by exposure to the low concentration of the deterrents nor by exposure to the high concentration. These results indicate that the risk of habituation to two volatile deterrent compounds after repeated exposure is not evident in F. occidentalis . This makes the two compounds potential candidates to be integrated in pest management strategies.

Multi-equilibrium property of metabolic networks: SSI module.

PubMed

Lei, Hong-Bo; Zhang, Ji-Feng; Chen, Luonan

2011-06-20

Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Roles of jasmonate signalling in plant inflorescence and flower development.

PubMed

Yuan, Zheng; Zhang, Dabing

2015-10-01

Development of inflorescences and flowers in plants is controlled by the combined action of environmental and genetic signals. Investigations reveal that the phytohormone jasmonate (JA) plays a critical function in plant reproduction such as male fertility, sex determination and seed maturation. Here, we review recent progress on JA synthesis, signalling, the interplay between JAs and other hormones, and regulatory network of JA in controlling the development of inflorescence, flower and the male organ. The conserved and diversified roles of JAs in meristem transition and specification of flower organ identity and number, and multiple regulatory networks of JAs in stamen development are highlighted. Further, this review provides perspectives on future research endeavors to elucidate mechanisms underlying JAs homeostasis and transport during plant reproductive development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

PubMed Central

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE PAGES

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-11-21

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

PubMed

Haraldsdóttir, Hulda S; Fleming, Ronan M T

2016-11-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.

Effect of methyl jasmonate on sugarbeet yield and storage properties

USDA-ARS?s Scientific Manuscript database

Methyl jasmonate is an endogenous plant hormone that induces plant defense mechanisms against environmental stresses and pathogens. Applied exogenously, methyl jasmonate has been shown to provide protection against a wide array of pathogens and environmental stresses in a variety of crop plants and ...

Jasmonic acid/methyl jasmonate accumulate in wounded soybean hypocotyls and modulate wound gene expression.

PubMed Central

Creelman, R A; Tierney, M L; Mullet, J E

1992-01-01

Jasmonic acid (JA) and its methyl ester, methyl jasmonate (MeJA), are plant lipid derivatives that resemble mammalian eicosanoids in structure and biosynthesis. These compounds are proposed to play a role in plant wound and pathogen responses. Here we report the quantitative determination of JA/MeJA in planta by a procedure based on the use of [13C,2H3]MeJA as an internal standard. Wounded soybean (Glycine max [L] Merr. cv. Williams) stems rapidly accumulated MeJA and JA. Addition of MeJA to soybean suspension cultures also increased mRNA levels for three wound-responsive genes (chalcone synthase, vegetative storage protein, and proline-rich cell wall protein) suggesting a role for MeJA/JA in the mediation of several changes in gene expression associated with the plants' response to wounding. Images PMID:1594598

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Decreased Metabolism in the Posterior Medial Network with Concomitantly Increased Metabolism in the Anterior Temporal Network During Transient Global Amnesia.

PubMed

Yi, SangHak; Park, Young Ho; Jang, Jae-Won; Lim, Jae-Sung; Chun, In Kook; Kim, SangYun

2018-05-01

Perturbation of corticohippocampal circuits is a key step in the pathogenesis of transient global amnesia. We evaluated the spatial distribution of altered cerebral metabolism to determine the location of the corticohippocampal circuits perturbed during the acute stage of transient global amnesia. A consecutive series of 12 patients with transient global amnesia who underwent 18 F-fluorodeoxyglucose positron emission tomography within 3 days after symptom onset was identified. We used statistical parametric mapping with two contrasts to identify regions of decreased and increased brain metabolism in transient global amnesia patients compared with 25 age-matched controls. Transient global amnesia patients showed hypometabolic clusters in the left temporal and bilateral parieto-occipital regions that belong to the posterior medial network as well as, hypermetabolic clusters in the bilateral inferior frontal regions that belong to the anterior temporal network. The posterior medial and anterior temporal networks are the two main corticohippocampal circuits involved in memory-guided behavior. Decreased metabolism in the posterior medial network might explain the impairment of episodic memory observed during the acute stage of transient global amnesia. Concomitant increased metabolism within the anterior temporal network might occur as a compensatory mechanism.

Multi-equilibrium property of metabolic networks: SSI module

PubMed Central

2011-01-01

Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module. PMID:21689474

Continuous exposure to the deterrents cis-jasmone and methyl jasmonate does not alter the behavioural responses of Frankliniella occidentalis

PubMed Central

Egger, Barbara; Spangl, Bernhard; Koschier, Elisabeth Helene

2016-01-01

Behavioural responses of Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), a generalist, cell sap-feeding insect species with piercing-sucking mouthparts, after continuous exposure to two deterrent secondary plant compounds are investigated. We compared in choice assays on bean leaf discs, the settling, feeding, and oviposition preferences of F. occidentalis females that had no experience with the two fatty acid derivatives methyl jasmonate and cis-jasmone before testing (naïve thrips) vs. females that had been exposed to the deterrent compounds before testing (experienced thrips). The thrips were exposed to the deterrents at low or high concentrations for varied time periods and subsequently tested on bean leaf discs treated with the respective deterrent at either a low or a high concentration. Frankliniella occidentalis females avoided settling on the deterrent-treated bean leaf discs for an observation period of 6 h, independent of their previous experience. Our results demonstrate that feeding and oviposition deterrence of the jasmonates to the thrips were not altered by continuous exposure of the thrips to the jasmonates. Habituation was not induced, neither by exposure to the low concentration of the deterrents nor by exposure to the high concentration. These results indicate that the risk of habituation to two volatile deterrent compounds after repeated exposure is not evident in F. occidentalis. This makes the two compounds potential candidates to be integrated in pest management strategies. PMID:26726263

Metabolic network visualization eliminating node redundance and preserving metabolic pathways

PubMed Central

Bourqui, Romain; Cottret, Ludovic; Lacroix, Vincent; Auber, David; Mary, Patrick; Sagot, Marie-France; Jourdan, Fabien

2007-01-01

Background The tools that are available to draw and to manipulate the representations of metabolism are usually restricted to metabolic pathways. This limitation becomes problematic when studying processes that span several pathways. The various attempts that have been made to draw genome-scale metabolic networks are confronted with two shortcomings: 1- they do not use contextual information which leads to dense, hard to interpret drawings, 2- they impose to fit to very constrained standards, which implies, in particular, duplicating nodes making topological analysis considerably more difficult. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. PMID:17608928

Fluxes through plant metabolic networks: measurements, predictions, insights and challenges.

PubMed

Kruger, Nicholas J; Ratcliffe, R George

2015-01-01

Although the flows of material through metabolic networks are central to cell function, they are not easy to measure other than at the level of inputs and outputs. This is particularly true in plant cells, where the network spans multiple subcellular compartments and where the network may function either heterotrophically or photoautotrophically. For many years, kinetic modelling of pathways provided the only method for describing the operation of fragments of the network. However, more recently, it has become possible to map the fluxes in central carbon metabolism using the stable isotope labelling techniques of metabolic flux analysis (MFA), and to predict intracellular fluxes using constraints-based modelling procedures such as flux balance analysis (FBA). These approaches were originally developed for the analysis of microbial metabolism, but over the last decade, they have been adapted for the more demanding analysis of plant metabolic networks. Here, the principal features of MFA and FBA as applied to plants are outlined, followed by a discussion of the insights that have been gained into plant metabolic networks through the application of these time-consuming and non-trivial methods. The discussion focuses on how a system-wide view of plant metabolism has increased our understanding of network structure, metabolic perturbations and the provision of reducing power and energy for cell function. Current methodological challenges that limit the scope of plant MFA are discussed and particular emphasis is placed on the importance of developing methods for cell-specific MFA.

On Functional Module Detection in Metabolic Networks

PubMed Central

Koch, Ina; Ackermann, Jörg

2013-01-01

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

CardioNet: a human metabolic network suited for the study of cardiomyocyte metabolism.

PubMed

Karlstädt, Anja; Fliegner, Daniela; Kararigas, Georgios; Ruderisch, Hugo Sanchez; Regitz-Zagrosek, Vera; Holzhütter, Hermann-Georg

2012-08-29

Availability of oxygen and nutrients in the coronary circulation is a crucial determinant of cardiac performance. Nutrient composition of coronary blood may significantly vary in specific physiological and pathological conditions, for example, administration of special diets, long-term starvation, physical exercise or diabetes. Quantitative analysis of cardiac metabolism from a systems biology perspective may help to a better understanding of the relationship between nutrient supply and efficiency of metabolic processes required for an adequate cardiac output. Here we present CardioNet, the first large-scale reconstruction of the metabolic network of the human cardiomyocyte comprising 1793 metabolic reactions, including 560 transport processes in six compartments. We use flux-balance analysis to demonstrate the capability of the network to accomplish a set of 368 metabolic functions required for maintaining the structural and functional integrity of the cell. Taking the maintenance of ATP, biosynthesis of ceramide, cardiolipin and further important phospholipids as examples, we analyse how a changed supply of glucose, lactate, fatty acids and ketone bodies may influence the efficiency of these essential processes. CardioNet is a functionally validated metabolic network of the human cardiomyocyte that enables theorectical studies of cellular metabolic processes crucial for the accomplishment of an adequate cardiac output.

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

PubMed

Bardoscia, Marco; Marsili, Matteo; Samal, Areejit

2015-07-01

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

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism.

PubMed

Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E

2007-12-01

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.

Mapping methyl jasmonate-mediated transcriptional reprogramming of metabolism and cell cycle progression in cultured Arabidopsis cells

PubMed Central

Pauwels, Laurens; Morreel, Kris; De Witte, Emilie; Lammertyn, Freya; Van Montagu, Marc; Boerjan, Wout; Inzé, Dirk; Goossens, Alain

2008-01-01

Jasmonates (JAs) are plant-specific signaling molecules that steer a diverse set of physiological and developmental processes. Pathogen attack and wounding inflicted by herbivores induce the biosynthesis of these hormones, triggering defense responses both locally and systemically. We report on alterations in the transcriptome of a fast-dividing cell culture of the model plant Arabidopsis thaliana after exogenous application of methyl JA (MeJA). Early MeJA response genes encoded the JA biosynthesis pathway proteins and key regulators of MeJA responses, including most JA ZIM domain proteins and MYC2, together with transcriptional regulators with potential, but yet unknown, functions in MeJA signaling. In a second transcriptional wave, MeJA reprogrammed cellular metabolism and cell cycle progression. Up-regulation of the monolignol biosynthesis gene set resulted in an increased production of monolignols and oligolignols, the building blocks of lignin. Simultaneously, MeJA repressed activation of M-phase genes, arresting the cell cycle in G2. MeJA-responsive transcription factors were screened for their involvement in early signaling events, in particular the regulation of JA biosynthesis. Parallel screens based on yeast one-hybrid and transient transactivation assays identified both positive (MYC2 and the AP2/ERF factor ORA47) and negative (the C2H2 Zn finger proteins STZ/ZAT10 and AZF2) regulators, revealing a complex control of the JA autoregulatory loop and possibly other MeJA-mediated downstream processes. PMID:18216250

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

PubMed Central

Martín-Jiménez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; González, Janneth

2017-01-01

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework to elucidate how astrocytes modulate human brain metabolic states during normal conditions and in neurodegenerative diseases. We performed a Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network with the purpose of elucidating a significant portion of the metabolic map of the astrocyte. This is the first global high-quality, manually curated metabolic reconstruction network of a human astrocyte. It includes 5,007 metabolites and 5,659 reactions distributed among 8 cell compartments, (extracellular, cytoplasm, mitochondria, endoplasmic reticle, Golgi apparatus, lysosome, peroxisome and nucleus). Using the reconstructed network, the metabolic capabilities of human astrocytes were calculated and compared both in normal and ischemic conditions. We identified reactions activated in these two states, which can be useful for understanding the astrocytic pathways that are affected during brain disease. Additionally, we also showed that the obtained flux distributions in the model, are in accordance with literature-based findings. Up to date, this is the most complete representation of the human astrocyte in terms of inclusion of genes, proteins, reactions and metabolic pathways, being a useful guide for in-silico analysis of several metabolic behaviors of the astrocyte during normal and pathologic states. PMID:28243200

Metabolic Network Modeling of Microbial Communities

PubMed Central

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

2015-01-01

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

Phylogeny of metabolic networks: a spectral graph theoretical approach.

PubMed

Deyasi, Krishanu; Banerjee, Anirban; Deb, Bony

2015-10-01

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

Chloroplast Galactolipids: The Link Between Photosynthesis, Chloroplast Shape, Jasmonates, Phosphate Starvation and Freezing Tolerance.

PubMed

Li, Hsou-Min; Yu, Chun-Wei

2018-06-01

Monogalactosyldiacylglycerol (MGDG) and digalactosyldiacylglycerol (DGDG) together constitute approximately 80% of chloroplast lipids. Apart from facilitating the photosynthesis light reaction in the thylakoid membrane, these two lipids are important for maintaining chloroplast morphology and for plant survival under abiotic stresses such as phosphate starvation and freezing. Recently it was shown that severe growth retardation phenotypes of the DGDG-deficient mutant dgd1 were due to jasmonate overproduction, linking MGDG and DGDG homeostasis with phytohormone production and suggesting MGDG as a major substrate for jasmonate biosynthesis. Induction of jasmonate synthesis and jasmonic acid (JA) signaling was also observed under conditions of phosphate starvation. We hypothesize that when DGDG is recruited to substitute for phospholipids in extraplastidic membranes during phosphate deficiency, the altered MGDG to DGDG ratio in the chloroplast envelope triggers the conversion of galactolipids into jasmonates. The conversion may contribute to rebalancing the MGDG to DGDG ratio rapidly to maintain chloroplast shape, and jasmonate production can reduce the growth rate and enhance predator deterrence. We also hypothesize that other conditions, such as suppression of dgd1 phenotypes by trigalactosyldiacylglycerol (tgd) mutations, may all be linked to altered jasmonate production, indicating that caution should be exercised when interpreting phenotypes caused by conditions that may alter the MGDG to DGDG ratio at the chloroplast envelope.

Effect of methyl jasmonate application to grapevine leaves on grape amino acid content.

PubMed

Garde-Cerdán, Teresa; Portu, Javier; López, Rosa; Santamaría, Pilar

2016-07-15

Over the last few years, considerable attention has been paid to the application of elicitors to vineyard. However, research about the effect of elicitors on grape amino acid content is scarce. Therefore, the aim of this study was to evaluate the influence of foliar application of methyl jasmonate on must amino acid content. Results revealed that total amino acid content was not modified by the application of methyl jasmonate. However, the individual content of certain amino acids was increased as consequence of methyl jasmonate foliar application, i.e., histidine, serine, tryptophan, phenylalanine, tyrosine, asparagine, methionine, and lysine. Among them, phenylalanine content was considerably increased; this amino acid is precursor of phenolic and aromatic compounds. In conclusion, foliar application of methyl jasmonate improved must nitrogen composition. This finding suggests that methyl jasmonate treatment might be conducive to obtain wines of higher quality since must amino acid composition could affect the wine volatile composition and the fermentation kinetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolic networks in epilepsy by MR spectroscopic imaging.

PubMed

Pan, J W; Spencer, D D; Kuzniecky, R; Duckrow, R B; Hetherington, H; Spencer, S S

2012-12-01

The concept of an epileptic network has long been suggested from both animal and human studies of epilepsy. Based on the common observation that the MR spectroscopic imaging measure of NAA/Cr is sensitive to neuronal function and injury, we use this parameter to assess for the presence of a metabolic network in mesial temporal lobe epilepsy (MTLE) patients. A multivariate factor analysis is performed with controls and MTLE patients, using NAA/Cr measures from 12 loci: the bilateral hippocampi, thalami, basal ganglia, and insula. The factor analysis determines which and to what extent these loci are metabolically covarying. We extract two independent factors that explain the data's variability in control and MTLE patients. In controls, these factors characterize a 'thalamic' and 'dominant subcortical' function. The MTLE patients also exhibit a 'thalamic' factor, in addition to a second factor involving the ipsilateral insula and bilateral basal ganglia. These data suggest that MTLE patients demonstrate a metabolic network that involves the thalami, also seen in controls. The MTLE patients also display a second set of metabolically covarying regions that may be a manifestation of the epileptic network that characterizes limbic seizure propagation. © 2012 John Wiley & Sons A/S.

Jasmonate signaling is activated in the very early stages of iron deficiency responses in rice roots.

PubMed

Kobayashi, Takanori; Itai, Reiko Nakanishi; Senoura, Takeshi; Oikawa, Takaya; Ishimaru, Yasuhiro; Ueda, Minoru; Nakanishi, Hiromi; Nishizawa, Naoko K

2016-07-01

Under low iron availability, plants induce the expression of various genes involved in iron uptake and translocation at the transcriptional level. This iron deficiency response is affected by various plant hormones, but the roles of jasmonates in this response are not well-known. We investigated the involvement of jasmonates in rice iron deficiency responses. High rates of jasmonate-inducible genes were induced during the very early stages of iron deficiency treatment in rice roots. Many jasmonate-inducible genes were also negatively regulated by the ubiquitin ligases OsHRZ1 and OsHRZ2 and positively regulated by the transcription factor IDEF1. Ten out of 35 genes involved in jasmonate biosynthesis and signaling were rapidly induced at 3 h of iron deficiency treatment, and this induction preceded that of known iron deficiency-inducible genes involved in iron uptake and translocation. Twelve genes involved in jasmonate biosynthesis and signaling were also upregulated in HRZ-knockdown roots. Endogenous concentrations of jasmonic acid and jasmonoyl isoleucine tended to be rapidly increased in roots in response to iron deficiency treatment, whereas these concentrations were higher in HRZ-knockdown roots under iron-sufficient conditions. Analysis of the jasmonate-deficient cpm2 mutant revealed that jasmonates repress the expression of many iron deficiency-inducible genes involved in iron uptake and translocation under iron sufficiency, but this repression is partly canceled under an early stage of iron deficiency. These results indicate that jasmonate signaling is activated during the very early stages of iron deficiency, which is partly regulated by IDEF1 and OsHRZs.

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright �

Combinatorial complexity of pathway analysis in metabolic networks.

PubMed

Klamt, Steffen; Stelling, Jörg

2002-01-01

Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

Transcriptome-wide analysis of jasmonate-treated BY-2 cells reveals new transcriptional regulators associated with alkaloid formation in tobacco.

PubMed

Yang, Yuping; Yan, Pengcheng; Yi, Che; Li, Wenzheng; Chai, Yuhui; Fei, Lingling; Gao, Ping; Zhao, Heping; Wang, Yingdian; Timko, Michael P; Wang, Bingwu; Han, Shengcheng

2017-08-01

Jasmonates (JAs) are well-known regulators of stress, defence, and secondary metabolism in plants, with JA perception triggering extensive transcriptional reprogramming, including both activation and/or repression of entire metabolic pathways. We performed RNA sequencing based transcriptomic profiling of tobacco BY-2 cells before and after treatment with methyl jasmonate (MeJA) to identify novel transcriptional regulators associated with alkaloid formation. A total of 107,140 unigenes were obtained through de novo assembly, and at least 33,213 transcripts (31%) encode proteins, in which 3419 transcription factors (TFs) were identified, representing 72 gene families, as well as 840 transcriptional regulators (TRs) distributed among 19 gene families. After MeJA treatment BY-2 cells, 7260 differentially expressed transcripts were characterised, which include 4443 MeJA-upregulated and 2817 MeJA-downregulated genes. Of these, 227 TFs/TRs in 36 families were specifically upregulated, and 102 TFs/TRs in 38 families were downregulated in MeJA-treated BY-2 cells. We further showed that the expression of 12 ethylene response factors and four basic helix-loop-helix factors increased at the transcriptional level after MeJA treatment in BY-2 cells and displayed specific expression patterns in nic mutants with or without MeJA treatments. Our data provide a catalogue of transcripts of tobacco BY-2 cells and benefit future study of JA-modulated regulation of secondary metabolism in tobacco. Copyright © 2017 Elsevier GmbH. All rights reserved.

Structuring evolution: biochemical networks and metabolic diversification in birds.

PubMed

Morrison, Erin S; Badyaev, Alexander V

2016-08-25

Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a "global" carotenoid network - comprising of all known enzymatic reactions among naturally occurring carotenoids - with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds. We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network - compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution. The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

Interactive Effects of Jasmonic Acid, Salicylic Acid, and Gibberellin on Induction of Trichomes in Arabidopsis1

PubMed Central

Traw, M. Brian; Bergelson, Joy

2003-01-01

Leaf trichomes protect plants from attack by insect herbivores and are often induced following damage. Hormonal regulation of this plant induction response has not been previously studied. In a series of experiments, we addressed the effects of artificial damage, jasmonic acid, salicylic acid, and gibberellin on induction of trichomes in Arabidopsis. Artificial damage and jasmonic acid caused significant increases in trichome production of leaves. The jar1-1 mutant exhibited normal trichome induction following treatment with jasmonic acid, suggesting that adenylation of jasmonic acid is not necessary. Salicylic acid had a negative effect on trichome production and consistently reduced the effect of jasmonic acid, suggesting negative cross-talk between the jasmonate and salicylate-dependent defense pathways. Interestingly, the effect of salicylic acid persisted in the nim1-1 mutant, suggesting that the Npr1/Nim1 gene is not downstream of salicylic acid in the negative regulation of trichome production. Last, we found that gibberellin and jasmonic acid had a synergistic effect on the induction of trichomes, suggesting important interactions between these two compounds. PMID:14551332

Alternative oxidase (AOX) and phenolic metabolism in methyl jasmonate-treated hairy root cultures of Daucus carota L.

PubMed

Sircar, Debabrata; Cardoso, Hélia G; Mukherjee, Chiranjit; Mitra, Adinpunya; Arnholdt-Schmitt, Birgit

2012-05-01

Methyl-jasmonate (MJ)-treated hairy roots of Daucus carota L. were used to study the influence of alternative oxidase (AOX) in phenylpropanoid metabolism. Phenolic acid accumulation, as well as total flavonoids and lignin content of the MJ-treated hairy roots were decreased by treatment with salicylhydroxamic acid (SHAM), a known inhibitor of AOX. The inhibitory effect of SHAM was concentration dependent. Treatment with propyl gallate (PG), another inhibitor of AOX, also had a similar inhibitory effect on accumulation of phenolic acid, total flavonoids and lignin. The transcript levels of two DcAOX genes (DcAOX2a and DcAOX1a) were monitored at selected post-elicitation time points. A notable rise in the transcript levels of both DcAOX genes was observed preceding the MJ-induced enhanced accumulation of phenolics, flavonoids and lignin. An appreciable increase in phenylalanine ammonia-lyase (PAL) transcript level was also observed prior to enhanced phenolics accumulation. Both DcAOX genes showed differential transcript accumulation patterns after the onset of elicitation. The transcript levels of DcAOX1a and DcAOX2a attained peak at 6hours post elicitation (hpe) and 12hpe, respectively. An increase in the transcript levels of both DcAOX genes preceding the accumulation of phenylpropanoid-derivatives and lignin showed a positive correlation between AOX activity and phenylpropanoid biosynthesis. The results provide important new insight about the influence of AOX in phenylpropanoid biosynthesis. Copyright © 2012 Elsevier GmbH. All rights reserved.

A new network representation of the metabolism to detect chemical transformation modules.

PubMed

Sorokina, Maria; Medigue, Claudine; Vallenet, David

2015-11-14

Metabolism is generally modeled by directed networks where nodes represent reactions and/or metabolites. In order to explore metabolic pathway conservation and divergence among organisms, previous studies were based on graph alignment to find similar pathways. Few years ago, the concept of chemical transformation modules, also called reaction modules, was introduced and correspond to sequences of chemical transformations which are conserved in metabolism. We propose here a novel graph representation of the metabolic network where reactions sharing a same chemical transformation type are grouped in Reaction Molecular Signatures (RMS). RMS were automatically computed for all reactions and encode changes in atoms and bonds. A reaction network containing all available metabolic knowledge was then reduced by an aggregation of reaction nodes and edges to obtain a RMS network. Paths in this network were explored and a substantial number of conserved chemical transformation modules was detected. Furthermore, this graph-based formalism allows us to define several path scores reflecting different biological conservation meanings. These scores are significantly higher for paths corresponding to known metabolic pathways and were used conjointly to build association rules that should predict metabolic pathway types like biosynthesis or degradation. This representation of metabolism in a RMS network offers new insights to capture relevant metabolic contexts. Furthermore, along with genomic context methods, it should improve the detection of gene clusters corresponding to new metabolic pathways.

Identification of jasmonic acid and its methyl ester as gum-inducing factors in tulips.

PubMed

Skrzypek, Edyta; Miyamoto, Kensuke; Saniewski, Marian; Ueda, Junichi

2005-02-01

The purpose of this study was to identify endogenous factors that induce gummosis and to show their role in gummosis in tulip (Tulipa gesneriana L. cv. Apeldoorn) stems. Using procedures to detect endogenous factors that induce gum in the stem of tulips, jasmonic acid (JA) and methyl jasmonate (JA-Me) were successfully identified using gas-liquid chromatography-mass spectrometry. Total amounts of JA and JA-Me designated as jasmonates in tulip stems were also estimated at about 70-80 ng/g fresh weight, using deuterium-labeled jasmonates as internal standards. The application of JA and JA-Me as lanolin pastes substantially induced gums in tulip stems with ethylene production. The application of ethephon, an ethylene-generating compound, however, induced no gummosis although it slightly affected jasmonate content in tulip stems. These results strongly suggest that JA and JA-Me are endogenous factors that induce gummosis in tulip stems.

Estrogen receptors and the metabolic network.

PubMed

Barros, Rodrigo P A; Gustafsson, Jan-Åke

2011-09-07

The metabolic syndrome has reached pandemic level worldwide, and evidence is that estradiol plays a key role in its development. The discovery of the second estrogen receptor, ERβ, in tissues previously not considered targets of estradiol was a breakthrough in endocrinology. In the present review, we discuss how the presence of ERβ and the previously described ERα in tissues involved in glucose and lipid homeostasis (brain, skeletal muscle, adipose tissue, pancreas, liver, and heart) may have important implications to risk factors associated with the metabolic syndrome. Imbalance of ERα/ERβ ratio in this "metabolic network" may lead to the metabolic syndrome. Copyright © 2011 Elsevier Inc. All rights reserved.

Metabolic networks in motion: 13C-based flux analysis

PubMed Central

Sauer, Uwe

2006-01-01

Many properties of complex networks cannot be understood from monitoring the components—not even when comprehensively monitoring all protein or metabolite concentrations—unless such information is connected and integrated through mathematical models. The reason is that static component concentrations, albeit extremely informative, do not contain functional information per se. The functional behavior of a network emerges only through the nonlinear gene, protein, and metabolite interactions across multiple metabolic and regulatory layers. I argue here that intracellular reaction rates are the functional end points of these interactions in metabolic networks, hence are highly relevant for systems biology. Methods for experimental determination of metabolic fluxes differ fundamentally from component concentration measurements; that is, intracellular reaction rates cannot be detected directly, but must be estimated through computer model-based interpretation of stable isotope patterns in products of metabolism. PMID:17102807

Path finding methods accounting for stoichiometry in metabolic networks

PubMed Central

2011-01-01

Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks. PMID:21619601

Jasmonates trigger prey-induced formation of 'outer stomach' in carnivorous sundew plants.

PubMed

Nakamura, Yoko; Reichelt, Michael; Mayer, Veronika E; Mithöfer, Axel

2013-05-22

It has been widely accepted that the growth-related phytohormone auxin is the endogenous signal that initiates bending movements of plant organs. In 1875, Charles Darwin described how the bending movement of leaves in carnivorous sundew species formed an 'outer stomach' that allowed the plants to enclose and digest captured insect prey. About 100 years later, auxin was suggested to be the factor responsible for this movement. We report that prey capture induces both leaf bending and the accumulation of defence-related jasmonate phytohormones. In Drosera capensis fed with fruitflies, within 3 h after prey capture and simultaneous with leaf movement, we detected an increase in jasmonic acid and its isoleucine conjugate. This accumulation was spatially restricted to the bending segment of the leaves. The application of jasmonates alone was sufficient to trigger leaf bending. Only living fruitflies or the body fluids of crushed fruitflies induced leaf curvature; neither dead flies nor mechanical treatment had any effect. Our findings strongly suggest that the formation of the 'outer stomach' in Drosera is a chemonastic movement that is triggered by accumulation of endogenous jasmonates. These results suggest that in carnivorous sundew plants the jasmonate cascade might have been adapted to facilitate carnivory rather than to defend against herbivores.

Metabolic networks evolve towards states of maximum entropy production.

PubMed

Unrean, Pornkamol; Srienc, Friedrich

2011-11-01

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. Copyright © 2011 Elsevier Inc. All rights reserved.

Reconstruction of biological pathways and metabolic networks from in silico labeled metabolites.

PubMed

Hadadi, Noushin; Hafner, Jasmin; Soh, Keng Cher; Hatzimanikatis, Vassily

2017-01-01

Reaction atom mappings track the positional changes of all of the atoms between the substrates and the products as they undergo the biochemical transformation. However, information on atom transitions in the context of metabolic pathways is not widely available in the literature. The understanding of metabolic pathways at the atomic level is of great importance as it can deconvolute the overlapping catabolic/anabolic pathways resulting in the observed metabolic phenotype. The automated identification of atom transitions within a metabolic network is a very challenging task since the degree of complexity of metabolic networks dramatically increases when we transit from metabolite-level studies to atom-level studies. Despite being studied extensively in various approaches, the field of atom mapping of metabolic networks is lacking an automated approach, which (i) accounts for the information of reaction mechanism for atom mapping and (ii) is extendable from individual atom-mapped reactions to atom-mapped reaction networks. Hereby, we introduce a computational framework, iAM.NICE (in silico Atom Mapped Network Integrated Computational Explorer), for the systematic atom-level reconstruction of metabolic networks from in silico labelled substrates. iAM.NICE is to our knowledge the first automated atom-mapping algorithm that is based on the underlying enzymatic biotransformation mechanisms, and its application goes beyond individual reactions and it can be used for the reconstruction of atom-mapped metabolic networks. We illustrate the applicability of our method through the reconstruction of atom-mapped reactions of the KEGG database and we provide an example of an atom-level representation of the core metabolic network of E. coli. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Chen, Xueying; Zhao, Min; Qu, Hong

2015-01-01

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

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

PubMed

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

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

Methyl jasmonate as a vital substance in plants.

PubMed

Cheong, Jong-Joo; Choi, Yang Do

2003-07-01

The plant floral scent methyl jasmonate (MeJA) has been identified as a vital cellular regulator that mediates diverse developmental processes and defense responses against biotic and abiotic stresses. The pleiotropic effects of MeJA have raised numerous questions about its regulation for biogenesis and mode of action. Characterization of the gene encoding jasmonic acid carboxyl methyltransferase has provided basic information on the role(s) of this phytohormone in gene-activation control and systemic long-distance signaling. Recent approaches using functional genomics and bioinformatics have identified a whole set of MeJA-responsive genes, and provide insights into how plants use volatile signals to withstand diverse and variable environments.

Second Law of Thermodynamics Applied to Metabolic Networks

NASA Technical Reports Server (NTRS)

Nigam, R.; Liang, S.

2003-01-01

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

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

PubMed

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

2010-05-01

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

Multi-Criteria Optimization of Regulation in Metabolic Networks

PubMed Central

Higuera, Clara; Villaverde, Alejandro F.; Banga, Julio R.; Ross, John; Morán, Federico

2012-01-01

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different “environments” (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks. PMID:22848435

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

Jasmonic acid-amino acid conjugation enzyme assays.

PubMed

Rowe, Martha L; Staswick, Paul E

2013-01-01

Jasmonic acid (JA) is activated for signaling by its conjugation to isoleucine (Ile) through an amide linkage. The Arabidopsis thaliana JASMONIC ACID RESISTANT1 (JAR1) enzyme carries out this Mg-ATP-dependent reaction in two steps, adenylation of the free carboxyl of JA, followed by condensation of the activated group to Ile. This chapter details the protocols used to detect and quantify the enzymatic activity obtained from a glutathione-S-transferase:JAR1 fusion protein produced in Escherichia coli, including an isotope exchange assay for the adenylation step and assays for the complete reaction that involve the high-performance liquid chromatography quantitation of adenosine monophosphate, a stoichiometric by-product of the reaction, and detection of the conjugation product by thin-layer chromatography or gas -chromatography/mass spectrometry.

Soybean Aphid Infestation Induces Changes in Fatty Acid Metabolism in Soybean

PubMed Central

Kanobe, Charles; McCarville, Michael T.; O’Neal, Matthew E.; Tylka, Gregory L.; MacIntosh, Gustavo C.

2015-01-01

The soybean aphid (Aphis glycines Matsumura) is one of the most important insect pests of soybeans in the North-central region of the US. It has been hypothesized that aphids avoid effective defenses by inhibition of jasmonate-regulated plant responses. Given the role fatty acids play in jasmonate-induced plant defenses, we analyzed the fatty acid profile of soybean leaves and seeds from aphid-infested plants. Aphid infestation reduced levels of polyunsaturated fatty acids in leaves with a concomitant increase in palmitic acid. In seeds, a reduction in polyunsaturated fatty acids was associated with an increase in stearic acid and oleic acid. Soybean plants challenged with the brown stem rot fungus or with soybean cyst nematodes did not present changes in fatty acid levels in leaves or seeds, indicating that the changes induced by aphids are not a general response to pests. One of the polyunsaturated fatty acids, linolenic acid, is the precursor of jasmonate; thus, these changes in fatty acid metabolism may be examples of “metabolic hijacking” by the aphid to avoid the induction of effective defenses. Based on the changes in fatty acid levels observed in seeds and leaves, we hypothesize that aphids potentially induce interference in the fatty acid desaturation pathway, likely reducing FAD2 and FAD6 activity that leads to a reduction in polyunsaturated fatty acids. Our data support the idea that aphids block jasmonate-dependent defenses by reduction of the hormone precursor. PMID:26684003

An objective function exploiting suboptimal solutions in metabolic networks

PubMed Central

2013-01-01

Background Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power. Results We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation. Conclusion Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network. PMID:24088221

Blueprint for antimicrobial hit discovery targeting metabolic networks.

PubMed

Shen, Y; Liu, J; Estiu, G; Isin, B; Ahn, Y-Y; Lee, D-S; Barabási, A-L; Kapatral, V; Wiest, O; Oltvai, Z N

2010-01-19

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

Metabolic network flux analysis for engineering plant systems.

PubMed

Shachar-Hill, Yair

2013-04-01

Metabolic network flux analysis (NFA) tools have proven themselves to be powerful aids to metabolic engineering of microbes by providing quantitative insights into the flows of material and energy through cellular systems. The development and application of NFA tools to plant systems has advanced in recent years and are yielding significant insights and testable predictions. Plants present substantial opportunities for the practical application of NFA but they also pose serious challenges related to the complexity of plant metabolic networks and to deficiencies in our knowledge of their structure and regulation. By considering the tools available and selected examples, this article attempts to assess where and how NFA is most likely to have a real impact on plant biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

The topology of metabolic isotope labeling networks.

PubMed

Weitzel, Michael; Wiechert, Wolfgang; Nöh, Katharina

2007-08-29

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

Ectopic expression of Arabidopsis genes encoding salicylic acid- and jasmonic acid-related proteins confers partial resistance to soybean cyst nematode (Heterodera glycines) in transgenic soybean roots

USDA-ARS?s Scientific Manuscript database

Background. Extensive studies using the model system Arabidopsis thaliana to elucidate plant defense signaling and pathway networks indicate that salicylic acid (SA) is the key hormone triggering the plant defense response against biotrophic and hemi-biotrophic pathogens, while jasmonic acid (JA) an...

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

PubMed

Pang, Tin Yau; Maslov, Sergei

2011-05-01

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

Metabolic Pathways and Networks Associated with Tobacco Use in Military Personnel

PubMed Central

Jones, Dean P.; Walker, Douglas I.; Uppal, Karan; Rohrbeck, Patricia; Mallon, Timothy M.; Go, Young-Mi

2016-01-01

Objective Use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel. Methods Four hundred de-identified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or non-users according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification. Results Eighty individuals were classified as tobacco users compared to 320 non-users based on cotinine levels ≥10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways. Conclusions Tobacco use has complex metabolic effects which must be considered in evaluation of deployment-associated environmental exposures in military personnel. PMID:27501098

Metabolic Pathways and Networks Associated With Tobacco Use in Military Personnel.

PubMed

Jones, Dean P; Walker, Douglas I; Uppal, Karan; Rohrbeck, Patricia; Mallon, Col Timothy M; Go, Young-Mi

2016-08-01

The aim of this study is to use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel. Four hundred deidentified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or nonusers according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification. Eighty individuals were classified as tobacco users compared with 320 nonusers on the basis of cotinine levels at least 10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid, and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways. Tobacco use has complex metabolic effects that must be considered in evaluation of deployment-associated environmental exposures in military personnel.

Exploring metabolic pathways in genome-scale networks via generating flux modes.

PubMed

Rezola, A; de Figueiredo, L F; Brock, M; Pey, J; Podhorski, A; Wittmann, C; Schuster, S; Bockmayr, A; Planes, F J

2011-02-15

The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity. In this article, we present a novel optimization-based method for determining a minimal generating set of EFMs, i.e. a convex basis. We show that a subset of elements of this convex basis can be effectively computed even in large metabolic networks. Our method was applied to examine the structure of pathways producing lysine in Escherichia coli. We obtained a more varied and informative set of pathways in comparison with existing methods. In addition, an alternative pathway to produce lysine was identified using a detour via propionyl-CoA, which shows the predictive power of our novel approach. The source code in C++ is available upon request.

Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

PubMed

Kiparissides, A; Hatzimanikatis, V

2017-01-01

The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier

Computational identification of obligatorily autocatalytic replicators embedded in metabolic networks

PubMed Central

Kun, Ádám; Papp, Balázs; Szathmáry, Eörs

2008-01-01

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

Blueprint for antimicrobial hit discovery targeting metabolic networks

PubMed Central

Shen, Y.; Liu, J.; Estiu, G.; Isin, B.; Ahn, Y-Y.; Lee, D-S.; Barabási, A-L.; Kapatral, V.; Wiest, O.; Oltvai, Z. N.

2010-01-01

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy. PMID:20080587

Metabolic GARD: Replicating Catalytic Network of Lipid-Anchored Metabolites

NASA Astrophysics Data System (ADS)

Lancet, D.; Zidovetzki, R.; Shenhav, B.; Markovitch, O.

2017-07-01

We propose a computer-simulated M-GARD model, with mutually catalytic metabolic network of amphiphiles. It can show compositional reproduction of both bilayer and lumen content of lipid vesicles, thus joining metabolism, compartment and replication.

Plants on constant alert: elevated levels of jasmonic acid and jasmonate-induced transcripts in caterpillar resistant maize

USDA-ARS?s Scientific Manuscript database

Plant defense responses against insect herbivores frequently depend on the biosynthesis and action of jasmonic acid (JA) and its conjugates. To better understand JA signaling pathways in maize (Zea mays L.), we have examined two maize genotypes, Mp708 and Tx601. Mp708 is resistant to feeding by le...

Systematic assignment of thermodynamic constraints in metabolic network models

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

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

An integrated network visualization framework towards metabolic engineering applications.

PubMed

Noronha, Alberto; Vilaça, Paulo; Rocha, Miguel

2014-12-30

Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.

Auxin Controls Arabidopsis Adventitious Root Initiation by Regulating Jasmonic Acid Homeostasis[W

PubMed Central

Gutierrez, Laurent; Mongelard, Gaëlle; Floková, Kristýna; Păcurar, Daniel I.; Novák, Ondřej; Staswick, Paul; Kowalczyk, Mariusz; Păcurar, Monica; Demailly, Hervé; Geiss, Gaia; Bellini, Catherine

2012-01-01

Vegetative shoot-based propagation of plants, including mass propagation of elite genotypes, is dependent on the development of shoot-borne roots, which are also called adventitious roots. Multiple endogenous and environmental factors control the complex process of adventitious rooting. In the past few years, we have shown that the auxin response factors ARF6 and ARF8, targets of the microRNA miR167, are positive regulators of adventitious rooting, whereas ARF17, a target of miR160, is a negative regulator. We showed that these genes have overlapping expression profiles during adventitious rooting and that they regulate each other’s expression at the transcriptional and posttranscriptional levels by modulating the homeostasis of miR160 and miR167. We demonstrate here that this complex network of transcription factors regulates the expression of three auxin-inducible Gretchen Hagen3 (GH3) genes, GH3.3, GH3.5, and GH3.6, encoding acyl-acid-amido synthetases. We show that these three GH3 genes are required for fine-tuning adventitious root initiation in the Arabidopsis thaliana hypocotyl, and we demonstrate that they act by modulating jasmonic acid homeostasis. We propose a model in which adventitious rooting is an adaptive developmental response involving crosstalk between the auxin and jasmonate regulatory pathways. PMID:22730403

The Mediator Complex Subunit PFT1 Is a Key Regulator of Jasmonate-Dependent Defense in Arabidopsis[C][W

PubMed Central

Kidd, Brendan N.; Edgar, Cameron I.; Kumar, Krish K.; Aitken, Elizabeth A.; Schenk, Peer M.; Manners, John M.; Kazan, Kemal

2009-01-01

Jasmonate signaling plays an important role in both plant defense and development. Here, we have identified a subunit of the Mediator complex as a regulator of the jasmonate signaling pathway in Arabidopsis thaliana. The Mediator complex is a conserved multiprotein complex that acts as a universal adaptor between transcription factors and the RNA polymerase II transcriptional machinery. We report that the PHYTOCHROME AND FLOWERING TIME1 (PFT1) gene, which encodes the MEDIATOR25 subunit of Mediator, is required for jasmonate-dependent defense gene expression and resistance to leaf-infecting necrotrophic fungal pathogens. Conversely, PFT1 appears to confer susceptibility to Fusarium oxysporum, a root-infecting hemibiotrophic fungal pathogen known to hijack jasmonate responses for disease development. Consistent with this, jasmonate gene expression was suppressed in the pft1 mutant during infection with F. oxysporum. In addition, a wheat (Triticum aestivum) homolog of PFT1 complemented the defense and the developmental phenotypes of the pft1 mutant, suggesting that the jasmonate signaling functions of PFT1 may be conserved in higher plants. Overall, our results identify an important control point in the regulation of the jasmonate signaling pathway within the transcriptional machinery. PMID:19671879

Advanced Stoichiometric Analysis of Metabolic Networks of Mammalian Systems

PubMed Central

Orman, Mehmet A.; Berthiaume, Francois; Androulakis, Ioannis P.; Ierapetritou, Marianthi G.

2013-01-01

Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted. PMID:22196224

Central Metabolic Responses to Ozone and Herbivory Affect Photosynthesis and Stomatal Closure1[OPEN

PubMed Central

Khaling, Eliezer; Lassueur, Steve

2016-01-01

Plants have evolved adaptive mechanisms that allow them to tolerate a continuous range of abiotic and biotic stressors. Tropospheric ozone (O3), a global anthropogenic pollutant, directly affects living organisms and ecosystems, including plant-herbivore interactions. In this study, we investigate the stress responses of Brassica nigra (wild black mustard) exposed consecutively to O3 and the specialist herbivore Pieris brassicae. Transcriptomics and metabolomics data were evaluated using multivariate, correlation, and network analyses for the O3 and herbivory responses. O3 stress symptoms resembled those of senescence and phosphate starvation, while a sequential shift from O3 to herbivory induced characteristic plant defense responses, including a decrease in central metabolism, induction of the jasmonic acid/ethylene pathways, and emission of volatiles. Omics network and pathway analyses predicted a link between glycerol and central energy metabolism that influences the osmotic stress response and stomatal closure. Further physiological measurements confirmed that while O3 stress inhibited photosynthesis and carbon assimilation, sequential herbivory counteracted the initial responses induced by O3, resulting in a phenotype similar to that observed after herbivory alone. This study clarifies the consequences of multiple stress interactions on a plant metabolic system and also illustrates how omics data can be integrated to generate new hypotheses in ecology and plant physiology. PMID:27758847

Identification of functional differences in metabolic networks using comparative genomics and constraint-based models.

PubMed

Hamilton, Joshua J; Reed, Jennifer L

2012-01-01

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

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

PubMed Central

Hamilton, Joshua J.; Reed, Jennifer L.

2012-01-01

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

Topological analysis of metabolic networks based on petri net theory.

PubMed

Zevedei-Oancea, Ionela; Schuster, Stefan

2011-01-01

Petri net concepts provide additional tools for the modelling of metabolic networks. Here, the similarities between the counterparts in traditional biochemical modelling and Petri net theory are discussed. For example the stoichiometry matrix of a metabolic network corresponds to the incidence matrix of the Petri net. The flux modes and conservation relations have the T-invariants, respectively, P-invariants as counterparts. We reveal the biological meaning of some notions specific to the Petri net framework (traps, siphons, deadlocks, liveness). We focus on the topological analysis rather than on the analysis of the dynamic behaviour. The treatment of external metabolites is discussed. Some simple theoretical examples are presented for illustration. Also the Petri nets corresponding to some biochemical networks are built to support our results. For example, the role of triose phosphate isomerase (TPI) in Trypanosoma brucei metabolism is evaluated by detecting siphons and traps. All Petri net properties treated in this contribution are exemplified on a system extracted from nucleotide metabolism.

Topological analysis of metabolic networks based on Petri net theory.

PubMed

Zevedei-Oancea, Ionela; Schuster, Stefan

2003-01-01

Petri net concepts provide additional tools for the modelling of metabolic networks. Here, the similarities between the counterparts in traditional biochemical modelling and Petri net theory are discussed. For example the stoichiometry matrix of a metabolic network corresponds to the incidence matrix of the Petri net. The flux modes and conservation relations have the T-invariants, respectively, P-invariants as counterparts. We reveal the biological meaning of some notions specific to the Petri net framework (traps, siphons, deadlocks, liveness). We focus on the topological analysis rather than on the analysis of the dynamic behaviour. The treatment of external metabolites is discussed. Some simple theoretical examples are presented for illustration. Also the Petri nets corresponding to some biochemical networks are built to support our results. For example, the role of triose phosphate isomerase (TPI) in Trypanosoma brucei metabolism is evaluated by detecting siphons and traps. All Petri net properties treated in this contribution are exemplified on a system extracted from nucleotide metabolism.

Structure versus time in the evolutionary diversification of avian carotenoid metabolic networks.

PubMed

Morrison, Erin S; Badyaev, Alexander V

2018-05-01

Historical associations of genes and proteins are thought to delineate pathways available to subsequent evolution; however, the effects of past functional involvements on contemporary evolution are rarely quantified. Here, we examined the extent to which the structure of a carotenoid enzymatic network persists in avian evolution. Specifically, we tested whether the evolution of carotenoid networks was most concordant with phylogenetically structured expansion from core reactions of common ancestors or with subsampling of biochemical pathway modules from an ancestral network. We compared structural and historical associations in 467 carotenoid networks of extant and ancestral species and uncovered the overwhelming effect of pre-existing metabolic network structure on carotenoid diversification over the last 50 million years of avian evolution. Over evolutionary time, birds repeatedly subsampled and recombined conserved biochemical modules, which likely maintained the overall structure of the carotenoid metabolic network during avian evolution. These findings explain the recurrent convergence of evolutionary distant species in carotenoid metabolism and weak phylogenetic signal in avian carotenoid evolution. Remarkable retention of an ancient metabolic structure throughout extensive and prolonged ecological diversification in avian carotenoid metabolism illustrates a fundamental requirement of organismal evolution - historical continuity of a deterministic network that links past and present functional associations of its components. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Methyl jasmonate elicits the biotransformation of geraniol stored as its glucose conjugate into methyl geranate in Achyranthes bidentata plant.

PubMed

Tamogami, Shigeru; Agrawal, Ganesh K; Rakwal, Randeep

2016-12-01

To investigate the biotransformation pathway of airborne geraniol by Achyranthes bidentata (A. bidentata), deuterium labeled geraniol was applied with or without methyl jasmonate (MeJA), and the biosynthesized metabolites were analyzed. In A. bidentata leaves, geraniol was conjugated with glucose. The conjugate was then metabolized to afford methyl geranate only under MeJA elicitation. MeJA elicits the biotransformation of geraniol into methyl geranate by inducing the conversion of the intermediate, glucose conjugate of geraniol. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

A general model for metabolic scaling in self-similar asymmetric networks

PubMed Central

Savage, Van M.; Enquist, Brian J.

2017-01-01

How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber’s Law can still be attained within many asymmetric networks. PMID:28319153

A general model for metabolic scaling in self-similar asymmetric networks.

PubMed

Brummer, Alexander Byers; Savage, Van M; Enquist, Brian J

2017-03-01

How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence

DTIC Science & Technology

2016-08-01

Award Number: TITLE: Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence PRINCIPAL INVESTIGATOR: COL (Ret) Marina N...2016 2. REPORT TYPE FINAL 3. DATES COVERED (From - To) 29 Sep 2011 – 31 May 2016 4. TITLE AND SUBTITLE "Metabolic Networks Integrative Cardiac Health...ABSTRACT The Integrative Cardiac Health Project (ICHP) aims to lead the way in Cardiovascular Disease (CVD) Prevention by conducting novel research

Dissecting Germ Cell Metabolism through Network Modeling.

PubMed

Whitmore, Leanne S; Ye, Ping

2015-01-01

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

Simultaneous determination of shikimic acid, salicylic acid and jasmonic acid in wild and transgenic Nicotiana langsdorffii plants exposed to abiotic stresses.

PubMed

Scalabrin, Elisa; Radaelli, Marta; Capodaglio, Gabriele

2016-06-01

The presence and relative concentration of phytohormones may be regarded as a good indicator of an organism's physiological state. The integration of the rolC gene from Agrobacterium rhizogenes and of the rat glucocorticoid receptor (gr) in Nicotiana langsdorffii Weinmann plants has shown to determine various physiological and metabolic effects. The analysis of wild and transgenic N. langsdorffii plants, exposed to different abiotic stresses (high temperature, water deficit, and high chromium concentrations) was conducted, in order to investigate the metabolic effects of the inserted genes in response to the applied stresses. The development of a new analytical procedure was necessary, in order to assure the simultaneous determination of analytes and to obtain an adequately low limit of quantification. For the first time, a sensitive HPLC-HRMS quantitative method for the simultaneous determination of salicylic acid, jasmonic acid and shikimic acid was developed and validated. The method was applied to 80 plant samples, permitting the evaluation of plant stress responses and highlighting some metabolic mechanisms. Salicylic, jasmonic and shikimic acids proved to be suitable for the comprehension of plant stress responses. Chemical and heat stresses showed to induce the highest changes in plant hormonal status, differently affecting plant response. The potential of each genetic modification toward the applied stresses was marked and particularly the resistance of the gr modified plants was evidenced. This work provides new information in the study of N. langsdorffii and transgenic organisms, which could be useful for the further application of these transgenes. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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

PubMed Central

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

2015-01-01

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

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT

PubMed Central

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

2016-01-01

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

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

PubMed

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

2016-06-01

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

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

PubMed Central

Prigent, Sylvain; Frioux, Clémence; Dittami, Simon M.; Larhlimi, Abdelhalim; Collet, Guillaume; Gutknecht, Fabien; Got, Jeanne; Eveillard, Damien; Bourdon, Jérémie; Plewniak, Frédéric; Tonon, Thierry; Siegel, Anne

2017-01-01

Increasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks.

PubMed

Prigent, Sylvain; Frioux, Clémence; Dittami, Simon M; Thiele, Sven; Larhlimi, Abdelhalim; Collet, Guillaume; Gutknecht, Fabien; Got, Jeanne; Eveillard, Damien; Bourdon, Jérémie; Plewniak, Frédéric; Tonon, Thierry; Siegel, Anne

2017-01-01

Increasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to

A Role for the GCC-Box in Jasmonate-Mediated Activation of the PDF1.2 Gene of Arabidopsis1

PubMed Central

Brown, Rebecca L.; Kazan, Kemal; McGrath, Ken C.; Maclean, Don J.; Manners, John M.

2003-01-01

The PDF1.2 gene of Arabidopsis encoding a plant defensin is commonly used as a marker for characterization of the jasmonate-dependent defense responses. Here, using PDF1.2 promoter-deletion lines linked to the β-glucoronidase-reporter gene, we examined putative promoter elements associated with jasmonate-responsive expression of this gene. Using stably transformed plants, we first characterized the extended promoter region that positively regulates basal expression from the PDF1.2 promoter. Second, using promoter deletion constructs including one from which the GCC-box region was deleted, we observed a substantially lower response to jasmonate than lines carrying this motif. In addition, point mutations introduced into the core GCC-box sequence substantially reduced jasmonate responsiveness, whereas addition of a 20-nucleotide-long promoter element carrying the core GCC-box and flanking nucleotides provided jasmonate responsiveness to a 35S minimal promoter. Taken together, these results indicated that the GCC-box plays a key role in conferring jasmonate responsiveness to the PDF1.2 promoter. However, deletion or specific mutations introduced into the core GCC-box did not completely abolish the jasmonate responsiveness of the promoter, suggesting that the other promoter elements lying downstream from the GCC-box region may also contribute to jasmonate responsiveness. In other experiments, we identified a jasmonate- and pathogen-responsive ethylene response factor transcription factor, AtERF2, which when overexpressed in transgenic Arabidopsis plants activated transcription from the PDF1.2, Thi2.1, and PR4 (basic chitinase) genes, all of which contain a GCC-box sequence in their promoters. Our results suggest that in addition to their roles in regulating ethylene-mediated gene expression, ethylene response factors also appear to play important roles in regulating jasmonate-responsive gene expression, possibly via interaction with the GCC-box. PMID:12805630

Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence

DTIC Science & Technology

2016-04-01

2.6; P = 0.001) among all variables, as the most significant predictor of abnormal CIMT, thus increasing risk for CVD. Conclusions: The Integrative ...1 Award Number: W81XWH-11-2-0227 TITLE: "Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence." PRINCIPAL...April 2016 2. REPORT TYPE ANNUAL 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE "Metabolic Networks Integrative Cardiac Health Project (ICHP

Transcriptional activation of a geranylgeranyl diphosphate synthase gene, GGPPS2, isolated from Scoparia dulcis by treatment with methyl jasmonate and yeast extract.

PubMed

Yamamura, Y; Mizuguchi, Y; Taura, F; Kurosaki, F

2014-10-01

A cDNA clone, designated SdGGPPS2, was isolated from young seedlings of Scoparia dulcis. The putative amino acid sequence of the translate of the gene showed high homology with geranylgeranyl diphosphate synthase (GGPPS) from various plant sources, and the N-terminal residues exhibited the characteristics of chloroplast targeting sequence. An appreciable increase in the transcriptional level of SdGGPPS2 was observed by exposure of the leaf tissues of S. dulcis to methyl jasmonate, yeast extract or Ca(2+) ionophore A23187. In contrast, SdGGPPS1, a homologous GGPPS gene of the plant, showed no or only negligible change in the expression level upon treatment with these stimuli. The truncated protein heterologously expressed in Escherichia coli in which the putative targeting domain was deleted catalyzed the condensation of farnesyl diphosphate and isopentenyl diphosphate to liberate geranylgeranyl diphosphate. These results suggested that SdGGPPS2 plays physiological roles in methyl jasmonate and yeast extract-induced metabolism in the chloroplast of S. dulcis cells.

Structural basis of JAZ repression of MYC transcription factors in jasmonate signalling

DOE PAGES

Zhang, Feng; Yao, Jian; Ke, Jiyuan; ...

2015-08-10

The plant hormone jasmonate plays crucial roles in regulating plant responses to herbivorous insects and microbial pathogens and is an important regulator of plant growth and development. Key mediators of jasmonate signalling include MYC transcription factors, which are repressed by jasmonate ZIM-domain (JAZ) transcriptional repressors in the resting state. In the presence of active jasmonate, JAZ proteins function as jasmonate co-receptors by forming a hormone-dependent complex with COI1, the F-box subunit of an SCF-type ubiquitin E3 ligase. The hormone-dependent formation of the COI1–JAZ co-receptor complex leads to ubiquitination and proteasome-dependent degradation of JAZ repressors and release of MYC proteins frommore » transcriptional repression. The mechanism by which JAZ proteins repress MYC transcription factors and how JAZ proteins switch between the repressor function in the absence of hormone and the co-receptor function in the presence of hormone remain enigmatic. In this paper, we show that Arabidopsis MYC3 undergoes pronounced conformational changes when bound to the conserved Jas motif of the JAZ9 repressor. The Jas motif, previously shown to bind to hormone as a partly unwound helix, forms a complete α-helix that displaces the amino (N)-terminal helix of MYC3 and becomes an integral part of the MYC N-terminal fold. In this position, the Jas helix competitively inhibits MYC3 interaction with the MED25 subunit of the transcriptional Mediator complex. Finally, our structural and functional studies elucidate a dynamic molecular switch mechanism that governs the repression and activation of a major plant hormone pathway.« less

Metagenomics reveals flavour metabolic network of cereal vinegar microbiota.

PubMed

Wu, Lin-Huan; Lu, Zhen-Ming; Zhang, Xiao-Juan; Wang, Zong-Min; Yu, Yong-Jian; Shi, Jin-Song; Xu, Zheng-Hong

2017-04-01

Multispecies microbial community formed through centuries of repeated batch acetic acid fermentation (AAF) is crucial for the flavour quality of traditional vinegar produced from cereals. However, the metabolism to generate and/or formulate the essential flavours by the multispecies microbial community is hardly understood. Here we used metagenomic approach to clarify in situ metabolic network of key microbes responsible for flavour synthesis of a typical cereal vinegar, Zhenjiang aromatic vinegar, produced by solid-state fermentation. First, we identified 3 organic acids, 7 amino acids, and 20 volatiles as dominant vinegar metabolites. Second, we revealed taxonomic and functional composition of the microbiota by metagenomic shotgun sequencing. A total of 86 201 predicted protein-coding genes from 35 phyla (951 genera) were involved in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of Metabolism (42.3%), Genetic Information Processing (28.3%), and Environmental Information Processing (10.1%). Furthermore, a metabolic network for substrate breakdown and dominant flavour formation in vinegar microbiota was constructed, and microbial distribution discrepancy in different metabolic pathways was charted. This study helps elucidating different metabolic roles of microbes during flavour formation in vinegar microbiota. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient searching and annotation of metabolic networks using chemical similarity

PubMed Central

Pertusi, Dante A.; Stine, Andrew E.; Broadbelt, Linda J.; Tyo, Keith E.J.

2015-01-01

Motivation: The urgent need for efficient and sustainable biological production of fuels and high-value chemicals has elicited a wave of in silico techniques for identifying promising novel pathways to these compounds in large putative metabolic networks. To date, these approaches have primarily used general graph search algorithms, which are prohibitively slow as putative metabolic networks may exceed 1 million compounds. To alleviate this limitation, we report two methods—SimIndex (SI) and SimZyme—which use chemical similarity of 2D chemical fingerprints to efficiently navigate large metabolic networks and propose enzymatic connections between the constituent nodes. We also report a Byers–Waterman type pathway search algorithm for further paring down pertinent networks. Results: Benchmarking tests run with SI show it can reduce the number of nodes visited in searching a putative network by 100-fold with a computational time improvement of up to 105-fold. Subsequent Byers–Waterman search application further reduces the number of nodes searched by up to 100-fold, while SimZyme demonstrates ∼90% accuracy in matching query substrates with enzymes. Using these modules, we have designed and annotated an alternative to the methylerythritol phosphate pathway to produce isopentenyl pyrophosphate with more favorable thermodynamics than the native pathway. These algorithms will have a significant impact on our ability to use large metabolic networks that lack annotation of promiscuous reactions. Availability and implementation: Python files will be available for download at http://tyolab.northwestern.edu/tools/. Contact: k-tyo@northwestern.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25417203

Estimating the size of the solution space of metabolic networks

PubMed Central

Braunstein, Alfredo; Mulet, Roberto; Pagnani, Andrea

2008-01-01

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

Methyl Jasmonate-Induced Lipidomic and Biochemical Alterations in the Intertidal Macroalga Gracilaria dura (Gracilariaceae, Rhodophyta)

PubMed Central

Kumari, Puja; Reddy, C.R.K.; Jha, Bhavanath

2015-01-01

The role of exogenously added methyl jasmonate (MeJA), a lipid-derived signaling compound, in inducing oxidative stress in the marine red macroalga Gracilaria dura was investigated. MeJA at a concentration of 1–100 µM was a strong stimulant of reactive oxygen species (H2O2, HO· and O2·−) (P < 0.05) causing considerable oxidative stress in G. dura. This further led to lipid peroxidation and degradation of the pigments Chl a and phycocyanin, with a concomitant increase in phycoerythrin. The MeJA-induced oxidative burst also led to the induction of a fatty acid oxidation cascade, resulting in the synthesis of hydroxy-oxylipins and the up-regulation of the 13-lipoxygenase pathway. Electrospray ionization-mass spectrometry-based shotgun lipidomic analysis revealed that monogalactosyldiacylglycerol (a chloroplastic glycerolipid) and phosphatidylcholine (extrachloroplastidic phopholipid) were the most affected lipid classes. The degradation of 18:3-fatty acid-containing monogalactosyldiacylglycerol inferred that it provided fatty acyl chains for the biosynthesis of 13-hydroperoxylinolenic acid, which was further directed towards either the jasmonate pathway or other alternative pathways of the fatty acid oxidation cascade, analogous to higher plants. Also, G. dura modulated the lipid acyl chains in such a way that no significant change was observed in the fatty acid profile of the treated thalli as compared with those of the control, except for C16:0, C16:1 (n-9), C20:3 (n-6) and C20:4 (n-6) (P < 0.05). Furthermore, MeJA caused the accumulation of phenolic compounds and the up-regulation of enzymes involved in secondary metabolism such as polyphenol oxidase, shikimate dehydrogenase and phenylalanine ammonia-lyase, indicating a shift towards secondary metabolism as a defense strategy to combat the induced oxidative stress. PMID:26276825

Structural kinetic modeling of metabolic networks.

PubMed

Steuer, Ralf; Gross, Thilo; Selbig, Joachim; Blasius, Bernd

2006-08-08

To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.

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

PubMed

Krumholz, Elias W; Libourel, Igor G L

2015-07-31

Genome-scale metabolic models are central in connecting genotypes to metabolic phenotypes. However, even for well studied organisms, such as Escherichia coli, draft networks do not contain a complete biochemical network. Missing reactions are referred to as gaps. These gaps need to be filled to enable functional analysis, and gap-filling choices influence model predictions. To investigate whether functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes. Quadratic programming revealed that the number of reactions that could partake in a gap-filling solution was vast: 3,270 in the case of E. coli, where 72% of the metabolites in the draft network could connect a gap-filling solution. Nonetheless, no network could be completed without the inclusion of orphaned enzymes, suggesting that parts of the biochemistry integral to biomass precursor formation are uncharacterized. However, many gap-filling reactions were well determined, and the resulting networks showed improved prediction of gene essentiality compared with networks generated through canonical gap filling. In addition, gene essentiality predictions that were sensitive to poorly determined gap-filling reactions were of poor quality, suggesting that damage to the network structure resulting from the inclusion of erroneous gap-filling reactions may be predictable. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Jasmonate regulates the inducer of cbf expression-C-repeat binding factor/DRE binding factor1 cascade and freezing tolerance in Arabidopsis.

PubMed

Hu, Yanru; Jiang, Liqun; Wang, Fang; Yu, Diqiu

2013-08-01

The inducer of cbf expression (ICE)-C-repeat binding factor/DRE binding factor1 (CBF/DREB1) transcriptional pathway plays a critical role in modulating cold stress responses in Arabidopsis thaliana. Dissecting crucial upstream regulatory signals or components of the ICE-CBF/DREB1 cascade will enhance our understanding of plant cold-tolerance mechanisms. Here, we show that jasmonate positively regulates plant responses to freezing stress in Arabidopsis. Exogenous application of jasmonate significantly enhanced plant freezing tolerance with or without cold acclimation. By contrast, blocking endogenous jasmonate biosynthesis and signaling rendered plants hypersensitive to freezing stress. Consistent with the positive role of jasmonate in freezing stress, production of endogenous jasmonate was triggered by cold treatment. In addition, cold induction of genes acting in the CBF/DREB1 signaling pathway was upregulated by jasmonate. Further investigation revealed that several jasmonate ZIM-domain (JAZ) proteins, the repressors of jasmonate signaling, physically interact with ICE1 and ICE2 transcription factors. JAZ1 and JAZ4 repress the transcriptional function of ICE1, thereby attenuating the expression of its regulon. Consistent with this, overexpression of JAZ1 or JAZ4 represses freezing stress responses of Arabidopsis. Taken together, our study provides evidence that jasmonate functions as a critical upstream signal of the ICE-CBF/DREB1 pathway to positively regulate Arabidopsis freezing tolerance.

Efficient searching and annotation of metabolic networks using chemical similarity.

PubMed

Pertusi, Dante A; Stine, Andrew E; Broadbelt, Linda J; Tyo, Keith E J

2015-04-01

The urgent need for efficient and sustainable biological production of fuels and high-value chemicals has elicited a wave of in silico techniques for identifying promising novel pathways to these compounds in large putative metabolic networks. To date, these approaches have primarily used general graph search algorithms, which are prohibitively slow as putative metabolic networks may exceed 1 million compounds. To alleviate this limitation, we report two methods--SimIndex (SI) and SimZyme--which use chemical similarity of 2D chemical fingerprints to efficiently navigate large metabolic networks and propose enzymatic connections between the constituent nodes. We also report a Byers-Waterman type pathway search algorithm for further paring down pertinent networks. Benchmarking tests run with SI show it can reduce the number of nodes visited in searching a putative network by 100-fold with a computational time improvement of up to 10(5)-fold. Subsequent Byers-Waterman search application further reduces the number of nodes searched by up to 100-fold, while SimZyme demonstrates ∼ 90% accuracy in matching query substrates with enzymes. Using these modules, we have designed and annotated an alternative to the methylerythritol phosphate pathway to produce isopentenyl pyrophosphate with more favorable thermodynamics than the native pathway. These algorithms will have a significant impact on our ability to use large metabolic networks that lack annotation of promiscuous reactions. Python files will be available for download at http://tyolab.northwestern.edu/tools/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Why does anatabine, but not nicotine, accumulate in jasmonate-elicited cultured tobacco BY-2 cells?

PubMed

Shoji, Tsubasa; Hashimoto, Takashi

2008-08-01

Suspension-cultured cells of Nicotiana tabacum cv. Bright Yellow-2 (BY-2) grow rapidly in a highly homogenous population and still exhibit the general behavior of plant cells, and thus are often used as model systems in several areas of plant molecular and cellular biology, including secondary metabolism. While the parental tobacco variety synthesizes nicotine as a major alkaloid, the cultured tobacco cells mainly produce a related alkaloid anatabine, instead of nicotine, when elicited with jasmonates. We report here that cultured BY-2 cells scarcely express N-methylputrescine oxidase (MPO) genes even after jasmonate elicitation. MPO is the second enzyme in the biosynthetic pathway that supplies the pyrrolidine moiety of nicotine and nornicotine, but is predicted to be dispensable for the biosynthesis of anatabine, anabasine and anatalline, which do not contain the pyrrolidine moiety. When MPO was overexpressed in tobacco BY-2 cells, nicotine synthesis was dramatically enhanced while anatabine formation was effectively suppressed. As a complementary approach, we suppressed MPO expression by RNA interference in tobacco hairy roots that normally accumulate nicotine. In the MPO-suppressed roots, the contents of anatabine, anabasine and anatalline, as well as N-methylputrescine and putrescine, markedly increased to compensate for suppressed formation of nicotine and nornicotine. These results identify the transcriptional regulation of MPO as a critical rate-limiting step that restricts nicotine formation in cultured tobacco BY-2 cells.

Enumeration of Smallest Intervention Strategies in Genome-Scale Metabolic Networks

PubMed Central

von Kamp, Axel; Klamt, Steffen

2014-01-01

One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal) provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs) which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions) in genome-scale metabolic network models. For this we combine two approaches, namely (i) the mapping of MCSs to EMs in a dual network, and (ii) a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine) by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth) than reported previously. The strength of the presented approach is that smallest intervention strategies can be quickly

Attraction of New Zealand flower thrips, Thrips obscuratus, to cis-jasmone, a volatile identified from Japanese honeysuckle flowers.

PubMed

El-Sayed, A M; Mitchell, V J; McLaren, G F; Manning, L M; Bunn, B; Suckling, D M

2009-06-01

This work was undertaken to identify floral compound(s) produced by honeysuckle flowers, Lonicera japonica (Thunberg), that mediate the attraction of New Zealand flower thrips Thrips obscuratus (Crawford). Volatiles were collected during the day and night and analyzed by gas chromatography-mass spectrometry (GC-MS) to determine their emission over these two periods. Nine compounds were identified in the headspace; the main compound was linalool, and the other compounds were germacrene D, E,E-alpha-farnesene, nerolidol, cis-jasmone, cis-3-hexenyl acetate, hexyl acetate, cis-hexenyl tiglate, and indole. There was a quantitative difference between day and night volatiles, with cis-3-hexenyl acetate, hexyl acetate, cis-hexenyl tiglate, and cis-jasmone emitted in higher amounts during the day compared to the night. When the compounds were tested individually in field trapping experiments, only cis-jasmone attracted New Zealand flower thrips in a significant number. In another field trapping experiment, cis-jasmone caught similar numbers of New Zealand flower thrips compared to a floral blend formulated to mimic the ratios of the compounds emitted during the day, while catch with the night-emitted floral blend was not significantly different from the control. Subsequently, two field trapping experiments were conducted to determine the optimal attraction dose for cis-jasmone, a range of 1-100 mg loaded onto a red rubber stopper was tested, and the highest catches were in traps baited with 100 mg loading. A higher range of 100-1000 mg loaded into polyethylene vials was tested, and the highest catch was in traps baited with 500 mg. In another experiment aimed at comparing the attraction efficacy of cis-jasmone with the two other known thrips attractants (ethyl nicotinate and p-anisaldehyde), ethyl nicotinate showed the highest trap catch followed by cis-jasmone. A smaller number of Thrips tabaci (Lindeman) was attracted to traps baited with cis-jasmone. These results

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

PubMed

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; Ng, Patrick; Khraiwesh, Basel; Jaiswal, Ashish; Jijakli, Kenan; Koussa, Joseph; Nelson, David R; Cai, Hong; Yang, Xinping; Chang, Roger L; Papin, Jason; Yu, Haiyuan; Balaji, Santhanam; Salehi-Ashtiani, Kourosh

2016-07-19

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

PubMed

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Foundations of metabolic organization: coherence as a basis of computational properties in metabolic networks.

PubMed

Igamberdiev, A U

1999-04-01

Biological organization is based on the coherent energy transfer allowing for macromolecules to operate with high efficiency and realize computation. Computation is executed with virtually 100% efficiency via the coherent operation of molecular machines in which low-energy recognitions trigger energy-driven non-equilibrium dynamic processes. The recognition process is of quantum mechanical nature being a non-demolition measurement. It underlies the enzymatic conversion of a substrate into the product (an elementary metabolic phenomenon); the switching via separation of the direct and reverse routes in futile cycles provides the generation and complication of metabolic networks (coherence within cycles is maintained by the supramolecular organization of enzymes); the genetic level corresponding to the appearance of digital information is based on reflective arrows (catalysts realize their own self-reproduction) and operation of hypercycles. Every metabolic cycle via reciprocal regulation of both its halves can generate rhythms and spatial structures (resulting from the temporally organized depositions from the cycles). Via coherent events which percolate from the elementary submolecular level to organismic entities, self-assembly based on the molecular complementarity is realized and the dynamic informational field operating within the metabolic network is generated.

Experimental determination of group flux control coefficients in metabolic networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

1998-04-20

Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmentalmore » 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.« less

A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

PubMed Central

2013-01-01

Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia

What Can Causal Networks Tell Us about Metabolic Pathways?

PubMed Central

Blair, Rachael Hageman; Kliebenstein, Daniel J.; Churchill, Gary A.

2012-01-01

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 BaySha 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. PMID:22496633

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

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

PubMed

Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Jasmonate-triggered plant immunity.

PubMed

Campos, Marcelo L; Kang, Jin-Ho; Howe, Gregg A

2014-07-01

The plant hormone jasmonate (JA) exerts direct control over the production of chemical defense compounds that confer resistance to a remarkable spectrum of plant-associated organisms, ranging from microbial pathogens to vertebrate herbivores. The underlying mechanism of JA-triggered immunity (JATI) can be conceptualized as a multi-stage signal transduction cascade involving: i) pattern recognition receptors (PRRs) that couple the perception of danger signals to rapid synthesis of bioactive JA; ii) an evolutionarily conserved JA signaling module that links fluctuating JA levels to changes in the abundance of transcriptional repressor proteins; and iii) activation (de-repression) of transcription factors that orchestrate the expression of myriad chemical and morphological defense traits. Multiple negative feedback loops act in concert to restrain the duration and amplitude of defense responses, presumably to mitigate potential fitness costs of JATI. The convergence of diverse plant- and non-plant-derived signals on the core JA module indicates that JATI is a general response to perceived danger. However, the modular structure of JATI may accommodate attacker-specific defense responses through evolutionary innovation of PRRs (inputs) and defense traits (outputs). The efficacy of JATI as a defense strategy is highlighted by its capacity to shape natural populations of plant attackers, as well as the propensity of plant-associated organisms to subvert or otherwise manipulate JA signaling. As both a cellular hub for integrating informational cues from the environment and a common target of pathogen effectors, the core JA module provides a focal point for understanding immune system networks and the evolution of chemical diversity in the plant kingdom.

Jasmonate Regulates the INDUCER OF CBF EXPRESSION–C-REPEAT BINDING FACTOR/DRE BINDING FACTOR1 Cascade and Freezing Tolerance in Arabidopsis[W

PubMed Central

Hu, Yanru; Jiang, Liqun; Wang, Fang; Yu, Diqiu

2013-01-01

The INDUCER OF CBF EXPRESSION (ICE)–C-REPEAT BINDING FACTOR/DRE BINDING FACTOR1 (CBF/DREB1) transcriptional pathway plays a critical role in modulating cold stress responses in Arabidopsis thaliana. Dissecting crucial upstream regulatory signals or components of the ICE-CBF/DREB1 cascade will enhance our understanding of plant cold-tolerance mechanisms. Here, we show that jasmonate positively regulates plant responses to freezing stress in Arabidopsis. Exogenous application of jasmonate significantly enhanced plant freezing tolerance with or without cold acclimation. By contrast, blocking endogenous jasmonate biosynthesis and signaling rendered plants hypersensitive to freezing stress. Consistent with the positive role of jasmonate in freezing stress, production of endogenous jasmonate was triggered by cold treatment. In addition, cold induction of genes acting in the CBF/DREB1 signaling pathway was upregulated by jasmonate. Further investigation revealed that several JASMONATE ZIM-DOMAIN (JAZ) proteins, the repressors of jasmonate signaling, physically interact with ICE1 and ICE2 transcription factors. JAZ1 and JAZ4 repress the transcriptional function of ICE1, thereby attenuating the expression of its regulon. Consistent with this, overexpression of JAZ1 or JAZ4 represses freezing stress responses of Arabidopsis. Taken together, our study provides evidence that jasmonate functions as a critical upstream signal of the ICE-CBF/DREB1 pathway to positively regulate Arabidopsis freezing tolerance. PMID:23933884

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.

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 moremore » 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. Lastly, 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.« less

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

DOE PAGES

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.; ...

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 moremore » 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. Lastly, 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.« less

Quantitative petri net model of gene regulated metabolic networks in the cell.

PubMed

Chen, Ming; Hofestädt, Ralf

2011-01-01

A method to exploit hybrid Petri nets (HPN) for quantitatively modeling and simulating gene regulated metabolic networks is demonstrated. A global kinetic modeling strategy and Petri net modeling algorithm are applied to perform the bioprocess functioning and model analysis. With the model, the interrelations between pathway analysis and metabolic control mechanism are outlined. Diagrammatical results of the dynamics of metabolites are simulated and observed by implementing a HPN tool, Visual Object Net ++. An explanation of the observed behavior of the urea cycle is proposed to indicate possibilities for metabolic engineering and medical care. Finally, the perspective of Petri nets on modeling and simulation of metabolic networks is discussed.

Validation of a metabolic network for Saccharomyces cerevisiae using mixed substrate studies.

PubMed

Vanrolleghem, P A; de Jong-Gubbels, P; van Gulik, W M; Pronk, J T; van Dijken, J P; Heijnen, S

1996-01-01

Setting up a metabolic network model for respiratory growth of Saccharomyces cerevisiae requires the estimation of only two (energetic) stoichiometric parameters: (1) the operational PO ratio and (2) a growth-related maintenance factor k. It is shown, both theoretically and practically, how chemostat cultivations with different mixtures of two substrates allow unique values to be given to these unknowns of the proposed metabolic model. For the yeast and model considered, an effective PO ratio of 1.09 mol of ATP/mol of O (95% confidence interval 1.07-1.11) and a k factor of 0.415 mol of ATP/C-mol of biomass (0.385-0.445) were obtained from biomass substrate yield data on glucose/ethanol mixtures. Symbolic manipulation software proved very valuable in this study as it supported the proof of theoretical identifiability and significantly reduced the necessary computations for parameter estimation. In the transition from 100% glucose to 100% ethanol in the feed, four metabolic regimes occur. Switching between these regimes is determined by cessation of an irreversible reaction and initiation of an alternative reaction. Metabolic network predictions of these metabolic switches compared well with activity measurements of key enzymes. As a second validation of the network, the biomass yield of S. cerevisiae on acetate was also compared to the network prediction. An excellent agreement was found for a network in which acetate transport was modeled with a proton symport, while passive diffusion of acetate gave significantly higher yield predictions.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra

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 metabolicmore » 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. As a result, 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.« less

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

DOE PAGES

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; ...

2016-06-14

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 metabolicmore » 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. As a result, 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.« less

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

PubMed

Oh, S June; Joung, Je-Gun; Chang, Jeong-Ho; Zhang, Byoung-Tak

2006-06-06

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence

Extracellular ATP Acts on Jasmonate Signaling to Reinforce Plant Defense.

PubMed

Tripathi, Diwaker; Zhang, Tong; Koo, Abraham J; Stacey, Gary; Tanaka, Kiwamu

2018-01-01

Damaged cells send various signals to stimulate defense responses. Recent identification and genetic studies of the plant purinoceptor, P2K1 (also known as DORN1), have demonstrated that extracellular ATP is a signal involved in plant stress responses, including wounding, perhaps to evoke plant defense. However, it remains largely unknown how extracellular ATP induces plant defense responses. Here, we demonstrate that extracellular ATP induces plant defense mediated through activation of the intracellular signaling of jasmonate (JA), a well-characterized defense hormone. In Arabidopsis ( Arabidopsis thaliana ) leaves, ATP pretreatment induced resistance against the necrotrophic fungus, Botrytis cinerea The induced resistance was enhanced in the P2K1 receptor overexpression line, but reduced in the receptor mutant, dorn1 - 3 Mining the transcriptome data revealed that ATP induces a set of JA-induced genes. In addition, the P2K1-associated coexpression network contains defense-related genes, including those encoding jasmonate ZIM-domain (JAZ) proteins, which play key roles as repressors of JA signaling. We examined whether extracellular ATP impacts the stability of JAZ1 in Arabidopsis. The results showed that the JAZ1 stability decreased in response to ATP addition in a proteasome-dependent manner. This reduction required intracellular signaling via second messengers-cytosolic calcium, reactive oxygen species, and nitric oxide. Interestingly, the ATP-induced JAZ1 degradation was attenuated in the JA receptor mutant, coi1 , but not in the JA biosynthesis mutant, aos , or upon addition of JA biosynthesis inhibitors. Immunoprecipitation analysis demonstrated that ATP increases the interaction between COI1 and JAZ1, suggesting direct cross talk between extracellular ATP and JA in intracellular signaling events. Taken together, these results suggest that extracellular ATP signaling directly impacts the JA signaling pathway to maximize plant defense responses. © 2018

Network-level architecture and the evolutionary potential of underground metabolism.

PubMed

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

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 remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

PubMed

Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

2018-01-01

In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the

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

PubMed Central

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

Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

PubMed Central

2014-01-01

Background Plant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis. Results The dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes’ expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0

PubMed Central

Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-01-01

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

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

PubMed

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.

Ongoing resolution of duplicate gene functions shapes the diversification of a metabolic network

PubMed Central

Kuang, Meihua Christina; Hutchins, Paul D; Russell, Jason D; Coon, Joshua J; Hittinger, Chris Todd

2016-01-01

The evolutionary mechanisms leading to duplicate gene retention are well understood, but the long-term impacts of paralog differentiation on the regulation of metabolism remain underappreciated. Here we experimentally dissect the functions of two pairs of ancient paralogs of the GALactose sugar utilization network in two yeast species. We show that the Saccharomyces uvarum network is more active, even as over-induction is prevented by a second co-repressor that the model yeast Saccharomyces cerevisiae lacks. Surprisingly, removal of this repression system leads to a strong growth arrest, likely due to overly rapid galactose catabolism and metabolic overload. Alternative sugars, such as fructose, circumvent metabolic control systems and exacerbate this phenotype. We further show that S. cerevisiae experiences homologous metabolic constraints that are subtler due to how the paralogs have diversified. These results show how the functional differentiation of paralogs continues to shape regulatory network architectures and metabolic strategies long after initial preservation. DOI: http://dx.doi.org/10.7554/eLife.19027.001 PMID:27690225

Dynamic brain glucose metabolism identifies anti-correlated cortical-cerebellar networks at rest.

PubMed

Tomasi, Dardo G; Shokri-Kojori, Ehsan; Wiers, Corinde E; Kim, Sunny W; Demiral, Şukru B; Cabrera, Elizabeth A; Lindgren, Elsa; Miller, Gregg; Wang, Gene-Jack; Volkow, Nora D

2017-12-01

It remains unclear whether resting state functional magnetic resonance imaging (rfMRI) networks are associated with underlying synchrony in energy demand, as measured by dynamic 2-deoxy-2-[ 18 F]fluoroglucose (FDG) positron emission tomography (PET). We measured absolute glucose metabolism, temporal metabolic connectivity (t-MC) and rfMRI patterns in 53 healthy participants at rest. Twenty-two rfMRI networks emerged from group independent component analysis (gICA). In contrast, only two anti-correlated t-MC emerged from FDG-PET time series using gICA or seed-voxel correlations; one included frontal, parietal and temporal cortices, the other included the cerebellum and medial temporal regions. Whereas cerebellum, thalamus, globus pallidus and calcarine cortex arose as the strongest t-MC hubs, the precuneus and visual cortex arose as the strongest rfMRI hubs. The strength of the t-MC linearly increased with the metabolic rate of glucose suggesting that t-MC measures are strongly associated with the energy demand of the brain tissue, and could reflect regional differences in glucose metabolism, counterbalanced metabolic network demand, and/or differential time-varying delivery of FDG. The mismatch between metabolic and functional connectivity patterns computed as a function of time could reflect differences in the temporal characteristics of glucose metabolism as measured with PET-FDG and brain activation as measured with rfMRI.

Random sampling of elementary flux modes in large-scale metabolic networks.

PubMed

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks.

PubMed

Laniau, Julie; Frioux, Clémence; Nicolas, Jacques; Baroukh, Caroline; Cortes, Maria-Paz; Got, Jeanne; Trottier, Camille; Eveillard, Damien; Siegel, Anne

2017-01-01

The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests , which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of compounds. By considering the best

Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks

PubMed Central

Frioux, Clémence; Nicolas, Jacques; Baroukh, Caroline; Cortes, Maria-Paz; Got, Jeanne; Trottier, Camille; Eveillard, Damien

2017-01-01

Background The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. Results We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests, which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. Conclusion The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of

CMPF: class-switching minimized pathfinding in metabolic networks.

PubMed

Lim, Kevin; Wong, Limsoon

2012-01-01

The metabolic network is an aggregation of enzyme catalyzed reactions that converts one compound to another. Paths in a metabolic network are a sequence of enzymes that describe how a chemical compound of interest can be produced in a biological system. As the number of such paths is quite large, many methods have been developed to score paths so that the k-shortest paths represent the set of paths that are biologically meaningful or efficient. However, these approaches do not consider whether the sequence of enzymes can be manufactured in the same pathway/species/localization. As a result, a predicted sequence might consist of groups of enzymes that operate in distinct pathway/species/localization and may not truly reflect the events occurring within cell. We propose a path weighting method CMPF (Class-switching Minimized Pathfinder) to search for routes in a metabolic network which minimizes pathway switching. In biological terms, a pathway is a series of chemical reactions which define a specific function (e.g. glycolysis). We conjecture that routes that cross many pathways are inefficient since different pathways define different metabolic functions. In addition, native routes are also well characterized within pathways, suggesting that reasonable paths should not involve too many pathway switches. Our method can be generalized when reactions participate in a class set (e.g., pathways, species or cellular localization) so that the paths predicted have minimal class crossings. We show that our method generates k-paths that involve the least number of class switching. In addition, we also show that native paths are recoverable and alternative paths deviates less from native paths compared to other methods. This suggests that paths ranked by our method could be a way to predict paths that are likely to occur in biological systems.

Effect of jasmonic acid and yeast extract elicitation on low-molecular antioxidants and antioxidant activity of marjoram (Origanum majorana L.).

PubMed

Złotek, Urszula

2017-01-01

Elicitation, which is a way of inducing plant secondary metabolism, may be an effective method for improving the quality of plant food. The aim of this study was to determine how the application of jasmonic acid (as an abiotic elicitor) and yeast extract (as a biotic elicitor) influences the production of some bioactive compounds in marjoram and the antioxidant activity of this herb. Elicitation with 0.01 µM and 1 µM jasmonic acid as well as 0.1% and 1% yeast extracts was used for improving the health-benefiting quality of marjoram. The study focused on the effects of eliciting the level of some phytochemicals and the antioxidant activity of marjoram. There were no significant differences in total phenolic content between the elicited and control plants. In turn, the elicitation with 0.1% and 1% yeast extracts caused 1.8- and 2.5-fold increases in the ascorbic acid content in marjoram leaves, respectively. Both biotic and abiotic elicitation resulted in elevation of chlorophyll content, but only the abiotic elicitor (jasmonic acid) caused a significant increase (by over 50%) in the carotenoid content of marjoram leaves. The antiradical activity of marjoram was increased by the abiotic and biotic elicitation, whereas only the abiotic elicitation resulted in improving the reducing power of this herb. In conclusion, biotic and abiotic elicitation could be an effective strategy for improving the level of some phytochemicals, as well as the antioxidant activity of marjoram. A particularly valuable finding obtained in this study is that natural elicitors e.g. yeast extract can be equally effective in elevating the content of some bioactive compounds in herbs e.g. marjoram as an abiotic one.

Short- and long-term changes in sugarbeet (Beta vulgaris L.) gene expression after postharvest jasmonic acid treatment

USDA-ARS?s Scientific Manuscript database

Jasmonic acid is a natural plant hormone that induces native defense responses in plants. Sugarbeet (Beta vulgaris L.) root unigenes that were differentially expressed 2 and 60 days after a postharvest jasmonic acid treatment are presented. Data include changes in unigene expression relative to wate...

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

PubMed

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

2016-01-01

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

Use of randomized sampling for analysis of metabolic networks.

PubMed

Schellenberger, Jan; Palsson, Bernhard Ø

2009-02-27

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

Jasmonate signaling in plant stress responses and development - active and inactive compounds.

PubMed

Wasternack, Claus; Strnad, Miroslav

2016-09-25

Jasmonates (JAs) are lipid-derived signals mediating plant responses to biotic and abiotic stresses and in plant development. Following the elucidation of each step in their biosynthesis and the important components of perception and signaling, several activators, repressors and co-repressors have been identified which contribute to fine-tuning the regulation of JA-induced gene expression. Many of the metabolic reactions in which JA participates, such as conjugation with amino acids, glucosylation, hydroxylation, carboxylation, sulfation and methylation, lead to numerous compounds with different biological activities. These metabolites may be highly active, partially active in specific processes or inactive. Hydroxylation, carboxylation and sulfation inactivate JA signaling. The precursor of JA biosynthesis, 12-oxo-phytodienoic acid (OPDA), has been identified as a JA-independent signaling compound. An increasing number of OPDA-specific processes is being identified. To conclude, the numerous JA compounds and their different modes of action allow plants to respond specifically and flexibly to alterations in the environment. Copyright © 2015 Elsevier B.V. All rights reserved.

FindPrimaryPairs: An efficient algorithm for predicting element-transferring reactant/product pairs in metabolic networks.

PubMed

Steffensen, Jon Lund; Dufault-Thompson, Keith; Zhang, Ying

2018-01-01

The metabolism of individual organisms and biological communities can be viewed as a network of metabolites connected to each other through chemical reactions. In metabolic networks, chemical reactions transform reactants into products, thereby transferring elements between these metabolites. Knowledge of how elements are transferred through reactant/product pairs allows for the identification of primary compound connections through a metabolic network. However, such information is not readily available and is often challenging to obtain for large reaction databases or genome-scale metabolic models. In this study, a new algorithm was developed for automatically predicting the element-transferring reactant/product pairs using the limited information available in the standard representation of metabolic networks. The algorithm demonstrated high efficiency in analyzing large datasets and provided accurate predictions when benchmarked with manually curated data. Applying the algorithm to the visualization of metabolic networks highlighted pathways of primary reactant/product connections and provided an organized view of element-transferring biochemical transformations. The algorithm was implemented as a new function in the open source software package PSAMM in the release v0.30 (https://zhanglab.github.io/psamm/).

Linking metabolic network features to phenotypes using sparse group lasso.

PubMed

Samal, Satya Swarup; Radulescu, Ovidiu; Weber, Andreas; Fröhlich, Holger

2017-11-01

Integration of metabolic networks with '-omics' data has been a subject of recent research in order to better understand the behaviour of such networks with respect to differences between biological and clinical phenotypes. Under the conditions of steady state of the reaction network and the non-negativity of fluxes, metabolic networks can be algebraically decomposed into a set of sub-pathways often referred to as extreme currents (ECs). Our objective is to find the statistical association of such sub-pathways with given clinical outcomes, resulting in a particular instance of a self-contained gene set analysis method. In this direction, we propose a method based on sparse group lasso (SGL) to identify phenotype associated ECs based on gene expression data. SGL selects a sparse set of feature groups and also introduces sparsity within each group. Features in our model are clusters of ECs, and feature groups are defined based on correlations among these features. We apply our method to metabolic networks from KEGG database and study the association of network features to prostate cancer (where the outcome is tumor and normal, respectively) as well as glioblastoma multiforme (where the outcome is survival time). In addition, simulations show the superior performance of our method compared to global test, which is an existing self-contained gene set analysis method. R code (compatible with version 3.2.5) is available from http://www.abi.bit.uni-bonn.de/index.php?id=17. samal@combine.rwth-aachen.de or frohlich@bit.uni-bonn.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Dissecting metabolic behavior of lipid over-producing strain of Mucor circinelloides through genome-scale metabolic network and multi-level data integration.

PubMed

Vongsangnak, Wanwipa; Kingkaw, Amornthep; Yang, Junhuan; Song, Yuanda; Laoteng, Kobkul

2018-09-05

Lipid accumulation is an important cellular process of oleaginous microorganisms. To dissect metabolic behavior of oleaginous Zygomycetes, the lipid over-producing strain, Mucor circinelloides WJ11, was subjected for omics-scale analysis. The genome annotation was improved and used for construction of genome-scale metabolic network of WJ11 strain. Then, the quality of the metabolic network was enhanced by incorporating gene and protein expression data. In addition to the known oleaginous genes, our results showed a number of newly identified unique genes of WJ11 strain, which involved in central carbon metabolism, lipid, amino acid and nitrogen metabolisms. The systematic compilations indicated the additional metabolic routes with the involvement in supplying precursors (acetyl-CoA, NADPH and fatty acyl substrate) for fatty acid and lipid biosynthesis. Interestingly, amino acid metabolism played a substantial role in responsive mechanism of the fungal cells to nutrient imbalance circumstance through lipogenesis as the finding of reporter metabolites (l-methionine, l-glutamate, l-aspartate, l-asparagine and l-glutamine) at lipid-accumulating stage. The cooperative function of certain lipid-degrading enzymes at the particular growth stage was elucidated by integrating the metabolic networks with gene expression data. The unique feature of carotenoid biosynthetic route in WJ11 strain was also identified by protein domain analysis. Taken together, there were cross-functional metabolisms in regulating lipid biosynthesis and retaining high level of cellular lipids in the representative of lipid over-producing strains. Copyright © 2018 Elsevier B.V. All rights reserved.

Abnormal metabolic brain networks in Parkinson's disease from blackboard to bedside.

PubMed

Tang, Chris C; Eidelberg, David

2010-01-01

Metabolic imaging in the rest state has provided valuable information concerning the abnormalities of regional brain function that underlie idiopathic Parkinson's disease (PD). Moreover, network modeling procedures, such as spatial covariance analysis, have further allowed for the quantification of these changes at the systems level. In recent years, we have utilized this strategy to identify and validate three discrete metabolic networks in PD associated with the motor and cognitive manifestations of the disease. In this chapter, we will review and compare the specific functional topographies underlying parkinsonian akinesia/rigidity, tremor, and cognitive disturbance. While network activity progressed over time, the rate of change for each pattern was distinctive and paralleled the development of the corresponding clinical symptoms in early-stage patients. This approach is already showing great promise in identifying individuals with prodromal manifestations of PD and in assessing the rate of progression before clinical onset. Network modulation was found to correlate with the clinical effects of dopaminergic treatment and surgical interventions, such as subthalamic nucleus (STN) deep brain stimulation (DBS) and gene therapy. Abnormal metabolic networks have also been identified for atypical parkinsonian syndromes, such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Using multiple disease-related networks for PD, MSA, and PSP, we have developed a novel, fully automated algorithm for accurate classification at the single-patient level, even at early disease stages. Copyright © 2010 Elsevier B.V. All rights reserved.

Discovery of Boolean metabolic networks: integer linear programming based approach.

PubMed

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets.

PubMed

Koch, Ina; Nöthen, Joachim; Schleiff, Enrico

2017-01-01

Motivation: Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem. Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana . We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs. Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the fixed carbon to

Identifying all moiety conservation laws in genome-scale metabolic networks.

PubMed

De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

2014-01-01

The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

MetaNET--a web-accessible interactive platform for biological metabolic network analysis.

PubMed

Narang, Pankaj; Khan, Shawez; Hemrom, Anmol Jaywant; Lynn, Andrew Michael

2014-01-01

Metabolic reactions have been extensively studied and compiled over the last century. These have provided a theoretical base to implement models, simulations of which are used to identify drug targets and optimize metabolic throughput at a systemic level. While tools for the perturbation of metabolic networks are available, their applications are limited and restricted as they require varied dependencies and often a commercial platform for full functionality. We have developed MetaNET, an open source user-friendly platform-independent and web-accessible resource consisting of several pre-defined workflows for metabolic network analysis. MetaNET is a web-accessible platform that incorporates a range of functions which can be combined to produce different simulations related to metabolic networks. These include (i) optimization of an objective function for wild type strain, gene/catalyst/reaction knock-out/knock-down analysis using flux balance analysis. (ii) flux variability analysis (iii) chemical species participation (iv) cycles and extreme paths identification and (v) choke point reaction analysis to facilitate identification of potential drug targets. The platform is built using custom scripts along with the open-source Galaxy workflow and Systems Biology Research Tool as components. Pre-defined workflows are available for common processes, and an exhaustive list of over 50 functions are provided for user defined workflows. MetaNET, available at http://metanet.osdd.net , provides a user-friendly rich interface allowing the analysis of genome-scale metabolic networks under various genetic and environmental conditions. The framework permits the storage of previous results, the ability to repeat analysis and share results with other users over the internet as well as run different tools simultaneously using pre-defined workflows, and user-created custom workflows.

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

PubMed Central

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

2013-01-01

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

Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.

PubMed

Wolff, Sara M; Ellison, Melinda J; Hao, Yue; Cockrum, Rebecca R; Austin, Kathy J; Baraboo, Michael; Burch, Katherine; Lee, Hyuk Jin; Maurer, Taylor; Patil, Rocky; Ravelo, Andrea; Taxis, Tasia M; Truong, Huan; Lamberson, William R; Cammack, Kristi M; Conant, Gavin C

2017-06-08

Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal's diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host's metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.

Metabolic PathFinding: inferring relevant pathways in biochemical networks.

PubMed

Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques

2005-07-01

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).

Ethylene and jasmonic acid act as negative modulators during mutualistic symbiosis between Laccaria bicolor and Populus roots.

PubMed

Plett, Jonathan M; Khachane, Amit; Ouassou, Malika; Sundberg, Björn; Kohler, Annegret; Martin, Francis

2014-04-01

The plant hormones ethylene, jasmonic acid and salicylic acid have interconnecting roles during the response of plant tissues to mutualistic and pathogenic symbionts. We used morphological studies of transgenic- or hormone-treated Populus roots as well as whole-genome oligoarrays to examine how these hormones affect root colonization by the mutualistic ectomycorrhizal fungus Laccaria bicolor S238N. We found that genes regulated by ethylene, jasmonic acid and salicylic acid were regulated in the late stages of the interaction between L. bicolor and poplar. Both ethylene and jasmonic acid treatments were found to impede fungal colonization of roots, and this effect was correlated to an increase in the expression of certain transcription factors (e.g. ETHYLENE RESPONSE FACTOR1) and a decrease in the expression of genes associated with microbial perception and cell wall modification. Further, we found that ethylene and jasmonic acid showed extensive transcriptional cross-talk, cross-talk that was opposed by salicylic acid signaling. We conclude that ethylene and jasmonic acid pathways are induced late in the colonization of root tissues in order to limit fungal growth within roots. This induction is probably an adaptive response by the plant such that its growth and vigor are not compromised by the fungus. © 2013 The Authors New Phytologist © 2013 New Phytologist Trust.

The evolution of metabolic networks of E. coli

PubMed Central

2011-01-01

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

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and

Inhibitory effect of jasmonic acid and ethylene on epicotyl growth and bud induction in the maritime pine, Pinus pinaster Soland. in ait.

PubMed

Martin, Maria Teresa; Pedranzani, Hilda; García-Molinero, Patricia; Pando, Valentin; Sierra-de-Grado, Rosario

2009-12-01

Two independent parameters, epicotyl height (cm) and number of induced buds were studied on Pinus pinaster explants to analyse the effects of three phytohormones (6-benzylaminopurine, jasmonic acid, ethylene) which were combined or not in 11 different treatments. Epicotyle length diminished significantly in relation to the control medium (medium without exogen phytohormones) in presence of jasmonic acid, 6-benzylaminopurine or Ethephon (which is converted to ethylene in plants) in any of treatments. Concentrations of 100 microM of jasmonic acid and Ethephon had a greater inhibitory effect than the treatments with 10 microM. In addition to that, jasmonic acid was a stronger inhibitor than Ethephon in any of the tried combinations. There were no significant differences between the control treatment and the treatments with only 10 microM of jasmonic acid or Ethephon. However, 10 microM 6-benzylaminopurine induced bud formation. The different combinations of 6-benzylaminopurine with jasmonic acid and Ethephon showed that concentrations of 10 to 100 microM did not affect the number of induced buds. Jasmonic acid had an inhibitory effect which Ethephon only showed when combined with 100 microM of jasmonic acid and 10 microM of 6-benzylaminopurine. Three response groups were defined by cluster analysis: group 1 produced the greatest mean number of buds (4 to 5) and a mean epicotyl growth of 1 to 1.5 cm; group 2 produced 2 to 4 buds and a mean growth of 0.5 to 1.2 cm; group 3 produced only one bud and a mean epicotyl length of 1.2 to 2 cm.

Effect of resistant and digestible rice starches on human cytokine and lactate metabolic networks in serum.

PubMed

Wang, Huisong; Pang, Guangchang

2017-05-01

Resistant starch generated after treating ordinary starch is of great significance to human health in the countries with overnutrition. However, its functional evaluation in the human body has been rarely reported. By determining the lactate metabolic flux, 12 serum enzymes expression level and 38 serum cytokines in healthy volunteers, the variation in cytokine network and lactate metabolic network in serum were investigated to compare the mechanism of the physiological effects between the two starches. The results indicated that compared with digestible starch, resistant starch had anti-inflammatory effects, increased anabolism, and decreased catabolism. Further, the intercellular communication networks including cytokine and lactate metabolic networks were mapped out. The relationship suggested that resistant starch might affect and control the secretion of cytokines to regulate lactate metabolic network in the body, promoting the development of immunometabolism. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimality principles in the regulation of metabolic networks.

PubMed

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

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.

Study on Incompatibility of Traditional Chinese Medicine: Evidence from Formula Network, Chemical Space, and Metabolism Room

PubMed Central

Zhang, Xiao-Dong; Wu, Hong-Ying; Jin, Jin; Yu, Guang-Yun; He, Xin; Wang, Hao; Shen, Xiu; Zhou, Ze-Wei; Liu, Pei-Xun; Fan, Sai-Jun

2013-01-01

A traditional Chinese medicine (TCM) formula network including 362 TCM formulas was built by using complex network methodologies. The properties of this network were analyzed including network diameter, average distance, clustering coefficient, and average degree. Meanwhile, we built a TCM chemical space and a TCM metabolism room under the theory of chemical space. The properties of chemical space and metabolism room were calculated and analyzed. The properties of the medicine pairs in “eighteen antagonisms and nineteen mutual inhibitors,” an ancient rule for TCM incompatibility, were studied based on the TCM formula network, chemical space, and metabolism room. The results showed that the properties of these incompatible medicine pairs are different from those of the other TCM based on the analysis of the TCM formula network, chemical space, and metabolism room. The lines of evidence derived from our work demonstrated that the ancient rule of TCM incompatibility, “eighteen antagonisms and nineteen mutual inhibitors,” is probably scientifically based. PMID:24369478

Bacterial Unculturability and the Formation of Intercellular Metabolic Networks.

PubMed

Pande, Samay; Kost, Christian

2017-05-01

The majority of known bacterial species cannot be cultivated under laboratory conditions. Here we argue that the adaptive emergence of obligate metabolic interactions in natural bacterial communities can explain this pattern. Bacteria commonly release metabolites into the external environment. Accumulating pools of extracellular metabolites create an ecological niche that benefits auxotrophic mutants, which have lost the ability to autonomously produce the corresponding metabolites. In addition to a diffusion-based metabolite transfer, auxotrophic cells can use contact-dependent means to obtain nutrients from other co-occurring cells. Spatial colocalisation and a continuous coevolution further increase the nutritional dependency and optimise fluxes through combined metabolic networks. Thus, bacteria likely function as networks of interacting cells that reciprocally exchange nutrients and biochemical functions rather than as physiologically autonomous units. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Arabidopsis mutant cev1 links cell wall signaling to jasmonate and ethylene responses.

PubMed

Ellis, Christine; Karafyllidis, Ioannis; Wasternack, Claus; Turner, John G

2002-07-01

Biotic and abiotic stresses stimulate the synthesis of jasmonates and ethylene, which, in turn, induce the expression of genes involved in stress response and enhance defense responses. The cev1 mutant has constitutive expression of stress response genes and has enhanced resistance to fungal pathogens. Here, we show that cev1 plants have increased production of jasmonate and ethylene and that its phenotype is suppressed by mutations that interrupt jasmonate and ethylene signaling. Genetic mapping, complementation analysis, and sequence analysis revealed that CEV1 is the cellulose synthase CeSA3. CEV1 was expressed predominantly in root tissues, and cev1 roots contained less cellulose than wild-type roots. Significantly, the cev1 mutant phenotype could be reproduced by treating wild-type plants with cellulose biosynthesis inhibitors, and the cellulose synthase mutant rsw1 also had constitutive expression of VSP. We propose that the cell wall can signal stress responses in plants.

The Arabidopsis Mutant cev1 Links Cell Wall Signaling to Jasmonate and Ethylene Responses

PubMed Central

Ellis, Christine; Karafyllidis, Ioannis; Wasternack, Claus; Turner, John G.

2002-01-01

Biotic and abiotic stresses stimulate the synthesis of jasmonates and ethylene, which, in turn, induce the expression of genes involved in stress response and enhance defense responses. The cev1 mutant has constitutive expression of stress response genes and has enhanced resistance to fungal pathogens. Here, we show that cev1 plants have increased production of jasmonate and ethylene and that its phenotype is suppressed by mutations that interrupt jasmonate and ethylene signaling. Genetic mapping, complementation analysis, and sequence analysis revealed that CEV1 is the cellulose synthase CeSA3. CEV1 was expressed predominantly in root tissues, and cev1 roots contained less cellulose than wild-type roots. Significantly, the cev1 mutant phenotype could be reproduced by treating wild-type plants with cellulose biosynthesis inhibitors, and the cellulose synthase mutant rsw1 also had constitutive expression of VSP. We propose that the cell wall can signal stress responses in plants. PMID:12119374

Reconstruction and Analysis of Human Kidney-Specific Metabolic Network Based on Omics Data

PubMed Central

Zhang, Ai-Di; Dai, Shao-Xing; Huang, Jing-Fei

2013-01-01

With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases. PMID:24222897

Optimality Principles in the Regulation of Metabolic Networks

PubMed Central

Berkhout, Jan; Bruggeman, Frank J.; Teusink, Bas

2012-01-01

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. PMID:24957646

Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster

PubMed Central

Williams, CM; Watanabe, M; Guarracino, MR; Ferraro, MB; Edison, AS; Morgan, TJ; Boroujerdi, AFB; Hahn, DA

2015-01-01

When ectotherms are exposed to low temperatures, they enter a cold-induced coma (chill coma) that prevents resource acquisition, mating, oviposition, and escape from predation. There is substantial variation in time taken to recover from chill coma both within and among species, and this variation is correlated with habitat temperatures such that insects from cold environments recover more quickly. This suggests an adaptive response, but the mechanisms underlying variation in recovery times are unknown, making it difficult to decisively test adaptive hypotheses. We use replicated lines of Drosophila melanogaster selected in the laboratory for fast (hardy) or slow (susceptible) chill-coma recovery times to investigate modifications to metabolic profiles associated with cold adaptation. We measured metabolite concentrations of flies before, during, and after cold exposure using NMR spectroscopy to test the hypotheses that hardy flies maintain metabolic homeostasis better during cold exposure and recovery, and that their metabolic networks are more robust to cold-induced perturbations. The metabolites of cold-hardy flies were less cold responsive and their metabolic networks during cold exposure were more robust, supporting our hypotheses. Metabolites involved in membrane lipid synthesis, tryptophan metabolism, oxidative stress, energy balance, and proline metabolism were altered by selection on cold tolerance. We discuss the potential significance of these alterations. PMID:25308124

Observability of Plant Metabolic Networks Is Reflected in the Correlation of Metabolic Profiles.

PubMed

Schwahn, Kevin; Küken, Anika; Kliebenstein, Daniel J; Fernie, Alisdair R; Nikoloski, Zoran

2016-10-01

Understanding whether the functionality of a biological system can be characterized by measuring few selected components is key to targeted phenotyping techniques in systems biology. Methods from observability theory have proven useful in identifying sensor components that have to be measured to obtain information about the entire system. Yet, the extent to which the data profiles reflect the role of components in the observability of the system remains unexplored. Here we first identify the sensor metabolites in the model plant Arabidopsis (Arabidopsis thaliana) by employing state-of-the-art genome-scale metabolic networks. By using metabolic data profiles from a set of seven environmental perturbations as well as from natural variability, we demonstrate that the data profiles of sensor metabolites are more correlated than those of nonsensor metabolites. This pattern was confirmed with in silico generated metabolic profiles from a medium-size kinetic model of plant central carbon metabolism. Altogether, due to the small number of identified sensors, our study implies that targeted metabolite analyses may provide the vast majority of relevant information about plant metabolic systems. © 2016 American Society of Plant Biologists. All Rights Reserved.

Preharvest methyl jasmonate and postharvest UVC treatments: increasing stilbenes in wine.

PubMed

Fernández-Marín, María Isabel; Puertas, Belén; Guerrero, Raúl F; García-Parrilla, María Carmen; Cantos-Villar, Emma

2014-03-01

Stilbene-enriched wine is considered to be an interesting new food product with added value due to its potential health-promoting properties. Stilbene concentration in grape is highly variable and rather scarce. However, it can be increased by stress treatments. For this reason, numerous pre- and postharvest grape treatments, and some combinations of them, have been tested to maximize stilbene content in grapes. In the present manuscript, Syrah grapes were treated with (i) methyl jasmonate (MEJA), (ii) ultraviolet light (UVC), and (iii) methyl jasmonate and ultraviolet light (MEJA-UVC) and compared with untreated grapes. Afterward, winemaking was developed. Wine achieved by combination of both treatments (MEJA-UVC) contained significantly higher stilbene concentration (trans-resveratrol and piceatannol) than its respective control (2.5-fold). Wine quality was improved in color-related parameters (color intensity, L*, a*, b*, ΔE*, anthocyanins, and tannin). Moreover, MEJA-UVC wines obtained the highest score in sensorial analysis. To the best of our knowledge, this is the first time that pre- and postharvest treatments are combined to increase stilbenes in wine. The effect of treatment combination (methyl jasmonate and UVC light) on grape and wine was evaluated. Our results highlight the positive effect of the treatments in stilbene content, color parameters, and sensorial analysis. Moreover, added-value by-products were achieved. © 2014 Institute of Food Technologists®

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

DOE PAGES

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan; ...

2016-04-15

Here, 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 meta-graph 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 networkmore » 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.« less

A Regulatory Network for Coordinated Flower Maturation

PubMed Central

Ploense, Sara E.; Wu, Miin-Feng; Yadav, Vandana; Tholl, Dorothea; Chételat, Aurore; Haupt, Ina; Kennerley, Brian J.; Hodgens, Charles; Farmer, Edward E.; Nagpal, Punita; Reed, Jason W.

2012-01-01

For self-pollinating plants to reproduce, male and female organ development must be coordinated as flowers mature. The Arabidopsis transcription factors AUXIN RESPONSE FACTOR 6 (ARF6) and ARF8 regulate this complex process by promoting petal expansion, stamen filament elongation, anther dehiscence, and gynoecium maturation, thereby ensuring that pollen released from the anthers is deposited on the stigma of a receptive gynoecium. ARF6 and ARF8 induce jasmonate production, which in turn triggers expression of MYB21 and MYB24, encoding R2R3 MYB transcription factors that promote petal and stamen growth. To understand the dynamics of this flower maturation regulatory network, we have characterized morphological, chemical, and global gene expression phenotypes of arf, myb, and jasmonate pathway mutant flowers. We found that MYB21 and MYB24 promoted not only petal and stamen development but also gynoecium growth. As well as regulating reproductive competence, both the ARF and MYB factors promoted nectary development or function and volatile sesquiterpene production, which may attract insect pollinators and/or repel pathogens. Mutants lacking jasmonate synthesis or response had decreased MYB21 expression and stamen and petal growth at the stage when flowers normally open, but had increased MYB21 expression in petals of older flowers, resulting in renewed and persistent petal expansion at later stages. Both auxin response and jasmonate synthesis promoted positive feedbacks that may ensure rapid petal and stamen growth as flowers open. MYB21 also fed back negatively on expression of jasmonate biosynthesis pathway genes to decrease flower jasmonate level, which correlated with termination of growth after flowers have opened. These dynamic feedbacks may promote timely, coordinated, and transient growth of flower organs. PMID:22346763

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

PubMed

Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

Occurrence of jasmonates during cystocarp development in the red alga Grateloupia imbricata.

PubMed

Pilar, Garcia-Jimenez; Olegario, Brito-Romano; Rafael, Robaina R

2016-12-01

In this study, we highlight the effects of methyl jasmonate (MeJa) on cystocarp development in the red macroscopic alga Grateloupia imbricata. In G. imbricata, jasmonate release is related to the reproductive state, as fertile thalli (i.e., those that have cystocarps) released significant amounts of this volatile compound (1.27 ± 0.20 mM · mg fw -1  · h -1 ) compared with infertile thalli (0.95 ± 0.12 mM · mg fw -1  · h -1 ). Treating G. imbricata thalli with MeJa revealed a significant increase in cystocarp number (1.5 ± 0.27 cystocarps · mm -2 ), which was ~7.5-fold greater than in untreated thalli (0.2 ± 0.07 cystocarps · mm -2 ). Maturation was completed within 48 h with MeJa treatment, a shortening of the typical >3-week maturation period, and included the opening of cystocarps and the presence of dehiscent cavities. Release rates of jasmonates after exogenous MeJa treatment were also modified based on the cystocarp maturation level. All of these effects were reduced in the presence of phenidone, which blocks MeJa production, indicating that the MeJa action is genuine. The effects of MeJa during cystocarp maturation were not replicated by derivatives of reactive oxygen species from the same jasmonic acid biosynthetic pathway, as the activities of scavenger enzymes and lipid peroxidation were unchanged between infertile and fertile thalli. Therefore, a reactive oxygen species-based mechanism is not involved during cystocarp development. We conclude that MeJa has an independent function as a growth regulator during G. imbricata reproduction. © 2016 Phycological Society of America.

Elicitation of Diosgenin Production in Trigonella foenum-graecum (Fenugreek) Seedlings by Methyl Jasmonate

PubMed Central

Chaudhary, Spandan; Chikara, Surendra K.; Sharma, Mahesh C.; Chaudhary, Abhinav; Alam Syed, Bakhtiyar; Chaudhary, Pooja S.; Mehta, Aditya; Patel, Maulik; Ghosh, Arpita; Iriti, Marcello

2015-01-01

The effects of methyl jasmonate (MeJA), an elicitor of plant defense mechanisms, on the biosynthesis of diosgenin, a steroidal saponin, were investigated in six fenugreek (Trigonella foenum-graecum) varieties (Gujarat Methi-2, Kasuri-1, Kasuri-2, Pusa Early Branching, Rajasthan Methi and Maharashtra Methi-5). Treatment with 0.01% MeJA increased diosgenin levels, in 12 days old seedlings, from 0.5%–0.9% to 1.1%–1.8%. In addition, MeJA upregulated the expression of two pivotal genes of the mevalonate pathway, the metabolic route leading to diosgenin: 3-hydroxy-3-methylglutaryl-CoA reductase (HMG) and sterol-3-β-glucosyl transferase (STRL). In particular, MeJA increased the expression of HMG and STRL genes by 3.2- and 22.2-fold, respectively, in the Gujarat Methi-2 variety, and by 25.4- and 28.4-fold, respectively, in the Kasuri-2 variety. Therefore, MeJA may be considered a promising elicitor for diosgenin production by fenugreek plants. PMID:26694357

Genetic variation in jasmonic acid- and spider mite-induced plant volatile emission of cucumber accessions and attraction of the predator Phytoseiulus persimilis.

PubMed

Kappers, Iris F; Verstappen, Francel W A; Luckerhoff, Ludo L P; Bouwmeester, Harro J; Dicke, Marcel

2010-05-01

Cucumber plants (Cucumis sativus L.) respond to spider-mite (Tetranychus urticae) damage with the release of specific volatiles that are exploited by predatory mites, the natural enemies of the spider mites, to locate their prey. The production of volatiles also can be induced by exposing plants to the plant hormone jasmonic acid. We analyzed volatile emissions from 15 cucumber accessions upon herbivory by spider mites and upon exposure to jasmonic acid using gas chromatography-mass spectrometry. Upon induction, cucumber plants emitted over 24 different compounds, and the blend of induced volatiles consisted predominantly of terpenoids. The total amount of volatiles was higher in plants treated with jasmonic acid than in those infested with spider mites, with (E)-4,8-dimethyl-1,3,7-nonatriene, (E,E)-alpha-farnesene, and (E)-beta-ocimene as the most abundant compounds in all accessions in both treatments. Significant variation among the accessions was found for the 24 major volatile compounds. The accessions differed strongly in total amount of volatiles emitted, and displayed very different odor profiles. Principal component analysis performed on the relative quantities of particular compounds within the blend revealed clusters of highly correlated volatiles, which is suggestive of common metabolic pathways. A number of cucumber accessions also were tested for their attractiveness to Phytoseiulus persimilis, a specialist predator of spider mites. Differences in the attraction of predatory mites by the various accessions correlated to differences in the individual chemical profiles of these accessions. The presence of genetic variation in induced plant volatile emission in cucumber shows that it is possible to breed for cucumber varieties that are more attractive to predatory mites and other biological control agents.

Genetic Variation in Jasmonic Acid- and Spider Mite-Induced Plant Volatile Emission of Cucumber Accessions and Attraction of the Predator Phytoseiulus persimilis

PubMed Central

Verstappen, Francel W. A.; Luckerhoff, Ludo L. P.; Bouwmeester, Harro J.; Dicke, Marcel

2010-01-01

Cucumber plants (Cucumis sativus L.) respond to spider–mite (Tetranychus urticae) damage with the release of specific volatiles that are exploited by predatory mites, the natural enemies of the spider mites, to locate their prey. The production of volatiles also can be induced by exposing plants to the plant hormone jasmonic acid. We analyzed volatile emissions from 15 cucumber accessions upon herbivory by spider mites and upon exposure to jasmonic acid using gas chromatography—mass spectrometry. Upon induction, cucumber plants emitted over 24 different compounds, and the blend of induced volatiles consisted predominantly of terpenoids. The total amount of volatiles was higher in plants treated with jasmonic acid than in those infested with spider mites, with (E)-4,8-dimethyl-1,3,7-nonatriene, (E,E)-α-farnesene, and (E)-β-ocimene as the most abundant compounds in all accessions in both treatments. Significant variation among the accessions was found for the 24 major volatile compounds. The accessions differed strongly in total amount of volatiles emitted, and displayed very different odor profiles. Principal component analysis performed on the relative quantities of particular compounds within the blend revealed clusters of highly correlated volatiles, which is suggestive of common metabolic pathways. A number of cucumber accessions also were tested for their attractiveness to Phytoseiulus persimilis, a specialist predator of spider mites. Differences in the attraction of predatory mites by the various accessions correlated to differences in the individual chemical profiles of these accessions. The presence of genetic variation in induced plant volatile emission in cucumber shows that it is possible to breed for cucumber varieties that are more attractive to predatory mites and other biological control agents. PMID:20383796

Methyl jasmonate stimulates biosynthesis of 2-phenylethylamine, phenylacetic acid and 2-phenylethanol in seedlings of common buckwheat.

PubMed

Horbowicz, Marcin; Wiczkowski, Wiesław; Sawicki, Tomasz; Szawara-Nowak, Dorota; Sytykiewicz, Hubert; Mitrus, Joanna

2015-01-01

Methyl jasmonate has a strong effect on secondary metabolizm in plants, by stimulating the biosynthesis a number of phenolic compounds and alkaloids. Common buckwheat (Fagopyrum esculentum Moench) is an important source of biologically active compounds. This research focuses on the detection and quantification of 2-phenylethylamine and its possible metabolites in the cotyledons, hypocotyl and roots of common buckwheat seedlings treated with methyl jasmonate. In cotyledons of buckwheat sprouts, only traces of 2-phenylethylamine were found, while in the hypocotyl and roots its concentration was about 150 and 1000-times higher, respectively. Treatment with methyl jasmonate resulted in a 4-fold increase of the 2-phenylethylamine level in the cotyledons of 7-day buckwheat seedlings, and an 11-fold and 5-fold increase in hypocotyl and roots, respectively. Methyl jasmonate treatment led also to about 4-fold increase of phenylacetic acid content in all examined seedling organs, but did not affect the 2-phenylethanol level in cotyledons, and slightly enhanced in hypocotyl and roots. It has been suggested that 2-phenylethylamine is a substrate for the biosynthesis of phenylacetic acid and 2-phenylethanol, as well as cinnamoyl 2-phenethylamide. In organs of buckwheat seedling treated with methyl jasmonate, higher amounts of aromatic amino acid transaminase mRNA were found. The enzyme can be involved in the synthesis of phenylpyruvic acid, but the presence of this compound could not be confirmed in any of the examined organs of common buckwheat seedling.

Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery☆

PubMed Central

Kell, Douglas B.; Goodacre, Royston

2014-01-01

Metabolism represents the ‘sharp end’ of systems biology, because changes in metabolite concentrations are necessarily amplified relative to changes in the transcriptome, proteome and enzyme activities, which can be modulated by drugs. To understand such behaviour, we therefore need (and increasingly have) reliable consensus (community) models of the human metabolic network that include the important transporters. Small molecule ‘drug’ transporters are in fact metabolite transporters, because drugs bear structural similarities to metabolites known from the network reconstructions and from measurements of the metabolome. Recon2 represents the present state-of-the-art human metabolic network reconstruction; it can predict inter alia: (i) the effects of inborn errors of metabolism; (ii) which metabolites are exometabolites, and (iii) how metabolism varies between tissues and cellular compartments. However, even these qualitative network models are not yet complete. As our understanding improves so do we recognise more clearly the need for a systems (poly)pharmacology. PMID:23892182

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets

PubMed Central

Koch, Ina; Nöthen, Joachim; Schleiff, Enrico

2017-01-01

Motivation: Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem. Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana. We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs. Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the fixed carbon to

Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism.

PubMed

Tabe-Bordbar, Shayan; Marashi, Sayed-Amir

2013-12-01

Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.

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

NASA Technical Reports Server (NTRS)

Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)

2001-01-01

Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

PubMed

Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

2018-04-01

Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

Arabidopsis Class I and Class II TCP Transcription Factors Regulate Jasmonic Acid Metabolism and Leaf Development Antagonistically1[C][W

PubMed Central

Danisman, Selahattin; van der Wal, Froukje; Dhondt, Stijn; Waites, Richard; de Folter, Stefan; Bimbo, Andrea; van Dijk, Aalt DJ; Muino, Jose M.; Cutri, Lucas; Dornelas, Marcelo C.; Angenent, Gerco C.; Immink, Richard G.H.

2012-01-01

TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR1 (TCP) transcription factors control developmental processes in plants. The 24 TCP transcription factors encoded in the Arabidopsis (Arabidopsis thaliana) genome are divided into two classes, class I and class II TCPs, which are proposed to act antagonistically. We performed a detailed phenotypic analysis of the class I tcp20 mutant, showing an increase in leaf pavement cell sizes in 10-d-old seedlings. Subsequently, a glucocorticoid receptor induction assay was performed, aiming to identify potential target genes of the TCP20 protein during leaf development. The LIPOXYGENASE2 (LOX2) and class I TCP9 genes were identified as TCP20 targets, and binding of TCP20 to their regulatory sequences could be confirmed by chromatin immunoprecipitation analyses. LOX2 encodes for a jasmonate biosynthesis gene, which is also targeted by class II TCP proteins that are under the control of the microRNA JAGGED AND WAVY (JAW), although in an antagonistic manner. Mutation of TCP9, the second identified TCP20 target, resulted in increased pavement cell sizes during early leaf developmental stages. Analysis of senescence in the single tcp9 and tcp20 mutants and the tcp9tcp20 double mutants showed an earlier onset of this process in comparison with wild-type control plants in the double mutant only. Both the cell size and senescence phenotypes are opposite to the known class II TCP mutant phenotype in JAW plants. Altogether, these results point to an antagonistic function of class I and class II TCP proteins in the control of leaf development via the jasmonate signaling pathway. PMID:22718775

Context-specific metabolic networks are consistent with experiments.

PubMed

Becker, Scott A; Palsson, Bernhard O

2008-05-16

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.

Response of Sunflower (Helianthus annuus L.) Leaf Surface Defenses to Exogenous Methyl Jasmonate

PubMed Central

Rowe, Heather C.; Ro, Dae-kyun; Rieseberg, Loren H.

2012-01-01

Helianthus annuus, the common sunflower, produces a complex array of secondary compounds that are secreted into glandular trichomes, specialized structures found on leaf surfaces and anther appendages of flowers. The primary components of these trichome secretions are sesquiterpene lactones (STL), a diverse class of compounds produced abundantly by the plant family Compositae and believed to contribute to plant defense against herbivory. We treated wild and cultivated H. annuus accessions with exogenous methyl jasmonate, a plant hormone that mediates plant defense against insect herbivores and certain classes of fungal pathogens. The wild sunflower produced a higher density of glandular trichomes on its leaves than the cultivar. Comparison of the profiles of glandular trichome extracts obtained by liquid chromatography–mass spectroscopy (LC-MS) showed that wild and cultivated H. annuus were qualitatively similar in surface chemistry, although differing in the relative size and proportion of various compounds detected. Despite observing consistent transcriptional responses to methyl jasmonate treatment, we detected no significant effect on glandular trichome density or LC-MS profile in cultivated or wild sunflower, with wild sunflower exhibiting a declining trend in overall STL production and foliar glandular trichome density of jasmonate-treated plants. These results suggest that glandular trichomes and associated compounds may act as constitutive defenses or require greater levels of stimulus for induction than the observed transcriptional responses to exogenous jasmonate. Reduced defense investment in domesticated lines is consistent with predicted tradeoffs caused by selection for increased yield; future research will focus on the development of genetic resources to explicitly test the ecological roles of glandular trichomes and associated effects on plant growth and fitness. PMID:22623991

Response of sunflower (Helianthus annuus L.) leaf surface defenses to exogenous methyl jasmonate.

PubMed

Rowe, Heather C; Ro, Dae-kyun; Rieseberg, Loren H

2012-01-01

Helianthus annuus, the common sunflower, produces a complex array of secondary compounds that are secreted into glandular trichomes, specialized structures found on leaf surfaces and anther appendages of flowers. The primary components of these trichome secretions are sesquiterpene lactones (STL), a diverse class of compounds produced abundantly by the plant family Compositae and believed to contribute to plant defense against herbivory. We treated wild and cultivated H. annuus accessions with exogenous methyl jasmonate, a plant hormone that mediates plant defense against insect herbivores and certain classes of fungal pathogens. The wild sunflower produced a higher density of glandular trichomes on its leaves than the cultivar. Comparison of the profiles of glandular trichome extracts obtained by liquid chromatography-mass spectroscopy (LC-MS) showed that wild and cultivated H. annuus were qualitatively similar in surface chemistry, although differing in the relative size and proportion of various compounds detected. Despite observing consistent transcriptional responses to methyl jasmonate treatment, we detected no significant effect on glandular trichome density or LC-MS profile in cultivated or wild sunflower, with wild sunflower exhibiting a declining trend in overall STL production and foliar glandular trichome density of jasmonate-treated plants. These results suggest that glandular trichomes and associated compounds may act as constitutive defenses or require greater levels of stimulus for induction than the observed transcriptional responses to exogenous jasmonate. Reduced defense investment in domesticated lines is consistent with predicted tradeoffs caused by selection for increased yield; future research will focus on the development of genetic resources to explicitly test the ecological roles of glandular trichomes and associated effects on plant growth and fitness.

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

PubMed

Abedpour, Nima; Kollmann, Markus

2015-11-23

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. We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networks can be calculated for different environmental conditions. We observe a significant structural reshaping of metabolic networks for a toy-network and E. coli core metabolism if we increase the share of invested resources for switching between different nutrient conditions. Here, hub nodes emerge and the optimal network structure becomes bow-tie-like as a consequence of limited cellular resource constraint. We confirm this theoretical finding by comparing the reconstructed metabolic networks of bacterial species with respect to their lifestyle. We show that bow-tie structure can give a system-level fitness advantage to organisms that live in highly competitive and fluctuating environments. Here, limitation of cellular resources can lead to an efficiency-flexibility tradeoff where it pays off for the organism to shorten catabolic pathways if they are frequently activated and deactivated. As a consequence, generalists that shuttle between diverse environmental conditions should have a more predominant bow-tie structure than specialists that visit just a few isomorphic habitats during their life cycle.

Metabolic network prediction through pairwise rational kernels.

PubMed

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

Review: Endoplasmic Reticulum-Associated Degradation (ERAD)-Dependent Control of (Tri)terpenoid Metabolism in Plants.

PubMed

Erffelinck, Marie-Laure; Goossens, Alain

2018-06-15

Plants are sessile organisms. Therefore, they developed the capacity to quickly respond to biotic and abiotic environmental stresses, for instance by producing a broad spectrum of bioactive specialized metabolites. In this defense response, the jasmonate phytohormones can instigate a signaling cascade that leads to the specific elicitation and reprograming of numerous metabolic pathways. Recent research progress has provided several insights into the regulatory networks of many specialized metabolic pathways, mainly at the transcriptional level. Nonetheless, our view on the regulation of defense metabolism remains far from comprehensive. Here, we describe the recent advances obtained with regard to one aspect of the regulation of plant specialized metabolism, namely the posttranslational regulation of enzyme stability. We focus on terpenoid biosynthesis and in particular on the rate-limiting and well-investigated enzyme of the terpenoid precursor pathway, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR). There are clear similarities, as well as important mechanistic differences, among the components involved in the posttranslational regulation of terpenoid biosynthesis via HMGR in plants, yeasts, and mammals. Furthermore, in plants, several of these components evolved to respond to specific signaling cues. Indeed, the elements of the plant endoplasmic reticulum-associated degradation (ERAD) and ER stress-associated processes can be induced upon environmental stresses and during specific developmental processes, thereby allowing a unique posttranslational regulation of terpenoid biosynthesis pathways. Georg Thieme Verlag KG Stuttgart · New York.

Gender Differences of Brain Glucose Metabolic Networks Revealed by FDG-PET: Evidence from a Large Cohort of 400 Young Adults

PubMed Central

Li, Kai; Zhu, Hong; Qi, Rongfeng; Zhang, Zhiqiang; Lu, Guangming

2013-01-01

Background Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample. Materials and Methods FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25∼45 years, mean age±SD: 40.9±3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders. Results Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study. Conclusion This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control

Gender differences of brain glucose metabolic networks revealed by FDG-PET: evidence from a large cohort of 400 young adults.

PubMed

Hu, Yuxiao; Xu, Qiang; Li, Kai; Zhu, Hong; Qi, Rongfeng; Zhang, Zhiqiang; Lu, Guangming

2013-01-01

Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample. FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25:45 years, mean age ± SD: 40.9 ± 3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders. Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study. This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control and experimental individuals or patients.

Jasmonic acid signaling modulates ozone-induced hypersensitive cell death.

PubMed

Rao, M V; Lee, H; Creelman, R A; Mullet, J E; Davis, K R

2000-09-01

Recent studies suggest that cross-talk between salicylic acid (SA)-, jasmonic acid (JA)-, and ethylene-dependent signaling pathways regulates plant responses to both abiotic and biotic stress factors. Earlier studies demonstrated that ozone (O(3)) exposure activates a hypersensitive response (HR)-like cell death pathway in the Arabidopsis ecotype Cvi-0. We now have confirmed the role of SA and JA signaling in influencing O(3)-induced cell death. Expression of salicylate hydroxylase (NahG) in Cvi-0 reduced O(3)-induced cell death. Methyl jasmonate (Me-JA) pretreatment of Cvi-0 decreased O(3)-induced H(2)O(2) content and SA concentrations and completely abolished O(3)-induced cell death. Cvi-0 synthesized as much JA as did Col-0 in response to O(3) exposure but exhibited much less sensitivity to exogenous Me-JA. Analyses of the responses to O(3) of the JA-signaling mutants jar1 and fad3/7/8 also demonstrated an antagonistic relationship between JA- and SA-signaling pathways in controlling the magnitude of O(3)-induced HR-like cell death.

Methyl jasmonate and yeast elicitor induce differential transcriptional and metabolic re-programming in cell suspension cultures of the model legume Medicago truncatula.

PubMed

Suzuki, Hideyuki; Reddy, M S Srinivasa; Naoumkina, Marina; Aziz, Naveed; May, Gregory D; Huhman, David V; Sumner, Lloyd W; Blount, Jack W; Mendes, Pedro; Dixon, Richard A

2005-03-01

Exposure of cell suspension cultures of Medicago truncatula Gaerth. to methyl jasmonate (MeJA) resulted in up to 50-fold induction of transcripts encoding the key triterpene biosynthetic enzyme beta-amyrin synthase (betaAS; EC 5.4.99.-). Transcripts reached maximum levels at 24 h post-elicitation with 0.5 mM MeJA. The entry point enzymes into the phenylpropanoid and flavonoid pathways, L: -phenylalanine ammonia-lyase (PAL; EC 4.3.1.5) and chalcone synthase (CHS; EC 2.3.1.74), respectively, were not induced by MeJA. In contrast, exposure of cells to yeast elicitor (YE) resulted in up to 45- and 14-fold induction of PAL and CHS transcripts, respectively, at only 2 h post-elicitation. betaAS transcripts were weakly induced at 12 h after exposure to YE. Over 30 different triterpene saponins were identified in the cultures, many of which were strongly induced by MeJA, but not by YE. In contrast, cinnamic acids, benzoic acids and isoflavone-derived compounds accumulated following exposure of cultures to YE, but few changes in phenylpropanoid levels were observed in response to MeJA. DNA microarray analysis confirmed the strong differential transcriptional re-programming of the cell cultures for multiple genes in the phenylpropanoid and triterpene pathways in response to MeJA and YE, and indicated different responses of individual members of gene families. This work establishes Medicago cell cultures as an excellent model for future genomics approaches to understand the regulation of legume secondary metabolism.

Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis

PubMed Central

Sung, Jaeyun; Kim, Seunghyeon; Cabatbat, Josephine Jill T.; Jang, Sungho; Jin, Yong-Su; Jung, Gyoo Yeol; Chia, Nicholas; Kim, Pan-Jun

2017-01-01

A system-level framework of complex microbe–microbe and host–microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ∼570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut. PMID:28585563

Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis.

PubMed

Sung, Jaeyun; Kim, Seunghyeon; Cabatbat, Josephine Jill T; Jang, Sungho; Jin, Yong-Su; Jung, Gyoo Yeol; Chia, Nicholas; Kim, Pan-Jun

2017-06-06

A system-level framework of complex microbe-microbe and host-microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ∼570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut.

Synthetic cis-jasmone exposure induces wheat and barley volatiles that repel the pest cereal leaf beetle, Oulema melanopus L.

PubMed

Delaney, Kevin J; Wawrzyniak, Maria; Lemańczyk, Grzegorz; Wrzesińska, Danuta; Piesik, Dariusz

2013-05-01

The plant semiochemical cis-jasmone primes/induces plant resistance that deters herbivores and attracts natural enemies. We studied the induction of volatile organic compounds (VOCs) in winter wheat and spring barley after exposure of plants to three synthetic cis-jasmone doses (50 μl of 1, 100, and 1 × 10(4) ng μl(-1)) and durations of exposure (1, 3, and 6 h). Cereal leaf beetle, Oulema melanopus, adult behavioral responses were examined in a Y-tube olfactometer to cis-jasmone induced plant VOC bouquets and to two synthetic blends of VOCs (3 green leaf volatiles (GLVs); 4 terpenes + indole). In both cereals, eight VOCs [(Z)-3-hexanal, (Z)-3-hexanol, (Z)-3-hexanyl acetate, (Z)-β-ocimene, linalool, β-caryophyllene, (E)-ß-farnesene, and indole] were induced 100- to 1000-fold after cis-jasmone exposure. The degree of induction in both cereals was usually positively and linearly associated with increasing exposure dose and duration. However, VOC emission rate was only ~2-fold greater from plants exposed to the highest vs. lowest cis-jasmone exposure doses (1 × 10(4) difference) or durations (6-fold difference). Male and female O. melanopus were deterred by both cereal VOC bouquets after plant exposure to the high cis-jasmone dose (1 × 10(4) ng μl(-1)), while females were also deterred after plant exposure to the low dose (1 ng μl(-1)) but attracted to unexposed plant VOC bouquets. Both O. melanopus sexes were repelled by terpene/indole and GLV blends at two concentrations (25 ng · min(-1); 125 ng · min(-1)), but attracted to the lowest dose (1 ng · min(-1)) of a GLV blend. It is possible that the biologically relevant low cis-jasmone dose has ecological activity and potential for inducing field crop VOCs to deter O. melanopus.

Detection of driver metabolites in the human liver metabolic network using structural controllability analysis

PubMed Central

2014-01-01

Background Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. Results We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. Conclusion There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. PMID:24885538

Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions

PubMed Central

Blais, Edik M.; Rawls, Kristopher D.; Dougherty, Bonnie V.; Li, Zhuo I.; Kolling, Glynis L.; Ye, Ping; Wallqvist, Anders; Papin, Jason A.

2017-01-01

The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications. PMID:28176778

Ongoing resolution of duplicate gene functions shapes the diversification of a metabolic network

DOE PAGES

Kuang, Meihua Christina; Hutchins, Paul D.; Russell, Jason D.; ...

2016-09-30

The evolutionary mechanisms leading to duplicate gene retention are well understood, but the long-term impacts of paralog differentiation on the regulation of metabolism remain underappreciated. Here we experimentally dissect the functions of two pairs of ancient paralogs of theGALactose sugar utilization network in two yeast species. Here, we show that theSaccharomyces uvarumnetwork is more active, even as over-induction is prevented by a second co-repressor that the model yeastSaccharomyces cerevisiaelacks. Surprisingly, removal of this repression system leads to a strong growth arrest, likely due to overly rapid galactose catabolism and metabolic overload. Alternative sugars, such as fructose, circumvent metabolic control systemsmore » and exacerbate this phenotype. Furthermore, we show thatS. cerevisiaeexperiences homologous metabolic constraints that are subtler due to how the paralogs have diversified. Our results show how the functional differentiation of paralogs continues to shape regulatory network architectures and metabolic strategies long after initial preservation.« less

The Importance of Transition Metals in the Expanding Network of Microbial Metabolism in the Archean Eon

NASA Astrophysics Data System (ADS)

Moore, E. K.; Jelen, B. I.; Giovannelli, D.; Prabhu, A.; Raanan, H.; Falkowski, P. G.

2017-12-01

Deep time changes in Earth surface redox conditions, particularly due to global oxygenation, has impacted the availability of different metals and substrates that are central in biology. Oxidoreductase proteins are molecular nanomachines responsible for all biological electron transfer processes across the tree of life. These enzymes largely contain transition metals in their active sites. Microbial metabolic pathways form a global network of electron transfer, which expanded throughout the Archean eon. Older metabolisms (sulfur reduction, methanogenesis, anoxygenic photosynthesis) accessed negative redox potentials, while later evolving metabolisms (oxygenic photosynthesis, nitrification/denitrification, aerobic respiration) accessed positive redox potentials. The incorporation of different transition metals facilitated biological innovation and the expansion of the network of microbial metabolism. Network analysis was used to examine the connections between microbial taxa, metabolic pathways, crucial metallocofactors, and substrates in deep time by incorporating biosignatures preserved in the geologic record. Nitrogen fixation and aerobic respiration have the highest level of betweenness among metabolisms in the network, indicating that the oldest metabolisms are not the most central. Fe has by far the highest betweenness among metals. Clustering analysis largely separates High Metal Bacteria (HMB), Low Metal Bacteria (LMB), and Archaea showing that simple un-weighted links between taxa, metabolism, and metals have phylogenetic relevance. On average HMB have the highest betweenness among taxa, followed by Archaea and LMB. There is a correlation between the number of metallocofactors and metabolic pathways in representative bacterial taxa, but Archaea do not follow this trend. In many cases older and more recently evolved metabolisms were clustered together supporting previous findings that proliferation of metabolic pathways is not necessarily chronological.

Integrating data from biological experiments into metabolic networks with the DBE information system.

PubMed

Borisjuk, Ljudmilla; Hajirezaei, Mohammad-Reza; Klukas, Christian; Rolletschek, Hardy; Schreiber, Falk

2005-01-01

Modern 'omics'-technologies result in huge amounts of data about life processes. For analysis and data mining purposes this data has to be considered in the context of the underlying biological networks. This work presents an approach for integrating data from biological experiments into metabolic networks by mapping the data onto network elements and visualising the data enriched networks automatically. This methodology is implemented in DBE, an information system that supports the analysis and visualisation of experimental data in the context of metabolic networks. It consists of five parts: (1) the DBE-Database for consistent data storage, (2) the Excel-Importer application for the data import, (3) the DBE-Website as the interface for the system, (4) the DBE-Pictures application for the up- and download of binary (e. g. image) files, and (5) DBE-Gravisto, a network analysis and graph visualisation system. The usability of this approach is demonstrated in two examples.

Polycyclic aromatic hydrocarbon metabolic network in Mycobacterium vanbaalenii PYR-1.

PubMed

Kweon, Ohgew; Kim, Seong-Jae; Holland, Ricky D; Chen, Hongyan; Kim, Dae-Wi; Gao, Yuan; Yu, Li-Rong; Baek, Songjoon; Baek, Dong-Heon; Ahn, Hongsik; Cerniglia, Carl E

2011-09-01

This study investigated a metabolic network (MN) from Mycobacterium vanbaalenii PYR-1 for polycyclic aromatic hydrocarbons (PAHs) from the perspective of structure, behavior, and evolution, in which multilayer omics data are integrated. Initially, we utilized a high-throughput proteomic analysis to assess the protein expression response of M. vanbaalenii PYR-1 to seven different aromatic compounds. A total of 3,431 proteins (57.38% of the genome-predicted proteins) were identified, which included 160 proteins that seemed to be involved in the degradation of aromatic hydrocarbons. Based on the proteomic data and the previous metabolic, biochemical, physiological, and genomic information, we reconstructed an experiment-based system-level PAH-MN. The structure of PAH-MN, with 183 metabolic compounds and 224 chemical reactions, has a typical scale-free nature. The behavior and evolution of the PAH-MN reveals a hierarchical modularity with funnel effects in structure/function and intimate association with evolutionary modules of the functional modules, which are the ring cleavage process (RCP), side chain process (SCP), and central aromatic process (CAP). The 189 commonly upregulated proteins in all aromatic hydrocarbon treatments provide insights into the global adaptation to facilitate the PAH metabolism. Taken together, the findings of our study provide the hierarchical viewpoint from genes/proteins/metabolites to the network via functional modules of the PAH-MN equipped with the engineering-driven approaches of modularization and rationalization, which may expand our understanding of the metabolic potential of M. vanbaalenii PYR-1 for bioremediation applications.

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

PubMed Central

Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

Polyamines in the Context of Metabolic Networks.

PubMed

Wuddineh, Wegi; Minocha, Rakesh; Minocha, Subhash C

2018-01-01

Polyamines (PAs) are essential biomolecules that are known to be involved in the regulation of many plant developmental and growth processes as well as their response to different environmental stimuli. Maintaining the cellular pools of PAs or their metabolic precursors and by-products is critical to accomplish their normal functions. Therefore, the titre of PAs in the cells must be under tight regulation to enable cellular PA homeostasis. Polyamine homeostasis is hence achieved by the regulation of their input into the cellular PA pool, their conversion into secondary metabolites, their transport to other issues/organs, and their catabolism or turnover. The major contributors of input to the PA pools are their in vivo biosynthesis, interconversion between different PAs, and transport from other tissues/organs; while the output or turnover of PAs is facilitated by transport, conjugation and catabolism. Polyamine metabolic pathways including the biosynthesis, catabolism/turnover and conjugation with various organic molecules have been widely studied in all kingdoms. Discoveries on the molecular transporters facilitating the intracellular and intercellular translocation of PAs have also been reported. Numerous recent studies using transgenic approaches and mutagenesis have shown that plants can tolerate quite large concentrations of PAs in the cells; even though, at times, high cellular accumulation of PAs is quite detrimental, and so is high rate of catabolism. The mechanism by which plants tolerate such large quantities of PAs is still unclear. Interestingly, enhanced PA biosynthesis via manipulation of the PA metabolic networks has been suggested to contribute directly to increased growth and improvements in plant abiotic and biotic stress responses; hence greater biomass and productivity. Genetic manipulation of the PA metabolic networks has also been shown to improve plant nitrogen assimilation capacity, which may in turn lead to enhanced carbon assimilation

The Basic Helix-Loop-Helix Transcription Factor MYC2 Directly Represses PLETHORA Expression during Jasmonate-Mediated Modulation of the Root Stem Cell Niche in Arabidopsis[W][OA

PubMed Central

Chen, Qian; Sun, Jiaqiang; Zhai, Qingzhe; Zhou, Wenkun; Qi, Linlin; Xu, Li; Wang, Bao; Chen, Rong; Jiang, Hongling; Qi, Jing; Li, Xugang; Palme, Klaus; Li, Chuanyou

2011-01-01

The root stem cell niche, which in the Arabidopsis thaliana root meristem is an area of four mitotically inactive quiescent cells (QCs) and the surrounding mitotically active stem cells, is critical for root development and growth. We report here that during jasmonate-induced inhibition of primary root growth, jasmonate reduces root meristem activity and leads to irregular QC division and columella stem cell differentiation. Consistently, jasmonate reduces the expression levels of the AP2-domain transcription factors PLETHORA1 (PLT1) and PLT2, which form a developmentally instructive protein gradient and mediate auxin-induced regulation of stem cell niche maintenance. Not surprisingly, the effects of jasmonate on root stem cell niche maintenance and PLT expression require the functioning of MYC2/JASMONATE INSENSITIVE1, a basic helix-loop-helix transcription factor that involves versatile aspects of jasmonate-regulated gene expression. Gel shift and chromatin immunoprecipitation experiments reveal that MYC2 directly binds the promoters of PLT1 and PLT2 and represses their expression. We propose that MYC2-mediated repression of PLT expression integrates jasmonate action into the auxin pathway in regulating root meristem activity and stem cell niche maintenance. This study illustrates a molecular framework for jasmonate-induced inhibition of root growth through interaction with the growth regulator auxin. PMID:21954460

Jasmonate-Mediated Induced Volatiles in the American Cranberry, Vaccinium macrocarpon: From Gene Expression to Organismal Interactions

PubMed Central

Rodriguez-Saona, Cesar R.; Polashock, James; Malo, Edi A.

2013-01-01

Jasmonates, i.e., jasmonic acid (JA) and methyl jasmonate (MeJA), are signaling hormones that regulate a large number of defense responses in plants which in turn affect the plants’ interactions with herbivores and their natural enemies. Here, we investigated the effect of jasmonates on the emission of volatiles in the American cranberry, Vaccinium macrocarpon, at different levels of biological organization from gene expression to organismal interactions. At the molecular level, four genes (BCS, LLS, NER1, and TPS21) responded significantly to gypsy moth larval feeding, MeJA, and mechanical wounding, but to different degrees. The most dramatic changes in expression of BCS and TPS21 (genes in the sesquiterpenoid pathway) were when treated with MeJA. Gypsy moth-damaged and MeJA-treated plants also had significantly elevated expression of LLS and NER1 (genes in the monoterpene and homoterpene biosynthesis pathways, respectively). At the biochemical level, MeJA induced a complex blend of monoterpene and sesquiterpene compounds that differed from gypsy moth and mechanical damage, and followed a diurnal pattern of emission. At the organismal level, numbers of Sparganothis sulfureana moths were lower while numbers of parasitic wasps were higher on sticky traps near MeJA-treated cranberry plants than those near untreated plants. Out of 11 leaf volatiles tested, (Z)-3-hexenyl acetate, linalool, and linalool oxide elicited strong antennal (EAG) responses from S. sulfureana, whereas sesquiterpenes elicited weak EAG responses. In addition, mortality of S. sulfureana larvae increased by about 43% in JA treated cranberry plants as compared with untreated plants, indicating a relationship among adult preference, antennal sensitivity to plant odors, and offspring performance. This study highlights the role of the jasmonate-dependent defensive pathway in the emissions of herbivore-induced volatiles in cranberries and its importance in multi-trophic level interactions. PMID

Jasmonate-Mediated Induced Volatiles in the American Cranberry, Vaccinium macrocarpon: From Gene Expression to Organismal Interactions.

PubMed

Rodriguez-Saona, Cesar R; Polashock, James; Malo, Edi A

2013-01-01

Jasmonates, i.e., jasmonic acid (JA) and methyl jasmonate (MeJA), are signaling hormones that regulate a large number of defense responses in plants which in turn affect the plants' interactions with herbivores and their natural enemies. Here, we investigated the effect of jasmonates on the emission of volatiles in the American cranberry, Vaccinium macrocarpon, at different levels of biological organization from gene expression to organismal interactions. At the molecular level, four genes (BCS, LLS, NER1, and TPS21) responded significantly to gypsy moth larval feeding, MeJA, and mechanical wounding, but to different degrees. The most dramatic changes in expression of BCS and TPS21 (genes in the sesquiterpenoid pathway) were when treated with MeJA. Gypsy moth-damaged and MeJA-treated plants also had significantly elevated expression of LLS and NER1 (genes in the monoterpene and homoterpene biosynthesis pathways, respectively). At the biochemical level, MeJA induced a complex blend of monoterpene and sesquiterpene compounds that differed from gypsy moth and mechanical damage, and followed a diurnal pattern of emission. At the organismal level, numbers of Sparganothis sulfureana moths were lower while numbers of parasitic wasps were higher on sticky traps near MeJA-treated cranberry plants than those near untreated plants. Out of 11 leaf volatiles tested, (Z)-3-hexenyl acetate, linalool, and linalool oxide elicited strong antennal (EAG) responses from S. sulfureana, whereas sesquiterpenes elicited weak EAG responses. In addition, mortality of S. sulfureana larvae increased by about 43% in JA treated cranberry plants as compared with untreated plants, indicating a relationship among adult preference, antennal sensitivity to plant odors, and offspring performance. This study highlights the role of the jasmonate-dependent defensive pathway in the emissions of herbivore-induced volatiles in cranberries and its importance in multi-trophic level interactions.

Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study

PubMed Central

An, Jianping; Chen, Xuejiao; Xie, Yuanwei; Zhao, Hui; Mao, Junfeng; Liang, Wangsheng; Ma, Xiangxing

2016-01-01

This study aimed to investigate the metabolic brain network and its relationship with depression symptoms using 18F-fluorodeoxyglucose positron emission tomography data in 78 pre-chemotherapy cancer patients with depression and 80 matched healthy subjects. Functional and structural imbalance or disruption of brain networks frequently occur following chemotherapy in cancer patients. However, few studies have focused on the topological organization of the metabolic brain network in cancer with depression, especially those without chemotherapy. The nodal and global parameters of the metabolic brain network were computed for cancer patients and healthy subjects. Significant decreases in metabolism were found in the frontal and temporal gyri in cancer patients compared with healthy subjects. Negative correlations between depression and metabolism were found predominantly in the inferior frontal and cuneus regions, whereas positive correlations were observed in several regions, primarily including the insula, hippocampus, amygdala, and middle temporal gyri. Furthermore, a higher clustering efficiency, longer path length, and fewer hubs were found in cancer patients compared with healthy subjects. The topological organization of the whole-brain metabolic networks may be disrupted in cancer. Finally, the present findings may provide a new avenue for exploring the neurobiological mechanism, which plays a key role in lessening the depression effects in pre-chemotherapy cancer patients. PMID:27832148

Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study.

PubMed

Fang, Lei; Yao, Zhijun; An, Jianping; Chen, Xuejiao; Xie, Yuanwei; Zhao, Hui; Mao, Junfeng; Liang, Wangsheng; Ma, Xiangxing

2016-01-01

This study aimed to investigate the metabolic brain network and its relationship with depression symptoms using 18F-fluorodeoxyglucose positron emission tomography data in 78 pre-chemotherapy cancer patients with depression and 80 matched healthy subjects. Functional and structural imbalance or disruption of brain networks frequently occur following chemotherapy in cancer patients. However, few studies have focused on the topological organization of the metabolic brain network in cancer with depression, especially those without chemotherapy. The nodal and global parameters of the metabolic brain network were computed for cancer patients and healthy subjects. Significant decreases in metabolism were found in the frontal and temporal gyri in cancer patients compared with healthy subjects. Negative correlations between depression and metabolism were found predominantly in the inferior frontal and cuneus regions, whereas positive correlations were observed in several regions, primarily including the insula, hippocampus, amygdala, and middle temporal gyri. Furthermore, a higher clustering efficiency, longer path length, and fewer hubs were found in cancer patients compared with healthy subjects. The topological organization of the whole-brain metabolic networks may be disrupted in cancer. Finally, the present findings may provide a new avenue for exploring the neurobiological mechanism, which plays a key role in lessening the depression effects in pre-chemotherapy cancer patients.

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

DOE PAGES

Gargouri, Mahmoud; Park, Jeong -Jin; Holguin, F. Omar; ...

2015-05-28

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

Nuclear jasmonate and salicylate signaling and crosstalk in defense against pathogens.

PubMed

Gimenez-Ibanez, Selena; Solano, Roberto

2013-01-01

An extraordinary progress has been made over the last two decades on understanding the components and mechanisms governing plant innate immunity. After detection of a pathogen, effective plant resistance depends on the activation of a complex signaling network integrated by small signaling molecules and hormonal pathways, and the balance of these hormone systems determines resistance to particular pathogens. The discovery of new components of hormonal signaling pathways, including plant nuclear hormone receptors, is providing a picture of complex crosstalk and induced hormonal changes that modulate disease and resistance through several protein families that perceive hormones within the nucleus and lead to massive gene induction responses often achieved by de-repression. This review highlights recent advances in our understanding of positive and negative regulators of these hormones signaling pathways that are crucial regulatory targets of hormonal crosstalk in disease and defense. We focus on the most recent discoveries on the jasmonate and salicylate pathway components that explain their crosstalk with other hormonal pathways in the nucleus. We discuss how these components fine-tune defense responses to build a robust plant immune system against a great number of different microbes and, finally, we summarize recent discoveries on specific nuclear hormonal manipulation by microbes which exemplify the ingenious ways by which pathogens can take control over the plant's hormone signaling network to promote disease.

Nuclear jasmonate and salicylate signaling and crosstalk in defense against pathogens

PubMed Central

Gimenez-Ibanez, Selena; Solano, Roberto

2013-01-01

An extraordinary progress has been made over the last two decades on understanding the components and mechanisms governing plant innate immunity. After detection of a pathogen, effective plant resistance depends on the activation of a complex signaling network integrated by small signaling molecules and hormonal pathways, and the balance of these hormone systems determines resistance to particular pathogens. The discovery of new components of hormonal signaling pathways, including plant nuclear hormone receptors, is providing a picture of complex crosstalk and induced hormonal changes that modulate disease and resistance through several protein families that perceive hormones within the nucleus and lead to massive gene induction responses often achieved by de-repression. This review highlights recent advances in our understanding of positive and negative regulators of these hormones signaling pathways that are crucial regulatory targets of hormonal crosstalk in disease and defense. We focus on the most recent discoveries on the jasmonate and salicylate pathway components that explain their crosstalk with other hormonal pathways in the nucleus. We discuss how these components fine-tune defense responses to build a robust plant immune system against a great number of different microbes and, finally, we summarize recent discoveries on specific nuclear hormonal manipulation by microbes which exemplify the ingenious ways by which pathogens can take control over the plant’s hormone signaling network to promote disease. PMID:23577014

Mimoza: web-based semantic zooming and navigation in metabolic networks.

PubMed

Zhukova, Anna; Sherman, David J

2015-02-26

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

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

PubMed

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

2014-12-01

Rapid eye movement sleep behaviour disorder has been evaluated using Parkinson's disease-related metabolic network. It is unknown whether this disorder is itself associated with a unique metabolic network. 18F-fluorodeoxyglucose positron emission tomography was performed in 21 patients (age 65.0±5.6 years) with idiopathic rapid eye movement sleep behaviour disorder and 21 age/gender-matched healthy control subjects (age 62.5±7.5 years) to identify a disease-related pattern and examine its evolution in 21 hemi-parkinsonian patients (age 62.6±5.0 years) and 16 moderate parkinsonian patients (age 56.9±12.2 years). We identified a rapid eye movement sleep behaviour disorder-related metabolic network characterized by increased activity in pons, thalamus, medial frontal and sensorimotor areas, hippocampus, supramarginal and inferior temporal gyri, and posterior cerebellum, with decreased activity in occipital and superior temporal regions. Compared to the healthy control subjects, network expressions were elevated (P<0.0001) in the patients with this disorder and in the parkinsonian cohorts but decreased with disease progression. Parkinson's disease-related network activity was also elevated (P<0.0001) in the patients with rapid eye movement sleep behaviour disorder but lower than in the hemi-parkinsonian cohort. Abnormal metabolic networks may provide markers of idiopathic rapid eye movement sleep behaviour disorder to identify those at higher risk to develop neurodegenerative parkinsonism. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Sink limitation induces the expression of multiple soybean vegetative lipoxygenase mRNAs while the endogenous jasmonic acid level remains low.

PubMed Central

Bunker, T W; Koetje, D S; Stephenson, L C; Creelman, R A; Mullet, J E; Grimes, H D

1995-01-01

The response of individual members of the lipoxygenase multigene family in soybeans to sink deprivation was analyzed. RNase protection assays indicated that a novel vegetative lipoxygenase gene, vlxC, and three other vegetative lipoxygenase mRNAs accumulated in mature leaves in response to a variety of sink limitations. These data suggest that several members of the lipoxygenase multigene family are involved in assimilate partitioning. The possible involvement of jasmonic acid as a signaling molecule regulating assimilate partitioning into the vegetative storage proteins and lipoxygenases was directly assessed by determining the endogenous level of jasmonic acid in leaves from plants with their pods removed. There was no rise in the level of endogenous jasmonic acid coincident with the strong increase in both vlxC and vegetative storage protein VspB transcripts in response to sink limitation. Thus, expression of the vegetative lipoxygenases and vegetative storage proteins is not regulated by jasmonic acid in sink-limited leaves. PMID:7549487

Sink limitation induces the expression of multiple soybean vegetative lipoxygenase mRNAs while the endogenous jasmonic acid level remains low.

PubMed

Bunker, T W; Koetje, D S; Stephenson, L C; Creelman, R A; Mullet, J E; Grimes, H D

1995-08-01

The response of individual members of the lipoxygenase multigene family in soybeans to sink deprivation was analyzed. RNase protection assays indicated that a novel vegetative lipoxygenase gene, vlxC, and three other vegetative lipoxygenase mRNAs accumulated in mature leaves in response to a variety of sink limitations. These data suggest that several members of the lipoxygenase multigene family are involved in assimilate partitioning. The possible involvement of jasmonic acid as a signaling molecule regulating assimilate partitioning into the vegetative storage proteins and lipoxygenases was directly assessed by determining the endogenous level of jasmonic acid in leaves from plants with their pods removed. There was no rise in the level of endogenous jasmonic acid coincident with the strong increase in both vlxC and vegetative storage protein VspB transcripts in response to sink limitation. Thus, expression of the vegetative lipoxygenases and vegetative storage proteins is not regulated by jasmonic acid in sink-limited leaves.

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

PubMed Central

2011-01-01

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

Human-Centered Development of an Online Social Network for Metabolic Syndrome Management.

PubMed

Núñez-Nava, Jefersson; Orozco-Sánchez, Paola A; López, Diego M; Ceron, Jesus D; Alvarez-Rosero, Rosa E

2016-01-01

According to the International Diabetes Federation (IDF), a quarter of the world's population has Metabolic Syndrome (MS). To develop (and assess the users' degree of satisfaction of) an online social network for patients who suffer from Metabolic Syndrome, based on the recommendations and requirements of the Human-Centered Design. Following the recommendations of the ISO 9241-210 for Human-Centered Design (HCD), an online social network was designed to promote physical activity and healthy nutrition. In order to guarantee the active participation of the users during the development of the social network, a survey, an in-depth interview, a focal group, and usability tests were carried out with people suffering from MS. The study demonstrated how the different activities, recommendations, and requirements of the ISO 9241-210 are integrated into a traditional software development process. Early usability tests demonstrated that the user's acceptance and the effectiveness and efficiency of the social network are satisfactory.

Jasmonate-Dependent Induction of Indole Glucosinolates in Arabidopsis by Culture Filtrates of the Nonspecific Pathogen Erwinia carotovora1

PubMed Central

Brader, Günter; Tas, Éva; Palva, E. Tapio

2001-01-01

Elicitors from the plant pathogen Erwinia carotovora trigger coordinate induction of the tryptophan (Trp) biosynthesis pathway and Trp oxidizing genes in Arabidopsis. To elucidate the biological role of such pathogen-induced activation we characterized the production of secondary defense metabolites such as camalexin and indole glucosinolates derived from precursors of this pathway. Elicitor induction was followed by a specific increase in 3-indolylmethylglucosinolate (IGS) content, but only a barely detectable accumulation of the indole-derived phytoalexin camalexin. The response is mediated by jasmonic acid as shown by lack of IGS induction in the jasmonate-insensitive mutant coi1-1. In accordance with this, methyl jasmonate was able to trigger IGS accumulation in Arabidopsis. In contrast, ethylene and salicylic acid seem to play a minor role in the response. They did not trigger alterations in IGS levels, and methyl jasmonate- or elicitor-induced IGS accumulation in NahG and ethylene-insensitive ein2-1 mutant plants was similar as in the wild type. The breakdown products of IGS and other glucosinolates were able to inhibit growth of E. carotovora. The results suggest that IGS is of importance in the defense against bacterial pathogens. PMID:11402212

Control of jasmonate biosynthesis and senescence by miR319 targets.

PubMed

Schommer, Carla; Palatnik, Javier F; Aggarwal, Pooja; Chételat, Aurore; Cubas, Pilar; Farmer, Edward E; Nath, Utpal; Weigel, Detlef

2008-09-23

Considerable progress has been made in identifying the targets of plant microRNAs, many of which regulate the stability or translation of mRNAs that encode transcription factors involved in development. In most cases, it is unknown, however, which immediate transcriptional targets mediate downstream effects of the microRNA-regulated transcription factors. We identified a new process controlled by the miR319-regulated clade of TCP (TEOSINTE BRANCHED/CYCLOIDEA/PCF) transcription factor genes. In contrast to other miRNA targets, several of which modulate hormone responses, TCPs control biosynthesis of the hormone jasmonic acid. Furthermore, we demonstrate a previously unrecognized effect of TCPs on leaf senescence, a process in which jasmonic acid has been proposed to be a critical regulator. We propose that miR319-controlled TCP transcription factors coordinate two sequential processes in leaf development: leaf growth, which they negatively regulate, and leaf senescence, which they positively regulate.

Theoretical Basis for Dynamic Label Propagation in Stationary Metabolic Networks under Step and Periodic Inputs

PubMed Central

Sokol, Serguei; Portais, Jean-Charles

2015-01-01

The dynamics of label propagation in a stationary metabolic network during an isotope labeling experiment can provide highly valuable information on the network topology, metabolic fluxes, and on the size of metabolite pools. However, major issues, both in the experimental set-up and in the accompanying numerical methods currently limit the application of this approach. Here, we propose a method to apply novel types of label inputs, sinusoidal or more generally periodic label inputs, to address both the practical and numerical challenges of dynamic labeling experiments. By considering a simple metabolic system, i.e. a linear, non-reversible pathway of arbitrary length, we develop mathematical descriptions of label propagation for both classical and novel label inputs. Theoretical developments and computer simulations show that the application of rectangular periodic pulses has both numerical and practical advantages over other approaches. We applied the strategy to estimate fluxes in a simulated experiment performed on a complex metabolic network (the central carbon metabolism of Escherichia coli), to further demonstrate its value in conditions which are close to those in real experiments. This study provides a theoretical basis for the rational interpretation of label propagation curves in real experiments, and will help identify the strengths, pitfalls and limitations of such experiments. The cases described here can also be used as test cases for more general numerical methods aimed at identifying network topology, analyzing metabolic fluxes or measuring concentrations of metabolites. PMID:26641860

A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

PubMed

Röhl, Annika; Bockmayr, Alexander

2017-01-03

Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

Metabolic network failures in Alzheimer’s disease: A biochemical road map

PubMed Central

Toledo, Jon B.; Arnold, Matthias; Kastenmüuller, Gabi; Chang, Rui; Baillie, Rebecca A.; Han, Xianlin; Thambisetty, Madhav; Tenenbaum, Jessica D.; Suhre, Karsten; Thompson, J. Will; St. John-Williams, Lisa; MahmoudianDehkordi, Siamak; Rotroff, Daniel M.; Jack, John R.; Motsinger-Reif, Alison; Risacher, Shannon L.; Blach, Colette; Lucas, Joseph E.; Massaro, Tyler; Louie, Gregory; Zhu, Hongjie; Dallmann, Guido; Klavins, Kristaps; Koal, Therese; Kim, Sungeun; Nho, Kwangsik; Shen, Li; Casanova, Ramon; Varma, Sudhir; Legido-Quigley, Cristina; Moseley, M. Arthur; Zhu, Kuixi; Henrion, Marc Y. R.; van der Lee, Sven J.; Harms, Amy C.; Demirkan, Ayse; Hankemeier, Thomas; van Duijn, Cornelia M.; Trojanowski, John Q.; Shaw, Leslie M.; Saykin, Andrew J.; Weiner, Michael W.; Doraiswamy, P. Murali; Kaddurah-Daouk, Rima

2018-01-01

Introduction The Alzheimer’s Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer’s disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. Methods Fasting serum samples from the Alzheimer’s Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. Results Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1–42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. Discussion Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery. PMID:28341160

Network thermodynamic curation of human and yeast genome-scale metabolic models.

PubMed

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Arabidopsis AGAMOUS Regulates Sepal Senescence by Driving Jasmonate Production

PubMed Central

Jibran, Rubina; Tahir, Jibran; Cooney, Janine; Hunter, Donald A.; Dijkwel, Paul P.

2017-01-01

The signal that initiates the age-regulated senescence program in flowers is still unknown. Here we propose for the ephemeral Arabidopsis thaliana flower that it dies because of continued expression of the MADS-box transcription factor AGAMOUS (AG). AG is necessary for specifying the reproductive structures of the flower. Flowers of ag-1, which lack AG, exhibited delayed sepal senescence and abscission. The flowers also had reduced jasmonic acid (JA) content. Other anther-defective sterile mutants deficient in JA, defective in anther dehiscence 1 (dad1) and delayed dehiscence 2 (dde2), exhibited delayed sepal senescence and abscission as well. Manually pollinated dad1 flowers produced siliques but still had delayed senescence, demonstrating that absence of pollination does not cause delayed senescence. When ag-1, dad1 and dde2 flowers were sprayed with 100 μM methyl jasmonate, the sepal senescence and abscission phenotypes were rescued, suggesting that JA has a role in these processes. Our study uncovers a novel role for AG in determining the timing of death of the flower it helps develop and highlights a role for JA in sepal senescence. PMID:29312374

Jasmonic Acid Signaling Modulates Ozone-Induced Hypersensitive Cell Death

PubMed Central

Rao, Mulpuri V.; Lee, Hyung-il; Creelman, Robert A.; Mullet, John E.; Davis, Keith R.

2000-01-01

Recent studies suggest that cross-talk between salicylic acid (SA)–, jasmonic acid (JA)–, and ethylene-dependent signaling pathways regulates plant responses to both abiotic and biotic stress factors. Earlier studies demonstrated that ozone (O3) exposure activates a hypersensitive response (HR)–like cell death pathway in the Arabidopsis ecotype Cvi-0. We now have confirmed the role of SA and JA signaling in influencing O3-induced cell death. Expression of salicylate hydroxylase (NahG) in Cvi-0 reduced O3-induced cell death. Methyl jasmonate (Me-JA) pretreatment of Cvi-0 decreased O3-induced H2O2 content and SA concentrations and completely abolished O3-induced cell death. Cvi-0 synthesized as much JA as did Col-0 in response to O3 exposure but exhibited much less sensitivity to exogenous Me-JA. Analyses of the responses to O3 of the JA-signaling mutants jar1 and fad3/7/8 also demonstrated an antagonistic relationship between JA- and SA-signaling pathways in controlling the magnitude of O3-induced HR-like cell death. PMID:11006337

Novel polymeric monolith materials with a β-cyclodextrin-graphene composite for the highly selective extraction of methyl jasmonate.

PubMed

Yu, Xinhong; Ling, Xu; Zou, Li; Chen, Zilin

2017-04-01

A novel polymeric monolith column with a  β-cyclodextrin-graphene composite was prepared for extraction of methyl jasmonate. A simple, sensitive, and effective polymeric monolith microextraction with high-performance liquid chromatography method has been presented for the determination. To carry out the best microextraction efficiency, several parameters such as sample flow rate, sample volume, and sample pH value were systematically optimized. In addition, the method validation showed a wide linear range of 5-2000 ng/mL, with a good linearity and low limits of detection for methyl jasmonate. The proposed method was successfully applied for the determination of methyl jasmonate in wintersweet flowers with recoveries of 90.67%. The result was confirmed by high-performance liquid chromatography with mass spectrometry. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ocsESTdb: a database of oil crop seed EST sequences for comparative analysis and investigation of a global metabolic network and oil accumulation metabolism.

PubMed

Ke, Tao; Yu, Jingyin; Dong, Caihua; Mao, Han; Hua, Wei; Liu, Shengyi

2015-01-21

Oil crop seeds are important sources of fatty acids (FAs) for human and animal nutrition. Despite their importance, there is a lack of an essential bioinformatics resource on gene transcription of oil crops from a comparative perspective. In this study, we developed ocsESTdb, the first database of expressed sequence tag (EST) information on seeds of four large-scale oil crops with an emphasis on global metabolic networks and oil accumulation metabolism that target the involved unigenes. A total of 248,522 ESTs and 106,835 unigenes were collected from the cDNA libraries of rapeseed (Brassica napus), soybean (Glycine max), sesame (Sesamum indicum) and peanut (Arachis hypogaea). These unigenes were annotated by a sequence similarity search against databases including TAIR, NR protein database, Gene Ontology, COG, Swiss-Prot, TrEMBL and Kyoto Encyclopedia of Genes and Genomes (KEGG). Five genome-scale metabolic networks that contain different numbers of metabolites and gene-enzyme reaction-association entries were analysed and constructed using Cytoscape and yEd programs. Details of unigene entries, deduced amino acid sequences and putative annotation are available from our database to browse, search and download. Intuitive and graphical representations of EST/unigene sequences, functional annotations, metabolic pathways and metabolic networks are also available. ocsESTdb will be updated regularly and can be freely accessed at http://ocri-genomics.org/ocsESTdb/ . ocsESTdb may serve as a valuable and unique resource for comparative analysis of acyl lipid synthesis and metabolism in oilseed plants. It also may provide vital insights into improving oil content in seeds of oil crop species by transcriptional reconstruction of the metabolic network.

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

PubMed

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

A discrete mathematical model applied to genetic regulation and metabolic networks.

PubMed

Asenjo, A J; Ramirez, P; Rapaport, I; Aracena, J; Goles, E; Andrews, B A

2007-03-01

This paper describes the use of a discrete mathematical model to represent the basic mechanisms of regulation of the bacteria E. coli in batch fermentation. The specific phenomena studied were the changes in metabolism and genetic regulation when the bacteria use three different carbon substrates (glucose, glycerol, and acetate). The model correctly predicts the behavior of E. coli vis-à-vis substrate mixtures. In a mixture of glucose, glycerol, and acetate, it prefers glucose, then glycerol, and finally acetate. The model included 67 nodes; 28 were genes, 20 enzymes, and 19 regulators/biochemical compounds. The model represents both the genetic regulation and metabolic networks in an inrtegrated form, which is how they function biologically. This is one of the first attempts to include both of these networks in one model. Previously, discrete mathematical models were used only to describe genetic regulation networks. The study of the network dynamics generated 8 (2(3)) fixed points, one for each nutrient configuration (substrate mixture) in the medium. The fixed points of the discrete model reflect the phenotypes described. Gene expression and the patterns of the metabolic fluxes generated are described accurately. The activation of the gene regulation network depends basically on the presence of glucose and glycerol. The model predicts the behavior when mixed carbon sources are utilized as well as when there is no carbon source present. Fictitious jokers (Joker1, Joker2, and Repressor SdhC) had to be created to control 12 genes whose regulation mechanism is unknown, since glycerol and glucose do not act directly on the genes. The approach presented in this paper is particularly useful to investigate potential unknown gene regulation mechanisms; such a novel approach can also be used to describe other gene regulation situations such as the comparison between non-recombinant and recombinant yeast strain, producing recombinant proteins, presently under

Connexin 43-Mediated Astroglial Metabolic Networks Contribute to the Regulation of the Sleep-Wake Cycle.

PubMed

Clasadonte, Jerome; Scemes, Eliana; Wang, Zhongya; Boison, Detlev; Haydon, Philip G

2017-09-13

Astrocytes produce and supply metabolic substrates to neurons through gap junction-mediated astroglial networks. However, the role of astroglial metabolic networks in behavior is unclear. Here, we demonstrate that perturbation of astroglial networks impairs the sleep-wake cycle. Using a conditional Cre-Lox system in mice, we show that knockout of the gap junction subunit connexin 43 in astrocytes throughout the brain causes excessive sleepiness and fragmented wakefulness during the nocturnal active phase. This astrocyte-specific genetic manipulation silenced the wake-promoting orexin neurons located in the lateral hypothalamic area (LHA) by impairing glucose and lactate trafficking through astrocytic networks. This global wakefulness instability was mimicked with viral delivery of Cre recombinase to astrocytes in the LHA and rescued by in vivo injections of lactate. Our findings propose a novel regulatory mechanism critical for maintaining normal daily cycle of wakefulness and involving astrocyte-neuron metabolic interactions. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2009-04-17

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.

Interactions between the jasmonic and salicylic acid pathway modulate the plant metabolome and affect herbivores of different feeding types.

PubMed

Schweiger, R; Heise, A-M; Persicke, M; Müller, C

2014-07-01

The phytohormones jasmonic acid (JA) and salicylic acid (SA) mediate induced plant defences and the corresponding pathways interact in a complex manner as has been shown on the transcript and proteine level. Downstream, metabolic changes are important for plant-herbivore interactions. This study investigated metabolic changes in leaf tissue and phloem exudates of Plantago lanceolata after single and combined JA and SA applications as well as consequences on chewing-biting (Heliothis virescens) and piercing-sucking (Myzus persicae) herbivores. Targeted metabolite profiling and untargeted metabolic fingerprinting uncovered different categories of plant metabolites, which were influenced in a specific manner, indicating points of divergence, convergence, positive crosstalk and pronounced mutual antagonism between the signaling pathways. Phytohormone-specific decreases of primary metabolite pool sizes in the phloem exudates may indicate shifts in sink-source relations, resource allocation, nutrient uptake or photosynthesis. Survival of both herbivore species was significantly reduced by JA and SA treatments. However, the combined application of JA and SA attenuated the negative effects at least against H. virescens suggesting that mutual antagonism between the JA and SA pathway may be responsible. Pathway interactions provide a great regulatory potential for the plant that allows triggering of appropriate defences when attacked by different antagonist species. © 2013 John Wiley & Sons Ltd.

An efficient graph theory based method to identify every minimal reaction set in a metabolic network

PubMed Central

2014-01-01

Background Development of cells with minimal metabolic functionality is gaining importance due to their efficiency in producing chemicals and fuels. Existing computational methods to identify minimal reaction sets in metabolic networks are computationally expensive. Further, they identify only one of the several possible minimal reaction sets. Results In this paper, we propose an efficient graph theory based recursive optimization approach to identify all minimal reaction sets. Graph theoretical insights offer systematic methods to not only reduce the number of variables in math programming and increase its computational efficiency, but also provide efficient ways to find multiple optimal solutions. The efficacy of the proposed approach is demonstrated using case studies from Escherichia coli and Saccharomyces cerevisiae. In case study 1, the proposed method identified three minimal reaction sets each containing 38 reactions in Escherichia coli central metabolic network with 77 reactions. Analysis of these three minimal reaction sets revealed that one of them is more suitable for developing minimal metabolism cell compared to other two due to practically achievable internal flux distribution. In case study 2, the proposed method identified 256 minimal reaction sets from the Saccharomyces cerevisiae genome scale metabolic network with 620 reactions. The proposed method required only 4.5 hours to identify all the 256 minimal reaction sets and has shown a significant reduction (approximately 80%) in the solution time when compared to the existing methods for finding minimal reaction set. Conclusions Identification of all minimal reactions sets in metabolic networks is essential since different minimal reaction sets have different properties that effect the bioprocess development. The proposed method correctly identified all minimal reaction sets in a both the case studies. The proposed method is computationally efficient compared to other methods for finding minimal

Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network1[OPEN

PubMed Central

Kim, Taehyong; Dreher, Kate; Nilo-Poyanco, Ricardo; Lee, Insuk; Fiehn, Oliver; Lange, Bernd Markus; Nikolau, Basil J.; Sumner, Lloyd; Welti, Ruth; Wurtele, Eve S.; Rhee, Seung Y.

2015-01-01

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes. PMID:25670818

GmCYP82A3, a Soybean Cytochrome P450 Family Gene Involved in the Jasmonic Acid and Ethylene Signaling Pathway, Enhances Plant Resistance to Biotic and Abiotic Stresses

PubMed Central

Yan, Qiang; Cui, Xiaoxia; Lin, Shuai; Gan, Shuping; Xing, Han; Dou, Daolong

2016-01-01

The cytochrome P450 monooxygenases (P450s) represent a large and important enzyme superfamily in plants. They catalyze numerous monooxygenation/hydroxylation reactions in biochemical pathways, P450s are involved in a variety of metabolic pathways and participate in the homeostasis of phytohormones. The CYP82 family genes specifically reside in dicots and are usually induced by distinct environmental stresses. However, their functions are largely unknown, especially in soybean (Glycine max L.). Here, we report the function of GmCYP82A3, a gene from soybean CYP82 family. Its expression was induced by Phytophthora sojae infection, salinity and drought stresses, and treatment with methyl jasmonate (MeJA) or ethephon (ETH). Its expression levels were consistently high in resistant cultivars. Transgenic Nicotiana benthamiana plants overexpressing GmCYP82A3 exhibited strong resistance to Botrytis cinerea and Phytophthora parasitica, and enhanced tolerance to salinity and drought stresses. Furthermore, transgenic plants were less sensitive to jasmonic acid (JA), and the enhanced resistance was accompanied with increased expression of the JA/ET signaling pathway-related genes. PMID:27588421

Mass Conservation and Inference of Metabolic Networks from High-Throughput Mass Spectrometry Data

PubMed Central

Bandaru, Pradeep; Bansal, Mukesh

2011-01-01

Abstract We present a step towards the metabolome-wide computational inference of cellular metabolic reaction networks from metabolic profiling data, such as mass spectrometry. The reconstruction is based on identification of irreducible statistical interactions among the metabolite activities using the ARACNE reverse-engineering algorithm and on constraining possible metabolic transformations to satisfy the conservation of mass. The resulting algorithms are validated on synthetic data from an abridged computational model of Escherichia coli metabolism. Precision rates upwards of 50% are routinely observed for identification of full metabolic reactions, and recalls upwards of 20% are also seen. PMID:21314454

Lasiojasmonates A-C, three jasmonic acid esters produced by Lasiodiplodia sp., a grapevine pathogen.

PubMed

Andolfi, Anna; Maddau, Lucia; Cimmino, Alessio; Linaldeddu, Benedetto T; Basso, Sara; Deidda, Antonio; Serra, Salvatorica; Evidente, Antonio

2014-07-01

In this study, a strain (BL 101) of a species of Lasiodiplodia, not yet formally described, which was isolated from declining grapevine plants showing wedge-shaped cankers, was investigated for its ability to produce in vitro bioactive secondary metabolites. From culture filtrates of this strain three jasmonic acid esters, named lasiojasmonates A-C and 16-O-acetylbotryosphaerilactones A and C were isolated together with (1R,2R)-jasmonic acid, its methyl ester, botryosphaerilactone A, (3S,4R,5R)-4-hydroxymethyl-3,5-dimethyldihydro-2-furanone and (3R,4S)-botryodiplodin. The structures of lasiojasmonates A-C were established by spectroscopic methods as (1R*,2R*,3'S*,4'R*,5'R*)-4-hydroxymethyl-3,5-dimethyldihydro-2-furanone, (1R*,2R*,3'S*,4'R*,5'R*,10'R*,12'R*,13'R*,14'S*) and (1R*,2R*,3'S*,4'R*,5'R*,10'S*,12'R*,13'R*,14'S*)-4-(4-hydroxymethyl-3,5-dimethyltetrahydro-furan-2-yloxymethyl)-3,5-dimethyldihydro-2-furanones jasmonates (1, 4 and 5). The structures of 16-O-acetylbotryosphaerilactones A and C were determined by comparison of their spectral data with those of the corresponding acetyl derivatives obtained by acetylation of botryosphaerilactone A. The metabolites isolated, except 4 and 5, were tested at 1mg/mL on leaves of grapevine cv. Cannonau and cork oak using the leaf puncture assay. They were also tested on detached grapevine leaves at 0.5mg/mL and tomato cuttings at 0.1mg/mL. In all phytotoxic assays only jasmonic acid was found to be active. All metabolites were inactive in the zootoxic assay at 50 μg/mL. Copyright © 2014. Published by Elsevier Ltd.

Peroxisomal plant metabolism - an update on nitric oxide, Ca2+ and the NADPH recycling network.

PubMed

Corpas, Francisco J; Barroso, Juan B

2018-01-29

Plant peroxisomes are recognized organelles that - with their capacity to generate greater amounts of H 2 O 2 than other subcellular compartments - have a remarkable oxidative metabolism. However, over the last 15 years, new information has shown that plant peroxisomes contain other important molecules and enzymes, including nitric oxide (NO), peroxynitrite, a NADPH-recycling system, Ca 2+ and lipid-derived signals, such as jasmonic acid (JA) and nitro-fatty acid (NO 2 -FA). This highlights the potential for complex interactions within the peroxisomal nitro-oxidative metabolism, which also affects the status of the cell and consequently its physiological processes. In this review, we provide an update on the peroxisomal interactions between all these molecules. Particular emphasis will be placed on the generation of the free-radical NO, which requires the presence of Ca 2+ , calmodulin and NADPH redox power. Peroxisomes possess several NADPH regeneration mechanisms, such as those mediated by glucose-6-phosphate dehydrogenase (G6PDH) and 6-phosphogluconate dehydrogenase (6PGDH) proteins, which are involved in the oxidative phase of the pentose phosphate pathway, as well as that mediated by NADP-isocitrate dehydrogenase (ICDH). The generated NADPH is also an essential cofactor across other peroxisomal pathways, including the antioxidant ascorbate-glutathione cycle and unsaturated fatty acid β-oxidation, the latter being a source of powerful signaling molecules such as JA and NO 2 -FA. © 2018. Published by The Company of Biologists Ltd.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

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.

Metabolic Network Modeling for Computer-Aided Design of Microbial Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Nelson, William C.; Lee, Joon-Yong

Interest in applying microbial communities to biotechnology continues to increase. Successful engineering of microbial communities requires a fundamental shift in focus from enhancing metabolic capabilities in individual organisms to promoting synergistic interspecies interactions. This goal necessitates in silico tools that provide a predictive understanding of how microorganisms interact with each other and their environments. In this regard, we highlight a need for a new concept that we have termed biological computer-aided design of interactions (BioCADi). We ground this discussion within the context of metabolic network modeling.

Ultrasensitive determination of jasmonic acid in plant tissues using high-performance liquid chromatography with fluorescence detection.

PubMed

Xiong, Xu-Jie; Rao, Wan-Bing; Guo, Xiao-Feng; Wang, Hong; Zhang, Hua-Shan

2012-05-23

An ultrasensitive and selective high-performance liquid chromatographic method for the volatile signaling hormone, jasmonic acid, has been developed based on precolumn derivatization with 1,3,5,7-tetramethyl-8-aminozide-difluoroboradiaza-s-indacene (BODIPY-aminozide). The derivatization reaction was carried out at 60 °C for 30 min in the presence of phosphoric acid. The formed jasmonic acid derivative was eluted using a mobile phase of methanol/pH 6.50 ammonium formate buffer/tetrahydrofuran (67:30:3, v/v/v) in 10 min on a C(18) column and detected with fluorescence detection at excitation and emission wavelengths of 495 and 505 nm, respectively. The detection limit (signal-to-noise ratio = 4) reached 1.14 × 10(-10) M or 2.29 fmol per injection (20 μL), which is the lowest of the existing methods. The proposed method has been successfully applied to the direct determination of trace jasmonic acid in the crude extracts of soybean leaves from soybean mosaic virus-infected and normal plants with recoveries of 95-104%.

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

DOE PAGES

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.; ...

2017-02-14

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

The Transcription Factor ABI4 Is Required for the Ascorbic Acid–Dependent Regulation of Growth and Regulation of Jasmonate-Dependent Defense Signaling Pathways in Arabidopsis[C][W

PubMed Central

Kerchev, Pavel I.; Pellny, Till K.; Vivancos, Pedro Diaz; Kiddle, Guy; Hedden, Peter; Driscoll, Simon; Vanacker, Hélène; Verrier, Paul; Hancock, Robert D.; Foyer, Christine H.

2011-01-01

Cellular redox homeostasis is a hub for signal integration. Interactions between redox metabolism and the ABSCISIC ACID-INSENSITIVE-4 (ABI4) transcription factor were characterized in the Arabidopsis thaliana vitamin c defective1 (vtc1) and vtc2 mutants, which are defective in ascorbic acid synthesis and show a slow growth phenotype together with enhanced abscisic acid (ABA) levels relative to the wild type (Columbia-0). The 75% decrease in the leaf ascorbate pool in the vtc2 mutants was not sufficient to adversely affect GA metabolism. The transcriptome signatures of the abi4, vtc1, and vtc2 mutants showed significant overlap, with a large number of transcription factors or signaling components similarly repressed or induced. Moreover, lincomycin-dependent changes in LIGHT HARVESTING CHLOROPHYLL A/B BINDING PROTEIN 1.1 expression were comparable in these mutants, suggesting overlapping participation in chloroplast to nucleus signaling. The slow growth phenotype of vtc2 was absent in the abi4 vtc2 double mutant, as was the sugar-insensitive phenotype of the abi4 mutant. Octadecanoid derivative-responsive AP2/ERF-domain transcription factor 47 (ORA47) and AP3 (an ABI5 binding factor) transcripts were enhanced in vtc2 but repressed in abi4 vtc2, suggesting that ABI4 and ascorbate modulate growth and defense gene expression through jasmonate signaling. We conclude that low ascorbate triggers ABA- and jasmonate-dependent signaling pathways that together regulate growth through ABI4. Moreover, cellular redox homeostasis exerts a strong influence on sugar-dependent growth regulation. PMID:21926335

A FDG-PET Study of Metabolic Networks in Apolipoprotein E ε4 Allele Carriers

PubMed Central

Yao, Zhijun; Hu, Bin; Zheng, Jiaxiang; Zheng, Weihao; Chen, Xuejiao; Gao, Xiang; Xie, Yuanwei; Fang, Lei

2015-01-01

Recently, some studies have applied the graph theory in brain network analysis in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). However, relatively little research has specifically explored the properties of the metabolic network in apolipoprotein E (APOE) ε4 allele carriers. In our study, all the subjects, including ADs, MCIs and NCs (normal controls) were divided into 165 APOE ε4 carriers and 165 APOE ε4 noncarriers. To establish the metabolic network for all brain regions except the cerebellum, cerebral glucose metabolism data obtained from FDG-PET (18F-fluorodeoxyglu-cose positron emission tomography) were segmented into 90 areas with automated anatomical labeling (AAL) template. Then, the properties of the networks were computed to explore the between-group differences. Our results suggested that both APOE ε4 carriers and noncarriers showed the small-world properties. Besides, compared with APOE ε4 noncarriers, the carriers showed a lower clustering coefficient. In addition, significant changes in 6 hub brain regions were found in between-group nodal centrality. Namely, compared with APOE ε4 noncarriers, significant decreases of the nodal centrality were found in left insula, right insula, right anterior cingulate, right paracingulate gyri, left cuneus, as well as significant increases in left paracentral lobule and left heschl gyrus in APOE ε4 carriers. Increased local short distance interregional correlations and disrupted long distance interregional correlations were found, which may support the point that the APOE ε4 carriers were more similar with AD or MCI in FDG uptake. In summary, the organization of metabolic network in APOE ε4 carriers indicated a less optimal pattern and APOE ε4 might be a risk factor for AD. PMID:26161964

Isolation and functional characterization of a methyl jasmonate-responsive 3-carene synthase from Lavandula x intermedia.

PubMed

Adal, Ayelign M; Sarker, Lukman S; Lemke, Ashley D; Mahmoud, Soheil S

2017-04-01

A methyl jasmonate responsive 3-carene synthase (Li3CARS) gene was isolated from Lavandula x intermedia and functionally characterized in vitro. Lavenders produce essential oils consisting mainly of monoterpenes, including the potent antimicrobial and insecticidal monoterpene 3-carene. In this study we isolated and functionally characterized a leaf-specific, methyl jasmonate (MeJA)-responsive monoterpene synthase (Li3CARS) from Lavandula x intermedia. The ORF excluding transit peptides encoded a 64.9 kDa protein that was expressed in E. coli, and purified with Ni-NTA agarose affinity chromatography. The recombinant Li3CARS converted GPP into 3-carene as the major product, with K m and k cat of 3.69 ± 1.17 µM and 2.01 s -1 respectively. Li3CARS also accepted NPP as a substrate to produce multiple products including a small amount of 3-carene. The catalytic efficiency of Li3CARS to produce 3-carene was over ten fold higher for GPP (k cat /K m = 0.56 µM -1 s -1 ) than NPP (k cat /K m = 0.044 µM -1 s -1 ). Production of distinct end product profiles from different substrates (GPP versus NPP) by Li3CARS indicates that monoterpene metabolism may be controlled in part through substrate availability. Li3CARS transcripts were found to be highly abundant in leaves (16-fold) as compared to flower tissues. The transcriptional activity of Li3CARS correlated with 3-carene production, and was up-regulated (1.18- to 3.8-fold) with MeJA 8-72 h post-treatment. The results suggest that Li3CARS may have a defensive role in Lavandula.

Effects of Methyl Jasmonate on the Composition of Volatile Compounds in Pyropia yezoensis

NASA Astrophysics Data System (ADS)

He, Lihong; Wang, Liang; Wang, Linfang; Shen, Songdong

2018-04-01

Volatile organic compounds in marine algae have been reported to comprise characteristic flavor of algae and play an important role in their growth, development and defensive response. Yet their biogeneration remain largely unknown. Here we studied the composition of volatile compouds in Pyropia yezoensis and their variations in response to methyl jasmonate (MeJA) and diethyldithiocarbamic acid (DIECA) treatment using gas chromatography-mass spectrometry (GC-MS). A total of 44 compounds belonging to the following chemical classes (n) were identified, including aldehydes (11), alcohols (8), acids and esters (6), alkanes (5), ketones (5), alkenes (3), and S- or N-containing miscellaneous compounds (6). External treatment with plant hormone MeJA increased the content of 1-dodecanol, 4-heptenal, and 2-propenoic acid-2-methyl dodecylester, but decreased the content of phytol, 3-heptadecene, 2-pentadecanone, and isophytol. When pretreated with DIECA, an inhibitor of the octadecanoid pathway leading to the biosynthesis of endogeneous jasmonates and some secondary metabolites, phytol and isophytol were increased, while 4-heptenal, 1-dodecanol, and 2-propenoic acid-2-methyl dodecylester were decreased, both of which were negatively correlated with their variations under MeJA treatment. Collectively, these results suggest that MeJA does affect the volatile composition of P. yezoensis, and the octadecanoid pathway together with endogenous jasmonate pathway may be involved in the biosynthesis of volatile compounds, thereby providing some preliminary envision on the composition and biogeneration of volatile compounds in P. yezoensis.

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

PubMed Central

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

2016-01-01

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

Energetics of glucose metabolism: a phenomenological approach to metabolic network modeling.

PubMed

Diederichs, Frank

2010-08-12

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 [Ca(2+)] 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 O(2) 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.

Priming of jasmonate-mediated anti-herbivore defense responses in rice by silicon

USDA-ARS?s Scientific Manuscript database

While the function of silicon (Si) in plant physiology has long been debated, its beneficial effects on plant resistance against abiotic and biotic stresses, ¬including insect herbivory, have been well-documented. In addition, the jasmonate (JA) signaling pathway plays a crucial role in mediating an...

78 FR 22789 - Methyl Jasmonate; Exemption From the Requirement of a Tolerance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-17

.... The acute toxicity data show virtual non-toxicity for all routes of exposure and suggest that any...) and confirmed virtual non-toxicity through the oral route of exposure. There were no observed... virtual non-toxicity through the dermal route of exposure. (MRID No. 48653902). Methyl jasmonate is...

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

PubMed

Fernandez-de-Cossio-Diaz, Jorge; Leon, Kalet; Mulet, Roberto

2017-11-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

PubMed Central

Leon, Kalet; Mulet, Roberto

2017-01-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. PMID:29131817

Alterations in metabolic pathways and networks in Alzheimer's disease

PubMed Central

Kaddurah-Daouk, R; Zhu, H; Sharma, S; Bogdanov, M; Rozen, S G; Matson, W; Oki, N O; Motsinger-Reif, A A; Churchill, E; Lei, Z; Appleby, D; Kling, M A; Trojanowski, J Q; Doraiswamy, P M; Arnold, S E

2013-01-01

The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure. PMID:23571809

Alterations in metabolic pathways and networks in Alzheimer's disease.

PubMed

Kaddurah-Daouk, R; Zhu, H; Sharma, S; Bogdanov, M; Rozen, S G; Matson, W; Oki, N O; Motsinger-Reif, A A; Churchill, E; Lei, Z; Appleby, D; Kling, M A; Trojanowski, J Q; Doraiswamy, P M; Arnold, S E

2013-04-09

The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.

Lipoxygenase in Caragana jubata responds to low temperature, abscisic acid, methyl jasmonate and salicylic acid.

PubMed

Bhardwaj, Pardeep Kumar; Kaur, Jagdeep; Sobti, Ranbir Chander; Ahuja, Paramvir Singh; Kumar, Sanjay

2011-09-01

Lipoxygenase (LOX) catalyses oxygenation of free polyunsaturated fatty acids into oxylipins, and is a critical enzyme of the jasmonate signaling pathway. LOX has been shown to be associated with biotic and abiotic stress responses in diverse plant species, though limited data is available with respect to low temperature and the associated cues. Using rapid amplification of cDNA ends, a full-length cDNA (CjLOX) encoding lipoxygenase was cloned from apical buds of Caragana jubata, a temperate plant species that grows under extreme cold. The cDNA obtained was 2952bp long consisting of an open reading frame of 2610bp encoding 869 amino acids protein. Multiple alignment of the deduced amino acid sequence with those of other plants demonstrated putative LH2/ PLAT domain, lipoxygenase iron binding catalytic domain and lipoxygenase_2 signature sequences. CjLOX exhibited up- and down-regulation of gene expression pattern in response to low temperature (LT), abscisic acid (ABA), methyl jasmonate (MJ) and salicylic acid (SA). Among all the treatments, a strong up-regulation was observed in response to MJ. Data suggests an important role of jasmonate signaling pathway in response to LT in C. jubata. Copyright © 2011 Elsevier B.V. All rights reserved.

Parthenolide accumulation and expression of genes related to parthenolide biosynthesis affected by exogenous application of methyl jasmonate and salicylic acid in Tanacetum parthenium.

PubMed

Majdi, Mohammad; Abdollahi, Mohammad Reza; Maroufi, Asad

2015-11-01

Up-regulation of germacrene A synthase and down-regulation of parthenolide hydroxylase genes play key role in parthenolide accumulation of feverfew plants treated with methyl jasmonate and salicylic acid. Parthenolide is an important sesquiterpene lactone due to its anti-migraine and anti-cancer properties. Parthenolide amount was quantified by high-performance liquid chromatography after foliar application of methyl jasmonate (100 µM) or salicylic acid (1.0 mM) on feverfew leaves in time course experiment (3-96 h). Results indicate that exogenous application of methyl jasmonate or salicylic acid activated parthenolide biosynthesis. Parthenolide content reached its highest amount at 24 h after methyl jasmonate or salicylic acid treatments, which were 3.1- and 1.96-fold higher than control plants, respectively. Parthenolide transiently increased due to methyl jasmonate or salicylic acid treatments until 24 h, but did not show significant difference compared with control plants at 48 and 96 h time points in both treatments. Also, the transcript levels of early pathway (upstream) genes of terpene biosynthesis including 3-hydroxy-3-methylglutaryl-coenzyme A reductase, 1-deoxy-D-xylulose-5-phosphate reductoisomerase and hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase and the biosynthetic genes of parthenolide including germacrene A synthase, germacrene A oxidase, costunolide synthase and parthenolide synthase were increased by methyl jasmonate and salicylic acid treatments, but with different intensity. The transcriptional levels of these genes were higher in methyl jasmonate-treated plants than salicylic acid-treated plants. Parthenolide content measurements along with expression pattern analysis of the aforementioned genes and parthenolide hydroxylase as side branch gene of parthenolide suggest that the expression patterns of early pathway genes were not directly consistent with parthenolide accumulation pattern; hence, parthenolide accumulation is

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

PubMed

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolic Profiling during Peach Fruit Development and Ripening Reveals the Metabolic Networks That Underpin Each Developmental Stage1[C][W

PubMed Central

Lombardo, Verónica A.; Osorio, Sonia; Borsani, Julia; Lauxmann, Martin A.; Bustamante, Claudia A.; Budde, Claudio O.; Andreo, Carlos S.; Lara, María V.; Fernie, Alisdair R.; Drincovich, María F.

2011-01-01

Fruit from rosaceous species collectively display a great variety of flavors and textures as well as a generally high content of nutritionally beneficial metabolites. However, relatively little analysis of metabolic networks in rosaceous fruit has been reported. Among rosaceous species, peach (Prunus persica) has stone fruits composed of a juicy mesocarp and lignified endocarp. Here, peach mesocarp metabolic networks were studied across development using metabolomics and analysis of key regulatory enzymes. Principal component analysis of peach metabolic composition revealed clear metabolic shifts from early through late development stages and subsequently during postharvest ripening. Early developmental stages were characterized by a substantial decrease in protein abundance and high levels of bioactive polyphenols and amino acids, which are substrates for the phenylpropanoid and lignin pathways during stone hardening. Sucrose levels showed a large increase during development, reflecting translocation from the leaf, while the importance of galactinol and raffinose is also inferred. Our study further suggests that posttranscriptional mechanisms are key for metabolic regulation at early stages. In contrast to early developmental stages, a decrease in amino acid levels is coupled to an induction of transcripts encoding amino acid and organic acid catabolic enzymes during ripening. These data are consistent with the mobilization of amino acids to support respiration. In addition, sucrose cycling, suggested by the parallel increase of transcripts encoding sucrose degradative and synthetic enzymes, appears to operate during postharvest ripening. When taken together, these data highlight singular metabolic programs for peach development and may allow the identification of key factors related to agronomic traits of this important crop species. PMID:22021422

Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model

PubMed Central

Lu, Wei; Song, Jiangning; Akutsu, Tatsuya

2015-01-01

Abstract This article considers the problem whereby, given two metabolic networks N1 and N2, a set of source compounds, and a set of target compounds, we must find the minimum set of reactions whose removal (knockout) ensures that the target compounds are not producible in N1 but are producible in N2. Similar studies exist for the problem of finding the minimum knockout with the smallest side effect for a single network. However, if technologies of external perturbations are advanced in the near future, it may be important to develop methods of computing the minimum knockout for multiple networks (MKMN). Flux balance analysis (FBA) is efficient if a well-polished model is available. However, that is not always the case. Therefore, in this article, we study MKMN in Boolean models and an elementary mode (EM)-based model. Integer linear programming (ILP)-based methods are developed for these models, since MKMN is NP-complete for both the Boolean model and the EM-based model. Computer experiments are conducted with metabolic networks of clostridium perfringens SM101 and bifidobacterium longum DJO10A, respectively known as bad bacteria and good bacteria for the human intestine. The results show that larger networks are more likely to have MKMN solutions. However, solving for these larger networks takes a very long time, and often the computation cannot be completed. This is reasonable, because small networks do not have many alternative pathways, making it difficult to satisfy the MKMN condition, whereas in large networks the number of candidate solutions explodes. Our developed software minFvskO is available online. PMID:25684199

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

PubMed

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

2015-02-01

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

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

PubMed

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

2013-05-01

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

Neuropsychiatric subsyndromes and brain metabolic network dysfunctions in early onset Alzheimer's disease.

PubMed

Ballarini, Tommaso; Iaccarino, Leonardo; Magnani, Giuseppe; Ayakta, Nagehan; Miller, Bruce L; Jagust, William J; Gorno-Tempini, Maria Luisa; Rabinovici, Gil D; Perani, Daniela

2016-12-01

Neuropsychiatric symptoms (NPSs) often occur in early-age-of-onset Alzheimer's disease (EOAD) and cluster into sub-syndromes (SSy). The aim of this study was to investigate the association between 18 F-FDG-PET regional and connectivity-based brain metabolic dysfunctions and neuropsychiatric SSy. NPSs were assessed in 27 EOAD using the Neuropsychiatric Inventory and further clustered into four SSy (apathetic, hyperactivity, affective, and psychotic SSy). Eighty-five percent of EOAD showed at least one NPS. Voxel-wise correlations between SSy scores and brain glucose metabolism (assessed with 18 F-FDG positron emission tomography) were studied. Interregional correlation analysis was used to explore metabolic connectivity in the salience (aSN) and default mode networks (DMN) in a larger sample of EOAD (N = 51) and Healthy Controls (N = 57). The apathetic, hyperactivity, and affective SSy were highly prevalent (>60%) as compared to the psychotic SSy (33%). The hyperactivity SSy scores were associated with increase of glucose metabolism in frontal and limbic structures, implicated in behavioral control. A comparable positive correlation with part of the same network was found for the affective SSy scores. On the other hand, the apathetic SSy scores were negatively correlated with metabolism in the bilateral orbitofrontal and dorsolateral frontal cortex known to be involved in motivation and decision-making processes. Consistent with these SSy regional correlations with brain metabolic dysfunction, the connectivity analysis showed increases in the aSN and decreases in the DMN. Behavioral abnormalities in EOAD are associated with specific dysfunctional changes in brain metabolic activity, in particular in the aSN that seems to play a crucial role in NPSs in EOAD. Hum Brain Mapp 37:4234-4247, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The DELLA Protein SLR1 Integrates and Amplifies Salicylic Acid- and Jasmonic Acid-Dependent Innate Immunity in Rice1

PubMed Central

De Vleesschauwer, David; Seifi, Hamed Soren; Haeck, Ashley; Huu, Son Nguyen; Demeestere, Kristof

2016-01-01

Gibberellins are a class of tetracyclic plant hormones that are well known to promote plant growth by inducing the degradation of a class of nuclear growth-repressing proteins, called DELLAs. In recent years, GA and DELLAs are also increasingly implicated in plant responses to pathogen attack, although our understanding of the underlying mechanisms is still limited, especially in monocotyledonous crop plants. Aiming to further decipher the molecular underpinnings of GA- and DELLA-modulated plant immunity, we studied the dynamics and impact of GA and DELLA during infection of the model crop rice (Oryza sativa) with four different pathogens exhibiting distinct lifestyles and infection strategies. Opposite to previous findings in Arabidopsis (Arabidopsis thaliana), our findings reveal a prominent role of the DELLA protein Slender Rice1 (SLR1) in the resistance toward (hemi)biotrophic but not necrotrophic rice pathogens. Moreover, contrary to the differential effect of DELLA on the archetypal defense hormones salicylic acid (SA) and jasmonic acid (JA) in Arabidopsis, we demonstrate that the resistance-promoting effect of SLR1 is due at least in part to its ability to boost both SA- and JA-mediated rice defenses. In a reciprocal manner, we found JA and SA treatment to interfere with GA metabolism and stabilize SLR1. Together, these findings favor a model whereby SLR1 acts as a positive regulator of hemibiotroph resistance in rice by integrating and amplifying SA- and JA-dependent defense signaling. Our results highlight the differences in hormone defense networking between rice and Arabidopsis and underscore the importance of GA and DELLA in molding disease outcomes. PMID:26829979

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

PubMed

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

2016-01-01

Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. © 2015 The Authors.The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Development of an internet based system for modeling biotin metabolism using Bayesian networks.

PubMed

Zhou, Jinglei; Wang, Dong; Schlegel, Vicki; Zempleni, Janos

2011-11-01

Biotin is an essential water-soluble vitamin crucial for maintaining normal body functions. The importance of biotin for human health has been under-appreciated but there is plenty of opportunity for future research with great importance for human health. Currently, carrying out predictions of biotin metabolism involves tedious manual manipulations. In this paper, we report the development of BiotinNet, an internet based program that uses Bayesian networks to integrate published data on various aspects of biotin metabolism. Users can provide a combination of values on the levels of biotin related metabolites to obtain the predictions on other metabolites that are not specified. As an inherent feature of Bayesian networks, the uncertainty of the prediction is also quantified and reported to the user. This program enables convenient in silico experiments regarding biotin metabolism, which can help researchers design future experiments while new data can be continuously incorporated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Small-worldness and gender differences of large scale brain metabolic covariance networks in young adults: a FDG PET study of 400 subjects.

PubMed

Hu, Yuxiao; Xu, Qiang; Shen, Junkang; Li, Kai; Zhu, Hong; Zhang, Zhiqiang; Lu, Guangming

2015-02-01

Many studies have demonstrated the small-worldness of the human brain, and have revealed a sexual dimorphism in brain network properties. However, little is known about the gender effects on the topological organization of the brain metabolic covariance networks. To investigate the small-worldness and the gender differences in the topological architectures of human brain metabolic networks. FDG-PET data of 400 healthy right-handed subjects (200 women and 200 age-matched men) were involved in the present study. Metabolic networks of each gender were constructed by calculating the covariance of regional cerebral glucose metabolism (rCMglc) across subjects on the basis of AAL parcellation. Gender differences of network and nodal properties were investigated by using the graph theoretical approaches. Moreover, the gender-related difference of rCMglc in each brain region was tested for investigating the relationships between the hub regions and the brain regions showing significant gender-related differences in rCMglc. We found prominent small-world properties in the domain of metabolic networks in each gender. No significant gender difference in the global characteristics was found. Gender differences of nodal characteristic were observed in a few brain regions. We also found bilateral and lateralized distributions of network hubs in the females and males. Furthermore, we first reported that some hubs of a gender located in the brain regions showing weaker rCMglc in this gender than the other gender. The present study demonstrated that small-worldness was existed in metabolic networks, and revealed gender differences of organizational patterns in metabolic network. These results maybe provided insights into the understanding of the metabolic substrates underlying individual differences in cognition and behaviors. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Methyl Jasmonate-Elicited Transcriptional Responses and Pentacyclic Triterpene Biosynthesis in Sweet Basil1[C][W

PubMed Central

Misra, Rajesh Chandra; Maiti, Protiti; Chanotiya, Chandan Singh; Shanker, Karuna; Ghosh, Sumit

2014-01-01

Sweet basil (Ocimum basilicum) is well known for its diverse pharmacological properties and has been widely used in traditional medicine for the treatment of various ailments. Although a variety of secondary metabolites with potent biological activities are identified, our understanding of the biosynthetic pathways that produce them has remained largely incomplete. We studied transcriptional changes in sweet basil after methyl jasmonate (MeJA) treatment, which is considered an elicitor of secondary metabolites, and identified 388 candidate MeJA-responsive unique transcripts. Transcript analysis suggests that in addition to controlling its own biosynthesis and stress responses, MeJA up-regulates transcripts of the various secondary metabolic pathways, including terpenoids and phenylpropanoids/flavonoids. Furthermore, combined transcript and metabolite analysis revealed MeJA-induced biosynthesis of the medicinally important ursane-type and oleanane-type pentacyclic triterpenes. Two MeJA-responsive oxidosqualene cyclases (ObAS1 and ObAS2) that encode for 761- and 765-amino acid proteins, respectively, were identified and characterized. Functional expressions of ObAS1 and ObAS2 in Saccharomyces cerevisiae led to the production of β-amyrin and α-amyrin, the direct precursors of oleanane-type and ursane-type pentacyclic triterpenes, respectively. ObAS1 was identified as a β-amyrin synthase, whereas ObAS2 was a mixed amyrin synthase that produced both α-amyrin and β-amyrin but had a product preference for α-amyrin. Moreover, transcript and metabolite analysis shed light on the spatiotemporal regulation of pentacyclic triterpene biosynthesis in sweet basil. Taken together, these results will be helpful in elucidating the secondary metabolic pathways of sweet basil and developing metabolic engineering strategies for enhanced production of pentacyclic triterpenes. PMID:24367017

Identification of lethal reactions in the Esherichia coli metabolic network: Graph theory approach

NASA Astrophysics Data System (ADS)

Ghim, C.-M.; Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

As a first step toward holistic modeling of cells, we analyze the biochemical reactions occurring in the genome-scale metabolism of Esherichia coli. To this end, we construct a directed bipartite graph by assigning metabolite or reaction to each node. We apply various measures of centrality, a well-known concept in the graph theory, and their modifications to the metabolic network, finding that there exist lethal reactions involved in the central metabolism. Such lethal reactions or associated enzymes under diverse environments in silico are identified and compared with earlier results obtained from flux balance analysis.

An integrated approach to characterize genetic interaction networks in yeast metabolism

PubMed Central

Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs

2011-01-01

Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372

Oligogalacturonide-mediated induction of a gene involved in jasmonic acid synthesis in response to the cell-wall-degrading enzymes of the plant pathogen Erwinia carotovora.

PubMed

Norman, C; Vidal, S; Palva, E T

1999-07-01

Identification of Arabidopsis thaliana genes responsive to plant cell-wall-degrading enzymes of Erwinia carotovora subsp. carotovora led to the isolation of a cDNA clone with high sequence homology to the gene for allene oxide synthase, an enzyme involved in the biosynthesis of jasmonates. Expression of the corresponding gene was induced by the extracellular enzymes from this pathogen as well as by treatment with methyl jasmonate and short oligogalacturonides (OGAs). This suggests that OGAs are involved in the induction of the jasmonate pathway during plant defense response to E. carotovora subsp. carotovora attack.

Version 6 of the consensus yeast metabolic network refines biochemical coverage and improves model performance

PubMed Central

Heavner, Benjamin D.; Smallbone, Kieran; Price, Nathan D.; Walker, Larry P.

2013-01-01

Updates to maintain a state-of-the art reconstruction of the yeast metabolic network are essential to reflect our understanding of yeast metabolism and functional organization, to eliminate any inaccuracies identified in earlier iterations, to improve predictive accuracy and to continue to expand into novel subsystems to extend the comprehensiveness of the model. Here, we present version 6 of the consensus yeast metabolic network (Yeast 6) as an update to the community effort to computationally reconstruct the genome-scale metabolic network of Saccharomyces cerevisiae S288c. Yeast 6 comprises 1458 metabolites participating in 1888 reactions, which are annotated with 900 yeast genes encoding the catalyzing enzymes. Compared with Yeast 5, Yeast 6 demonstrates improved sensitivity, specificity and positive and negative predictive values for predicting gene essentiality in glucose-limited aerobic conditions when analyzed with flux balance analysis. Additionally, Yeast 6 improves the accuracy of predicting the likelihood that a mutation will cause auxotrophy. The network reconstruction is available as a Systems Biology Markup Language (SBML) file enriched with Minimium Information Requested in the Annotation of Biochemical Models (MIRIAM)-compliant annotations. Small- and macromolecules in the network are referenced to authoritative databases such as Uniprot or ChEBI. Molecules and reactions are also annotated with appropriate publications that contain supporting evidence. Yeast 6 is freely available at http://yeast.sf.net/ as three separate SBML files: a model using the SBML level 3 Flux Balance Constraint package, a model compatible with the MATLAB® COBRA Toolbox for backward compatibility and a reconstruction containing only reactions for which there is experimental evidence (without the non-biological reactions necessary for simulating growth). Database URL: http://yeast.sf.net/ PMID:23935056

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network.

PubMed

Gloaguen, Pauline; Bournais, Sylvain; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Tardif, Marianne; Kuntz, Marcel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves; Curien, Gilles

2017-06-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. © 2017 American Society of Plant Biologists. All Rights Reserved.

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

PubMed

Peterson, Christine; Vannucci, Marina; Karakas, Cemal; Choi, William; Ma, Lihua; Maletić-Savatić, Mirjana

2013-10-01

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

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

PubMed Central

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

2014-01-01

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

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

PubMed

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

PubMed

Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

2017-08-15

Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

PubMed Central

Hoppe, Andreas; Hoffmann, Sabrina; Holzhütter, Hermann-Georg

2007-01-01

Background In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions. Results To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state. Conclusion Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The

Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection.

PubMed

Yoon, Jeongah; Si, Yaguang; Nolan, Ryan; Lee, Kyongbum

2007-09-15

The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top-down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. Supplementary data are available at Bioinformatics online.

A proof for loop-law constraints in stoichiometric metabolic networks

PubMed Central

2012-01-01

Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling. PMID:23146116

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA

PubMed Central

2017-01-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository. PMID:28263984

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

PubMed

Biggs, Matthew B; Papin, Jason A

2017-03-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

Neuropsychiatric Subsyndromes and Brain Metabolic Network Dysfunctions in Early Onset Alzheimer’s Disease

PubMed Central

Tommaso, Ballarini; Leonardo, Iaccarino; Giuseppe, Magnani; Nagehan, Ayakta; Bruce L, Miller; William J, Jagust; Luisa, Gorno-Tempini Maria; Gil D, Rabinovici; Daniela, Perani

2017-01-01

Neuropsychiatric symptoms (NPSs) often occur in early-age-of-onset Alzheimer’s disease (EOAD) and cluster into sub-syndromes (SSy). The aim of this study was to investigate the association between 18F-FDG-PET regional and connectivity-based brain metabolic dysfunctions and neuropsychiatric SSy. NPSs were assessed in 27 EOAD using the Neuropsychiatric Inventory and further clustered into four SSy (apathetic, hyperactivity, affective and psychotic SSy). 85% of EOAD showed at least one NPS. Voxel-wise correlations between SSy scores and brain glucose metabolism (assessed with 18F-FDG positron emission tomography) were studied. Interregional correlation analysis was used to explore metabolic connectivity in the salience (aSN) and default mode networks (DMN) in a larger sample of EOAD (N=51) and Healthy Controls (N=57). The apathetic, hyperactivity and affective SSy were highly prevalent (>60%) as compared to the psychotic SSy (33%). The hyperactivity SSy scores were associated with increase of glucose metabolism in frontal and limbic structures, implicated in behavioral control. A comparable positive correlation with part of the same network was found for the affective SSy scores. On the other hand, the apathetic SSy scores were negatively correlated with metabolism in the bilateral orbitofrontal and dorsolateral frontal cortex known to be involved in motivation and decision-making processes. Consistent with these SSy regional correlations with brain metabolic dysfunction, the connectivity analysis showed increases in the aSN and decreases in the DMN. Behavioral abnormalities in EOAD are associated with specific dysfunctional changes in brain metabolic activity, in particular in the aSN that seems to play a crucial role in NPSs in EOAD. PMID:27412866

Exogenous application of methyl jasmonate and salicylic acid on citrus foliage: Effecs on foliar volatiles and aggregation behavior of Asian citrus psyllid (Diaphorina citri)

USDA-ARS?s Scientific Manuscript database

Methyl jasmonate (MeJA) and salicylic acid (SA) are well-known activators of chemical defenses in plants. The SA pathway is involved in citrus response to infection by Candidatus Liberibacter asiaticus (CLas); less is known about the role of jasmonates in citrus defense response. We examined the eff...

MYC2 Differentially Modulates Diverse Jasmonate-Dependent Functions in Arabidopsis[W

PubMed Central

Dombrecht, Bruno; Xue, Gang Ping; Sprague, Susan J.; Kirkegaard, John A.; Ross, John J.; Reid, James B.; Fitt, Gary P.; Sewelam, Nasser; Schenk, Peer M.; Manners, John M.; Kazan, Kemal

2007-01-01

The Arabidopsis thaliana basic helix-loop-helix Leu zipper transcription factor (TF) MYC2/JIN1 differentially regulates jasmonate (JA)-responsive pathogen defense (e.g., PDF1.2) and wound response (e.g., VSP) genes. In this study, genome-wide transcriptional profiling of wild type and mutant myc2/jin1 plants followed by functional analyses has revealed new roles for MYC2 in the modulation of diverse JA functions. We found that MYC2 negatively regulates Trp and Trp-derived secondary metabolism such as indole glucosinolate biosynthesis during JA signaling. Furthermore, MYC2 positively regulates JA-mediated resistance to insect pests, such as Helicoverpa armigera, and tolerance to oxidative stress, possibly via enhanced ascorbate redox cycling and flavonoid biosynthesis. Analyses of MYC2 cis binding elements and expression of MYC2-regulated genes in T-DNA insertion lines of a subset of MYC2–regulated TFs suggested that MYC2 might modulate JA responses via differential regulation of an intermediate spectrum of TFs with activating or repressing roles in JA signaling. MYC2 also negatively regulates its own expression, and this may be one of the mechanisms used in fine-tuning JA signaling. Overall, these results provide new insights into the function of MYC2 and the transcriptional coordination of the JA signaling pathway. PMID:17616737

A metabolic network approach for the identification and prioritization of antimicrobial drug targets

PubMed Central

Chavali, Arvind K.; D’Auria, Kevin M.; Hewlett, Erik L.; Pearson, Richard D.; Papin, Jason A.

2012-01-01

For many infectious diseases, novel treatment options are needed to address problems with cost, toxicity and resistance to current drugs. Systems biology tools can be used to gain valuable insight into pathogenic processes and aid in expediting drug discovery. In the past decade, constraint-based modeling of genome-scale metabolic networks has become widely used. Focusing on pathogen metabolic networks, we review in silico strategies to identify effective drug targets, and we highlight recent successes as well as limitations associated with such computational analyses. We further discuss how accounting for the host environment and even targeting the host may offer new therapeutic options. These systems-level approaches are beginning to provide novel avenues for drug targeting against infectious agents. PMID:22300758

Jasmonate is involved in the induction of tyrosine aminotransferase and tocopherol biosynthesis in Arabidopsis thaliana.

PubMed

Sandorf, Iris; Holländer-Czytko, Heike

2002-11-01

Coronatine-inducible tyrosine aminotransferase (TAT), which catalyses the transamination from tyrosine to p-hydroxyphenylpyruvate, is the first enzyme of a pathway leading via homogentisic acid to plastoquinone and tocopherols, the latter of which are known to be radical scavengers in plants. TAT can be also induced by the octadecanoids methyl jasmonate (MeJA) and methyl-12-oxophytodienoic acid (MeOPDA), as well as by wounding, high light, UV light and the herbicide oxyfluorfen. In order to elucidate the role of octadecanoids in the process of TAT induction in Arabidopsis thaliana (L.) Heynh., the jasmonate-deficient mutant delayed dehiscence (dde1) was used, in which the gene for 12-oxophytodienoic acid reductase 3 is disrupted. The amount of immunodetectable TAT was low. The enzyme was still fully induced by coronatine as well as by MeJA although induction by the latter was to a lesser extent and later than in the wild type. Treatment with MeOPDA, wounding and UV light, however, had hardly any effects. Tocopherol levels that showed considerable increases in the wild type after some treatments were much less affected in the mutant. However, starting levels of tocopherol were higher in non-induced dde1 than in the wild type. We conclude that jasmonate plays an important role in the signal transduction pathway regulating TAT activity and the biosynthesis of its product tocopherol.

Predicting selective drug targets in cancer through metabolic networks

PubMed Central

Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

2011-01-01

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718

Expression of geminiviral AC2 RNA silencing suppressor changes sugar and jasmonate responsive gene expression in transgenic tobacco plants

PubMed Central

2012-01-01

Background RNA-silencing is a conserved gene regulation and surveillance machinery, which in plants, is also used as major defence mechanism against viruses. Various virus-specific dsRNA structures are recognized by the silencing machinery leading to degradation of the viral RNAs or, as in case of begomoviruses, to methylation of their DNA genomes. Viruses produce specific RNA silencing suppressor (RSS) proteins to prevent these host defence mechanisms, and as these interfere with the silencing machinery they also disturb the endogenous silencing reactions. In this paper, we describe how expression of AC2 RSS, derived from African cassava mosaic geminivirus changes transcription profile in tobacco (Nicotiana tabacum) leaves and in flowers. Results Expression of AC2 RSS in transgenic tobacco plants induced clear phenotypic changes both in leaves and in flowers. Transcriptomes of these plants were strongly altered, with total of 1118 and 251 differentially expressed genes in leaves and flowers, respectively. The three most up-regulated transcript groups were related to stress, cell wall modifications and signalling, whereas the three most down-regulated groups were related to translation, photosynthesis and transcription. It appears that many of the gene expression alterations appeared to be related to enhanced biosynthesis of jasmonate and ethylene, and consequent enhancement of the genes and pathways that are regulated by these hormones, or to the retrograde signalling caused by the reduced photosynthetic activity and sugar metabolism. Comparison of these results to a previous transcriptional profiling of HC-Pro RSS-expressing plants revealed that some of same genes were induced by both RSSs, but their expression levels were typically higher in AC2 than in HC-Pro RSS expressing plants. All in all, a large number of transcript alterations were found to be specific to each of the RSS expressing transgenic plants. Conclusions AC2 RSS in transgenic tobacco plants

The DELLA Protein SLR1 Integrates and Amplifies Salicylic Acid- and Jasmonic Acid-Dependent Innate Immunity in Rice.

PubMed

De Vleesschauwer, David; Seifi, Hamed Soren; Filipe, Osvaldo; Haeck, Ashley; Huu, Son Nguyen; Demeestere, Kristof; Höfte, Monica

2016-03-01

Gibberellins are a class of tetracyclic plant hormones that are well known to promote plant growth by inducing the degradation of a class of nuclear growth-repressing proteins, called DELLAs. In recent years, GA and DELLAs are also increasingly implicated in plant responses to pathogen attack, although our understanding of the underlying mechanisms is still limited, especially in monocotyledonous crop plants. Aiming to further decipher the molecular underpinnings of GA- and DELLA-modulated plant immunity, we studied the dynamics and impact of GA and DELLA during infection of the model crop rice (Oryza sativa) with four different pathogens exhibiting distinct lifestyles and infection strategies. Opposite to previous findings in Arabidopsis (Arabidopsis thaliana), our findings reveal a prominent role of the DELLA protein Slender Rice1 (SLR1) in the resistance toward (hemi)biotrophic but not necrotrophic rice pathogens. Moreover, contrary to the differential effect of DELLA on the archetypal defense hormones salicylic acid (SA) and jasmonic acid (JA) in Arabidopsis, we demonstrate that the resistance-promoting effect of SLR1 is due at least in part to its ability to boost both SA- and JA-mediated rice defenses. In a reciprocal manner, we found JA and SA treatment to interfere with GA metabolism and stabilize SLR1. Together, these findings favor a model whereby SLR1 acts as a positive regulator of hemibiotroph resistance in rice by integrating and amplifying SA- and JA-dependent defense signaling. Our results highlight the differences in hormone defense networking between rice and Arabidopsis and underscore the importance of GA and DELLA in molding disease outcomes. © 2016 American Society of Plant Biologists. All Rights Reserved.

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

PubMed

Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

PubMed

Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

2013-12-23

Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

Regulation of sesquiterpenoid metabolism in recombinant and elicited Valeriana officinalis hairy roots.

PubMed

Ricigliano, Vincent; Kumar, Santosh; Kinison, Scott; Brooks, Christopher; Nybo, S Eric; Chappell, Joe; Howarth, Dianella G

2016-05-01

The medicinal properties of Valerian (Valeriana officinalis) root preparations are attributed to the anxiolytic sesquiterpenoid valerenic acid and its biosynthetic precursors valerenal and valerenadiene, as well as the anti-inflammatory sesquiterpenoid β-caryophyllene. In order to study and engineer the biosynthesis of these pharmacologically active metabolites, a binary vector co-transformation system was developed for V. officinalis hairy roots. The relative expression levels and jasmonate-inducibility of a number of genes associated with sesquiterpenoid metabolism were profiled in roots: farnesyl pyrophosphate synthase (VoFPS), valerendiene synthase (VoVDS), germacrene C synthase (VoGCS), and a cytochrome P450 (CYP71D442) putatively associated with terpene metabolism based on sequence homology. Recombinant hairy root lines overexpressing VoFPS or VoVDS were generated and compared to control cultures. Overexpression of the VoFPS cDNA increased levels of the corresponding transcript 4- to 8-fold and sesquiterpene hydrocarbon accumulation by 1.5- to 4-fold. Overexpression of the VoVDS cDNA increased the corresponding transcript levels 5- to 9-fold and markedly increased yields of the oxygenated sesquiterpenoids valerenic acid and valerenal. Our findings suggest that the availability of cytoplasmic farnesyl diphosphate and valerenadiene are potential bottlenecks in Valeriana-specific sesquiterpenoid biosynthesis, which is also subject to regulation by methyl jasmonate elicitation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Crosstalk among Jasmonate, Salicylate and Ethylene Signaling Pathways in Plant Disease and Immune Responses.

PubMed

Yang, You-Xin; Ahammed, Golam J; Wu, Caijun; Fan, Shu-ying; Zhou, Yan-Hong

2015-01-01

Phytohormone crosstalk is crucial for plant defenses against pathogens and insects in which salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) play key roles. These low molecular mass signals critically trigger and modulate plant resistance against biotrophic as well as necrotrophic pathogens through a complex signaling network that even involves participation of other hormones. Crosstalk among SA, JA and ET is mediated by different molecular players, considered as integral part of these crosscommunicating signal transduction pathways. Recent progress has revealed that the positive versus negative interactions among those pathways ultimately enable a plant to fine-tune its defense against specific aggressors. On the other hand, pathogens have evolved strategies to manipulate the signaling network to their favour in order to intensify virulence on host plant. Here we review recent advances and current knowledge on the role of classical primary defense hormones SA, JA and ET as well as their synergistic and antagonistic interaction in plant disease and immune responses. Crosstalk with other hormones such as abscisic acid, auxin, brassinosteroids, cytokinins and melatonin is also discussed mainly in plant disease resistance. In addition to our keen focus on hormonal crosstalk, this review also highlights potential implication of positive and negative regulatory interactions for developing an efficient disease management strategy through manipulation of hormone signaling in plant.

Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803.

PubMed

Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio; de Córdoba, Pedro Fernández; Urchueguía, Javier F; Patil, Kiran Raosaheb

2011-03-01

Synechocystis sp. PCC6803 is a model cyanobacterium capable of producing biofuels with CO(2) as carbon source and with its metabolism fueled by light, for which it stands as a potential production platform of socio-economic importance. Compilation and characterization of Synechocystis genome-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling networks, surrounded by a stable core of pathways leading to biomass building blocks. This analysis identified potential bottlenecks for hydrogen and ethanol production. Integration of transcriptomic data with the Synechocystis flux coupling networks lead to identification of reporter flux coupling pairs and reporter flux coupling groups - regulatory hot spots during metabolic shifts triggered by the availability of light. Overall, flux coupling analysis provided insight into the structural organization of Synechocystis sp. PCC6803 metabolic network toward designing of a photosynthesis-based production platform. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microbial metabolic networks in a complex electrogenic biofilm recovered from a stimulus-induced metatranscriptomics approach

PubMed Central

Ishii, Shun’ichi; Suzuki, Shino; Tenney, Aaron; Norden-Krichmar, Trina M.; Nealson, Kenneth H.; Bretschger, Orianna

2015-01-01

Microorganisms almost always exist as mixed communities in nature. While the significance of microbial community activities is well appreciated, a thorough understanding about how microbial communities respond to environmental perturbations has not yet been achieved. Here we have used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches existing in a complex microbial biofilm that was producing electrical current via extracellular electron transfer (EET) to a solid electrode surface. Two stimuli were employed: to increase EET and to stop EET. An analysis of cell activity marker genes after stimuli exposure revealed that only two strains within eleven binned genomes had strong transcriptional responses to increased EET rates, with one responding positively and the other responding negatively. Potential metabolic switches between eleven dominant members were mainly observed for acetate, hydrogen, and ethanol metabolisms. These results have enabled the estimation of a multi-species metabolic network and the associated short-term responses to EET stimuli that induce changes to metabolic flow and cooperative or competitive microbial interactions. This systematic meta-omics approach represents a next step towards understanding complex microbial roles within a community and how community members respond to specific environmental stimuli. PMID:26443302

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

PubMed

Megchelenbrink, Wout; Huynen, Martijn; Marchiori, Elena

2014-01-01

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/.

Control of Carbon Assimilation and Partitioning by Jasmonate: An Accounting of Growth-Defense Tradeoffs.

PubMed

Havko, Nathan E; Major, Ian T; Jewell, Jeremy B; Attaran, Elham; Browse, John; Howe, Gregg A

2016-01-15

Plant growth is often constrained by the limited availability of resources in the microenvironment. Despite the continuous threat of attack from insect herbivores and pathogens, investment in defense represents a lost opportunity to expand photosynthetic capacity in leaves and absorption of nutrients and water by roots. To mitigate the metabolic expenditure on defense, plants have evolved inducible defense strategies. The plant hormone jasmonate (JA) is a key regulator of many inducible defenses. Synthesis of JA in response to perceived danger leads to the deployment of a variety of defensive structures and compounds, along with a potent inhibition of growth. Genetic studies have established an important role for JA in mediating tradeoffs between growth and defense. However, several gaps remain in understanding of how JA signaling inhibits growth, either through direct transcriptional control of JA-response genes or crosstalk with other signaling pathways. Here, we highlight recent progress in uncovering the role of JA in controlling growth-defense balance and its relationship to resource acquisition and allocation. We also discuss tradeoffs in the context of the ability of JA to promote increased leaf mass per area (LMA), which is a key indicator of leaf construction costs and leaf life span.

Proteomic analysis of JAZ interacting proteins under methyl jasmonate treatment in finger millet.

PubMed

Sen, Saswati; Kundu, Sangeeta; Dutta, Samir Kr

2016-11-01

Jasmonic acid (JA) signaling pathway in plants is activated against various developmental processes as well as biotic and abiotic stresses. The Jasmonate ZIM-domain (JAZ) protein family, the key regulator of plant JA signaling pathway, also participates in phytohormone crosstalk. This is the first study revealing the in vivo interactions of finger millet (Eleusine coracana (L.) Gaertn.) JAZ protein (EcJAZ) under methyl jasmonate (MJ) treatment. The aim of the study was to explore not only the JA signaling pathway but also the phytohormone signaling crosstalk of finger millet, a highly important future crop. From the MJ-treated finger millet seedlings, the EcJAZ interacting proteins were purified by affinity chromatography with the EcJAZ-matrix. Twenty-one proteins of varying functionalities were successfully identified by MALDI-TOF-TOF Mass spectrometry. Apart from the previously identified JAZ binding proteins, most prominently, EcJAZ was found to interact with transcription factors like NAC, GATA and also with Cold responsive protein (COR), etc. that might have extended the range of functionalities of JAZ proteins. Moreover, to evaluate the interactions of EcJAZ in the JA-co-receptor complex, we generated ten in-silico models containing the EcJAZ degron and the COI1-SKP1 of five monocot cereals viz., rice, wheat, maize, Sorghum and Setaria with JA-Ile or coronatine. Our results indicated that the EcJAZ protein of finger millet could act as the signaling hub for the JA and other phytohormone signaling pathways, in response to a diverse set of stressors and developmental cues to provide survival fitness to the plant. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Induced jasmonate signaling leads to contrasting effects on root damage and herbivore performance.

PubMed

Lu, Jing; Robert, Christelle Aurélie Maud; Riemann, Michael; Cosme, Marco; Mène-Saffrané, Laurent; Massana, Josep; Stout, Michael Joseph; Lou, Yonggen; Gershenzon, Jonathan; Erb, Matthias

2015-03-01

Induced defenses play a key role in plant resistance against leaf feeders. However, very little is known about the signals that are involved in defending plants against root feeders and how they are influenced by abiotic factors. We investigated these aspects for the interaction between rice (Oryza sativa) and two root-feeding insects: the generalist cucumber beetle (Diabrotica balteata) and the more specialized rice water weevil (Lissorhoptrus oryzophilus). Rice plants responded to root attack by increasing the production of jasmonic acid (JA) and abscisic acid, whereas in contrast to in herbivore-attacked leaves, salicylic acid and ethylene levels remained unchanged. The JA response was decoupled from flooding and remained constant over different soil moisture levels. Exogenous application of methyl JA to the roots markedly decreased the performance of both root herbivores, whereas abscisic acid and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid did not have any effect. JA-deficient antisense 13-lipoxygenase (asLOX) and mutant allene oxide cyclase hebiba plants lost more root biomass under attack from both root herbivores. Surprisingly, herbivore weight gain was decreased markedly in asLOX but not hebiba mutant plants, despite the higher root biomass removal. This effect was correlated with a herbivore-induced reduction of sucrose pools in asLOX roots. Taken together, our experiments show that jasmonates are induced signals that protect rice roots from herbivores under varying abiotic conditions and that boosting jasmonate responses can strongly enhance rice resistance against root pests. Furthermore, we show that a rice 13-lipoxygenase regulates root primary metabolites and specifically improves root herbivore growth. © 2015 American Society of Plant Biologists. All Rights Reserved.

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

PubMed

Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

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

PubMed Central

Ray, Sandipan

2016-01-01

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

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE PAGES

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; ...

2015-03-27

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

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.

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

Induced Jasmonate Signaling Leads to Contrasting Effects on Root Damage and Herbivore Performance1

PubMed Central

Lu, Jing; Robert, Christelle Aurélie Maud; Riemann, Michael; Cosme, Marco; Mène-Saffrané, Laurent; Massana, Josep; Stout, Michael Joseph; Lou, Yonggen; Gershenzon, Jonathan; Erb, Matthias

2015-01-01

Induced defenses play a key role in plant resistance against leaf feeders. However, very little is known about the signals that are involved in defending plants against root feeders and how they are influenced by abiotic factors. We investigated these aspects for the interaction between rice (Oryza sativa) and two root-feeding insects: the generalist cucumber beetle (Diabrotica balteata) and the more specialized rice water weevil (Lissorhoptrus oryzophilus). Rice plants responded to root attack by increasing the production of jasmonic acid (JA) and abscisic acid, whereas in contrast to in herbivore-attacked leaves, salicylic acid and ethylene levels remained unchanged. The JA response was decoupled from flooding and remained constant over different soil moisture levels. Exogenous application of methyl JA to the roots markedly decreased the performance of both root herbivores, whereas abscisic acid and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid did not have any effect. JA-deficient antisense 13-lipoxygenase (asLOX) and mutant allene oxide cyclase hebiba plants lost more root biomass under attack from both root herbivores. Surprisingly, herbivore weight gain was decreased markedly in asLOX but not hebiba mutant plants, despite the higher root biomass removal. This effect was correlated with a herbivore-induced reduction of sucrose pools in asLOX roots. Taken together, our experiments show that jasmonates are induced signals that protect rice roots from herbivores under varying abiotic conditions and that boosting jasmonate responses can strongly enhance rice resistance against root pests. Furthermore, we show that a rice 13-lipoxygenase regulates root primary metabolites and specifically improves root herbivore growth. PMID:25627217

Analysis of optimality in natural and perturbed metabolic networks

PubMed Central

Segrè, Daniel; Vitkup, Dennis; Church, George M.

2002-01-01

An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

Salicylic acid suppresses jasmonic acid signaling downstream of SCFCOI1-JAZ by targeting GCC promoter motifs via transcription factor ORA59.

PubMed

Van der Does, Dieuwertje; Leon-Reyes, Antonio; Koornneef, Annemart; Van Verk, Marcel C; Rodenburg, Nicole; Pauwels, Laurens; Goossens, Alain; Körbes, Ana P; Memelink, Johan; Ritsema, Tita; Van Wees, Saskia C M; Pieterse, Corné M J

2013-02-01

Antagonism between the defense hormones salicylic acid (SA) and jasmonic acid (JA) plays a central role in the modulation of the plant immune signaling network, but the molecular mechanisms underlying this phenomenon are largely unknown. Here, we demonstrate that suppression of the JA pathway by SA functions downstream of the E3 ubiquitin-ligase Skip-Cullin-F-box complex SCF(COI1), which targets JASMONATE ZIM-domain transcriptional repressor proteins (JAZs) for proteasome-mediated degradation. In addition, neither the stability nor the JA-induced degradation of JAZs was affected by SA. In silico promoter analysis of the SA/JA crosstalk transcriptome revealed that the 1-kb promoter regions of JA-responsive genes that are suppressed by SA are significantly enriched in the JA-responsive GCC-box motifs. Using GCC:GUS lines carrying four copies of the GCC-box fused to the β-glucuronidase reporter gene, we showed that the GCC-box motif is sufficient for SA-mediated suppression of JA-responsive gene expression. Using plants overexpressing the GCC-box binding APETALA2/ETHYLENE RESPONSE FACTOR (AP2/ERF) transcription factors ERF1 or ORA59, we found that SA strongly reduces the accumulation of ORA59 but not that of ERF1. Collectively, these data indicate that the SA pathway inhibits JA signaling downstream of the SCF(COI1)-JAZ complex by targeting GCC-box motifs in JA-responsive promoters via a negative effect on the transcriptional activator ORA59.

Modification and translocation of Rac/Rop guanosine 5'-triphosphate-binding proteins of Scoparia dulcis in response to stimulation with methyl jasmonate.

PubMed

Mitamura, Toshiaki; Yamamura, Yoshimi; Kurosaki, Fumiya

2011-01-01

Translocation of two Rac/Rop guanosine 5'-triphosphate-binding proteins from Scoparia dulcis, Sdrac-1 and Sdrac-2, was examined employing transformed belladonna which overproduces these proteins as glutathione-S-transferase-tagged forms. The transferase activities of the fused proteins in microsomal fraction of belladonna markedly increased by the incubation with methyl jasmonate either in Sdrac-1 or Sdrac-2 transformant, while low and constant activities were observed in the untreated control. Recombinant Sdrac-2 protein was found to bind to prenyl chain in the presence of cell extracts prepared from methyl jasmonate-treated S. dulcis, however, Sdrac-1 was palmitoylated by the addition of the cell extracts. These results suggest that both Sdrac-1 and Sdrac-2 translocate to plant membranes by the stimulation with methyl jasmonate, however, targeting of these proteins is triggered by the independent modification mechanisms, palmitoylation for Sdrac-1 and prenylation for Sdrac-2.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus