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Sample records for production metabolism scaling

  1. Metabolic engineering of strains: from industrial-scale to lab-scale chemical production.

    PubMed

    Sun, Jie; Alper, Hal S

    2015-03-01

    A plethora of successful metabolic engineering case studies have been published over the past several decades. Here, we highlight a collection of microbially produced chemicals using a historical framework, starting with titers ranging from industrial scale (more than 50 g/L), to medium-scale (5-50 g/L), and lab-scale (0-5 g/L). Although engineered Escherichia coli and Saccharomyces cerevisiae emerge as prominent hosts in the literature as a result of well-developed genetic engineering tools, several novel native-producing strains are gaining attention. This review catalogs the current progress of metabolic engineering towards production of compounds such as acids, alcohols, amino acids, natural organic compounds, and others.

  2. Biofuel production: an odyssey from metabolic engineering to fermentation scale-up

    PubMed Central

    Hollinshead, Whitney; He, Lian; Tang, Yinjie J.

    2014-01-01

    Metabolic engineering has developed microbial cell factories that can convert renewable carbon sources into biofuels. Current molecular biology tools can efficiently alter enzyme levels to redirect carbon fluxes toward biofuel production, but low product yield and titer in large bioreactors prevent the fulfillment of cheap biofuels. There are three major roadblocks preventing economical biofuel production. First, carbon fluxes from the substrate dissipate into a complex metabolic network. Besides the desired product, microbial hosts direct carbon flux to synthesize biomass, overflow metabolites, and heterologous enzymes. Second, microbial hosts need to oxidize a large portion of the substrate to generate both ATP and NAD(P)H to power biofuel synthesis. High cell maintenance, triggered by the metabolic burdens from genetic modifications, can significantly affect the ATP supply. Thereby, fermentation of advanced biofuels (such as biodiesel and hydrocarbons) often requires aerobic respiration to resolve the ATP shortage. Third, mass transfer limitations in large bioreactors create heterogeneous growth conditions and micro-environmental fluctuations (such as suboptimal O2 level and pH) that induce metabolic stresses and genetic instability. To overcome these limitations, fermentation engineering should merge with systems metabolic engineering. Modern fermentation engineers need to adopt new metabolic flux analysis tools that integrate kinetics, hydrodynamics, and 13C-proteomics, to reveal the dynamic physiologies of the microbial host under large bioreactor conditions. Based on metabolic analyses, fermentation engineers may employ rational pathway modifications, synthetic biology circuits, and bioreactor control algorithms to optimize large-scale biofuel production. PMID:25071754

  3. Systems metabolic engineering of microorganisms to achieve large-scale production of flavonoid scaffolds.

    PubMed

    Wu, Junjun; Du, Guocheng; Zhou, Jingwen; Chen, Jian

    2014-10-20

    Flavonoids possess pharmaceutical potential due to their health-promoting activities. The complex structures of these products make extraction from plants difficult, and chemical synthesis is limited because of the use of many toxic solvents. Microbial production offers an alternate way to produce these compounds on an industrial scale in a more economical and environment-friendly manner. However, at present microbial production has been achieved only on a laboratory scale and improvements and scale-up of these processes remain challenging. Naringenin and pinocembrin, which are flavonoid scaffolds and precursors for most of the flavonoids, are the model molecules that are key to solving the current issues restricting industrial production of these chemicals. The emergence of systems metabolic engineering, which combines systems biology with synthetic biology and evolutionary engineering at the systems level, offers new perspectives on strain and process optimization. In this review, current challenges in large-scale fermentation processes involving flavonoid scaffolds and the strategies and tools of systems metabolic engineering used to overcome these challenges are summarized. This will offer insights into overcoming the limitations and challenges of large-scale microbial production of these important pharmaceutical compounds.

  4. Genome-scale analysis of Saccharomyces cerevisiae metabolism and ethanol production in fed-batch culture.

    PubMed

    Hjersted, Jared L; Henson, Michael A; Mahadevan, Radhakrishnan

    2007-08-01

    A dynamic flux balance model based on a genome-scale metabolic network reconstruction is developed for in silico analysis of Saccharomyces cerevisiae metabolism and ethanol production in fed-batch culture. Metabolic engineering strategies previously identified for their enhanced steady-state biomass and/or ethanol yields are evaluated for fed-batch performance in glucose and glucose/xylose media. Dynamic analysis is shown to provide a single quantitative measure of fed-batch ethanol productivity that explicitly handles the possible tradeoff between the biomass and ethanol yields. Productivity optimization conducted to rank achievable fed-batch performance demonstrates that the genetic manipulation strategy and the fed-batch operating policy should be considered simultaneously. A library of candidate gene insertions is assembled and directly screened for their achievable ethanol productivity in fed-batch culture. A number of novel gene insertions with ethanol productivities identical to the best metabolic engineering strategies reported in previous studies are identified, thereby providing additional targets for experimental evaluation. The top performing gene insertions were substrate dependent, with the highest ranked insertions for glucose media yielding suboptimal performance in glucose/xylose media. The analysis results suggest that enhancements in biomass yield are most beneficial for the enhancement of fed-batch ethanol productivity by recombinant xylose utilizing yeast strains. We conclude that steady-state flux balance analysis is not sufficient to predict fed-batch performance and that the media, genetic manipulations, and fed-batch operating policy should be considered simultaneously to achieve optimal metabolite productivity. (c) 2007 Wiley Periodicals, Inc.

  5. Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis

    PubMed Central

    2017-01-01

    The yeast Scheffersomyces stipitis naturally produces ethanol from xylose, however reaching high ethanol yields is strongly dependent on aeration conditions. It has been reported that changes in the availability of NAD(H/+) cofactors can improve fermentation in some microorganisms. In this work genome-scale metabolic modeling and phenotypic phase plane analysis were used to characterize metabolic response on a range of uptake rates. Sensitivity analysis was used to assess the effect of ARC on ethanol production indicating that modifying ARC by inhibiting the respiratory chain ethanol production can be improved. It was shown experimentally in batch culture using Rotenone as an inhibitor of the mitochondrial NADH dehydrogenase complex I (CINADH), increasing ethanol yield by 18%. Furthermore, trajectories for uptakes rates, specific productivity and specific growth rate were determined by modeling the batch culture, to calculate ARC associated to the addition of CINADH inhibitor. Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC. PMID:28658270

  6. Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis.

    PubMed

    Acevedo, Alejandro; Conejeros, Raúl; Aroca, Germán

    2017-01-01

    The yeast Scheffersomyces stipitis naturally produces ethanol from xylose, however reaching high ethanol yields is strongly dependent on aeration conditions. It has been reported that changes in the availability of NAD(H/+) cofactors can improve fermentation in some microorganisms. In this work genome-scale metabolic modeling and phenotypic phase plane analysis were used to characterize metabolic response on a range of uptake rates. Sensitivity analysis was used to assess the effect of ARC on ethanol production indicating that modifying ARC by inhibiting the respiratory chain ethanol production can be improved. It was shown experimentally in batch culture using Rotenone as an inhibitor of the mitochondrial NADH dehydrogenase complex I (CINADH), increasing ethanol yield by 18%. Furthermore, trajectories for uptakes rates, specific productivity and specific growth rate were determined by modeling the batch culture, to calculate ARC associated to the addition of CINADH inhibitor. Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC.

  7. Genome-scale metabolic network guided engineering of Streptomyces tsukubaensis for FK506 production improvement

    PubMed Central

    2013-01-01

    Background FK506 is an important immunosuppressant, which can be produced by Streptomyces tsukubaensis. However, the production capacity of the strain is very low. Hereby, a computational guided engineering approach was proposed in order to improve the intracellular precursor and cofactor availability of FK506 in S. tsukubaensis. Results First, a genome-scale metabolic model of S. tsukubaensis was constructed based on its annotated genome and biochemical information. Subsequently, several potential genetic targets (knockout or overexpression) that guaranteed an improved yield of FK506 were identified by the recently developed methodology. To validate the model predictions, each target gene was manipulated in the parent strain D852, respectively. All the engineered strains showed a higher FK506 production, compared with D852. Furthermore, the combined effect of the genetic modifications was evaluated. Results showed that the strain HT-ΔGDH-DAZ with gdhA-deletion and dahp-, accA2-, zwf2-overexpression enhanced FK506 concentration up to 398.9 mg/L, compared with 143.5 mg/L of the parent strain D852. Finally, fed-batch fermentations of HT-ΔGDH-DAZ were carried out, which led to the FK506 production of 435.9 mg/L, 1.47-fold higher than the parent strain D852 (158.7 mg/L). Conclusions Results confirmed that the promising targets led to an increase in FK506 titer. The present work is the first attempt to engineer the primary precursor pathways to improve FK506 production in S. tsukubaensis with genome-scale metabolic network guided metabolic engineering. The relationship between model prediction and experimental results demonstrates the rationality and validity of this approach for target identification. This strategy can also be applied to the improvement of other important secondary metabolites. PMID:23705993

  8. Large-scale production of UDP-galactose and globotriose by coupling metabolically engineered bacteria.

    PubMed

    Koizumi, S; Endo, T; Tabata, K; Ozaki, A

    1998-09-01

    A large-scale production system of uridine 5'-diphospho-galactose (UDP-Gal) has been established by the combination of recombinant Escherichia coli and Corynebacterium ammoniagenes. Recombinant E. coli that overexpress the UDP-Gal biosynthetic genes galT, galK, and galU were generated. C. ammoniagenes contribute the production of uridine triphosphate (UTP), a substrate for UDP-Gal biosynthesis, from orotic acid, an inexpensive precursor of UTP. UDP-Gal accumulated to 72 mM (44 g/L) after a 21 h reaction starting with orotic acid and galactose. When E. coli cells that expressed the alpha1,4-galactosyltransferase gene of Neisseria gonorrhoeae were coupled with this UDP-Gal production system, 372 mM (188 g/L) globotriose (Galalpha1-4Galbeta1-4Glc), a trisaccharide portion of verotoxin receptor, was produced after a 36 h reaction starting with orotic acid, galactose, and lactose. No oligosaccharide by-products were observed in the reaction mixture. The production of globotriose was several times higher than that of UDP-Gal. The strategy of producing sugar nucleotides by combining metabolically engineered recombinant E. coli with a nucleoside 5'-triphosphate producing microorganism, and the concept of producing oligosaccharides by coupling sugar nucleotide production systems with glycosyltransferases, can be applied to the manufacture of other sugar nucleotides and oligosaccharides.

  9. Designing intracellular metabolism for production of target compounds by introducing a heterologous metabolic reaction based on a Synechosystis sp. 6803 genome-scale model.

    PubMed

    Shirai, Tomokazu; Osanai, Takashi; Kondo, Akihiko

    2016-01-18

    Designing optimal intracellular metabolism is essential for using microorganisms to produce useful compounds. Computerized calculations for flux balance analysis utilizing a genome-scale model have been performed for such designs. Many genome-scale models have been developed for different microorganisms. However, optimal designs of intracellular metabolism aimed at producing a useful compound often utilize metabolic reactions of only the host microbial cells. In the present study, we added reactions other than the metabolic reactions with Synechosystis sp. 6803 as a host to its genome-scale model, and constructed a metabolic model of hybrid cells (SyHyMeP) using computerized analysis. Using this model provided a metabolic design that improves the theoretical yield of succinic acid, which is a useful compound. Constructing the SyHyMeP model enabled new metabolic designs for producing useful compounds. In the present study, we developed a metabolic design that allowed for improved theoretical yield in the production of succinic acid during glycogen metabolism by Synechosystis sp. 6803. The theoretical yield of succinic acid production using a genome-scale model of these cells was 1.00 mol/mol-glucose, but use of the SyHyMeP model enabled a metabolic design with which a 33 % increase in theoretical yield is expected due to the introduction of isocitrate lyase, adding activations of endogenous tree reactions via D-glycerate in Synechosystis sp. 6803. The SyHyMeP model developed in this study has provided a new metabolic design that is not restricted only to the metabolic reactions of individual microbial cells. The concept of construction of this model requires only replacement of the genome-scale model of the host microbial cells and can thus be applied to various useful microorganisms for metabolic design to produce compounds.

  10. Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production.

    PubMed

    Loira, Nicolás; Mendoza, Sebastian; Paz Cortés, María; Rojas, Natalia; Travisany, Dante; Genova, Alex Di; Gajardo, Natalia; Ehrenfeld, Nicole; Maass, Alejandro

    2017-07-04

    Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols. iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data.

  11. Replacement of a Metabolic Pathway for Large-Scale Production of Lactic Acid from Engineered Yeasts

    PubMed Central

    Porro, Danilo; Bianchi, Michele M.; Brambilla, Luca; Menghini, Rossella; Bolzani, Davide; Carrera, Vittorio; Lievense, Jefferson; Liu, Chi-Li; Ranzi, Bianca Maria; Frontali, Laura; Alberghina, Lilia

    1999-01-01

    Interest in the production of l-(+)-lactic acid is presently growing in relation to its applications in the synthesis of biodegradable polymer materials. With the aim of obtaining efficient production and high productivity, we introduced the bovine l-lactate dehydrogenase gene (LDH) into a wild-type Kluyveromyces lactis yeast strain. The observed lactic acid production was not satisfactory due to the continued coproduction of ethanol. A further restructuring of the cellular metabolism was obtained by introducing the LDH gene into a K. lactis strain in which the unique pyruvate decarboxylase gene had been deleted. With this modified strain, in which lactic fermentation substituted completely for the pathway leading to the production of ethanol, we obtained concentrations, productivities, and yields of lactic acid as high as 109 g liter−1, 0.91 g liter−1 h−1, and 1.19 mol per mole of glucose consumed, respectively. The organic acid was also produced at pH levels lower than those usual for bacterial processes. PMID:10473436

  12. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

    PubMed

    Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

    2013-07-01

    In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

  13. Toward systems-level analysis of agricultural production from crassulacean acid metabolism (CAM): scaling from cell to commercial production.

    PubMed

    Davis, Sarah C; Ming, Ray; LeBauer, David S; Long, Stephen P

    2015-10-01

    Systems-level analyses have become prominent tools for assessing the yield, viability, economic consequences and environmental impacts of agricultural production. Such analyses are well-developed for many commodity crops that are used for food and biofuel, but have not been developed for agricultural production systems based on drought-tolerant plants that use crassulacean acid metabolism (CAM). We review the components of systems-level evaluations, and identify the information available for completing such analyses for CAM cropping systems. Specific needs for developing systems-level evaluations of CAM agricultural production include: improvement of physiological models; assessment of product processing after leaving the farm gate; and application of newly available genetic tools to the optimization of CAM species for commercial production. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  14. In silico method for modelling metabolism and gene product expression at genome scale

    SciTech Connect

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  15. Scaling metabolic rate fluctuations

    PubMed Central

    Labra, Fabio A.; Marquet, Pablo A.; Bozinovic, Francisco

    2007-01-01

    Complex ecological and economic systems show fluctuations in macroscopic quantities such as exchange rates, size of companies or populations that follow non-Gaussian tent-shaped probability distributions of growth rates with power-law decay, which suggests that fluctuations in complex systems may be governed by universal mechanisms, independent of particular details and idiosyncrasies. We propose here that metabolic rate within individual organisms may be considered as an example of an emergent property of a complex system and test the hypothesis that the probability distribution of fluctuations in the metabolic rate of individuals has a “universal” form regardless of body size or taxonomic affiliation. We examined data from 71 individuals belonging to 25 vertebrate species (birds, mammals, and lizards). We report three main results. First, for all these individuals and species, the distribution of metabolic rate fluctuations follows a tent-shaped distribution with power-law decay. Second, the standard deviation of metabolic rate fluctuations decays as a power-law function of both average metabolic rate and body mass, with exponents −0.352 and −1/4 respectively. Finally, we find that the distributions of metabolic rate fluctuations for different organisms can all be rescaled to a single parent distribution, supporting the existence of general principles underlying the structure and functioning of individual organisms. PMID:17578913

  16. Metabolic scaling in turtles.

    PubMed

    Ultsch, Gordon R

    2013-04-01

    Bennett and Dawson (1976) presented an analysis of the relationship of metabolic rate (MR) and body mass among turtles, based on 10 studies, but unlike most of other groups of ectotherms, there has been no update to include the many later reports on turtles. Here I present a review of the data on turtle metabolic rates at 20, 25, and 30°C, along with regression equations and graphical analyses from a large number of studies. Two generalities emerge: (1) reported metabolic rates for sea turtles are higher than for other chelonians, although it is not certain whether this is an intrinsic characteristic of sea turtles or an artifact related to experimental conditions (such as greater activity of sea turtles in metabolic chambers and the fact that a number of studies were done with the turtles out of water), and (2) the slopes of the log-log plots of metabolic rate (MR) vs. body mass [b in the allometric equation MR=a(mass)(b)] are mostly lower than previously reported in smaller studies.

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

    SciTech Connect

    Harwood, Caroline S

    2012-12-17

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

  18. Form and metabolic scaling in colonial animals.

    PubMed

    Hartikainen, Hanna; Humphries, Stuart; Okamura, Beth

    2014-03-01

    Benthic colonial organisms exhibit a wide variation in size and shape and provide excellent model systems for testing the predictions of models that describe the scaling of metabolic rate with organism size. We tested the hypothesis that colony form will influence metabolic scaling and its derivatives by characterising metabolic and propagule production rates in three species of freshwater bryozoans that vary in morphology and module organisation and which demonstrate two- and three-dimensional growth forms. The results were evaluated with respect to predictions from two models for metabolic scaling. Isometric metabolic scaling in two-dimensional colonies supported predictions of a model based on dynamic energy budget theory (DEB) and not those of a model based on fractally branching supply networks. This metabolic isometry appears to be achieved by equivalent energy budgets of edge and central modules, in one species (Cristatella mucedo) via linear growth and in a second species (Lophopus crystallinus) by colony fission. Allometric scaling characterised colonies of a three-dimensional species (Fredericella sultana), also providing support for the DEB model. Isometric scaling of propagule production rates for C. mucedo and F. sultana suggests that the number of propagules produced in colonies increases in direct proportion with the number of modules within colonies. Feeding currents generated by bryozoans function in both food capture and respiration, thus linking metabolic scaling with dynamics of self-shading and resource capture. Metabolic rates fundamentally dictate organismal performance (e.g. growth, reproduction) and, as we show here, are linked with colony form. Metabolic profiles and associated variation in colony form should therefore influence the outcome of biotic interactions in habitats dominated by colonial animals and may drive patterns of macroevolution.

  19. Metabolic scaling in solid tumours

    PubMed Central

    Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

    2013-01-01

    Tumour metabolism is an outstanding topic of cancer research, as it determines the growth rate and the global activity of tumours. Recently, by combining the diffusion of oxygen, nutrients, and metabolites in the extracellular environment, and the internal motions that mix live and dead cells, we derived a growth law of solid tumours which is linked to parameters at the cellular level1. Here we use this growth law to obtain a metabolic scaling law for solid tumours, which is obeyed by tumours of different histotypes both in vitro and in vivo, and we display its relation with the fractal dimension of the distribution of live cells in the tumour mass. The scaling behaviour is related to measurable parameters, with potential applications in the clinical practice. PMID:23727729

  20. Metabolic scaling in solid tumours

    NASA Astrophysics Data System (ADS)

    Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

    2013-06-01

    Tumour metabolism is an outstanding topic of cancer research, as it determines the growth rate and the global activity of tumours. Recently, by combining the diffusion of oxygen, nutrients, and metabolites in the extracellular environment, and the internal motions that mix live and dead cells, we derived a growth law of solid tumours which is linked to parameters at the cellular level. Here we use this growth law to obtain a metabolic scaling law for solid tumours, which is obeyed by tumours of different histotypes both in vitro and in vivo, and we display its relation with the fractal dimension of the distribution of live cells in the tumour mass. The scaling behaviour is related to measurable parameters, with potential applications in the clinical practice.

  1. Genome-scale metabolic modeling to provide insight into the production of storage compounds during feast-famine cycles of activated sludge.

    PubMed

    Tajparast, Mohammad; Frigon, Dominic

    2013-01-01

    Studying storage metabolism during feast-famine cycles of activated sludge treatment systems provides profound insight in terms of both operational issues (e.g., foaming and bulking) and process optimization for the production of value added by-products (e.g., bioplastics). We examined the storage metabolism (including poly-β-hydroxybutyrate [PHB], glycogen, and triacylglycerols [TAGs]) during feast-famine cycles using two genome-scale metabolic models: Rhodococcus jostii RHA1 (iMT1174) and Escherichia coli K-12 (iAF1260) for growth on glucose, acetate, and succinate. The goal was to develop the proper objective function (OF) for the prediction of the main storage compound produced in activated sludge for given feast-famine cycle conditions. For the flux balance analysis, combinations of three OFs were tested. For all of them, the main OF was to maximize growth rates. Two additional sub-OFs were used: (1) minimization of biochemical fluxes, and (2) minimization of metabolic adjustments (MoMA) between the feast and famine periods. All (sub-)OFs predicted identical substrate-storage associations for the feast-famine growth of the above-mentioned metabolic models on a given substrate when glucose and acetate were set as sole carbon sources (i.e., glucose-glycogen and acetate-PHB), in agreement with experimental observations. However, in the case of succinate as substrate, the predictions depended on the network structure of the metabolic models such that the E. coli model predicted glycogen accumulation and the R. jostii model predicted PHB accumulation. While the accumulation of both PHB and glycogen was observed experimentally, PHB showed higher dynamics during an activated sludge feast-famine growth cycle with succinate as substrate. These results suggest that new modeling insights between metabolic predictions and population ecology will be necessary to properly predict metabolisms likely to emerge within the niches of activated sludge communities. Nonetheless

  2. The genome-scale metabolic network analysis of Zymomonas mobilis ZM4 explains physiological features and suggests ethanol and succinic acid production strategies

    PubMed Central

    2010-01-01

    Background Zymomonas mobilis ZM4 is a Gram-negative bacterium that can efficiently produce ethanol from various carbon substrates, including glucose, fructose, and sucrose, via the Entner-Doudoroff pathway. However, systems metabolic engineering is required to further enhance its metabolic performance for industrial application. As an important step towards this goal, the genome-scale metabolic model of Z. mobilis is required to systematically analyze in silico the metabolic characteristics of this bacterium under a wide range of genotypic and environmental conditions. Results The genome-scale metabolic model of Z. mobilis ZM4, ZmoMBEL601, was reconstructed based on its annotated genes, literature, physiological and biochemical databases. The metabolic model comprises 579 metabolites and 601 metabolic reactions (571 biochemical conversion and 30 transport reactions), built upon extensive search of existing knowledge. Physiological features of Z. mobilis were then examined using constraints-based flux analysis in detail as follows. First, the physiological changes of Z. mobilis as it shifts from anaerobic to aerobic environments (i.e. aerobic shift) were investigated. Then the intensities of flux-sum, which is the cluster of either all ingoing or outgoing fluxes through a metabolite, and the maximum in silico yields of ethanol for Z. mobilis and Escherichia coli were compared and analyzed. Furthermore, the substrate utilization range of Z. mobilis was expanded to include pentose sugar metabolism by introducing metabolic pathways to allow Z. mobilis to utilize pentose sugars. Finally, double gene knock-out simulations were performed to design a strategy for efficiently producing succinic acid as another example of application of the genome-scale metabolic model of Z. mobilis. Conclusion The genome-scale metabolic model reconstructed in this study was able to successfully represent the metabolic characteristics of Z. mobilis under various conditions as validated by

  3. Scaling the metabolic balance of the oceans

    PubMed Central

    López-Urrutia, Ángel; San Martin, Elena; Harris, Roger P.; Irigoien, Xabier

    2006-01-01

    Oceanic communities are sources or sinks of CO2, depending on the balance between primary production and community respiration. The prediction of how global climate change will modify this metabolic balance of the oceans is limited by the lack of a comprehensive underlying theory. Here, we show that the balance between production and respiration is profoundly affected by environmental temperature. We extend the general metabolic theory of ecology to the production and respiration of oceanic communities and show that ecosystem rates can be reliably scaled from theoretical knowledge of organism physiology and measurement of population abundance. Our theory predicts that the differential temperature-dependence of respiration and photosynthesis at the organism level determines the response of the metabolic balance of the epipelagic ocean to changes in ambient temperature, a prediction that we support with empirical data over the global ocean. Furthermore, our model predicts that there will be a negative feedback of ocean communities to climate warming because they will capture less CO2 with a future increase in ocean temperature. This feedback of marine biota will further aggravate the anthropogenic effects on global warming. PMID:16731624

  4. Scaling the metabolic balance of the oceans.

    PubMed

    López-Urrutia, Angel; San Martin, Elena; Harris, Roger P; Irigoien, Xabier

    2006-06-06

    Oceanic communities are sources or sinks of CO2, depending on the balance between primary production and community respiration. The prediction of how global climate change will modify this metabolic balance of the oceans is limited by the lack of a comprehensive underlying theory. Here, we show that the balance between production and respiration is profoundly affected by environmental temperature. We extend the general metabolic theory of ecology to the production and respiration of oceanic communities and show that ecosystem rates can be reliably scaled from theoretical knowledge of organism physiology and measurement of population abundance. Our theory predicts that the differential temperature-dependence of respiration and photosynthesis at the organism level determines the response of the metabolic balance of the epipelagic ocean to changes in ambient temperature, a prediction that we support with empirical data over the global ocean. Furthermore, our model predicts that there will be a negative feedback of ocean communities to climate warming because they will capture less CO2 with a future increase in ocean temperature. This feedback of marine biota will further aggravate the anthropogenic effects on global warming.

  5. Ontogenetic and interspecific metabolic scaling in insects.

    PubMed

    Maino, James L; Kearney, Michael R

    2014-12-01

    Design constraints imposed by increasing size cause metabolic rate in animals to increase more slowly than mass. This ubiquitous biological phenomenon is referred to as metabolic scaling. However, mechanistic explanations for interspecific metabolic scaling do not apply to ontogenetic size changes within a species, implying different mechanisms for scaling phenomena. Here, we show that the dynamic energy budget theory approach of compartmentalizing biomass into reserve and structural components provides a unified framework for understanding ontogenetic and interspecific metabolic scaling. We formulate the theory for insects and show that it can account for ontogenetic metabolic scaling during the embryonic and larval phases, as well as the U-shaped respiration curve during pupation. After correcting for the predicted ontogenetic scaling effects, which we show to follow universal curves, the scaling of respiration between species is approximated by a three-quarters power law, supporting past empirical studies on insect metabolic scaling and our theoretical predictions. The ability to explain ontogenetic and interspecific metabolic scaling effects under one consistent framework suggests that the partitioning of biomass into reserve and structure is a necessary foundation to a general metabolic theory.

  6. Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models.

    PubMed

    Andreozzi, Stefano; Chakrabarti, Anirikh; Soh, Keng Cher; Burgard, Anthony; Yang, Tae Hoon; Van Dien, Stephen; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2016-05-01

    Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and

  7. Applications of genome-scale metabolic reconstructions

    PubMed Central

    Oberhardt, Matthew A; Palsson, Bernhard Ø; Papin, Jason A

    2009-01-01

    The availability and utility of genome-scale metabolic reconstructions have exploded since the first genome-scale reconstruction was published a decade ago. Reconstructions have now been built for a wide variety of organisms, and have been used toward five major ends: (1) contextualization of high-throughput data, (2) guidance of metabolic engineering, (3) directing hypothesis-driven discovery, (4) interrogation of multi-species relationships, and (5) network property discovery. In this review, we examine the many uses and future directions of genome-scale metabolic reconstructions, and we highlight trends and opportunities in the field that will make the greatest impact on many fields of biology. PMID:19888215

  8. The effect of heating rate on Escherichia coli metabolism, physiological stress, transcriptional response, and production of temperature-induced recombinant protein: a scale-down study.

    PubMed

    Caspeta, Luis; Flores, Noemí; Pérez, Néstor O; Bolívar, Francisco; Ramírez, Octavio T

    2009-02-01

    At the laboratory scale, sudden step increases from 30 to 42 degrees C can be readily accomplished when expressing heterologous proteins in heat-inducible systems. However, for large scale-cultures only slow ramp-type increases in temperature are possible due to heat transfer limitations, where the heating rate decreases as the scale increases. In this work, the transcriptional and metabolic responses of a recombinant Escherichia coli strain to temperature-induced synthesis of pre-proinsulin in high cell density cultures were examined at different heating rates. Heating rates of 6, 1.7, 0.8, and 0.4 degrees C/min were tested in a scale-down approach to mimic fermentors of 0.1, 5, 20, and 100 m(3), respectively. The highest yield and concentration of recombinant protein was obtained for the slowest heating rate. As the heating rate increased, the yield and maximum recombinant protein concentration decreased, whereas a larger fraction of carbon skeletons was lost as acetate, lactate, and formate. Compared to 30 degrees C, the mRNA levels of selected heat-shock genes at 38 and 42 degrees C, as quantified by qRT-PCR, increased between 2- to over 42-fold when cultures were induced at 6, 1.7, and 0.8 degrees C/min, but no increase was observed at 0.4 degrees C/min. Only small increases (between 1.5- and 4-fold) in the expression of the stress genes spoT and relA were observed at 42 degrees C for cultures induced at 1.7 and 6 degrees C/min, suggesting that cells subjected to slow temperature increases can adapt to stress. mRNA levels of genes from the transcription-translation machinery (tufB, rpoA, and tig) decreased between 40% and 80% at 6, 1.7 and 0.8 degrees C/min, whereas a transient increase occurred for 0.4 degrees C/min at 42 degrees C. mRNA levels of the gene coding for pre-proinsulin showed a similar profile to transcripts of heat-shock genes, reflecting a probable analogous induction mechanism. Altogether, the results obtained indicate that slow heating rates

  9. Genome-scale modeling for metabolic engineering

    SciTech Connect

    Simeonidis, E; Price, ND

    2015-01-13

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  10. Genome-scale modeling for metabolic engineering

    PubMed Central

    Simeonidis, Evangelos

    2015-01-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information—an area which we expect will become increasingly important for metabolic engineering—and present recent developments in the field of metabolic and regulatory integration. PMID:25578304

  11. Genome-scale modeling for metabolic engineering.

    PubMed

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  12. Systems metabolic engineering: Genome-scale models and beyond

    PubMed Central

    Blazeck, John; Alper, Hal

    2010-01-01

    The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches – based on the data collected with high throughput technologies – to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems. PMID:20151446

  13. Systems metabolic engineering: genome-scale models and beyond.

    PubMed

    Blazeck, John; Alper, Hal

    2010-07-01

    The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.

  14. Genome scale engineering techniques for metabolic engineering.

    PubMed

    Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

    2015-11-01

    Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  15. Production of natural products through metabolic engineering of Saccharomyces cerevisiae.

    PubMed

    Krivoruchko, Anastasia; Nielsen, Jens

    2015-12-01

    Many high-value metabolites are produced in nature by organisms that are not ideal for large-scale production. Therefore, interest exists in expressing the biosynthetic pathways of these compounds in organisms that are more suitable for industrial production. Recent years have seen developments in both the discovery of various biosynthetic pathways, as well as development of metabolic engineering tools that allow reconstruction of complex pathways in microorganisms. In the present review we discuss recent advances in reconstruction of the biosynthetic pathways of various high-value products in the yeast Saccharomyces cerevisiae, a commonly used industrial microorganism. Key achievements in the production of different isoprenoids, aromatics and polyketides are presented and the metabolic engineering strategies underlying these accomplishments are discussed.

  16. Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

    PubMed Central

    2013-01-01

    Background The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H2/CO2, and more importantly on synthesis gas (H2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. Results Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. Conclusions iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels. PMID:24274140

  17. Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

    SciTech Connect

    Nagarajan, H; Sahin, M; Nogales, J; Latif, H; Lovley, DR; Ebrahim, A; Zengler, K

    2013-11-25

    Background: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H-2/CO2, and more importantly on synthesis gas (H-2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. Results: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. Conclusions: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.

  18. Genome-scale metabolic representation of Amycolatopsis balhimycina.

    PubMed

    Vongsangnak, Wanwipa; Figueiredo, Luís Filipe; Förster, Jochen; Weber, Tilmann; Thykaer, Jette; Stegmann, Evi; Wohlleben, Wolfgang; Nielsen, Jens

    2012-07-01

    Infection caused by methicillin-resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin biosynthesis in Amycolatopsis balhimycina. The balhimycin yield obtained by A. balhimycina is, however, low and there is therefore a need to improve balhimycin production. In this study, we performed genome sequencing, assembly and annotation analysis of A. balhimycina and further used these annotated data to reconstruct a genome-scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC-genome (∼ 69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR for functional annotation and then integrated annotated data with biochemical and physiological information available for this organism to reconstruct a genome-scale metabolic model of A. balhimycina. The resulting metabolic model contains 583 ORFs as protein encoding genes (7% of the predicted 8,585 ORFs), 407 EC numbers, 647 metabolites and 1,363 metabolic reactions. During the analysis of the metabolic model, linear, quadratic and evolutionary programming algorithms using flux balance analysis (FBA), minimization of metabolic adjustment (MOMA), and OptGene, respectively were applied as well as phenotypic behavior and improved balhimycin production were simulated. The A. balhimycina model shows a good agreement between in silico data and experimental data and also identifies key reactions associated with increased balhimycin production. The reconstruction of the genome-scale metabolic model of A. balhimycina serves as a basis for physiological characterization. The model allows a rational design of engineering strategies for increasing balhimycin production in A

  19. Ontogenetic scaling of metabolism, growth, and assimilation: testing metabolic scaling theory with Manduca sexta larvae.

    PubMed

    Sears, Katie E; Kerkhoff, Andrew J; Messerman, Arianne; Itagaki, Haruhiko

    2012-01-01

    Metabolism, growth, and the assimilation of energy and materials are essential processes that are intricately related and depend heavily on animal size. However, models that relate the ontogenetic scaling of energy assimilation and metabolism to growth rely on assumptions that have yet to be rigorously tested. Based on detailed daily measurements of metabolism, growth, and assimilation in tobacco hornworms, Manduca sexta, we provide a first experimental test of the core assumptions of a metabolic scaling model of ontogenetic growth. Metabolic scaling parameters changed over development, in violation of the model assumptions. At the same time, the scaling of growth rate matches that of metabolic rate, with similar scaling exponents both across and within developmental instars. Rates of assimilation were much higher than expected during the first two instars and did not match the patterns of scaling of growth and metabolism, which suggests high costs of biosynthesis early in development. The rapid increase in size and discrete instars observed in larval insect development provide an ideal system for understanding how patterns of growth and metabolism emerge from fundamental cellular processes and the exchange of materials and energy between an organism and its environment.

  20. Modeling cancer metabolism on a genome scale.

    PubMed

    Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

    2015-06-30

    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field.

  1. Modeling cancer metabolism on a genome scale

    PubMed Central

    Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

    2015-01-01

    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

  2. Quantum metabolism explains the allometric scaling of metabolic rates.

    PubMed

    Demetrius, Lloyd; Tuszynski, J A

    2010-03-06

    A general model explaining the origin of allometric laws of physiology is proposed based on coupled energy-transducing oscillator networks embedded in a physical d-dimensional space (d = 1, 2, 3). This approach integrates Mitchell's theory of chemi-osmosis with the Debye model of the thermal properties of solids. We derive a scaling rule that relates the energy generated by redox reactions in cells, the dimensionality of the physical space and the mean cycle time. Two major regimes are found corresponding to classical and quantum behaviour. The classical behaviour leads to allometric isometry while the quantum regime leads to scaling laws relating metabolic rate and body size that cover a broad range of exponents that depend on dimensionality and specific parameter values. The regimes are consistent with a range of behaviours encountered in micelles, plants and animals and provide a conceptual framework for a theory of the metabolic function of living systems.

  3. Quantum metabolism explains the allometric scaling of metabolic rates

    PubMed Central

    Demetrius, Lloyd; Tuszynski, J. A.

    2010-01-01

    A general model explaining the origin of allometric laws of physiology is proposed based on coupled energy-transducing oscillator networks embedded in a physical d-dimensional space (d = 1, 2, 3). This approach integrates Mitchell's theory of chemi-osmosis with the Debye model of the thermal properties of solids. We derive a scaling rule that relates the energy generated by redox reactions in cells, the dimensionality of the physical space and the mean cycle time. Two major regimes are found corresponding to classical and quantum behaviour. The classical behaviour leads to allometric isometry while the quantum regime leads to scaling laws relating metabolic rate and body size that cover a broad range of exponents that depend on dimensionality and specific parameter values. The regimes are consistent with a range of behaviours encountered in micelles, plants and animals and provide a conceptual framework for a theory of the metabolic function of living systems. PMID:19734187

  4. Imaging the time-integrated cerebral metabolic activity with subcellular resolution through nanometer-scale detection of biosynthetic products deriving from (13)C-glucose.

    PubMed

    Takado, Yuhei; Knott, Graham; Humbel, Bruno M; Masoodi, Mojgan; Escrig, Stéphane; Meibom, Anders; Comment, Arnaud

    2015-11-01

    Glucose is the primary source of energy for the brain but also an important source of building blocks for proteins, lipids, and nucleic acids. Little is known about the use of glucose for biosynthesis in tissues at the cellular level. We demonstrate that local cerebral metabolic activity can be mapped in mouse brain tissue by quantitatively imaging the biosynthetic products deriving from [U-(13)C]glucose metabolism using a combination of in situ electron microscopy and secondary ion mass-spectroscopy (NanoSIMS). Images of the (13)C-label incorporated into cerebral ultrastructure with ca. 100 nm resolution allowed us to determine the timescale on which the metabolic products of glucose are incorporated into different cells, their sub-compartments and organelles. These were mapped in astrocytes and neurons in the different layers of the motor cortex. We see evidence for high metabolic activity in neurons via the nucleus (13)C enrichment. We observe that in all the major cell compartments, such as e.g. nucleus and Golgi apparatus, neurons incorporate substantially higher concentrations of (13)C-label than astrocytes.

  5. Genome-scale metabolic network reconstruction.

    PubMed

    Fondi, Marco; Liò, Pietro

    2015-01-01

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

  6. 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

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

    PubMed Central

    2011-01-01

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

  8. Next-generation genome-scale models for metabolic engineering.

    PubMed

    King, Zachary A; Lloyd, Colton J; Feist, Adam M; Palsson, Bernhard O

    2015-12-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Synthetic metabolism: engineering biology at the protein and pathway scales.

    PubMed

    Martin, Collin H; Nielsen, David R; Solomon, Kevin V; Prather, Kristala L Jones

    2009-03-27

    Biocatalysis has become a powerful tool for the synthesis of high-value compounds, particularly so in the case of highly functionalized and/or stereoactive products. Nature has supplied thousands of enzymes and assembled them into numerous metabolic pathways. Although these native pathways can be use to produce natural bioproducts, there are many valuable and useful compounds that have no known natural biochemical route. Consequently, there is a need for both unnatural metabolic pathways and novel enzymatic activities upon which these pathways can be built. Here, we review the theoretical and experimental strategies for engineering synthetic metabolic pathways at the protein and pathway scales, and highlight the challenges that this subfield of synthetic biology currently faces.

  10. Improved succinate production by metabolic engineering.

    PubMed

    Cheng, Ke-Ke; Wang, Gen-Yu; Zeng, Jing; Zhang, Jian-An

    2013-01-01

    Succinate is a promising chemical which has wide applications and can be produced by biological route. The history of the biosuccinate production shows that the joint effort of different metabolic engineering approaches brings successful results. In order to enhance the succinate production, multiple metabolical strategies have been sought. In this review, different overproducers for succinate production, including natural succinate overproducers and metabolic engineered overproducers, are examined and the metabolic engineering strategies and performances are discussed. Modification of the mechanism of substrate transportation, knocking-out genes responsible for by-products accumulation, overexpression of the genes directly involved in the pathway, and improvement of internal NADH and ATP formation are some of the strategies applied. Combination of the appropriate genes from homologous and heterologous hosts, extension of substrate, integrated production of succinate, and other high-value-added products are expected to bring a desired objective of producing succinate from renewable resources economically and efficiently.

  11. Improved Succinate Production by Metabolic Engineering

    PubMed Central

    Cheng, Ke-Ke; Wang, Gen-Yu; Zeng, Jing; Zhang, Jian-An

    2013-01-01

    Succinate is a promising chemical which has wide applications and can be produced by biological route. The history of the biosuccinate production shows that the joint effort of different metabolic engineering approaches brings successful results. In order to enhance the succinate production, multiple metabolical strategies have been sought. In this review, different overproducers for succinate production, including natural succinate overproducers and metabolic engineered overproducers, are examined and the metabolic engineering strategies and performances are discussed. Modification of the mechanism of substrate transportation, knocking-out genes responsible for by-products accumulation, overexpression of the genes directly involved in the pathway, and improvement of internal NADH and ATP formation are some of the strategies applied. Combination of the appropriate genes from homologous and heterologous hosts, extension of substrate, integrated production of succinate, and other high-value-added products are expected to bring a desired objective of producing succinate from renewable resources economically and efficiently. PMID:23691505

  12. Metabolic engineering of biosynthetic pathway for production of renewable biofuels.

    PubMed

    Singh, Vijai; Mani, Indra; Chaudhary, Dharmendra Kumar; Dhar, Pawan Kumar

    2014-02-01

    Metabolic engineering is an important area of research that involves editing genetic networks to overproduce a certain substance by the cells. Using a combination of genetic, metabolic, and modeling methods, useful substances have been synthesized in the past at industrial scale and in a cost-effective manner. Currently, metabolic engineering is being used to produce sufficient, economical, and eco-friendly biofuels. In the recent past, a number of efforts have been made towards engineering biosynthetic pathways for large scale and efficient production of biofuels from biomass. Given the adoption of metabolic engineering approaches by the biofuel industry, this paper reviews various approaches towards the production and enhancement of renewable biofuels such as ethanol, butanol, isopropanol, hydrogen, and biodiesel. We have also identified specific areas where more work needs to be done in the future.

  13. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    PubMed

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  14. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction

    PubMed Central

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source. PMID:26640947

  15. Rewriting yeast central carbon metabolism for industrial isoprenoid production.

    PubMed

    Meadows, Adam L; Hawkins, Kristy M; Tsegaye, Yoseph; Antipov, Eugene; Kim, Youngnyun; Raetz, Lauren; Dahl, Robert H; Tai, Anna; Mahatdejkul-Meadows, Tina; Xu, Lan; Zhao, Lishan; Dasika, Madhukar S; Murarka, Abhishek; Lenihan, Jacob; Eng, Diana; Leng, Joshua S; Liu, Chi-Li; Wenger, Jared W; Jiang, Hanxiao; Chao, Lily; Westfall, Patrick; Lai, Jefferson; Ganesan, Savita; Jackson, Peter; Mans, Robert; Platt, Darren; Reeves, Christopher D; Saija, Poonam R; Wichmann, Gale; Holmes, Victor F; Benjamin, Kirsten; Hill, Paul W; Gardner, Timothy S; Tsong, Annie E

    2016-09-29

    A bio-based economy has the potential to provide sustainable substitutes for petroleum-based products and new chemical building blocks for advanced materials. We previously engineered Saccharomyces cerevisiae for industrial production of the isoprenoid artemisinic acid for use in antimalarial treatments. Adapting these strains for biosynthesis of other isoprenoids such as β-farnesene (C15H24), a plant sesquiterpene with versatile industrial applications, is straightforward. However, S. cerevisiae uses a chemically inefficient pathway for isoprenoid biosynthesis, resulting in yield and productivity limitations incompatible with commodity-scale production. Here we use four non-native metabolic reactions to rewire central carbon metabolism in S. cerevisiae, enabling biosynthesis of cytosolic acetyl coenzyme A (acetyl-CoA, the two-carbon isoprenoid precursor) with a reduced ATP requirement, reduced loss of carbon to CO2-emitting reactions, and improved pathway redox balance. We show that strains with rewired central metabolism can devote an identical quantity of sugar to farnesene production as control strains, yet produce 25% more farnesene with that sugar while requiring 75% less oxygen. These changes lower feedstock costs and dramatically increase productivity in industrial fermentations which are by necessity oxygen-constrained. Despite altering key regulatory nodes, engineered strains grow robustly under taxing industrial conditions, maintaining stable yield for two weeks in broth that reaches >15% farnesene by volume. This illustrates that rewiring yeast central metabolism is a viable strategy for cost-effective, large-scale production of acetyl-CoA-derived molecules.

  16. Metabolic engineering of yeast for production of fuels and chemicals.

    PubMed

    Nielsen, Jens; Larsson, Christer; van Maris, Antonius; Pronk, Jack

    2013-06-01

    Microbial production of fuels and chemicals from renewable carbohydrate feedstocks offers sustainable and economically attractive alternatives to their petroleum-based production. The yeast Saccharomyces cerevisiae offers many advantages as a platform cell factory for such applications. Already applied on a huge scale for bioethanol production, this yeast is easy to genetically engineer, its physiology, metabolism and genetics have been intensively studied and its robustness enables it to handle harsh industrial conditions. Introduction of novel pathways and optimization of its native cellular processes by metabolic engineering are rapidly expanding its range of cell-factory applications. Here we review recent scientific progress in metabolic engineering of S. cerevisiae for the production of bioethanol, advanced biofuels, and chemicals. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Applications of genome-scale metabolic network model in metabolic engineering.

    PubMed

    Kim, Byoungjin; Kim, Won Jun; Kim, Dong In; Lee, Sang Yup

    2015-03-01

    Genome-scale metabolic network model (GEM) is a fundamental framework in systems metabolic engineering. GEM is built upon extensive experimental data and literature information on gene annotation and function, metabolites and enzymes so that it contains all known metabolic reactions within an organism. Constraint-based analysis of GEM enables the identification of phenotypic properties of an organism and hypothesis-driven engineering of cellular functions to achieve objectives. Along with the advances in omics, high-throughput technology and computational algorithms, the scope and applications of GEM have substantially expanded. In particular, various computational algorithms have been developed to predict beneficial gene deletion and amplification targets and used to guide the strain development process for the efficient production of industrially important chemicals. Furthermore, an Escherichia coli GEM was integrated with a pathway prediction algorithm and used to evaluate all possible routes for the production of a list of commodity chemicals in E. coli. Combined with the wealth of experimental data produced by high-throughput techniques, much effort has been exerted to add more biological contexts into GEM through the integration of omics data and regulatory network information for the mechanistic understanding and improved prediction capabilities. In this paper, we review the recent developments and applications of GEM focusing on the GEM-based computational algorithms available for microbial metabolic engineering.

  18. Central metabolic nodes for diverse biochemical production.

    PubMed

    Cordova, Lauren T; Alper, Hal S

    2016-12-01

    Central carbon metabolism is conserved among all organisms for cellular function and energy generation. The connectivity of this metabolic map gives rises to key metabolite nodes. Five of these nodes in particular, pyruvate, citric acid, tyrosine and aspartate, acetyl-CoA, serve as critical starting points for the generation of a broad class of relevant chemical molecules with ranging applications from fuels, pharmaceuticals and polymer precursors. This review highlights recent progress in converting these metabolite nodes into valuable products. In particular, acetyl-CoA, the most well-connected node, serves as the building block for several classes of molecules including fatty acids and terpenes. Systematic metabolic engineering efforts focused on these metabolic building blocks has enabled the production of industrially-relevant, biobased compounds.

  19. Hypothalamic Leucine Metabolism Regulates Liver Glucose Production

    PubMed Central

    Su, Ya; Lam, Tony K.T.; He, Wu; Pocai, Alessandro; Bryan, Joseph; Aguilar-Bryan, Lydia; Gutiérrez-Juárez, Roger

    2012-01-01

    Amino acids profoundly affect insulin action and glucose metabolism in mammals. Here, we investigated the role of the mediobasal hypothalamus (MBH), a key center involved in nutrient-dependent metabolic regulation. Specifically, we tested the novel hypothesis that the metabolism of leucine within the MBH couples the central sensing of leucine with the control of glucose production by the liver. We performed either central (MBH) or systemic infusions of leucine in Sprague-Dawley male rats during basal pancreatic insulin clamps in combination with various pharmacological and molecular interventions designed to modulate leucine metabolism in the MBH. We also examined the role of hypothalamic ATP-sensitive K+ channels (KATP channels) in the effects of leucine. Enhancing the metabolism of leucine acutely in the MBH lowered blood glucose through a biochemical network that was insensitive to rapamycin but strictly dependent on the hypothalamic metabolism of leucine to α-ketoisocaproic acid and, further, insensitive to acetyl- and malonyl-CoA. Functional KATP channels were also required. Importantly, molecular attenuation of this central sensing mechanism in rats conferred susceptibility to developing hyperglycemia. We postulate that the metabolic sensing of leucine in the MBH is a previously unrecognized mechanism for the regulation of hepatic glucose production required to maintain glucose homeostasis. PMID:22187376

  20. Cyanobacterial metabolic engineering for biofuel and chemical production.

    PubMed

    Oliver, Neal J; Rabinovitch-Deere, Christine A; Carroll, Austin L; Nozzi, Nicole E; Case, Anna E; Atsumi, Shota

    2016-12-01

    Rising levels of atmospheric CO2 are contributing to the global greenhouse effect. Large scale use of atmospheric CO2 may be a sustainable and renewable means of chemical and liquid fuel production to mitigate global climate change. Photosynthetic organisms are an ideal platform for efficient, natural CO2 conversion to a broad range of chemicals. Cyanobacteria are especially attractive for these purposes, due to their genetic malleability and relatively fast growth rate. Recent years have yielded a range of work in the metabolic engineering of cyanobacteria and have led to greater knowledge of the host metabolism. Understanding of endogenous and heterologous carbon regulation mechanisms leads to the expansion of productive capacity and chemical variety. This review discusses the recent progress in metabolic engineering of cyanobacteria for biofuel and bulk chemical production since 2014.

  1. Randomizing Genome-Scale Metabolic Networks

    PubMed Central

    Samal, Areejit; Martin, Olivier C.

    2011-01-01

    Networks coming from protein-protein interactions, transcriptional regulation, signaling, or metabolism may appear to have “unusual” properties. To quantify this, it is appropriate to randomize the network and test the hypothesis that the network is not statistically different from expected in a motivated ensemble. However, when dealing with metabolic networks, the randomization of the network using edge exchange generates fictitious reactions that are biochemically meaningless. Here we provide several natural ensembles of randomized metabolic networks. A first constraint is to use valid biochemical reactions. Further constraints correspond to imposing appropriate functional constraints. We explain how to perform these randomizations with the help of Markov Chain Monte Carlo (MCMC) and show that they allow one to approach the properties of biological metabolic networks. The implication of the present work is that the observed global structural properties of real metabolic networks are likely to be the consequence of simple biochemical and functional constraints. PMID:21779409

  2. Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

    PubMed Central

    Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

  3. Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism.

    PubMed

    Saha, Rajib; Suthers, Patrick F; Maranas, Costas D

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species.

  4. Genome-scale analysis of the metabolic networks of oleaginous Zygomycete fungi.

    PubMed

    Vongsangnak, Wanwipa; Ruenwai, Rawisara; Tang, Xin; Hu, Xinjie; Zhang, Hao; Shen, Bairong; Song, Yuanda; Laoteng, Kobkul

    2013-05-25

    Microbial lipids are becoming an attractive option for the industrial production of foods and oleochemicals. To investigate the lipid physiology of the oleaginous microorganisms, at the system level, genome-scale metabolic networks of Mortierella alpina and Mucor circinelloides were constructed using bioinformatics and systems biology. As scaffolds for integrated data analysis focusing on lipid production, consensus metabolic routes governing fatty acid synthesis, and lipid storage and mobilisation were identified by comparative analysis of developed metabolic networks. Unique metabolic features were identified in individual fungi, particularly in NADPH metabolism and sterol biosynthesis, which might be related to differences in fungal lipid phenotypes. The frameworks detailing the metabolic relationship between M. alpina and M. circinelloides generated in this study is useful for further elucidation of the microbial oleaginicity, which might lead to the production improvement of microbial oils as alternative feedstocks for oleochemical industry.

  5. Metabolic scaling in animals: methods, empirical results, and theoretical explanations.

    PubMed

    White, Craig R; Kearney, Michael R

    2014-01-01

    Life on earth spans a size range of around 21 orders of magnitude across species and can span a range of more than 6 orders of magnitude within species of animal. The effect of size on physiology is, therefore, enormous and is typically expressed by how physiological phenomena scale with mass(b). When b ≠ 1 a trait does not vary in direct proportion to mass and is said to scale allometrically. The study of allometric scaling goes back to at least the time of Galileo Galilei, and published scaling relationships are now available for hundreds of traits. Here, the methods of scaling analysis are reviewed, using examples for a range of traits with an emphasis on those related to metabolism in animals. Where necessary, new relationships have been generated from published data using modern phylogenetically informed techniques. During recent decades one of the most controversial scaling relationships has been that between metabolic rate and body mass and a number of explanations have been proposed for the scaling of this trait. Examples of these mechanistic explanations for metabolic scaling are reviewed, and suggestions made for comparing between them. Finally, the conceptual links between metabolic scaling and ecological patterns are examined, emphasizing the distinction between (1) the hypothesis that size- and temperature-dependent variation among species and individuals in metabolic rate influences ecological processes at levels of organization from individuals to the biosphere and (2) mechanistic explanations for metabolic rate that may explain the size- and temperature-dependence of this trait.

  6. Yeast metabolic chassis designs for diverse biotechnological products

    PubMed Central

    Jouhten, Paula; Boruta, Tomasz; Andrejev, Sergej; Pereira, Filipa; Rocha, Isabel; Patil, Kiran Raosaheb

    2016-01-01

    The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae – a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains. PMID:27430744

  7. Yeast metabolic chassis designs for diverse biotechnological products.

    PubMed

    Jouhten, Paula; Boruta, Tomasz; Andrejev, Sergej; Pereira, Filipa; Rocha, Isabel; Patil, Kiran Raosaheb

    2016-07-19

    The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae - a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains.

  8. Metabolic heat production by human and animal populations in cities

    NASA Astrophysics Data System (ADS)

    Stewart, Iain D.; Kennedy, Chris A.

    2016-12-01

    Anthropogenic heating from building energy use, vehicle fuel consumption, and human metabolism is a key term in the urban energy budget equation. Heating from human metabolism, however, is often excluded from urban energy budgets because it is widely observed to be negligible. Few reports for low-latitude cities are available to support this observation, and no reports exist on the contribution of domestic animals to urban heat budgets. To provide a more comprehensive view of metabolic heating in cities, we quantified all terms of the anthropogenic heat budget at metropolitan scale for the world's 26 largest cities, using a top-down statistical approach. Results show that metabolic heat release from human populations in mid-latitude cities (e.g. London, Tokyo, New York) accounts for 4-8% of annual anthropogenic heating, compared to 10-45% in high-density tropical cities (e.g. Cairo, Dhaka, Kolkata). Heat release from animal populations amounts to <1% of anthropogenic heating in all cities. Heat flux density from human and animal metabolism combined is highest in Mumbai—the world's most densely populated megacity—at 6.5 W m-2, surpassing heat production by electricity use in buildings (5.8 W m-2) and fuel combustion in vehicles (3.9 W m-2). These findings, along with recent output from global climate models, suggest that in the world's largest and most crowded cities, heat emissions from human metabolism alone can force measurable change in mean annual temperature at regional scale.

  9. Metabolic heat production by human and animal populations in cities

    NASA Astrophysics Data System (ADS)

    Stewart, Iain D.; Kennedy, Chris A.

    2017-07-01

    Anthropogenic heating from building energy use, vehicle fuel consumption, and human metabolism is a key term in the urban energy budget equation. Heating from human metabolism, however, is often excluded from urban energy budgets because it is widely observed to be negligible. Few reports for low-latitude cities are available to support this observation, and no reports exist on the contribution of domestic animals to urban heat budgets. To provide a more comprehensive view of metabolic heating in cities, we quantified all terms of the anthropogenic heat budget at metropolitan scale for the world's 26 largest cities, using a top-down statistical approach. Results show that metabolic heat release from human populations in mid-latitude cities (e.g. London, Tokyo, New York) accounts for 4-8% of annual anthropogenic heating, compared to 10-45% in high-density tropical cities (e.g. Cairo, Dhaka, Kolkata). Heat release from animal populations amounts to <1% of anthropogenic heating in all cities. Heat flux density from human and animal metabolism combined is highest in Mumbai—the world's most densely populated megacity—at 6.5 W m-2, surpassing heat production by electricity use in buildings (5.8 W m-2) and fuel combustion in vehicles (3.9 W m-2). These findings, along with recent output from global climate models, suggest that in the world's largest and most crowded cities, heat emissions from human metabolism alone can force measurable change in mean annual temperature at regional scale.

  10. Redirection of metabolism for hydrogen production

    SciTech Connect

    Harwood, Caroline S.

    2011-11-28

    This project is to develop and apply techniques in metabolic engineering to improve the biocatalytic potential of the bacterium Rhodopseudomonas palustris for nitrogenase-catalyzed hydrogen gas production. R. palustris, is an ideal platform to develop as a biocatalyst for hydrogen gas production because it is an extremely versatile microbe that produces copious amounts of hydrogen by drawing on abundant natural resources of sunlight and biomass. Anoxygenic photosynthetic bacteria, such as R. palustris, generate hydrogen and ammonia during a process known as biological nitrogen fixation. This reaction is catalyzed by the enzyme nitrogenase and normally consumes nitrogen gas, ATP and electrons. The applied use of nitrogenase for hydrogen production is attractive because hydrogen is an obligatory product of this enzyme and is formed as the only product when nitrogen gas is not supplied. Our challenge is to understand the systems biology of R. palustris sufficiently well to be able to engineer cells to produce hydrogen continuously, as fast as possible and with as high a conversion efficiency as possible of light and electron donating substrates. For many experiments we started with a strain of R. palustris that produces hydrogen constitutively under all growth conditions. We then identified metabolic pathways and enzymes important for removal of electrons from electron-donating organic compounds and for their delivery to nitrogenase in whole R. palustris cells. For this we developed and applied improved techniques in 13C metabolic flux analysis. We identified reactions that are important for generating electrons for nitrogenase and that are yield-limiting for hydrogen production. We then increased hydrogen production by blocking alternative electron-utilizing metabolic pathways by mutagenesis. In addition we found that use of non-growing cells as biocatalysts for hydrogen gas production is an attractive option, because cells divert all resources away from growth and

  11. Northern Florida reef tract benthic metabolism scaled by remote sensing

    USGS Publications Warehouse

    Brock, J.C.; Yates, K.K.; Halley, R.B.; Kuffner, I.B.; Wright, C.W.; Hatcher, B.G.

    2006-01-01

    Holistic rates of excess organic carbon production (E) and calcification for a 0.5 km2 segment of the backreef platform of the northern Florida reef tract (NFRT) were estimated by combining biotope mapping using remote sensing with community metabolic rates determined with a benthic incubation system. The use of ASTER multispectral satellite imaging for the spatial scaling of benthic metabolic processes resulted in errors in E and net calcification (G) of 48 and 431% respectively, relative to estimates obtained using AISA hyperspectral airborne scanning. At 19 and 125%, the E and G errors relative to the AISA-based estimates were less pronounced for an analysis that used IKONOS multispectral satellite imagery to spatially extrapolate the chamber process measurements. Our scaling analysis indicates that the holistic calcification rate of the backreef platform of the northern Florida reef tract is negligible at 0.07 g CaCO3 m-2 d-1. All of the mapped biotopes in this reef zone are net heterotrophic, resulting in an estimated holistic excess production rate of -0.56 g C m-2 d-1, and an overall gross primary production to respiration ratio of 0.85. Based on our finding of ubiquitous heterotrophy, we infer that the backreef platform of the NFRT is a sink for external inputs of suspended particulate organic matter. Further, our results suggest that the inward advection of inorganic nutrients is not a dominant forcing mechanism for benthic biogeochemical function in the NFRT. We suggest that the degradation of the northern Florida reef tract may parallel the community phase shifts documented within other reef systems polluted by organic detritus.

  12. Metabolic engineering for higher alcohol production.

    PubMed

    Nozzi, Nicole E; Desai, Shuchi H; Case, Anna E; Atsumi, Shota

    2014-09-01

    Engineering microbial hosts for the production of higher alcohols looks to combine the benefits of renewable biological production with the useful chemical properties of larger alcohols. In this review we outline the array of metabolic engineering strategies employed for the efficient diversion of carbon flux from native biosynthetic pathways to the overproduction of a target alcohol. Strategies for pathway design from amino acid biosynthesis through 2-keto acids, from isoprenoid biosynthesis through pyrophosphate intermediates, from fatty acid biosynthesis and degradation by tailoring chain length specificity, and the use and expansion of natural solvent production pathways will be covered.

  13. Metabolic Engineering for the Production of Natural Products

    PubMed Central

    Pickens, Lauren B.; Tang, Yi; Chooi, Yit-Heng

    2014-01-01

    Natural products and natural product derived compounds play an important role in modern healthcare as frontline treatments for many diseases and as inspiration for chemically synthesized therapeutics. With advances in sequencing and recombinant DNA technology, many of the biosynthetic pathways responsible for the production of these chemically complex and pharmaceutically valuable compounds have been elucidated. With an ever expanding toolkit of biosynthetic components, metabolic engineering is an increasingly powerful method to improve natural product titers and generate novel compounds. Heterologous production platforms have enabled access to pathways from difficult to culture strains; systems biology and metabolic modeling tools have resulted in increasing predictive and analytic capabilities; advances in expression systems and regulation have enabled the fine-tuning of pathways for increased efficiency, and characterization of individual pathway components has facilitated the construction of hybrid pathways for the production of new compounds. These advances in the many aspects of metabolic engineering have not only yielded fascinating scientific discoveries but also make it an increasingly viable approach for the optimization of natural product biosynthesis. PMID:22432617

  14. Multi-scale modeling for sustainable chemical production.

    PubMed

    Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

    2013-09-01

    With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production.

  15. Dairy product consumption and the metabolic syndrome.

    PubMed

    van Meijl, Leonie E C; Vrolix, Ruth; Mensink, Ronald P

    2008-12-01

    The metabolic syndrome is an important risk factor for type 2 diabetes mellitus and CVD. Epidemiological studies have now suggested protective effects of dairy product consumption on the development of this syndrome. Here we review the physiological effects and possible mechanisms involved of three main dairy constituents (Ca, protein, fat) on important components of the metabolic syndrome. Ca supplements improve the serum lipoprotein profile, particularly by decreasing serum total and LDL-cholesterol concentrations. They also lower systolic and diastolic blood pressure. Insufficient evidence exists for a significant role of Ca supplements or dairy in body-weight management. Effects of Ca may be related to intestinal binding to fatty acids or bile acids, or to changes in intracellular Ca metabolism by suppressing calciotropic hormones. Dietary proteins may increase satiety in both the short and longer term, which may result in a reduced energy intake. They have also been reported to improve the serum lipoprotein profile as compared with carbohydrates. Dairy proteins are precursors of angiotensin-I-converting enzyme-inhibitory peptides, which may lower blood pressure. Such effects, however, have inconsistently been reported in human studies. Finally, conjugated linoleic acid, which effectively lowers body weight in animals, has no such effect in humans in the quantities provided by dairy products. To reduce the intake of SFA, the consumption of low-fat instead of high-fat dairy products is recommended. In conclusion, more research is warranted to better understand the physiological effects and the mechanisms involved of dairy products in the prevention and treatment of the metabolic syndrome.

  16. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

    PubMed Central

    2012-01-01

    Background Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. Results A new method called “flux balance analysis with flux ratios (FBrAtio)” was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. Conclusions FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum. PMID:22583864

  17. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    PubMed

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed Central

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

    2009-01-01

    Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities. PMID:19067749

  19. Metabolic engineering of Corynebacterium glutamicum for L-arginine production.

    PubMed

    Park, Seok Hyun; Kim, Hyun Uk; Kim, Tae Yong; Park, Jun Seok; Kim, Suok-Su; Lee, Sang Yup

    2014-08-05

    L-arginine is an important amino acid for diverse industrial and health product applications. Here we report the development of metabolically engineered Corynebacterium glutamicum ATCC 21831 for the production of L-arginine. Random mutagenesis is first performed to increase the tolerance of C. glutamicum to L-arginine analogues, followed by systems metabolic engineering for further strain improvement, involving removal of regulatory repressors of arginine operon, optimization of NADPH level, disruption of L-glutamate exporter to increase L-arginine precursor and flux optimization of rate-limiting L-arginine biosynthetic reactions. Fed-batch fermentation of the final strain in 5 l and large-scale 1,500 l bioreactors allows production of 92.5 and 81.2 g l(-1) of L-arginine with the yields of 0.40 and 0.35 g L-arginine per gram carbon source (glucose plus sucrose), respectively. The systems metabolic engineering strategy described here will be useful for engineering Corynebacteria strains for the industrial production of L-arginine and related products.

  20. Scaling the respiratory metabolism to phosphorus relationship in plant seedlings

    PubMed Central

    Wang, Zhi-Qiang; Huang, Heng; Deng, Jian-Ming; Liu, Jian-Quan

    2015-01-01

    There are empirical indications of an isometric scaling relationship between plants’ respiratory metabolism rates and nitrogen contents. To test the hypothesis that there may be a similar relationship between plants’ respiratory metabolism and phosphorus contents we used data obtained from 150 laboratory and field-grown seedlings representing 30 herbaceous species and 20 woody deciduous species. Our results show that whole-plant respiration rates strongly scaled to the 0.81-power of the whole-plant phosphorus content, across wide ranges of growth conditions and functional classifications. Moreover, we also found a similar scaling exponent between whole-plant respiration rates and total nitrogen contents for the same set of samples. The similarities of the metabolic scaling relationships suggest that similar mechanisms may be involved in the transport and storage of phosphorus and nitrogen in plants. PMID:26560344

  1. Universal scaling of respiratory metabolism, size and nitrogen in plants.

    PubMed

    Reich, Peter B; Tjoelker, Mark G; Machado, Jose-Luis; Oleksyn, Jacek

    2006-01-26

    The scaling of respiratory metabolism to body size in animals is considered to be a fundamental law of nature, and there is substantial evidence for an approximate (3/4)-power relation. Studies suggest that plant respiratory metabolism also scales as the (3/4)-power of mass, and that higher plant and animal scaling follow similar rules owing to the predominance of fractal-like transport networks and associated allometric scaling. Here, however, using data obtained from about 500 laboratory and field-grown plants from 43 species and four experiments, we show that whole-plant respiration rate scales approximately isometrically (scaling exponent approximately 1) with total plant mass in individual experiments and has no common relation across all data. Moreover, consistent with theories about biochemically based physiological scaling, isometric scaling of whole-plant respiration rate to total nitrogen content is observed within and across all data sets, with a single relation common to all data. This isometric scaling is unaffected by growth conditions including variation in light, nitrogen availability, temperature and atmospheric CO2 concentration, and is similar within or among species or functional groups. These findings suggest that plants and animals follow different metabolic scaling relations, driven by distinct mechanisms.

  2. Activity affects intraspecific body-size scaling of metabolic rate in ectothermic animals.

    PubMed

    Glazier, Douglas Stewart

    2009-10-01

    Metabolic rate is commonly thought to scale with body mass (M) to the 3/4 power. However, the metabolic scaling exponent (b) may vary with activity state, as has been shown chiefly for interspecific relationships. Here I use a meta-analysis of literature data to test whether b changes with activity level within species of ectothermic animals. Data for 19 species show that b is usually higher during active exercise (mean +/- 95% confidence limits = 0.918 +/- 0.038) than during rest (0.768 +/- 0.069). This significant upward shift in b to near 1 is consistent with the metabolic level boundaries hypothesis, which predicts that maximal metabolic rate during exercise should be chiefly influenced by volume-related muscular power production (scaling as M (1)). This dependence of b on activity level does not appear to be a simple temperature effect because body temperature in ectotherms changes very little during exercise.

  3. 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

  4. Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network.

    PubMed

    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.

  5. Yeast metabolic engineering for hemicellulosic ethanol production.

    PubMed

    Van Vleet, J H; Jeffries, T W

    2009-06-01

    Efficient fermentation of hemicellulosic sugars is critical for the bioconversion of lignocellulosics to ethanol. Efficient sugar uptake through the heterologous expression of yeast and fungal xylose/glucose transporters can improve fermentation if other metabolic steps are not rate limiting. Rectification of cofactor imbalances through heterologous expression of fungal xylose isomerase or modification of cofactor requirements in the yeast oxidoreductase pathway can reduce xylitol production while increasing ethanol yields, but these changes often occur at the expense of xylose utilization rates. Genetic engineering and evolutionary adaptation to increase glycolytic flux coupled with transcriptomic and proteomic studies have identified targets for further modification, as have genomic and metabolic engineering studies in native xylose fermenting yeasts.

  6. A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica

    PubMed Central

    2012-01-01

    Background Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism. Results Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inserted specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions. Conclusions Y. lipolytica iNL895 represents the first well-annotated metabolic model of an oleaginous yeast, providing a base for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts. PMID:22558935

  7. Genome-scale metabolic network of Cordyceps militaris useful for comparative analysis of entomopathogenic fungi.

    PubMed

    Vongsangnak, Wanwipa; Raethong, Nachon; Mujchariyakul, Warasinee; Nguyen, Nam Ninh; Leong, Hon Wai; Laoteng, Kobkul

    2017-08-30

    The first genome-scale metabolic network of Cordyceps militaris (iWV1170) was constructed representing its whole metabolisms, which consisted of 894 metabolites and 1,267 metabolic reactions across five compartments, including the plasma membrane, cytoplasm, mitochondria, peroxisome and extracellular space. The iWV1170 could be exploited to explain its phenotypes of growth ability, cordycepin and other metabolites production on various substrates. A high number of genes encoding extracellular enzymes for degradation of complex carbohydrates, lipids and proteins were existed in C. militaris genome. By comparative genome-scale analysis, the adenine metabolic pathway towards putative cordycepin biosynthesis was reconstructed, indicating their evolutionary relationships across eleven species of entomopathogenic fungi. The overall metabolic routes involved in the putative cordycepin biosynthesis were also identified in C. militaris, including central carbon metabolism, amino acid metabolism (glycine, l-glutamine and l-aspartate) and nucleotide metabolism (adenosine and adenine). Interestingly, a lack of the sequence coding for ribonucleotide reductase inhibitor was observed in C. militaris that might contribute to its over-production of cordycepin. Copyright © 2017. Published by Elsevier B.V.

  8. Metabolic heat production by human and animal populations in cities.

    PubMed

    Stewart, Iain D; Kennedy, Chris A

    2016-12-26

    Anthropogenic heating from building energy use, vehicle fuel consumption, and human metabolism is a key term in the urban energy budget equation. Heating from human metabolism, however, is often excluded from urban energy budgets because it is widely observed to be negligible. Few reports for low-latitude cities are available to support this observation, and no reports exist on the contribution of domestic animals to urban heat budgets. To provide a more comprehensive view of metabolic heating in cities, we quantified all terms of the anthropogenic heat budget at metropolitan scale for the world's 26 largest cities, using a top-down statistical approach. Results show that metabolic heat release from human populations in mid-latitude cities (e.g. London, Tokyo, New York) accounts for 4-8% of annual anthropogenic heating, compared to 10-45% in high-density tropical cities (e.g. Cairo, Dhaka, Kolkata). Heat release from animal populations amounts to <1% of anthropogenic heating in all cities. Heat flux density from human and animal metabolism combined is highest in Mumbai-the world's most densely populated megacity-at 6.5 W m(-2), surpassing heat production by electricity use in buildings (5.8 W m(-2)) and fuel combustion in vehicles (3.9 W m(-2)). These findings, along with recent output from global climate models, suggest that in the world's largest and most crowded cities, heat emissions from human metabolism alone can force measurable change in mean annual temperature at regional scale.

  9. Metabolic heat production and evaporation of poultry.

    PubMed

    Nascimento, Sheila T; Maia, Alex S C; Gebremedhin, Kifle G; Nascimento, Carolina C N

    2017-05-03

    Accurate measurements of gas exchange between an animal and its environment is critical in determining metabolic heat production and respiratory functions of broilers. Information on non-invasive methods to measure gas exchange of broiler chicks and chickens under uncontrolled environmental conditions is lacking in the literature. The aims of this study were: (1) to develop an indirect calorimetric system including a hood that allows gas exchange for chickens, (2) to measure gas exchange and respiratory functions (respiration rate, ventilation rate, and tidal volume) of broiler chickens weighing greater than 250 g, and (3) to calculate heat production and respiratory evaporation of the birds based on measured gas and vapor exchanges. We conducted two trials. The first trial involved 6 broiler chicks evaluated for 6 days in 6 different schedules (6 × 6 Latin square). The chicks were kept inside a heat exchanger with a continuous air flow of 150 mL min-1. The second trial involved 12 birds evaluated for 12 days in 12 different schedules (12 × 12 Latin square). Metabolic heat production and evaporation were influenced by live weight of chicks, varying between evaluation days (P < 0.05). The respiratory functions (tidal volume, ventilation rate, and respiratory rate) varied between days, and were strongly influenced by live weight of the broilers (P < 0.05). © 2017 Poultry Science Association Inc.

  10. Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels.

    PubMed

    Juneja, Ankita; Chaplen, Frank W R; Murthy, Ganti S

    2016-08-01

    A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. This reconstructed metabolic network will serve an important role in systems biology for further exploration of metabolism for specific target metabolites and enable improved characteristics in the strain through metabolic engineering.

  11. Large-scale profiling of metabolic dysregulation in ovarian cancer.

    PubMed

    Ke, Chaofu; Hou, Yan; Zhang, Haiyu; Fan, Lijun; Ge, Tingting; Guo, Bing; Zhang, Fan; Yang, Kai; Wang, Jingtao; Lou, Ge; Li, Kang

    2015-02-01

    Ovarian cancer is the leading cause of death in gynecologic malignancies. Profiling of endogenous metabolites has potential to identify changes caused by cancer and provide inspiring insights into cancer metabolism. To systematically investigate ovarian cancer metabolism, we performed metabolic profiling of 448 plasma samples related to epithelial ovarian cancer (EOC) based on ultra-performance liquid chromatography mass spectrometry in both positive and negative modes. These unbiased metabolomic profiles could well distinguish EOC from benign ovarian tumor (BOT) and uterine fibroid (UF). Fifty-three metabolites were identified as specific biomarkers for EOC, and this is the first report of piperine, 3-indolepropionic acid, 5-hydroxyindoleacetaldehyde and hydroxyphenyllactate as metabolic biomarkers of EOC. The AUC values of these metabolites for discriminating EOC from BOT/UF and early-stage EOC from BOT/UF were 0.9100/0.9428 and 0.8385/0.8624, respectively. Meanwhile, our metabolites were able to distinguish early-stage EOC from late-stage EOC with an AUC of 0.8801. Importantly, analysis of dysregulated metabolic pathways extends our current understanding of EOC metabolism. Metabolic pathways in EOC patients are mainly characterized by abnormal phospholipid metabolism, altered l-tryptophan catabolism, aggressive fatty acid β-oxidation and aberrant metabolism of piperidine derivatives. Together, these metabolic pathways provide a foundation to support cancer development and progression. In conclusion, our large-scale plasma metabolomics study yielded fundamental insights into dysregulated metabolism in ovarian cancer, which could facilitate clinical diagnosis, therapy, prognosis and shed new lights on ovarian cancer pathogenesis.

  12. MEMOSys: Bioinformatics platform for genome-scale metabolic models

    PubMed Central

    2011-01-01

    Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys. PMID:21276275

  13. 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.

  14. Automation on the generation of genome-scale metabolic models.

    PubMed

    Reyes, R; Gamermann, D; Montagud, A; Fuente, D; Triana, J; Urchueguía, J F; de Córdoba, P Fernández

    2012-12-01

    Nowadays, the reconstruction of genome-scale metabolic models is a nonautomatized and interactive process based on decision making. This lengthy process usually requires a full year of one person's work in order to satisfactory collect, analyze, and validate the list of all metabolic reactions present in a specific organism. In order to write this list, one manually has to go through a huge amount of genomic, metabolomic, and physiological information. Currently, there is no optimal algorithm that allows one to automatically go through all this information and generate the models taking into account probabilistic criteria of unicity and completeness that a biologist would consider. This work presents the automation of a methodology for the reconstruction of genome-scale metabolic models for any organism. The methodology that follows is the automatized version of the steps implemented manually for the reconstruction of the genome-scale metabolic model of a photosynthetic organism, Synechocystis sp. PCC6803. The steps for the reconstruction are implemented in a computational platform (COPABI) that generates the models from the probabilistic algorithms that have been developed. For validation of the developed algorithm robustness, the metabolic models of several organisms generated by the platform have been studied together with published models that have been manually curated. Network properties of the models, like connectivity and average shortest mean path of the different models, have been compared and analyzed.

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

    PubMed

    Triana, Julián; Montagud, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F

    2014-08-20

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

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

    PubMed Central

    Triana, Julián; Montagud†, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F.

    2014-01-01

    The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. PMID:25141288

  17. A Quantitative System-Scale Characterization of the Metabolism of Clostridium acetobutylicum

    PubMed Central

    Yoo, Minyeong; Bestel-Corre, Gwenaelle; Croux, Christian; Riviere, Antoine; Meynial-Salles, Isabelle

    2015-01-01

    ABSTRACT Engineering industrial microorganisms for ambitious applications, for example, the production of second-generation biofuels such as butanol, is impeded by a lack of knowledge of primary metabolism and its regulation. A quantitative system-scale analysis was applied to the biofuel-producing bacterium Clostridium acetobutylicum, a microorganism used for the industrial production of solvent. An improved genome-scale model, iCac967, was first developed based on thorough biochemical characterizations of 15 key metabolic enzymes and on extensive literature analysis to acquire accurate fluxomic data. In parallel, quantitative transcriptomic and proteomic analyses were performed to assess the number of mRNA molecules per cell for all genes under acidogenic, solventogenic, and alcohologenic steady-state conditions as well as the number of cytosolic protein molecules per cell for approximately 700 genes under at least one of the three steady-state conditions. A complete fluxomic, transcriptomic, and proteomic analysis applied to different metabolic states allowed us to better understand the regulation of primary metabolism. Moreover, this analysis enabled the functional characterization of numerous enzymes involved in primary metabolism, including (i) the enzymes involved in the two different butanol pathways and their cofactor specificities, (ii) the primary hydrogenase and its redox partner, (iii) the major butyryl coenzyme A (butyryl-CoA) dehydrogenase, and (iv) the major glyceraldehyde-3-phosphate dehydrogenase. This study provides important information for further metabolic engineering of C. acetobutylicum to develop a commercial process for the production of n-butanol. PMID:26604256

  18. Genome-scale metabolic models: reconstruction and analysis.

    PubMed

    Baart, Gino J E; Martens, Dirk E

    2012-01-01

    Metabolism can be defined as the complete set of chemical reactions that occur in living organisms in order to maintain life. Enzymes are the main players in this process as they are responsible for catalyzing the chemical reactions. The enzyme-reaction relationships can be used for the reconstruction of a network of reactions, which leads to a metabolic model of metabolism. A genome-scale metabolic network of chemical reactions that take place inside a living organism is primarily reconstructed from the information that is present in its genome and the literature and involves steps such as functional annotation of the genome, identification of the associated reactions and determination of their stoichiometry, assignment of localization, determination of the biomass composition, estimation of energy requirements, and definition of model constraints. This information can be integrated into a stoichiometric model of metabolism that can be used for detailed analysis of the metabolic potential of the organism using constraint-based modeling approaches and hence is valuable in understanding its metabolic capabilities.

  19. 13C metabolic flux analysis at a genome-scale.

    PubMed

    Gopalakrishnan, Saratram; Maranas, Costas D

    2015-11-01

    Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non

  20. Scaling of metabolism in Helix aspersa snails: changes through ontogeny and response to selection for increased size.

    PubMed

    Czarnołeski, Marcin; Kozłowski, Jan; Dumiot, Guillaume; Bonnet, Jean-Claude; Mallard, Jacques; Dupont-Nivet, Mathilde

    2008-02-01

    Though many are convinced otherwise, variability of the size-scaling of metabolism is widespread in nature, and the factors driving that remain unknown. Here we test a hypothesis that the increased expenditure associated with faster growth increases metabolic scaling. We compare metabolic scaling in the fast- and slow-growth phases of ontogeny of Helix aspersa snails artificially selected or not selected for increased adult size. The selected line evolved larger egg and adult sizes and a faster size-specific growth rate, without a change in the developmental rate. Both lines had comparable food consumption but the selected snails grew more efficiently and had lower metabolism early in ontogeny. Attainment of lower metabolism was accompanied by decreased shell production, indicating that the increased growth was fuelled partly at the expense of shell production. As predicted, the scaling of oxygen consumption with body mass was isometric or nearly isometric in the fast-growing (early) ontogenetic stage, and it became negatively allometric in the slow-growing (late) stage; metabolic scaling tended to be steeper in selected (fast-growing) than in control (slow-growing) snails; this difference disappeared later in ontogeny. Differences in metabolic scaling were not related to shifts in the scaling of metabolically inert shell. Our results support the view that changes in metabolic scaling through ontogeny and the variability of metabolic scaling between organisms can be affected by differential growth rates. We stress that future approaches to this phenomenon should consider the metabolic effects of cell size changes which underlie shifts in the growth pattern.

  1. Probing the genome-scale metabolic landscape of Bordetella pertussis, the causative agent of whooping cough.

    PubMed

    Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe

    2017-08-25

    Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussis. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content.IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis, and challenged its predictions

  2. Heterogeneity of cells may explain allometric scaling of metabolic rate.

    PubMed

    Takemoto, Kazuhiro

    2015-04-01

    The origin of allometric scaling of metabolic rate is a long-standing question in biology. Several models have been proposed for explaining the origin; however, they have advantages and disadvantages. In particular, previous models only demonstrate either two important observations for the allometric scaling: the variability of scaling exponents and predominance of 3/4-power law. Thus, these models have a dispute over their validity. In this study, we propose a simple geometry model, and show that a hypothesis that total surface area of cells determines metabolic rate can reproduce these two observations by combining two concepts: the impact of cell sizes on metabolic rate and fractal-like (hierarchical) organization. The proposed model both theoretically and numerically demonstrates the approximately 3/4-power law although several different biological strategies are considered. The model validity is confirmed using empirical data. Furthermore, the model suggests the importance of heterogeneity of cell size for the emergence of the allometric scaling. The proposed model provides intuitive and unique insights into the origin of allometric scaling laws in biology, despite several limitations of the model.

  3. Predicting novel pathways in genome-scale metabolic networks.

    PubMed

    Schuster, Stefan; de Figueiredo, Luís F; Kaleta, Christoph

    2010-10-01

    Elementary-modes analysis has become a well-established theoretical tool in metabolic pathway analysis. It allows one to decompose complex metabolic networks into the smallest functional entities, which can be interpreted as biochemical pathways. This analysis has, in medium-size metabolic networks, led to the successful theoretical prediction of hitherto unknown pathways. For illustration, we discuss the example of the phosphoenolpyruvate-glyoxylate cycle in Escherichia coli. Elementary-modes analysis meets with the problem of combinatorial explosion in the number of pathways with increasing system size, which has hampered scaling it up to genome-wide models. We present a novel approach to overcoming this obstacle. That approach is based on elementary flux patterns, which are defined as sets of reactions representing the basic routes through a particular subsystem that are compatible with admissible fluxes in a (possibly) much larger metabolic network. The subsystem can be made up by reactions in which we are interested in, for example, reactions producing a certain metabolite. This allows one to predict novel metabolic pathways in genome-scale networks.

  4. Engineering microbial cell factories for the production of plant natural products: from design principles to industrial-scale production.

    PubMed

    Liu, Xiaonan; Ding, Wentao; Jiang, Huifeng

    2017-07-19

    Plant natural products (PNPs) are widely used as pharmaceuticals, nutraceuticals, seasonings, pigments, etc., with a huge commercial value on the global market. However, most of these PNPs are still being extracted from plants. A resource-conserving and environment-friendly synthesis route for PNPs that utilizes microbial cell factories has attracted increasing attention since the 1940s. However, at the present only a handful of PNPs are being produced by microbial cell factories at an industrial scale, and there are still many challenges in their large-scale application. One of the challenges is that most biosynthetic pathways of PNPs are still unknown, which largely limits the number of candidate PNPs for heterologous microbial production. Another challenge is that the metabolic fluxes toward the target products in microbial hosts are often hindered by poor precursor supply, low catalytic activity of enzymes and obstructed product transport. Consequently, despite intensive studies on the metabolic engineering of microbial hosts, the fermentation costs of most heterologously produced PNPs are still too high for industrial-scale production. In this paper, we review several aspects of PNP production in microbial cell factories, including important design principles and recent progress in pathway mining and metabolic engineering. In addition, implemented cases of industrial-scale production of PNPs in microbial cell factories are also highlighted.

  5. Swimming in Light: A Large-Scale Computational Analysis of the Metabolism of Dinoroseobacter shibae

    PubMed Central

    Rex, Rene; Bill, Nelli; Schmidt-Hohagen, Kerstin; Schomburg, Dietmar

    2013-01-01

    The Roseobacter clade is a ubiquitous group of marine α-proteobacteria. To gain insight into the versatile metabolism of this clade, we took a constraint-based approach and created a genome-scale metabolic model (iDsh827) of Dinoroseobacter shibae DFL12T. Our model is the first accounting for the energy demand of motility, the light-driven ATP generation and experimentally determined specific biomass composition. To cover a large variety of environmental conditions, as well as plasmid and single gene knock-out mutants, we simulated 391,560 different physiological states using flux balance analysis. We analyzed our results with regard to energy metabolism, validated them experimentally, and revealed a pronounced metabolic response to the availability of light. Furthermore, we introduced the energy demand of motility as an important parameter in genome-scale metabolic models. The results of our simulations also gave insight into the changing usage of the two degradation routes for dimethylsulfoniopropionate, an abundant compound in the ocean. A side product of dimethylsulfoniopropionate degradation is dimethyl sulfide, which seeds cloud formation and thus enhances the reflection of sunlight. By our exhaustive simulations, we were able to identify single-gene knock-out mutants, which show an increased production of dimethyl sulfide. In addition to the single-gene knock-out simulations we studied the effect of plasmid loss on the metabolism. Moreover, we explored the possible use of a functioning phosphofructokinase for D. shibae. PMID:24098096

  6. Scaling of metabolic rate on body mass in small laboratory mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.; Smith, A. H.

    1980-01-01

    The scaling of metabolic heat production rate on body mass is investigated for five species of small laboratory mammal in order to define selection of animals of metabolic rates and size range appropriate for the measurement of changes in the scaling relationship upon exposure to weightlessness in Shuttle/Spacelab experiment. Metabolic rates were measured according to oxygen consumption and carbon dioxide production for individual male and female Swiss-Webster mice, Syrian hamsters, Simonsen albino rats, Hartley guinea pigs and New Zealand white rabbits, which range in mass from 0.05 to 5 kg mature body size, at ages of 1, 2, 3, 5, 8, 12, 18 and 24 months. The metabolic intensity, defined as the heat produced per hour per kg body mass, is found to decrease dramatically with age until the animals are 6 to 8 months old, with little or no sex difference. When plotted on a logarithmic graph, the relation of metabolic rate to total body mass is found to obey a power law of index 0.676, which differs significantly from the classical value of 0.75. When the values for the mice are removed, however, an index of 0.749 is obtained. It is thus proposed that six male animals, 8 months of age, of each of the four remaining species be used to study the effects of gravitational loading on the metabolic energy requirements of terrestrial animals.

  7. Scaling of metabolic rate on body mass in small laboratory mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.; Smith, A. H.

    1980-01-01

    The scaling of metabolic heat production rate on body mass is investigated for five species of small laboratory mammal in order to define selection of animals of metabolic rates and size range appropriate for the measurement of changes in the scaling relationship upon exposure to weightlessness in Shuttle/Spacelab experiment. Metabolic rates were measured according to oxygen consumption and carbon dioxide production for individual male and female Swiss-Webster mice, Syrian hamsters, Simonsen albino rats, Hartley guinea pigs and New Zealand white rabbits, which range in mass from 0.05 to 5 kg mature body size, at ages of 1, 2, 3, 5, 8, 12, 18 and 24 months. The metabolic intensity, defined as the heat produced per hour per kg body mass, is found to decrease dramatically with age until the animals are 6 to 8 months old, with little or no sex difference. When plotted on a logarithmic graph, the relation of metabolic rate to total body mass is found to obey a power law of index 0.676, which differs significantly from the classical value of 0.75. When the values for the mice are removed, however, an index of 0.749 is obtained. It is thus proposed that six male animals, 8 months of age, of each of the four remaining species be used to study the effects of gravitational loading on the metabolic energy requirements of terrestrial animals.

  8. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches

    PubMed Central

    2012-01-01

    Background Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. Results We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. Conclusions The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach

  9. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches.

    PubMed

    González-Domenech, Carmen Maria; Belda, Eugeni; Patiño-Navarrete, Rafael; Moya, Andrés; Peretó, Juli; Latorre, Amparo

    2012-01-18

    Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the

  10. The metabolic control of schistosome egg production

    PubMed Central

    Pearce, Edward J.; Huang, Stanley Ching-Cheng

    2015-01-01

    Schistosomiasis is a Neglected Tropical Disease caused by infection with trematode parasites of the genus Schistosoma. Despite ongoing treatment programs, the prevalence of schistosomiasis has failed to decline and the disease remains a cause of severe morbidity in millions of people. Understanding the biology of egg production by schistosomes is critical since eggs allow transmission of the infection, and when trapped in host tissues induce the immune responses that are responsible for the pathologic changes that underlie disease development. Unusually among trematodes, adult schistosomes exhibit sexual dimorphism and display a fascinating codependency in that the female is dependent on the male to grow and sexually mature. Thus virgin females are developmentally stunted compared to females from mixed-sex infections and are unable to lay eggs. Moreover, fecund female schistosomes rapidly lose the ability to produce eggs when placed in tissue culture. Here we discuss the metabolic regulation of egg production in schistosomes, and in particular the critical role played by fatty acid oxidation in this process. PMID:25850569

  11. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints.

    PubMed

    Sánchez, Benjamín J; Zhang, Cheng; Nilsson, Avlant; Lahtvee, Petri-Jaan; Kerkhoven, Eduard J; Nielsen, Jens

    2017-08-03

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  12. Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

    PubMed Central

    2017-01-01

    Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria. PMID:28133437

  13. A Quantitative System-Scale Characterization of the Metabolism of Clostridium acetobutylicum.

    PubMed

    Yoo, Minyeong; Bestel-Corre, Gwenaelle; Croux, Christian; Riviere, Antoine; Meynial-Salles, Isabelle; Soucaille, Philippe

    2015-11-24

    Engineering industrial microorganisms for ambitious applications, for example, the production of second-generation biofuels such as butanol, is impeded by a lack of knowledge of primary metabolism and its regulation. A quantitative system-scale analysis was applied to the biofuel-producing bacterium Clostridium acetobutylicum, a microorganism used for the industrial production of solvent. An improved genome-scale model, iCac967, was first developed based on thorough biochemical characterizations of 15 key metabolic enzymes and on extensive literature analysis to acquire accurate fluxomic data. In parallel, quantitative transcriptomic and proteomic analyses were performed to assess the number of mRNA molecules per cell for all genes under acidogenic, solventogenic, and alcohologenic steady-state conditions as well as the number of cytosolic protein molecules per cell for approximately 700 genes under at least one of the three steady-state conditions. A complete fluxomic, transcriptomic, and proteomic analysis applied to different metabolic states allowed us to better understand the regulation of primary metabolism. Moreover, this analysis enabled the functional characterization of numerous enzymes involved in primary metabolism, including (i) the enzymes involved in the two different butanol pathways and their cofactor specificities, (ii) the primary hydrogenase and its redox partner, (iii) the major butyryl coenzyme A (butyryl-CoA) dehydrogenase, and (iv) the major glyceraldehyde-3-phosphate dehydrogenase. This study provides important information for further metabolic engineering of C. acetobutylicum to develop a commercial process for the production of n-butanol. Currently, there is a resurgence of interest in Clostridium acetobutylicum, the biocatalyst of the historical Weizmann process, to produce n-butanol for use both as a bulk chemical and as a renewable alternative transportation fuel. To develop a commercial process for the production of n-butanol via a

  14. The Metabolic Cost of Sound Production in Odontocete Cetaceans

    DTIC Science & Technology

    2011-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. The Metabolic Cost of Sound Production in Odontocete...strategy to help reduce the probability of masking from environmental sounds (NRC 2003). Although accumulating evidence from recent research...data on the metabolic cost of sound production for any marine mammal species. Given that changes in vocal behavior in response to masking noise

  15. Engineering strategy of yeast metabolism for higher alcohol production

    PubMed Central

    2011-01-01

    Background While Saccharomyces cerevisiae is a promising host for cost-effective biorefinary processes due to its tolerance to various stresses during fermentation, the metabolically engineered S. cerevisiae strains exhibited rather limited production of higher alcohols than that of Escherichia coli. Since the structure of the central metabolism of S. cerevisiae is distinct from that of E. coli, there might be a problem in the structure of the central metabolism of S. cerevisiae. In this study, the potential production of higher alcohols by S. cerevisiae is compared to that of E. coli by employing metabolic simulation techniques. Based on the simulation results, novel metabolic engineering strategies for improving higher alcohol production by S. cerevisiae were investigated by in silico modifications of the metabolic models of S. cerevisiae. Results The metabolic simulations confirmed that the high production of butanols and propanols by the metabolically engineered E. coli strains is derived from the flexible behavior of their central metabolism. Reducing this flexibility by gene deletion is an effective strategy to restrict the metabolic states for producing target alcohols. In contrast, the lower yield using S. cerevisiae originates from the structurally limited flexibility of its central metabolism in which gene deletions severely reduced cell growth. Conclusions The metabolic simulation demonstrated that the poor productivity of S. cerevisiae was improved by the introduction of E. coli genes to compensate the structural difference. This suggested that gene supplementation is a promising strategy for the metabolic engineering of S. cerevisiae to produce higher alcohols which should be the next challenge for the synthetic bioengineering of S. cerevisiae for the efficient production of higher alcohols. PMID:21902829

  16. Engineering strategy of yeast metabolism for higher alcohol production.

    PubMed

    Matsuda, Fumio; Furusawa, Chikara; Kondo, Takashi; Ishii, Jun; Shimizu, Hiroshi; Kondo, Akihiko

    2011-09-08

    While Saccharomyces cerevisiae is a promising host for cost-effective biorefinary processes due to its tolerance to various stresses during fermentation, the metabolically engineered S. cerevisiae strains exhibited rather limited production of higher alcohols than that of Escherichia coli. Since the structure of the central metabolism of S. cerevisiae is distinct from that of E. coli, there might be a problem in the structure of the central metabolism of S. cerevisiae. In this study, the potential production of higher alcohols by S. cerevisiae is compared to that of E. coli by employing metabolic simulation techniques. Based on the simulation results, novel metabolic engineering strategies for improving higher alcohol production by S. cerevisiae were investigated by in silico modifications of the metabolic models of S. cerevisiae. The metabolic simulations confirmed that the high production of butanols and propanols by the metabolically engineered E. coli strains is derived from the flexible behavior of their central metabolism. Reducing this flexibility by gene deletion is an effective strategy to restrict the metabolic states for producing target alcohols. In contrast, the lower yield using S. cerevisiae originates from the structurally limited flexibility of its central metabolism in which gene deletions severely reduced cell growth. The metabolic simulation demonstrated that the poor productivity of S. cerevisiae was improved by the introduction of E. coli genes to compensate the structural difference. This suggested that gene supplementation is a promising strategy for the metabolic engineering of S. cerevisiae to produce higher alcohols which should be the next challenge for the synthetic bioengineering of S. cerevisiae for the efficient production of higher alcohols.

  17. Production-scale Direct Oxide Reduction demonstration

    SciTech Connect

    Humiston, T.J.; Santi, D.J.; Long, J.L.; Thomas, R.L.; Delaney, I.C.

    1989-01-23

    A detailed, statistically valid, examination of the direct oxide reduction parameters affecting process yield and purity was planned and executed. Guidelines for attaining yields approaching 100% are presented. Feed oxide, percent excess calcium, and stirrer design affected yield and product purity. Experiments were performed in production-scale equipment utilizing 800 grams of plutonium dioxide per charge. 1 ref., 9 figs., 3 tabs.

  18. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    PubMed Central

    2012-01-01

    Background Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform

  19. Classifying forest productivity at different scales

    SciTech Connect

    Graham, R.L.

    1991-01-01

    Spatial scale is an important consideration when evaluating, using, or constructing forest productivity classifications. First, the factors which dominate spatial variability in forest productivity are scale dependent. For example, within a stand, spatial variability in productivity is dominated by microsite differences; within a national forest such as the Cherokee National Forest, spatial variability is dominated by topography and land-use history (e.g., years since harvest); within a large region such as the southeast, spatial variability is dominated by climatic patterns. Second, classifications developed at different spatial scales are often used for different purposes. For example, stand-level classifications are often keys or rules used in the field to judge the quality or potential of a site. National-forest classifications are often presented as maps or tables and may be used in forest land planning. Regional classifications may be maps or tables and may be used to quantify or predict resource availability. These scale-related differences in controlling factors and purposes will affect both the methods and the data used to develop classifications. In this paper, I will illustrate these points by describing and comparing three forest productivity classifications, each developed for a specific purpose at a specific scale. My objective is not to argue for or against any of these particular classifications but rather to heighten awareness of the critical role that spatial scale plays in the use and development of forest productivity classifications. 8 refs., 2 figs., 1 tab.

  20. Metabolic engineering of microorganisms: general strategies and drug production.

    PubMed

    Lee, Sang Yup; Kim, Hyun Uk; Park, Jin Hwan; Park, Jong Myung; Kim, Tae Yong

    2009-01-01

    Many drugs and drug precursors found in natural organisms are rather difficult to synthesize chemically and to extract in large amounts. Metabolic engineering is playing an increasingly important role in the production of these drugs and drug precursors. This is typically achieved by establishing new metabolic pathways leading to the product formation, and enforcing or removing the existing metabolic pathways toward enhanced product formation. Recent advances in system biology and synthetic biology are allowing us to perform metabolic engineering at the whole cell level, thus enabling optimal design of a microorganism for the efficient production of drugs and drug precursors. In this review, we describe the general strategies for the metabolic engineering of microorganisms for the production of drugs and drug precursors. As successful examples of metabolic engineering, the approaches taken toward strain development for the production of artemisinin, an antimalarial drug, and benzylisoquinoline alkaloids, a family of antibacterial and anticancer drugs, are described in detail. Also, systems metabolic engineering of Escherichia coli for the production of L-valine, an important drug precursor, is showcased as an important strategy of future metabolic engineering effort.

  1. Metabolic network alignment in large scale by network compression.

    PubMed

    Ay, Ferhat; Dang, Michael; Kahveci, Tamer

    2012-03-21

    Metabolic network alignment is a system scale comparative analysis that discovers important similarities and differences across different metabolisms and organisms. Although the problem of aligning metabolic networks has been considered in the past, the computational complexity of the existing solutions has so far limited their use to moderately sized networks. In this paper, we address the problem of aligning two metabolic networks, particularly when both of them are too large to be dealt with using existing methods. We develop a generic framework that can significantly improve the scale of the networks that can be aligned in practical time. Our framework has three major phases, namely the compression phase, the alignment phase and the refinement phase. For the first phase, we develop an algorithm which transforms the given networks to a compressed domain where they are summarized using fewer nodes, termed supernodes, and interactions. In the second phase, we carry out the alignment in the compressed domain using an existing network alignment method as our base algorithm. This alignment results in supernode mappings in the compressed domain, each of which are smaller instances of network alignment problem. In the third phase, we solve each of the instances using the base alignment algorithm to refine the alignment results. We provide a user defined parameter to control the number of compression levels which generally determines the tradeoff between the quality of the alignment versus how fast the algorithm runs. Our experiments on the networks from KEGG pathway database demonstrate that the compression method we propose reduces the sizes of metabolic networks by almost half at each compression level which provides an expected speedup of more than an order of magnitude. We also observe that the alignments obtained by only one level of compression capture the original alignment results with high accuracy. Together, these suggest that our framework results in

  2. Uncinate Process Length in Birds Scales with Resting Metabolic Rate

    PubMed Central

    Tickle, Peter; Nudds, Robert; Codd, Jonathan

    2009-01-01

    A fundamental function of the respiratory system is the supply of oxygen to meet metabolic demand. Morphological constraints on the supply of oxygen, such as the structure of the lung, have previously been studied in birds. Recent research has shown that uncinate processes (UP) are important respiratory structures in birds, facilitating inspiratory and expiratory movements of the ribs and sternum. Uncinate process length (UPL) is important for determining the mechanical advantage for these respiratory movements. Here we report on the relationship between UPL, body size, metabolic demand and locomotor specialisation in birds. UPL was found to scale isometrically with body mass. Process length is greatest in specialist diving birds, shortest in walking birds and intermediate length in all others relative to body size. Examination of the interaction between the length of the UP and metabolic demand indicated that, relative to body size, species with high metabolic rates have corresponding elongated UP. We propose that elongated UP confer an advantage on the supply of oxygen, perhaps by improving the mechanical advantage and reducing the energetic cost of movements of the ribs and sternum. PMID:19479074

  3. Uncinate process length in birds scales with resting metabolic rate.

    PubMed

    Tickle, Peter; Nudds, Robert; Codd, Jonathan

    2009-05-27

    A fundamental function of the respiratory system is the supply of oxygen to meet metabolic demand. Morphological constraints on the supply of oxygen, such as the structure of the lung, have previously been studied in birds. Recent research has shown that uncinate processes (UP) are important respiratory structures in birds, facilitating inspiratory and expiratory movements of the ribs and sternum. Uncinate process length (UPL) is important for determining the mechanical advantage for these respiratory movements. Here we report on the relationship between UPL, body size, metabolic demand and locomotor specialisation in birds. UPL was found to scale isometrically with body mass. Process length is greatest in specialist diving birds, shortest in walking birds and intermediate length in all others relative to body size. Examination of the interaction between the length of the UP and metabolic demand indicated that, relative to body size, species with high metabolic rates have corresponding elongated UP. We propose that elongated UP confer an advantage on the supply of oxygen, perhaps by improving the mechanical advantage and reducing the energetic cost of movements of the ribs and sternum.

  4. Reconstructing genome-scale metabolic models with merlin.

    PubMed

    Dias, Oscar; Rocha, Miguel; Ferreira, Eugénio C; Rocha, Isabel

    2015-04-30

    The Metabolic Models Reconstruction Using Genome-Scale Information (merlin) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin.

  5. Reconstructing genome-scale metabolic models with merlin

    PubMed Central

    Dias, Oscar; Rocha, Miguel; Ferreira, Eugénio C.; Rocha, Isabel

    2015-01-01

    The Metabolic Models Reconstruction Using Genome-Scale Information (merlin) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin. PMID:25845595

  6. Integration of clinical data with a genome-scale metabolic model of the human adipocyte

    PubMed Central

    Mardinoglu, Adil; Agren, Rasmus; Kampf, Caroline; Asplund, Anna; Nookaew, Intawat; Jacobson, Peter; Walley, Andrew J; Froguel, Philippe; Carlsson, Lena M; Uhlen, Mathias; Nielsen, Jens

    2013-01-01

    We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte-specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome-scale metabolic model of adipocyte metabolism. The resulting metabolic model, iAdipocytes1809, enables mechanistic insights into adipocyte metabolism on a genome-wide level, and can serve as a scaffold for integration of omics data to understand the genotype–phenotype relationship in obese subjects. By integrating human transcriptome and fluxome data, we found an increase in the metabolic activity around androsterone, ganglioside GM2 and degradation products of heparan sulfate and keratan sulfate, and a decrease in mitochondrial metabolic activities in obese subjects compared with lean subjects. Our study hereby shows a path to identify new therapeutic targets for treating obesity through combination of high throughput patient data and metabolic modeling. PMID:23511207

  7. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    PubMed

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes.

  8. Metabolic engineering of cyanobacteria for the synthesis of commodity products.

    PubMed

    Angermayr, S Andreas; Gorchs Rovira, Aleix; Hellingwerf, Klaas J

    2015-06-01

    Through metabolic engineering cyanobacteria can be employed in biotechnology. Combining the capacity for oxygenic photosynthesis and carbon fixation with an engineered metabolic pathway allows carbon-based product formation from CO(2), light, and water directly. Such cyanobacterial 'cell factories' are constructed to produce biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers and synthetic biologists allow the modification of the intermediary metabolism at various branching points, expanding the product range. The new biosynthesis routes 'tap' the metabolism ever more efficiently, particularly through the engineering of driving forces and utilization of cofactors generated during the light reactions of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling ultimately allow an almost-complete allocation of fixed carbon to product above biomass. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Discovery of substrate cycles in large scale metabolic networks using hierarchical modularity.

    PubMed

    Sridharan, Gautham Vivek; Ullah, Ehsan; Hassoun, Soha; Lee, Kyongbum

    2015-02-13

    A substrate cycle is a set of metabolic reactions, arranged in a loop, which does not result in net consumption or production of the metabolites. The cycle operates by transforming a cofactor, e.g. oxidizing a reducing equivalent. Substrate cycles have been found experimentally in many parts of metabolism; however, their physiological roles remain unclear. As genome-scale metabolic models become increasingly available, there is now the opportunity to comprehensively catalogue substrate cycles, and gain additional insight into this potentially important motif of metabolic networks. We present a method to identify substrate cycles in the context of metabolic modules, which facilitates functional analysis. This method utilizes elementary flux mode (EFM) analysis to find potential substrate cycles in the form of cyclical EFMs, and combines this analysis with network partition based on retroactive (cyclical) interactions between reactions. In addition to providing functional context, partitioning the network into modules allowed exhaustive EFM calculations on smaller, tractable subnetworks that are enriched in metabolic cycles. Applied to a large-scale model of human liver metabolism (HepatoNet1), our method found not only well-known substrate cycles involving ATP hydrolysis, but also potentially novel substrate cycles involving the transformation of other cofactors. A key characteristic of the substrate cycles identified in this study is that the lengths are relatively short (2-13 reactions), comparable to many experimentally observed substrate cycles. EFM computation for large scale networks remains computationally intractable for exhaustive substrate cycle enumeration. Our algorithm utilizes a 'divide and conquer' strategy where EFM analysis is performed on systematically identified network modules that are designed to be enriched in cyclical interactions. We find that several substrate cycles uncovered using our approach are not identified when the network is

  10. 13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

    PubMed Central

    Guo, Weihua; Sheng, Jiayuan; Feng, Xueyang

    2015-01-01

    Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, 13C Metabolic Flux Analysis (13C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many 13C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of 13C-MFA and illustrate how 13C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms PMID:28952565

  11. The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

    PubMed

    Papin, Jason A; Price, Nathan D; Edwards, Jeremy S; Palsson B, Bernhard Ø

    2002-03-07

    Genome-scale metabolic networks can be characterized by a set of systemically independent and unique extreme pathways. These extreme pathways span a convex, high-dimensional space that circumscribes all potential steady-state flux distributions achievable by the defined metabolic network. Genome-scale extreme pathways associated with the production of non-essential amino acids in Haemophilus influenzae were computed. They offer valuable insight into the functioning of its metabolic network. Three key results were obtained. First, there were multiple internal flux maps corresponding to externally indistinguishable states. It was shown that there was an average of 37 internal states per unique exchange flux vector in H. influenzae when the network was used to produce a single amino acid while allowing carbon dioxide and acetate as carbon sinks. With the inclusion of succinate as an additional output, this ratio increased to 52, a 40% increase. Second, an analysis of the carbon fates illustrated that the extreme pathways were non-uniformly distributed across the carbon fate spectrum. In the detailed case study, 45% of the distinct carbon fate values associated with lysine production represented 85% of the extreme pathways. Third, this distribution fell between distinct systemic constraints. For lysine production, the carbon fate values that represented 85% of the pathways described above corresponded to only 2 distinct ratios of 1:1 and 4:1 between carbon dioxide and acetate. The present study analysed single outputs from one organism, and provides a start to genome-scale extreme pathways studies. These emergent system-level characterizations show the significance of metabolic extreme pathway analysis at the genome-scale.

  12. Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

    PubMed

    Muhamadali, Howbeer; Xu, Yun; Ellis, David I; Allwood, J William; Rattray, Nicholas J W; Correa, Elon; Alrabiah, Haitham; Lloyd, Jonathan R; Goodacre, Royston

    2015-05-15

    During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However

  13. Metabolic engineering of Mannheimia succiniciproducens for succinic acid production based on elementary mode analysis with clustering.

    PubMed

    Kim, Won Jun; Ahn, Jung Ho; Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

    2017-02-01

    Mannheimia succiniciproducens, a capnophilic gram-negative rumen bacterium, has been employed for the efficient production of succinic acid. Although M. succiniciproducens metabolism was previously studied using a genome-scale metabolic model, more metabolic characteristics are to be understood. To this end, elementary mode analysis accompanied with clustering ('EMC' analysis) is used to gain further insights on metabolic characteristics of M. succiniciproducens allowing efficient succinic acid production. Elementary modes (EMs) generated from the central carbon metabolic network of M. succiniciproducens are clustered to systematically analyze succinic acid production routes. Based on the results of EMC analysis, zwf gene is identified as a novel overexpression target for the improved succinic acid production. This gene is overexpressed in a previously constructed succinic acid-overproducing M. succiniciproducens LPK7 strain. Heterologous NADPH-dependent mdh is later intuitively selected for overexpression to synergistically improve succinic acid production by utilizing abundant NADPH pool mediated by the overexpressed zwf. The LPK7 strains co-expressing mdh alone and both zwf and mdh genes are subjected to fed-batch fermentation to better examine their succinic acid production performances. Strategies of EMC analysis will be useful for further metabolic engineering of M. succiniciproducens and other microorganisms to improve production of succinic acid and other chemicals of interest. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Targeting metabolic disorders by natural products.

    PubMed

    Tabatabaei-Malazy, Ozra; Larijani, Bagher; Abdollahi, Mohammad

    2015-01-01

    The most prevalent metabolic disorders are diabetes mellitus, obesity, dyslipidemia, osteoporosis and metabolic syndrome, which are developed when normal metabolic processes are disturbed. The most common pathophysiologies of the above disorders are oxidative stress, Nrf2 pathways, epigenetic, and change in miRNA expression. There is a challenge in the prevention and treatment of metabolic disorders due to severe adverse effects of some synthetic drugs, their high cost, lack of safety and poverty in some conditions, and insufficient accessibility for the general population in the world. With increasing interest in shifting from synthetic drugs to phytotherapy as an alternative treatment, there is still a gap in scientific evidences of plant-derived therapeutic benefits. One reason may be slow rate of translation of animal studies' findings into human clinical trials. Since metabolic disorders are multifactorial, it seems that poly-herbal medications, or drug-herbal combination are needed for their treatment. However, further researches to determine the most effective plant-derived metabolites, and their cellular mechanism in order to set priorities for well-designed animal and clinical trials, and also more studies with strong scientific evidences such as systematic review and meta-analysis of controlled studies are needed.

  15. Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism

    PubMed Central

    Solheim, Margrete; van Grinsven, Koen W. A.; Olivier, Brett G.; Levering, Jennifer; Grosseholz, Ruth; Hugenholtz, Jeroen; Holo, Helge; Nes, Ingolf; Teusink, Bas; Kummer, Ursula

    2014-01-01

    Increasing antibiotic resistance in pathogenic bacteria necessitates the development of new medication strategies. Interfering with the metabolic network of the pathogen can provide novel drug targets but simultaneously requires a deeper and more detailed organism-specific understanding of the metabolism, which is often surprisingly sparse. In light of this, we reconstructed a genome-scale metabolic model of the pathogen Enterococcus faecalis V583. The manually curated metabolic network comprises 642 metabolites and 706 reactions. We experimentally determined metabolic profiles of E. faecalis grown in chemically defined medium in an anaerobic chemostat setup at different dilution rates and calculated the net uptake and product fluxes to constrain the model. We computed growth-associated energy and maintenance parameters and studied flux distributions through the metabolic network. Amino acid auxotrophies were identified experimentally for model validation and revealed seven essential amino acids. In addition, the important metabolic hub of glutamine/glutamate was altered by constructing a glutamine synthetase knockout mutant. The metabolic profile showed a slight shift in the fermentation pattern toward ethanol production and increased uptake rates of multiple amino acids, especially l-glutamine and l-glutamate. The model was used to understand the altered flux distributions in the mutant and provided an explanation for the experimentally observed redirection of the metabolic flux. We further highlighted the importance of gene-regulatory effects on the redirection of the metabolic fluxes upon perturbation. The genome-scale metabolic model presented here includes gene-protein-reaction associations, allowing a further use for biotechnological applications, for studying essential genes, proteins, or reactions, and the search for novel drug targets. PMID:25527553

  16. Metabolic engineering of Saccharomyces cerevisiae to improve succinic acid production based on metabolic profiling.

    PubMed

    Ito, Yuma; Hirasawa, Takashi; Shimizu, Hiroshi

    2014-01-01

    We performed metabolic engineering on the budding yeast Saccharomyces cerevisiae for enhanced production of succinic acid. Aerobic succinic acid production in S. cerevisiae was achieved by disrupting the SDH1 and SDH2 genes, which encode the catalytic subunits of succinic acid dehydrogenase. Increased succinic acid production was achieved by eliminating the ethanol biosynthesis pathways. Metabolic profiling analysis revealed that succinic acid accumulated intracellularly following disruption of the SDH1 and SDH2 genes, which suggests that enhancing the export of intracellular succinic acid outside of cells increases succinic acid production in S. cerevisiae. The mae1 gene encoding the Schizosaccharomyces pombe malic acid transporter was introduced into S. cerevisiae, and as a result, succinic acid production was successfully improved. Metabolic profiling analysis is useful in producing chemicals for metabolic engineering of microorganisms.

  17. Metabolic engineering of Klebsiella pneumoniae based on in silico analysis and its pilot-scale application for 1,3-propanediol and 2,3-butanediol co-production.

    PubMed

    Park, Jong Myoung; Rathnasingh, Chelladurai; Song, Hyohak

    2017-03-01

    Klebsiella pneumoniae naturally produces relatively large amounts of 1,3-propanediol (1,3-PD) and 2,3-butanediol (2,3-BD) along with various byproducts using glycerol as a carbon source. The ldhA and mdh genes in K. pneumoniae were deleted based on its in silico gene knockout simulation with the criteria of maximizing 1,3-PD and 2,3-BD production and minimizing byproducts formation and cell growth retardation. In addition, the agitation speed, which is known to strongly affect 1,3-PD and 2,3-BD production in Klebsiella strains, was optimized. The K. pneumoniae ΔldhA Δmdh strain produced 125 g/L of diols (1,3-PD and 2,3-BD) with a productivity of 2.0 g/L/h in the lab-scale (5-L bioreactor) fed-batch fermentation using high-quality guaranteed reagent grade glycerol. To evaluate the industrial capacity of the constructed K. pneumoniae ΔldhA Δmdh strain, a pilot-scale (5000-L bioreactor) fed-batch fermentation was carried out using crude glycerol obtained from the industrial biodiesel plant. The pilot-scale fed-batch fermentation of the K. pneumoniae ΔldhA Δmdh strain produced 114 g/L of diols (70 g/L of 1,3-PD and 44 g/L of 2,3-BD), with a yield of 0.60 g diols per gram glycerol and a productivity of 2.2 g/L/h of diols, which should be suitable for the industrial co-production of 1,3-PD and 2,3-BD.

  18. Computational modelling of genome-scale metabolic networks and its application to CHO cell cultures.

    PubMed

    Rejc, Živa; Magdevska, Lidija; Tršelič, Tilen; Osolin, Timotej; Vodopivec, Rok; Mraz, Jakob; Pavliha, Eva; Zimic, Nikolaj; Cvitanović, Tanja; Rozman, Damjana; Moškon, Miha; Mraz, Miha

    2017-09-01

    Genome-scale metabolic models (GEMs) have become increasingly important in recent years. Currently, GEMs are the most accurate in silico representation of the genotype-phenotype link. They allow us to study complex networks from the systems perspective. Their application may drastically reduce the amount of experimental and clinical work, improve diagnostic tools and increase our understanding of complex biological phenomena. GEMs have also demonstrated high potential for the optimisation of bio-based production of recombinant proteins. Herein, we review the basic concepts, methods, resources and software tools used for the reconstruction and application of GEMs. We overview the evolution of the modelling efforts devoted to the metabolism of Chinese Hamster Ovary (CHO) cells. We present a case study on CHO cell metabolism under different amino acid depletions. This leads us to the identification of the most influential as well as essential amino acids in selected CHO cell lines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Multi-scale engineering of plant cell cultures for promotion of specialized metabolism.

    PubMed

    Wilson, Sarah A; Cummings, Elizabeth M; Roberts, Susan C

    2014-10-01

    To establish plant culture systems for product synthesis, a multi-scale engineering approach is necessary. At the intracellular level, the influx of 'omics' data has necessitated development of new methods to properly annotate and establish useful metabolic models that can be applied to elucidate unknown steps in specialized metabolite biosynthesis, define effective metabolic engineering strategies and increase enzyme diversity available for synthetic biology platforms. On an intercellular level, the presence of aggregates in culture leads to distinct metabolic sub-populations. Recent advances in flow cytometric analyses and mass spectrometry imaging allow for resolution of metabolites on the single cell level, providing an increased understanding of culture heterogeneity. Finally, extracellular engineering can be used to enhance culture performance through media manipulation, co-culture with bacteria, the use of exogenous elicitors or modulation of shear stress. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    PubMed Central

    2012-01-01

    Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis) has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale metabolic model developed for

  1. Plant Interactions Alter the Predictions of Metabolic Scaling Theory

    PubMed Central

    Lin, Yue; Berger, Uta; Grimm, Volker; Huth, Franka; Weiner, Jacob

    2013-01-01

    Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of −4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms’ internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than −4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive. PMID:23460884

  2. Genome-scale metabolic model in guiding metabolic engineering of microbial improvement.

    PubMed

    Xu, Chuan; Liu, Lili; Zhang, Zhao; Jin, Danfeng; Qiu, Juanping; Chen, Ming

    2013-01-01

    In the past few decades, despite all the significant achievements in industrial microbial improvement, the approaches of traditional random mutation and selection as well as the rational metabolic engineering based on the local knowledge cannot meet today's needs. With rapid reconstructions and accurate in silico simulations, genome-scale metabolic model (GSMM) has become an indispensable tool to study the microbial metabolism and design strain improvements. In this review, we highlight the application of GSMM in guiding microbial improvements focusing on a systematic strategy and its achievements in different industrial fields. This strategy includes a repetitive process with four steps: essential data acquisition, GSMM reconstruction, constraints-based optimizing simulation, and experimental validation, in which the second and third steps are the centerpiece. The achievements presented here belong to different industrial application fields, including food and nutrients, biopharmaceuticals, biopolymers, microbial biofuel, and bioremediation. This strategy and its achievements demonstrate a momentous guidance of GSMM for metabolic engineering breeding of industrial microbes. More efforts are required to extend this kind of study in the meantime.

  3. Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species.

    PubMed

    Pitkänen, Esa; Jouhten, Paula; Hou, Jian; Syed, Muhammad Fahad; Blomberg, Peter; Kludas, Jana; Oja, Merja; Holm, Liisa; Penttilä, Merja; Rousu, Juho; Arvas, Mikko

    2014-02-01

    We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

  4. Yeast metabolic engineering for hemicellulosic ethanol production

    Treesearch

    Jennifer Van Vleet; Thomas W. Jeffries

    2009-01-01

    Efficient fermentation of hemicellulosic sugars is critical for the bioconversion of lignocellulosics to ethanol. Efficient sugar uptake through the heterologous expression of yeast and fungal xylose/glucose transporters can improve fermentation if other metabolic steps are not rate limiting. Rectification of cofactor imbalances through heterologous expression of...

  5. The Metabolic Costs of Sound Production in Odontocete Cetaceans

    DTIC Science & Technology

    2012-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. The Metabolic Costs of Sound Production in Odontocete...of their acoustic signals as a strategy to help reduce the probability of masking from environmental sounds (NRC 2003). Although accumulating...our knowledge, there is no empirical data on the metabolic cost of sound production for any marine mammal species. Given that changes in vocal

  6. The Metabolic Costs of Sound Production in Odontocete Cetaceans

    DTIC Science & Technology

    2013-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. The Metabolic Costs of Sound Production in Odontocete...or repetition rate of their acoustic signals as a strategy to help reduce the probability of masking from environmental sounds (NRC 2003...are unknown. To our knowledge, there is no empirical data on the metabolic cost of sound production for any marine mammal species. Given that

  7. Production of bulk chemicals via novel metabolic pathways in microorganisms.

    PubMed

    Shin, Jae Ho; Kim, Hyun Uk; Kim, Dong In; Lee, Sang Yup

    2013-11-01

    Metabolic engineering has been playing important roles in developing high performance microorganisms capable of producing various chemicals and materials from renewable biomass in a sustainable manner. Synthetic and systems biology are also contributing significantly to the creation of novel pathways and the whole cell-wide optimization of metabolic performance, respectively. In order to expand the spectrum of chemicals that can be produced biotechnologically, it is necessary to broaden the metabolic capacities of microorganisms. Expanding the metabolic pathways for biosynthesizing the target chemicals requires not only the enumeration of a series of known enzymes, but also the identification of biochemical gaps whose corresponding enzymes might not actually exist in nature; this issue is the focus of this paper. First, pathway prediction tools, effectively combining reactions that lead to the production of a target chemical, are analyzed in terms of logics representing chemical information, and designing and ranking the proposed metabolic pathways. Then, several approaches for potentially filling in the gaps of the novel metabolic pathway are suggested along with relevant examples, including the use of promiscuous enzymes that flexibly utilize different substrates, design of novel enzymes for non-natural reactions, and exploration of hypothetical proteins. Finally, strain optimization by systems metabolic engineering in the context of novel metabolic pathways constructed is briefly described. It is hoped that this review paper will provide logical ways of efficiently utilizing 'big' biological data to design and develop novel metabolic pathways for the production of various bulk chemicals that are currently produced from fossil resources.

  8. Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

    PubMed

    Alam, Mohammad Tauqeer; Medema, Marnix H; Takano, Eriko; Breitling, Rainer

    2011-07-21

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of actinomycetes. Based on in silico knockouts we generated topological and genomic maps for each organism. Combining the collection of genome-wide models, we constructed a global enzyme association network to identify both a conserved "core network" and an "essential core network" of the entire group. As has been reported for low-degree metabolites in several organisms, low-degree enzymes (in linear pathways) turn out to be generally more essential than high-degree enzymes (in metabolic hubs).

  9. Metabolic engineering for the production of plant isoquinoline alkaloids.

    PubMed

    Diamond, Andrew; Desgagné-Penix, Isabel

    2016-06-01

    Several plant isoquinoline alkaloids (PIAs) possess powerful pharmaceutical and biotechnological properties. Thus, PIA metabolism and its fascinating molecules, including morphine, colchicine and galanthamine, have attracted the attention of both the industry and researchers involved in plant science, biochemistry, chemical bioengineering and medicine. Currently, access and availability of high-value PIAs [commercialized (e.g. galanthamine) or not (e.g. narciclasine)] is limited by low concentration in nature, lack of cultivation or geographic access, seasonal production and risk of overharvesting wild plant species. Nevertheless, most commercial PIAs are still extracted from plant sources. Efforts to improve the production of PIA have largely been impaired by the lack of knowledge on PIA metabolism. With the development and integration of next-generation sequencing technologies, high-throughput proteomics and metabolomics analyses and bioinformatics, systems biology was used to unravel metabolic pathways allowing the use of metabolic engineering and synthetic biology approaches to increase production of valuable PIAs. Metabolic engineering provides opportunity to overcome issues related to restricted availability, diversification and productivity of plant alkaloids. Engineered plant, plant cells and microbial cell cultures can act as biofactories by offering their metabolic machinery for the purpose of optimizing the conditions and increasing the productivity of a specific alkaloid. In this article, is presented an update on the production of PIA in engineered plant, plant cell cultures and heterologous micro-organisms. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  10. GRCop-84 Scaled Up for Production

    NASA Technical Reports Server (NTRS)

    Ellis, David L.

    2004-01-01

    GRCop-84 (Cu-8 at.% Cr-4 at.% Nb) was developed at the NASA Glenn Research Center for use in regeneratively cooled rocket engine main combustion chamber liners. The alloy has demonstrated high elevated-temperature strength, excellent creep resistance, long low-cycle-fatigue lives, low thermal expansion, and good thermal conductivity on a laboratory scale. The combination of properties has led to interest from the Rocketdyne Division of Boeing, Aerojet, and Pratt & Whitney for their new engines. Under the Space Launch Initiative/Next Generation Launch Technology program, GRCop-84 is being taken out of the laboratory and put into a full-scale production environment.

  11. Metabolic engineering as a tool for enhanced lactic acid production.

    PubMed

    Upadhyaya, Bikram P; DeVeaux, Linda C; Christopher, Lew P

    2014-12-01

    Metabolic engineering is a powerful biotechnological tool that finds, among others, increased use in constructing microbial strains for higher lactic acid productivity, lower costs and reduced pollution. Engineering the metabolic pathways has concentrated on improving the lactic acid fermentation parameters, enhancing the acid tolerance of production organisms and their abilities to utilize a broad range of substrates, including fermentable biomass-derived sugars. Recent efforts have focused on metabolic engineering of lactic acid bacteria as they produce high yields and have a small genome size that facilitates their genetic manipulation. We summarize here the current trends in metabolic engineering techniques and strategies for manipulating lactic acid producing organisms developed to address and overcome major challenges in the lactic acid production process.

  12. Metabolic engineering for the production of hydrocarbon fuels.

    PubMed

    Lee, Sang Yup; Kim, Hye Mi; Cheon, Seungwoo

    2015-06-01

    Biofuels have been attracting increasing attention to provide a solution to the problems of climate change and our dependence on limited fossil oil. During the last decade, metabolic engineering has been performed to develop superior microorganisms for the production of so called advanced biofuels. Among the advanced biofuels, hydrocarbons possess high-energy content and superior fuel properties to other biofuels, and thus have recently been attracting much research interest. Here we review the recent advances in the microbial production of hydrocarbon fuels together with the metabolic engineering strategies employed to develop their production strains. Strategies employed for the production of long-chain and short-chain hydrocarbons derived from fatty acid metabolism along with the isoprenoid-derived hydrocarbons are reviewed. Also, the current limitations and future prospects in hydrocarbon-based biofuel production are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Metabolic engineering for amino-, oligo-, and polysugar production in microbes.

    PubMed

    Hossain, Gazi Sakir; Shin, Hyun-Dong; Li, Jianghua; Wang, Miao; Du, Guocheng; Chen, Jian; Liu, Long

    2016-03-01

    Amino-, oligo-, and polysugars are important for both medicinal and industrial applications. Microbial processes used in production of such sugars are not only carbon-intensive and energy-demanding processes but also have other distinct disadvantages such as low productivity, low yields, and by-product contamination. Therefore, metabolic engineering has emerged as an effective tool for developing engineered strains to deliver production strategies for many valuable sugars, which were previously difficult to manufacture by other means, in necessary amounts to support their applications. In this review, the recent strategies used for metabolic engineering are summarized and future prospects of this technique are discussed. We hope that this review will contribute to the development of functional and high-value sugar production by metabolic engineering strategies.

  14. Scale up of proteoliposome derived Cochleate production.

    PubMed

    Zayas, Caridad; Bracho, Gustavo; Lastre, Miriam; González, Domingo; Gil, Danay; Acevedo, Reinaldo; del Campo, Judith; Taboada, Carlos; Solís, Rosa L; Barberá, Ramón; Pérez, Oliver

    2006-04-12

    Cochleate are highly stable structures with promising immunological features. Cochleate structures are usually obtaining from commercial lipids. Proteoliposome derived Cochleate are derived from an outer membrane vesicles of Neisseria meningitidis B. Previously, we obtained Cochleates using dialysis procedures. In order to increase the production process, we used a crossflow system (CFS) that allows easy scale up to obtain large batches in an aseptic environment. The raw material and solutions used in the production process are already approved for human application. This work demonstrates that CFS is very efficient process to obtain Cochleate structures with a yield of more than 80% and the immunogenicity comparable to that obtained by dialysis membrane.

  15. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    PubMed

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  16. Enumeration of smallest intervention strategies in genome-scale metabolic networks.

    PubMed

    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

  17. Replica scaling specifications for materials and production

    NASA Astrophysics Data System (ADS)

    Aune, R. B.; Lindgard, J.; Nygard, K.; Olden, V.

    1995-03-01

    Laboratory experiments of repeatable full scale precision tests on reinforced concrete elements exposed to blast loads require considerable resources, and are in many cases impossible with the test equipment available nationally and internationally. In this respect testing of scaled structural elements is advantageous. Model laws must be applied, and the effect of relaxations of a strict model law application must be well understood. The objective of this report is to give specifications for production of reinforced concrete slabs in replica scaling. Three slabs with different dimensions are included: 300 x 300 x 30 mm (P1), 1000 x 1000 x 100 mm (P2) and 3000 x 3000 x 300 mm (P3). Concrete mixes are developed for all three slabs. Concrete quality comply with C35, and similitude in the compressive strength between the mixes is required. Use of replica scaled accumulated aggregate grading curves was a part of the scope of work. Specifications for production of deformed bars with diameters 1.6 mm and 5.3 mm for P1 and P2, respectively, are developed. The material properties of the deformed bars comply with the Norwegian quality K500TE for reinforcement. Acceptable similitude between the stress-strain curves for the two dimensions is obtained.

  18. Unit Price Scaling Trends for Chemical Products

    SciTech Connect

    Qi, Wei; Sathre, Roger; William R. Morrow, III; Shehabi, Arman

    2015-08-01

    To facilitate early-stage life-cycle techno-economic modeling of emerging technologies, here we identify scaling relations between unit price and sales quantity for a variety of chemical products of three categories - metal salts, organic compounds, and solvents. We collect price quotations for lab-scale and bulk purchases of chemicals from both U.S. and Chinese suppliers. We apply a log-log linear regression model to estimate the price discount effect. Using the median discount factor of each category, one can infer bulk prices of products for which only lab-scale prices are available. We conduct out-of-sample tests showing that most of the price proxies deviate from their actual reference prices by a factor less than ten. We also apply the bootstrap method to determine if a sample median discount factor should be accepted for price approximation. We find that appropriate discount factors for metal salts and for solvents are both -0.56, while that for organic compounds is -0.67 and is less representative due to greater extent of product heterogeneity within this category.

  19. Large-scale ATLAS production on EGEE

    NASA Astrophysics Data System (ADS)

    Espinal, X.; Campana, S.; Walker, R.

    2008-07-01

    In preparation for first data at the LHC, a series of Data Challenges, of increasing scale and complexity, have been performed. Large quantities of simulated data have been produced on three different Grids, integrated into the ATLAS production system. During 2006, the emphasis moved towards providing stable continuous production, as is required in the immediate run-up to first data, and thereafter. Here, we discuss the experience of the production done on EGEE resources, using submission based on the gLite WMS, CondorG and a system using Condor Glide-ins. The overall wall time efficiency of around 90% is largely independent of the submission method, and the dominant source of wasted cpu comes from data handling issues. The efficiency of grid job submission is significantly worse than this, and the glide-in method benefits greatly from factorising this out.

  20. Scaling of standard metabolic rate in estuarine crocodiles Crocodylus porosus.

    PubMed

    Seymour, Roger S; Gienger, C M; Brien, Matthew L; Tracy, Christopher R; Charlie Manolis, S; Webb, Grahame J W; Christian, Keith A

    2013-05-01

    Standard metabolic rate (SMR, ml O2 min(-1)) of captive Crocodylus porosus at 30 °C scales with body mass (kg) according to the equation, SMR = 1.01 M(0.829), in animals ranging in body mass of 3.3 orders of magnitude (0.19-389 kg). The exponent is significantly higher than 0.75, so does not conform to quarter-power scaling theory, but rather is likely an emergent property with no single explanation. SMR at 1 kg body mass is similar to the literature for C. porosus and for alligators. The high exponent is not related to feeding, growth, or obesity of captive animals. The log-transformed data appear slightly curved, mainly because SMR is somewhat low in many of the largest animals (291-389 kg). A 3-parameter model is scarcely different from the linear one, but reveals a declining exponent between 0.862 and 0.798. A non-linear model on arithmetic axes overestimates SMR in 70% of the smallest animals and does not satisfactorily represent the data.

  1. Improvements in fermentative biological hydrogen production through metabolic engineering.

    PubMed

    Hallenbeck, Patrick C; Ghosh, Dipankar

    2012-03-01

    Replacement of fossil fuels with alternative energies is increasingly imperative in light of impending climate change and fossil fuel shortages. Biohydrogen has several potential advantages over other biofuels. Dark fermentation as a means of producing biohydrogen is attractive since a variety of readily available waste streams can be used. However, at present its practical application is prevented by the low yields obtained. Here the basic metabolisms leading to hydrogen production are outlined and current research to increase yields, either through modification of existing pathways, or by metabolic engineering to create new, higher yielding, pathways, is discussed. Inactivation of competing reactions and manipulation of culture conditions has lead to higher hydrogen yields, near those predicted by metabolic schemes. However, to be useful, hydrogen production must be increased beyond present limits. Several possibilities for surpassing those limits using metabolic engineering are presented.

  2. Plant Metabolic Engineering Strategies for the Production of Pharmaceutical Terpenoids

    PubMed Central

    Lu, Xu; Tang, Kexuan; Li, Ping

    2016-01-01

    Pharmaceutical terpenoids belong to the most diverse class of natural products. They have significant curative effects on a variety of diseases, such as cancer, cardiovascular diseases, malaria and Alzheimer’s disease. Nowadays, elicitors, including biotic and abiotic elicitors, are often used to activate the pathway of secondary metabolism and enhance the production of target terpenoids. Based on Agrobacterium-mediated genetic transformation, several plant metabolic engineering strategies hold great promise to regulate the biosynthesis of pharmaceutical terpenoids. Overexpressing terpenoids biosynthesis pathway genes in homologous and ectopic plants is an effective strategy to enhance the yield of pharmaceutical terpenoids. Another strategy is to suppress the expression of competitive metabolic pathways. In addition, global regulation which includes regulating the relative transcription factors, endogenous phytohormones and primary metabolism could also markedly increase their yield. All these strategies offer great opportunities to enhance the supply of scarce terpenoids drugs, reduce the price of expensive drugs and improve people’s standards of living. PMID:27877181

  3. A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation

    PubMed Central

    Dufault-Thompson, Keith; Jian, Huahua; Cheng, Ruixue; Li, Jiefu; Wang, Fengping

    2017-01-01

    ABSTRACT Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy

  4. A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation.

    PubMed

    Dufault-Thompson, Keith; Jian, Huahua; Cheng, Ruixue; Li, Jiefu; Wang, Fengping; Zhang, Ying

    2017-01-01

    Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation

  5. Universal scaling of production rates across mammalian lineages

    PubMed Central

    Hamilton, Marcus J.; Davidson, Ana D.; Sibly, Richard M.; Brown, James H.

    2011-01-01

    Over many millions of years of independent evolution, placental, marsupial and monotreme mammals have diverged conspicuously in physiology, life history and reproductive ecology. The differences in life histories are particularly striking. Compared with placentals, marsupials exhibit shorter pregnancy, smaller size of offspring at birth and longer period of lactation in the pouch. Monotremes also exhibit short pregnancy, but incubate embryos in eggs, followed by a long period of post-hatching lactation. Using a large sample of mammalian species, we show that, remarkably, despite their very different life histories, the scaling of production rates is statistically indistinguishable across mammalian lineages. Apparently all mammals are subject to the same fundamental metabolic constraints on productivity, because they share similar body designs, vascular systems and costs of producing new tissue. PMID:20798111

  6. Universal scaling of production rates across mammalian lineages.

    PubMed

    Hamilton, Marcus J; Davidson, Ana D; Sibly, Richard M; Brown, James H

    2011-02-22

    Over many millions of years of independent evolution, placental, marsupial and monotreme mammals have diverged conspicuously in physiology, life history and reproductive ecology. The differences in life histories are particularly striking. Compared with placentals, marsupials exhibit shorter pregnancy, smaller size of offspring at birth and longer period of lactation in the pouch. Monotremes also exhibit short pregnancy, but incubate embryos in eggs, followed by a long period of post-hatching lactation. Using a large sample of mammalian species, we show that, remarkably, despite their very different life histories, the scaling of production rates is statistically indistinguishable across mammalian lineages. Apparently all mammals are subject to the same fundamental metabolic constraints on productivity, because they share similar body designs, vascular systems and costs of producing new tissue.

  7. AlgaGEM – a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome

    PubMed Central

    2011-01-01

    Background Microalgae have the potential to deliver biofuels without the associated competition for land resources. In order to realise the rates and titres necessary for commercial production, however, system-level metabolic engineering will be required. Genome scale metabolic reconstructions have revolutionized microbial metabolic engineering and are used routinely for in silico analysis and design. While genome scale metabolic reconstructions have been developed for many prokaryotes and model eukaryotes, the application to less well characterized eukaryotes such as algae is challenging not at least due to a lack of compartmentalization data. Results We have developed a genome-scale metabolic network model (named AlgaGEM) covering the metabolism for a compartmentalized algae cell based on the Chlamydomonas reinhardtii genome. AlgaGEM is a comprehensive literature-based genome scale metabolic reconstruction that accounts for the functions of 866 unique ORFs, 1862 metabolites, 2249 gene-enzyme-reaction-association entries, and 1725 unique reactions. The reconstruction was compartmentalized into the cytoplasm, mitochondrion, plastid and microbody using available data for algae complemented with compartmentalisation data for Arabidopsis thaliana. AlgaGEM describes a functional primary metabolism of Chlamydomonas and significantly predicts distinct algal behaviours such as the catabolism or secretion rather than recycling of phosphoglycolate in photorespiration. AlgaGEM was validated through the simulation of growth and algae metabolic functions inferred from literature. Using efficient resource utilisation as the optimality criterion, AlgaGEM predicted observed metabolic effects under autotrophic, heterotrophic and mixotrophic conditions. AlgaGEM predicts increased hydrogen production when cyclic electron flow is disrupted as seen in a high producing mutant derived from mutational studies. The model also predicted the physiological pathway for H2 production and

  8. Genome-scale metabolic flux analysis of Streptomyces lividans growing on a complex medium.

    PubMed

    D'Huys, Pieter-Jan; Lule, Ivan; Vercammen, Dominique; Anné, Jozef; Van Impe, Jan F; Bernaerts, Kristel

    2012-09-15

    Constraint-based metabolic modeling comprises various excellent tools to assess experimentally observed phenotypic behavior of micro-organisms in terms of intracellular metabolic fluxes. In combination with genome-scale metabolic networks, micro-organisms can be investigated in much more detail and under more complex environmental conditions. Although complex media are ubiquitously applied in industrial fermentations and are often a prerequisite for high protein secretion yields, such multi-component conditions are seldom investigated using genome-scale flux analysis. In this paper, a systematic and integrative approach is presented to determine metabolic fluxes in Streptomyces lividans TK24 grown on a nutritious and complex medium. Genome-scale flux balance analysis and randomized sampling of the solution space are combined to extract maximum information from exometabolome profiles. It is shown that biomass maximization cannot predict the observed metabolite production pattern as such. Although this cellular objective commonly applies to batch fermentation data, both input and output constraints are required to reproduce the measured biomass production rate. Rich media hence not necessarily lead to maximum biomass growth. To eventually identify a unique intracellular flux vector, a hierarchical optimization of cellular objectives is adopted. Out of various tested secondary objectives, maximization of the ATP yield per flux unit returns the closest agreement with the maximum frequency in flux histograms. This unique flux estimation is hence considered as a reasonable approximation for the biological fluxes. Flux maps for different growth phases show no active oxidative part of the pentose phosphate pathway, but NADPH generation in the TCA cycle and NADPH transdehydrogenase activity are most important in fulfilling the NADPH balance. Amino acids contribute to biomass growth by augmenting the pool of available amino acids and by boosting the TCA cycle, particularly

  9. The Metabolic Costs of Sound Production in Odontocete Cetaceans

    DTIC Science & Technology

    2010-09-30

    1 DISTRIBUTION STATEMENT A: Approved for public release; distribution is unlimited. The Metabolic Costs of Sound Production in Odontocete...of masking from environmental sounds (NRC 2003). Although accumulating evidence from recent research (Scheifele et al. 2005, Holt et al. 2009, Parks...potential energetic costs of such compensation behavior are unknown. To our knowledge, there is no empirical data on the metabolic cost of sound

  10. The Metabolic Cost of Click Production in Bottlenose Dolphins

    DTIC Science & Technology

    2012-09-30

    of their acoustic signals as a strategy to help reduce the probability of masking from environmental sounds (NRC 2003). Although accumulating...date, the only empirical data on the metabolic cost of sound production as well as the metabolic cost of increasing the amplitude of acoustic signals...dolphins producing whistles and other communicative sounds (Holt et al. 2011 a, b, Noren et al. 2011). There is currently no information on energy

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

    PubMed Central

    2011-01-01

    Background Rhodobacter sphaeroides is one of the best studied purple non-sulfur photosynthetic bacteria and serves as an excellent model for the study of photosynthesis and the metabolic capabilities of this and related facultative organisms. The ability of R. sphaeroides to produce hydrogen (H2), polyhydroxybutyrate (PHB) or other hydrocarbons, as well as its ability to utilize atmospheric carbon dioxide (CO2) as a carbon source under defined conditions, make it an excellent candidate for use in a wide variety of biotechnological applications. A genome-level understanding of its metabolic capabilities should help realize this biotechnological potential. Results Here we present a genome-scale metabolic network model for R. sphaeroides strain 2.4.1, designated iRsp1095, consisting of 1,095 genes, 796 metabolites and 1158 reactions, including R. sphaeroides-specific biomass reactions developed in this study. Constraint-based analysis showed that iRsp1095 agreed well with experimental observations when modeling growth under respiratory and phototrophic conditions. Genes essential for phototrophic growth were predicted by single gene deletion analysis. During pathway-level analyses of R. sphaeroides metabolism, an alternative route for CO2 assimilation was identified. Evaluation of photoheterotrophic H2 production using iRsp1095 indicated that maximal yield would be obtained from growing cells, with this predicted maximum ~50% higher than that observed experimentally from wild type cells. Competing pathways that might prevent the achievement of this theoretical maximum were identified to guide future genetic studies. Conclusions iRsp1095 provides a robust framework for future metabolic engineering efforts to optimize the solar- and nutrient-powered production of biofuels and other valuable products by R. sphaeroides and closely related organisms. PMID:21777427

  12. Reducing maintenance metabolism by metabolic engineering of respiration improves riboflavin production by Bacillus subtilis.

    PubMed

    Zamboni, Nicola; Mouncey, Nigel; Hohmann, Hans-Peter; Sauer, Uwe

    2003-01-01

    We present redirection of electron flow to more efficient proton pumping branches within respiratory chains as a generally applicable metabolic engineering strategy, which tailors microbial metabolism to the specific requirements of high cell density processes by improving product and biomass yields. For the example of riboflavin production by Bacillus subtilis, we reduced the rate of maintenance metabolism by about 40% in a cytochrome bd oxidase knockout mutant. Since the putative Yth and the caa(3) oxidases were of minor importance, the most likely explanation for this improvement is translocation of two protons per transported electron via the remaining cytochrome aa(3) oxidase, instead of only one proton via the bd oxidase. The reduction of maintenance metabolism, in turn, significantly improved the yield of recombinant riboflavin and B. subtilis biomass in fed-batch cultures.

  13. Cardiac Metabolism in Heart Failure - Implications beyond ATP production

    PubMed Central

    Doenst, Torsten; Nguyen, T. Dung; Abel, E. Dale

    2013-01-01

    The heart has a high rate of ATP production and turnover which is required to maintain its continuous mechanical work. Perturbations in ATP generating processes may therefore affect contractile function directly. Characterizing cardiac metabolism in heart failure revealed several metabolic alterations termed metabolic remodeling, ranging from changes in substrate utilization to mitochondrial dysfunction, ultimately resulting in ATP deficiency and impaired contractility. However, ATP depletion is not the only relevant consequence of metabolic remodeling during heart failure. By providing cellular building blocks and signaling molecules, metabolic pathways control essential processes such as cell growth and regeneration. Thus, alterations in cardiac metabolism may also affect the progression to heart failure by mechanisms beyond ATP supply. Our aim is therefore to highlight that metabolic remodeling in heart failure not only results in impaired cardiac energetics, but also induces other processes implicated in the development of heart failure such as structural remodeling and oxidative stress. Accordingly, modulating cardiac metabolism in heart failure may have significant therapeutic relevance that goes beyond the energetic aspect. PMID:23989714

  14. Small-scale ethanol-production demonstration

    SciTech Connect

    Adcock, L.E. II; Eley, M.H.; Schroer, B.J.

    1981-09-01

    The Johnson Environmental and Energy Center with assistance from the Madison County Farm Bureau Association received a grant from the US Department of Energy to design, fabricate, and evaluate a small scale continuous ethanol plant. The scope of the study was to satisfy four specific objectives. The first objective was to design a small scale continuous distillation unit capable of producing 10 to 15 gallons per hour of 170 to 190 proof ethanol. A second objective was to economically fabricate the distillation unit. A third objective was to thoroughly evaluate the unit with emphasis on production potential, operation considerations, and energy balance. The fourth objective was to work with the Farm Bureau in identifying an organization that would place the unit in a production environment. The results of the study indicate that the distillation unit is capable of producing an average of 9 to 14 gallons per hour (based on alcohol percent in beer) of 174 proof ethanol. The energy ratio for distillation is a positive 3:1. Once the unit has reached steady state very little operator attention is required with the exception of periodically refluxing. Material cost of the plate column is approximately $5000. The unit could be built by an individual provided he is trained in welding and has the necessary shop equipment. The report also contains 7 appendices entitled: Principles of ethanol production; pump manufacturer specifications; boiler manufacturer specifications, water treatment manufacturer specifications; tank specifications; test results; and boiler efficiency data sheets. 39 figures, 112 tables.

  15. Metabolic Engineering of Microalgal Based Biofuel Production: Prospects and Challenges

    PubMed Central

    Banerjee, Chiranjib; Dubey, Kashyap K.; Shukla, Pratyoosh

    2016-01-01

    The current scenario in renewable energy is focused on development of alternate and sustainable energy sources, amongst which microalgae stands as one of the promising feedstock for biofuel production. It is well known that microalgae generate much larger amounts of biofuels in a shorter time than other sources based on plant seeds. However, the greatest challenge in a transition to algae-based biofuel production is the various other complications involved in microalgal cultivation, its harvesting, concentration, drying and lipid extraction. Several green microalgae accumulate lipids, especially triacylglycerols (TAGs), which are main precursors in the production of lipid. The various aspects on metabolic pathway analysis of an oleaginous microalgae i.e., Chlamydomonas reinhardtii have elucidated some novel metabolically important genes and this enhances the lipid production in this microalgae. Adding to it, various other aspects in metabolic engineering using OptFlux and effectual bioprocess design also gives an interactive snapshot of enhancing lipid production which ultimately improvises the oil yield. This article reviews the current status of microalgal based technologies for biofuel production, bioreactor process design, flux analysis and it also provides various strategies to increase lipids accumulation via metabolic engineering. PMID:27065986

  16. Metabolic Engineering of Microalgal Based Biofuel Production: Prospects and Challenges.

    PubMed

    Banerjee, Chiranjib; Dubey, Kashyap K; Shukla, Pratyoosh

    2016-01-01

    The current scenario in renewable energy is focused on development of alternate and sustainable energy sources, amongst which microalgae stands as one of the promising feedstock for biofuel production. It is well known that microalgae generate much larger amounts of biofuels in a shorter time than other sources based on plant seeds. However, the greatest challenge in a transition to algae-based biofuel production is the various other complications involved in microalgal cultivation, its harvesting, concentration, drying and lipid extraction. Several green microalgae accumulate lipids, especially triacylglycerols (TAGs), which are main precursors in the production of lipid. The various aspects on metabolic pathway analysis of an oleaginous microalgae i.e., Chlamydomonas reinhardtii have elucidated some novel metabolically important genes and this enhances the lipid production in this microalgae. Adding to it, various other aspects in metabolic engineering using OptFlux and effectual bioprocess design also gives an interactive snapshot of enhancing lipid production which ultimately improvises the oil yield. This article reviews the current status of microalgal based technologies for biofuel production, bioreactor process design, flux analysis and it also provides various strategies to increase lipids accumulation via metabolic engineering.

  17. Effects of hyperglycemia on bone metabolism and bone matrix in goldfish scales.

    PubMed

    Kitamura, Kei-Ichiro; Andoh, Tadashi; Okesaku, Wakana; Tazaki, Yuya; Ogai, Kazuhiro; Sugitani, Kayo; Kobayashi, Isao; Suzuki, Nobuo; Chen, Wenxi; Ikegame, Mika; Hattori, Atsuhiko

    2017-01-01

    Increased risk of fracture associated with type 2 diabetes has been a topic of recent concern. Fracture risk is related to a decrease in bone strength, which can be affected by bone metabolism and the quality of the bone. To investigate the cause of the increased fracture rate in patients with diabetes through analyses of bone metabolism and bone matrix protein properties, we used goldfish scales as a bone model for hyperglycemia. Using the scales of seven alloxan-treated and seven vehicle-treated control goldfish, we assessed bone metabolism by analyzing the activity of marker enzymes and mRNA expression of marker genes, and we measured the change in molecular weight of scale matrix proteins with SDS-PAGE. After only a 2-week exposure to hyperglycemia, the molecular weight of α- and β-fractions of bone matrix collagen proteins changed incrementally in the regenerating scales of hyperglycemic goldfish compared with those of euglycemic goldfish. In addition, the relative ratio of the γ-fraction significantly increased, and a δ-fraction appeared after adding glyceraldehyde-a candidate for the formation of advanced glycation end products in diabetes-to isolated type 1 collagen in vitro. The enzymatic activity and mRNA expression of osteoblast and osteoclast markers were not significantly different between hyperglycemic and euglycemic goldfish scales. These results indicate that hyperglycemia is likely to affect bone quality through glycation of matrix collagen from an early stage of hyperglycemia. Therefore, non-enzymatic glycation of collagen fibers in bone matrix may lead to the deterioration of bone quality from the onset of diabetes.

  18. Genome-Scale Model of Streptococcus thermophilus LMG18311 for Metabolic Comparison of Lactic Acid Bacteria▿ †

    PubMed Central

    Pastink, Margreet I.; Teusink, Bas; Hols, Pascal; Visser, Sanne; de Vos, Willem M.; Hugenholtz, Jeroen

    2009-01-01

    In this report, we describe the amino acid metabolism and amino acid dependency of the dairy bacterium Streptococcus thermophilus LMG18311 and compare them with those of two other characterized lactic acid bacteria, Lactococcus lactis and Lactobacillus plantarum. Through the construction of a genome-scale metabolic model of S. thermophilus, the metabolic differences between the three bacteria were visualized by direct projection on a metabolic map. The comparative analysis revealed the minimal amino acid auxotrophy (only histidine and methionine or cysteine) of S. thermophilus LMG18311 and the broad variety of volatiles produced from amino acids compared to the other two bacteria. It also revealed the limited number of pyruvate branches, forcing this strain to use the homofermentative metabolism for growth optimization. In addition, some industrially relevant features could be identified in S. thermophilus, such as the unique pathway for acetaldehyde (yogurt flavor) production and the absence of a complete pentose phosphate pathway. PMID:19346354

  19. Genome-scale reconstruction of Salinispora tropica CNB-440 metabolism to study strain-specific adaptation.

    PubMed

    Contador, C A; Rodríguez, V; Andrews, B A; Asenjo, J A

    2015-11-01

    The first manually curated genome-scale metabolic model for Salinispora tropica strain CNB-440 was constructed. The reconstruction enables characterization of the metabolic capabilities for understanding and modeling the cellular physiology of this actinobacterium. The iCC908 model was based on physiological and biochemical information of primary and specialised metabolism pathways. The reconstructed stoichiometric matrix consists of 1169 biochemical conversions, 204 transport reactions and 1317 metabolites. A total of 908 structural open reading frames (ORFs) were included in the reconstructed network. The number of gene functions included in the reconstructed network corresponds to 20% of all characterized ORFs in the S. tropica genome. The genome-scale metabolic model was used to study strain-specific capabilities in defined minimal media. iCC908 was used to analyze growth capabilities in 41 different minimal growth-supporting environments. These nutrient sources were evaluated experimentally to assess the accuracy of in silico growth simulations. The model predicted no auxotrophies for essential amino acids, which was corroborated experimentally. The strain is able to use 21 different carbon sources, 8 nitrogen sources and 4 sulfur sources from the nutrient sources tested. Experimental observation suggests that the cells may be able to store sulfur. False predictions provided opportunities to gain new insights into the physiology of this species, and to gap fill the missing knowledge. The incorporation of modifications led to increased accuracy in predicting the outcome of growth/no growth experiments from 76 to 93%. iCC908 can thus be used to define the metabolic capabilities of S. tropica and guide and enhance the production of specialised metabolites.

  20. BHP may scale up methanol production

    SciTech Connect

    Alperowicz, N.

    1993-06-23

    Broken Hill Pty. (BHP: Melbourne) says otherwise uneconomic gas reserves in the Timor Sea off northwest Australia could be developed if the company`s plans to commercialize a novel gas-to-methanol technology prove to be viable. BHP is building an A$70-million ($50 million) research unit in Victoria using ICI`s Leading Concept Methanol gas-to-methanol process. If this unit proves viable, it could be put on a vessel and taken to Timor Sea where BHP has oil exploration and production interests. Timor gas is not economically viable because of lack of nearby markets. The 54,000-m.t./year research plant, located at Werrbee near Melbourne, is scheduled to start production in the second half of 1994, according to BHP manager Joe Evon. The plant is being built by Davy/John Brown. Provided the economic climate is right, BHP is expected to build a world-scale methanol plant offshore.

  1. Advances in Metabolic Engineering of Cyanobacteria for Photosynthetic Biochemical Production

    PubMed Central

    Lai, Martin C.; Lan, Ethan I.

    2015-01-01

    Engineering cyanobacteria into photosynthetic microbial cell factories for the production of biochemicals and biofuels is a promising approach toward sustainability. Cyanobacteria naturally grow on light and carbon dioxide, bypassing the need of fermentable plant biomass and arable land. By tapping into the central metabolism and rerouting carbon flux towards desirable compound production, cyanobacteria are engineered to directly convert CO2 into various chemicals. This review discusses the diversity of bioproducts synthesized by engineered cyanobacteria, the metabolic pathways used, and the current engineering strategies used for increasing their titers. PMID:26516923

  2. Metabolic engineering for the microbial production of marine bioactive compounds.

    PubMed

    Mao, Xiangzhao; Liu, Zhen; Sun, Jianan; Lee, Sang Yup

    2017-03-06

    Many marine bioactive compounds have medicinal and nutritional values. These bioactive compounds have been prepared using solvent-based extraction from marine bio-resources or chemical synthesis, which are costly, inefficient with low yields, and environmentally unfriendly. Recent advances in metabolic engineering allowed to some extent more efficient production of these compounds, showing promises to meet the increasing demand of marine natural bioactive compounds. In this paper, we review the strategies and statuses of metabolic engineering applied to microbial production of marine natural bioactive compounds including terpenoids and their derivatives, omega-3 polyunsaturated fatty acids, and marine natural drugs, and provide perspectives. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast

    PubMed Central

    Misra, Ashish; Conway, Matthew F.; Johnnie, Joseph; Qureshi, Tabish M.; Lige, Bao; Derrick, Anne M.; Agbo, Eddy C.; Sriram, Ganesh

    2013-01-01

    Synthetic biology enables metabolic engineering of industrial microbes to synthesize value-added molecules. In this, a major challenge is the efficient redirection of carbon to the desired metabolic pathways. Pinpointing strategies toward this goal requires an in-depth investigation of the metabolic landscape of the organism, particularly primary metabolism, to identify precursor and cofactor availability for the target compound. The potent antimalarial therapeutic artemisinin and its precursors are promising candidate molecules for production in microbial hosts. Recent advances have demonstrated the production of artemisinin precursors in engineered yeast strains as an alternative to extraction from plants. We report the application of in silico and in vivo metabolic pathway analyses to identify metabolic engineering targets to improve the yield of the direct artemisinin precursor dihydroartemisinic acid (DHA) in yeast. First, in silico extreme pathway (ExPa) analysis identified NADPH-malic enzyme and the oxidative pentose phosphate pathway (PPP) as mechanisms to meet NADPH demand for DHA synthesis. Next, we compared key DHA-synthesizing ExPas to the metabolic flux distributions obtained from in vivo 13C metabolic flux analysis of a DHA-synthesizing strain. This comparison revealed that knocking out ethanol synthesis and overexpressing glucose-6-phosphate dehydrogenase in the oxidative PPP (gene YNL241C) or the NADPH-malic enzyme ME2 (YKL029C) are vital steps toward overproducing DHA. Finally, we employed in silico flux balance analysis and minimization of metabolic adjustment on a yeast genome-scale model to identify gene knockouts for improving DHA yields. The best strategy involved knockout of an oxaloacetate transporter (YKL120W) and an aspartate aminotransferase (YKL106W), and was predicted to improve DHA yields by 70-fold. Collectively, our work elucidates multiple non-trivial metabolic engineering strategies for improving DHA yield in yeast. PMID:23898325

  4. Segmented linear modeling of CHO fed-batch culture and its application to large scale production.

    PubMed

    Ben Yahia, Bassem; Gourevitch, Boris; Malphettes, Laetitia; Heinzle, Elmar

    2017-04-01

    We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed-batch cultures. Using the model structure and parameter values from a small-scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed-batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785-797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

  5. Segmented linear modeling of CHO fed‐batch culture and its application to large scale production

    PubMed Central

    Ben Yahia, Bassem; Gourevitch, Boris; Malphettes, Laetitia

    2016-01-01

    ABSTRACT We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed‐batch cultures. Using the model structure and parameter values from a small‐scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed‐batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785–797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. PMID:27869296

  6. Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets

    PubMed Central

    Kotera, Masaaki; Tabei, Yasuo; Yamanishi, Yoshihiro; Tokimatsu, Toshiaki; Goto, Susumu

    2013-01-01

    Motivation: The metabolic pathway is an important biochemical reaction network involving enzymatic reactions among chemical compounds. However, it is assumed that a large number of metabolic pathways remain unknown, and many reactions are still missing even in known pathways. Therefore, the most important challenge in metabolomics is the automated de novo reconstruction of metabolic pathways, which includes the elucidation of previously unknown reactions to bridge the metabolic gaps. Results: In this article, we develop a novel method to reconstruct metabolic pathways from a large compound set in the reaction-filling framework. We define feature vectors representing the chemical transformation patterns of compound–compound pairs in enzymatic reactions using chemical fingerprints. We apply a sparsity-induced classifier to learn what we refer to as ‘enzymatic-reaction likeness’, i.e. whether compound pairs are possibly converted to each other by enzymatic reactions. The originality of our method lies in the search for potential reactions among many compounds at a time, in the extraction of reaction-related chemical transformation patterns and in the large-scale applicability owing to the computational efficiency. In the results, we demonstrate the usefulness of our proposed method on the de novo reconstruction of 134 metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG). Our comprehensively predicted reaction networks of 15 698 compounds enable us to suggest many potential pathways and to increase research productivity in metabolomics. Availability: Softwares are available on request. Supplementary material are available at http://web.kuicr.kyoto-u.ac.jp/supp/kot/ismb2013/. Contact: goto@kuicr.kyoto-u.ac.jp PMID:23812977

  7. Design and application of genome-scale reconstructed metabolic models.

    PubMed

    Rocha, Isabel; Förster, Jochen; Nielsen, Jens

    2008-01-01

    In this chapter, the process for the reconstruction of genome-scale metabolic networks is described, and some of the main applications of such models are illustrated. The reconstruction process can be viewed as an iterative process where information obtained from several sources is combined to construct a preliminary set of reactions and constraints. This involves steps such as genome annotation; identification of the reactions from the annotated genome sequence and available literature; determination of the reaction stoichiometry; definition of compartmentation and assignment of localization; determination of the biomass composition; measurement, calculation, or fitting of energy requirements; and definition of additional constraints. The reaction and constraint sets, after debugging, may be integrated into a stoichiometric model that can be used for simulation using tools such as Flux Balance Analysis (Section 3.8). From the flux distributions obtained, physiologic parameters such as growth yields or minimal medium components can be calculated, and their distance from similar experimental data provides a basis from where the model may need to be improved.

  8. Metabolic engineering of bacteria for ethanol production

    SciTech Connect

    Ingram, L.O.; Gomez, P.F.; Lai, X.; Moniruzzaman, M.; Wood, B.E.; Yomano, L.P.; York, S.W.

    1998-04-20

    Technologies are available which will allow the conversion of lignocellulose into fuel ethanol using genetically engineered bacteria. Assembling these into a cost-effective process remains a challenge. The authors` work has focused primarily on the genetic engineering of enteric bacteria using a portable ethanol production pathway. Genes encoding Zymomonas mobilis pyruvate decarboxylase and alcohol dehydrogenase have been integrated into the chromosome of Escherichia coli B to produce strain KO11 for the fermentation of hemicellulose-derived syrups. This organism can efficiently ferment all hexose and pentose sugars present in the polymers of hemicellulose. Klebsiella oxytoca M5A1 has been genetically engineered in a similar manner to produce strain P2 for ethanol production from cellulose. This organism has the native ability to ferment cellobiose and cellotriose, eliminating the need for one class of cellulase enzymes. The optimal pH for cellulose fermentation with this organism is near that of fungal cellulases. The general approach for the genetic engineering of new biocatalysts has been most successful with enteric bacteria thus far. However, this approach may also prove useful with gram-positive bacteria which have other important traits for lignocellulose conversion. Many opportunities remain for further improvements in the biomass to ethanol processes.

  9. Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up

    PubMed Central

    Muhamadali, Howbeer; Xu, Yun; Ellis, David I.; Allwood, J. William; Rattray, Nicholas J. W.; Correa, Elon; Alrabiah, Haitham

    2015-01-01

    During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However

  10. A common scaling rule for abundance, energetics, and production of parasitic and free-living species

    USGS Publications Warehouse

    Hechinger, Ryan F.; Lafferty, Kevin D.; Dobson, Andy P.; Brown, James H.; Kuris, Armand M.

    2011-01-01

    The metabolic theory of ecology uses the scaling of metabolism with body size and temperature to explain the causes and consequences of species abundance. However, the theory and its empirical tests have never simultaneously examined parasites alongside free-living species. This is unfortunate because parasites represent at least half of species diversity. We show that metabolic scaling theory could not account for the abundance of parasitic or free-living species in three estuarine food webs until accounting for trophic dynamics. Analyses then revealed that the abundance of all species uniformly scaled with body mass to the - 3/4 power. This result indicates "production equivalence," where biomass production within trophic levels is invariant of body size across all species and functional groups: invertebrate or vertebrate, ectothermic or endothermic, and free-living or parasitic.

  11. A common scaling rule for abundance, energetics, and production of parasitic and free-living species.

    PubMed

    Hechinger, Ryan F; Lafferty, Kevin D; Dobson, Andy P; Brown, James H; Kuris, Armand M

    2011-07-22

    The metabolic theory of ecology uses the scaling of metabolism with body size and temperature to explain the causes and consequences of species abundance. However, the theory and its empirical tests have never simultaneously examined parasites alongside free-living species. This is unfortunate because parasites represent at least half of species diversity. We show that metabolic scaling theory could not account for the abundance of parasitic or free-living species in three estuarine food webs until accounting for trophic dynamics. Analyses then revealed that the abundance of all species uniformly scaled with body mass to the -¾ power. This result indicates "production equivalence," where biomass production within trophic levels is invariant of body size across all species and functional groups: invertebrate or vertebrate, ectothermic or endothermic, and free-living or parasitic.

  12. Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production

    PubMed Central

    Nocon, Justyna; Steiger, Matthias G.; Pfeffer, Martin; Sohn, Seung Bum; Kim, Tae Yong; Maurer, Michael; Rußmayer, Hannes; Pflügl, Stefan; Ask, Magnus; Haberhauer-Troyer, Christina; Ortmayr, Karin; Hann, Stephan; Koellensperger, Gunda; Gasser, Brigitte; Lee, Sang Yup; Mattanovich, Diethard

    2014-01-01

    The production of recombinant proteins is frequently enhanced at the levels of transcription, codon usage, protein folding and secretion. Overproduction of heterologous proteins, however, also directly affects the primary metabolism of the producing cells. By incorporation of the production of a heterologous protein into a genome scale metabolic model of the yeast Pichia pastoris, the effects of overproduction were simulated and gene targets for deletion or overexpression for enhanced productivity were predicted. Overexpression targets were localized in the pentose phosphate pathway and the TCA cycle, while knockout targets were found in several branch points of glycolysis. Five out of 9 tested targets led to an enhanced production of cytosolic human superoxide dismutase (hSOD). Expression of bacterial β-glucuronidase could be enhanced as well by most of the same genetic modifications. Beneficial mutations were mainly related to reduction of the NADP/H pool and the deletion of fermentative pathways. Overexpression of the hSOD gene itself had a strong impact on intracellular fluxes, most of which changed in the same direction as predicted by the model. In vivo fluxes changed in the same direction as predicted to improve hSOD production. Genome scale metabolic modeling is shown to predict overexpression and deletion mutants which enhance recombinant protein production with high accuracy. PMID:24853352

  13. Metabolic engineering of Escherichia coli for poly(3-hydroxybutyrate) production via threonine bypass.

    PubMed

    Lin, Zhenquan; Zhang, Yan; Yuan, Qianqian; Liu, Qiaojie; Li, Yifan; Wang, Zhiwen; Ma, Hongwu; Chen, Tao; Zhao, Xueming

    2015-11-20

    Poly(3-hydroxybutyrate) (PHB), have been considered to be good candidates for completely biodegradable polymers due to their similar mechanical properties to petroleum-derived polymers and complete biodegradability. Escherichia coli has been used to simulate the distribution of metabolic fluxes in recombinant E. coli producing poly(3-hydroxybutyrate) (PHB). Genome-scale metabolic network analysis can reveal unexpected metabolic engineering strategies to improve the production of biochemicals and biofuels. In this study, we reported the discovery of a new pathway called threonine bypass by flux balance analysis of the genome-scale metabolic model of E. coli. This pathway, mainly containing the reactions for threonine synthesis and degradation, can potentially increase the yield of PHB and other acetyl-CoA derived products by reutilizing the CO2 released at the pyruvate dehydrogenase step. To implement the threonine bypass for PHB production in E. coli, we deregulated the threonine and serine degradation pathway and enhanced the threonine synthesis, resulting in 2.23-fold improvement of PHB titer. Then, we overexpressed glyA to enhance the conversion of glycine to serine and activated transhydrogenase to generate NADPH required in the threonine bypass. The result strain TB17 (pBHR68) produced 6.82 g/L PHB with the yield of 0.36 g/g glucose in the shake flask fermentation and 35.92 g/L PHB with the yield of 0.23 g/g glucose in the fed-batch fermentation, which was almost 3.3-fold higher than the parent strain. The work outlined here shows that genome-scale metabolic network analysis can reveal novel metabolic engineering strategies for developing efficient microbial cell factories.

  14. Scale Impacts in Net Ecosystem Productivity Estimations

    NASA Astrophysics Data System (ADS)

    Carvalhais, N.; Myneni, R.

    2004-12-01

    Net ecosystem production (NEP) estimations play a key role in the terrestrial carbon cycle assessment, both at regional and global scales studies. The emergence of remote sensing greatly improved NEP estimation methods and analysis domain. Yet, spatial and temporal resolution of sensors and remote sensing products often imply adjustments to NEP calculation methods. The Carnegie Ames Stanford Approach (CASA) terrestrial biogeochemical model (Potter et al., 1993; Friedlingstein et al., 1999) simulates plant and soil processes allowing the estimation of NEP through the difference between net primary productivity and soil respiration. CASA inputs include climatic data: precipitation, temperature and solar radiation; soil texture; vegetation type and percentage cover; as well as leaf area index (LAI), fraction of photosynthetically active radiation absorbed by vegetation (FPAR) and normalized difference vegetation index (NDVI). With a research interest in regional vegetation dynamics in the Iberian Peninsula (IP), estimations of NEP were compared with local measurements over a Quercus ilex and Quercus suber with perennial grassland ecosystem, representing a region characteristic land cover. The CASA calibration process aimed the tuning of efficiency scalars directly related to net primary productivity and soil respiration calculations, maximum light use efficiency (å*) and temperature effect on soil fluxes (Q10). To this end local weather station data was used as climatic inputs, with remotely sensed LAI, FPAR and NDVI products from MODIS sensor. In a first approach the NEP calculations were performed at a finer spatial and temporal resolution of 1 km and 8 days, respectively, for the periods of 2002 and 2003 (years of available NEP measurements). A confident correlation is found, although local extremes tend to differ and affect the annual balance concordance between estimations and measurements of NEP. Consequently, calibrated å* and Q10 values were used at coarser

  15. Intramolecular stable isotope distributions detect plant metabolic responses on century time scales

    NASA Astrophysics Data System (ADS)

    Schleucher, Jürgen; Ehlers, Ina; Augusti, Angela; Betson, Tatiana

    2014-05-01

    Plants respond to environmental changes on a vast range of time scales, and plant gas exchanges constitute important feedback mechanisms in the global C cycle. Responses on time scales of decades to centuries are most important for climate models, for prediction of crop productivity, and for adaptation to climate change. Unfortunately, responses on these timescale are least understood. We argue that the knowledge gap on intermediate time scales is due to a lack of adequate methods that can bridge between short-term manipulative experiments (e.g. FACE) and paleo research. Manipulative experiments in plant ecophysiology give information on metabolism on time scales up to years. However, this information cannot be linked to results from retrospective studies in paleo research, because little metabolic information can be derived from paleo archives. Stable isotopes are prominent tools in plant ecophysiology, biogeochemistry and in paleo research, but in all applications to date, isotope ratios of whole molecules are measured. However, it is well established that stable isotope abundance varies among intramolecular groups of biochemical metabolites, that is each so-called "isotopomer" has a distinct abundance. This intramolecular variation carries information on metabolic regulation, which can even be traced to individual enzymes (Schleucher et al., Plant, Cell Environ 1999). Here, we apply intramolecular isotope distributions to study the metabolic response of plants to increasing atmospheric [CO2] during the past century. Greenhouse experiments show that the deuterium abundance among the two positions in the C6H2 group of photosynthetic glucose depends on [CO2] during growth. This is observed for all plants using C3 photosynthesis, and reflects the metabolic flux ratio between photorespiration and photosynthesis. Photorespiration is a major C flux that limits assimilation in C3 plants, which encompass the overwhelming fraction of terrestrial photosynthesis and the

  16. Metabolic Design and Control for Production in Prokaryotes

    SciTech Connect

    Chhabra, Swapnil R.; Keasling, J.D.

    2010-11-10

    Prokaryotic life on earth is manifested by its diversity and omnipresence. These microbes serve as natural sources of a large variety of compounds with the potential to serve the ever growing, medicinal, chemical and transportation needs of the human population. However, commercially viable production of these compounds can be realized only through significant improvement of the native production capacity of natural isolates. The most favorable way to achieve this goal is through the genetic manipulation of metabolic pathways that direct the production of these molecules. While random mutagenesis and screening have dominated the industrial production of such compounds in the past our increased understanding of microbial physiology over the last five decades has shifted this trend towards rational approaches for metabolic design. Major drivers of this trend include recombinant DNA technology, high throughput characterization of macromolecular cellular components, quantitative modeling for metabolic engine ring, targeted combinatorial engineering and synthetic biology. In this chapter we track the evolution of microbial engineering technologies from the black box era of random mutagenesis to the science and engineering-driven era of metabolic design.

  17. Metabolic differences in cattle with excitable temperaments can influence productivity

    USDA-ARS?s Scientific Manuscript database

    Temperament can negatively affect various production traits, including live weight, ADG, DMI, conception rates, and carcass weight. Three research studies are summarized which indicate the potential influence of temperament on metabolism. In Brahman heifers, (n=12) the 6 most temperamental and 6 mos...

  18. Production of L-carnitine by secondary metabolism of bacteria

    PubMed Central

    Bernal, Vicente; Sevilla, Ángel; Cánovas, Manuel; Iborra, José L

    2007-01-01

    The increasing commercial demand for L-carnitine has led to a multiplication of efforts to improve its production with bacteria. The use of different cell environments, such as growing, resting, permeabilized, dried, osmotically stressed, freely suspended and immobilized cells, to maintain enzymes sufficiently active for L-carnitine production is discussed in the text. The different cell states of enterobacteria, such as Escherichia coli and Proteus sp., which can be used to produce L-carnitine from crotonobetaine or D-carnitine as substrate, are analyzed. Moreover, the combined application of both bioprocess and metabolic engineering has allowed a deeper understanding of the main factors controlling the production process, such as energy depletion and the alteration of the acetyl-CoA/CoA ratio which are coupled to the end of the biotransformation. Furthermore, the profiles of key central metabolic activities such as the TCA cycle, the glyoxylate shunt and the acetate metabolism are seen to be closely interrelated and affect the biotransformation efficiency. Although genetically modified strains have been obtained, new strain improvement strategies are still needed, especially in Escherichia coli as a model organism for molecular biology studies. This review aims to summarize and update the state of the art in L-carnitine production using E. coli and Proteus sp, emphasizing the importance of proper reactor design and operation strategies, together with metabolic engineering aspects and the need for feed-back between wet and in silico work to optimize this biotransformation. PMID:17910757

  19. Reconstruction of genome-scale human metabolic models using omics data.

    PubMed

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-08-01

    The impact of genome-scale human metabolic models on human systems biology and medical sciences is becoming greater, thanks to increasing volumes of model building platforms and publicly available omics data. The genome-scale human metabolic models started with Recon 1 in 2007, and have since been used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic models. Integration of tissue/cell type-specific omics data with the generic human metabolic models is the key step, and we discuss omics data and their integration methods to achieve this task. The initial version of the tissue/cell type-specific human metabolic models can further be computationally refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model.

  20. Major evolutionary transitions of life, metabolic scaling and the number and size of mitochondria and chloroplasts.

    PubMed

    Okie, Jordan G; Smith, Val H; Martin-Cereceda, Mercedes

    2016-05-25

    We investigate the effects of trophic lifestyle and two types of major evolutionary transitions in individuality-the endosymbiotic acquisition of organelles and development of multicellularity-on organellar and cellular metabolism and allometry. We develop a quantitative framework linking the size and metabolic scaling of eukaryotic cells to the abundance, size and metabolic scaling of mitochondria and chloroplasts and analyse a newly compiled, unprecedented database representing unicellular and multicellular cells covering diverse phyla and tissues. Irrespective of cellularity, numbers and total volumes of mitochondria scale linearly with cell volume, whereas chloroplasts scale sublinearly and sizes of both organelles remain largely invariant with cell size. Our framework allows us to estimate the metabolic scaling exponents of organelles and cells. Photoautotrophic cells and organelles exhibit photosynthetic scaling exponents always less than one, whereas chemoheterotrophic cells and organelles have steeper respiratory scaling exponents close to one. Multicellularity has no discernible effect on the metabolic scaling of organelles and cells. In contrast, trophic lifestyle has a profound and uniform effect, and our results suggest that endosymbiosis fundamentally altered the metabolic scaling of free-living bacterial ancestors of mitochondria and chloroplasts, from steep ancestral scaling to a shallower scaling in their endosymbiotic descendants.

  1. Major evolutionary transitions of life, metabolic scaling and the number and size of mitochondria and chloroplasts

    PubMed Central

    Okie, Jordan G.; Smith, Val H.; Martin-Cereceda, Mercedes

    2016-01-01

    We investigate the effects of trophic lifestyle and two types of major evolutionary transitions in individuality—the endosymbiotic acquisition of organelles and development of multicellularity—on organellar and cellular metabolism and allometry. We develop a quantitative framework linking the size and metabolic scaling of eukaryotic cells to the abundance, size and metabolic scaling of mitochondria and chloroplasts and analyse a newly compiled, unprecedented database representing unicellular and multicellular cells covering diverse phyla and tissues. Irrespective of cellularity, numbers and total volumes of mitochondria scale linearly with cell volume, whereas chloroplasts scale sublinearly and sizes of both organelles remain largely invariant with cell size. Our framework allows us to estimate the metabolic scaling exponents of organelles and cells. Photoautotrophic cells and organelles exhibit photosynthetic scaling exponents always less than one, whereas chemoheterotrophic cells and organelles have steeper respiratory scaling exponents close to one. Multicellularity has no discernible effect on the metabolic scaling of organelles and cells. In contrast, trophic lifestyle has a profound and uniform effect, and our results suggest that endosymbiosis fundamentally altered the metabolic scaling of free-living bacterial ancestors of mitochondria and chloroplasts, from steep ancestral scaling to a shallower scaling in their endosymbiotic descendants. PMID:27194700

  2. 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.

  3. Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation.

    PubMed

    Flahaut, Nicolas A L; Wiersma, Anne; van de Bunt, Bert; Martens, Dirk E; Schaap, Peter J; Sijtsma, Lolke; Dos Santos, Vitor A Martins; de Vos, Willem M

    2013-10-01

    Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.

  4. Scaling violation in inclusive jet production

    NASA Astrophysics Data System (ADS)

    Akopian, Alexander Michael

    1999-10-01

    Inclusive jet production in proton-antiproton collisions is studied with the CDF detector in the [h] range 0.1-0.7, at center of mass energies of s=630 and 1800 GeV. The ratio of scaled cross sections at two values of s is compared to Next-to-Leading Order (NLO) QCD predictions. Discrepancy with NLO QCD predictions at low values of fractional transverse momenta of jet xt(≡2Et/ s) is observed. This result confirms the previous measurement by CDF at center of mass energies of 546 and 1800 GeV.

  5. A metabolic derivation of tritium transfer coefficients in animal products.

    PubMed

    Galeriu, D; Crout, N M; Melintescu, A; Beresford, N A; Peterson, S R; Van Hees, M

    2001-12-01

    Tritium is a potentially important environmental contaminant originating from the nuclear industry, and its behaviour in the environment is controlled by that of hydrogen. Animal food products represent a potentially important source of tritium in the human diet and a number of transfer coefficient values for tritium transfer to a limited number of animal products are available. In this paper we present an approach for the derivation of tritium transfer coefficients which is based on the metabolism of hydrogen in animals. The derived transfer coefficients separately account for transfer to and from free (i.e. water) and organically bound tritium. A novel aspect of the approach is that tritium transfer can be predicted for any animal product for which the required metabolic input parameters are available. The predicted transfer coefficients are compared to available independent data. Agreement is good (R2=0.97) with the exception of the transfer coefficient for transfer from tritiated water to organically bound tritium in ruminants. This may be attributable to the particular characteristics of ruminant digestion. We show that tritium transfer coefficients will vary in response to the metabolic status of an animal (e.g. stage of lactation, diet digestibility etc.) and that the use of a single transfer coefficient from diet to animal product is inappropriate. It is possible to derive concentration ratio values from the estimated transfer coefficients which relate the concentration of tritiated water and organically bound tritium in an animal product to their respective concentrations in the animals diet. These concentration ratios are shown to be less subject to metabolic variation and may be more useful radioecological parameters than transfer coefficients. For tritiated water the concentration ratio shows little variation between animal products ranging from 0.59 to 0.82. In the case of organically bound tritium the concentration ratios vary between animal products

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

  8. Investigation on metabolism of cisplatin resistant ovarian cancer using a genome scale metabolic model and microarray data

    PubMed Central

    Motamedian, Ehsan; Ghavami, Ghazaleh; Sardari, Soroush

    2015-01-01

    Objective(s): Many cancer cells show significant resistance to drugs that kill drug sensitive cancer cells and non-tumor cells and such resistance might be a consequence of the difference in metabolism. Therefore, studying the metabolism of drug resistant cancer cells and comparison with drug sensitive and normal cell lines is the objective of this research. Material and Methods: Metabolism of cisplatin resistant and sensitive A2780 epithelial ovarian cancer cells and normal ovarian epithelium has been studied using a generic human genome-scale metabolic model and transcription data. Result: The results demonstrate that the most different metabolisms belong to resistant and normal models, and the different reactions are involved in various metabolic pathways. However, large portion of distinct reactions are related to extracellular transport for three cell lines. Capability of metabolic models to secrete lactate was investigated to find the origin of Warburg effect. Computational results introduced SLC25A10 gene, which encodes mitochondrial dicarboxylate transporter involved in exchanging of small metabolites across the mitochondrial membrane that may play key role in high growing capacity of sensitive and resistant cancer cells. The metabolic models were also used to find single and combinatorial targets that reduce the cancer cells growth. Effect of proposed target genes on growth and oxidative phosphorylation of normal cells were determined to estimate drug side-effects. Conclusion: The deletion results showed that although the cisplatin did not cause resistant cancer cells death, but it shifts the cancer cells to a more vulnerable metabolism. PMID:25945240

  9. Fumaric Acid Production in Saccharomyces cerevisiae by In Silico Aided Metabolic Engineering

    PubMed Central

    Xu, Guoqiang; Zou, Wei; Chen, Xiulai; Xu, Nan; Liu, Liming; Chen, Jian

    2012-01-01

    Fumaric acid (FA) is a promising biomass-derived building-block chemical. Bio-based FA production from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. Here we report on FA production by direct fermentation using metabolically engineered Saccharomyces cerevisiae with the aid of in silico analysis of a genome-scale metabolic model. First, FUM1 was selected as the target gene on the basis of extensive literature mining. Flux balance analysis (FBA) revealed that FUM1 deletion can lead to FA production and slightly lower growth of S. cerevisiae. The engineered S. cerevisiae strain obtained by deleting FUM1 can produce FA up to a concentration of 610±31 mg L–1 without any apparent change in growth in fed-batch culture. FT-IR and 1H and 13C NMR spectra confirmed that FA was synthesized by the engineered S. cerevisiae strain. FBA identified pyruvate carboxylase as one of the factors limiting higher FA production. When the RoPYC gene was introduced, S. cerevisiae produced 1134±48 mg L–1 FA. Furthermore, the final engineered S. cerevisiae strain was able to produce 1675±52 mg L–1 FA in batch culture when the SFC1 gene encoding a succinate–fumarate transporter was introduced. These results demonstrate that the model shows great predictive capability for metabolic engineering. Moreover, FA production in S. cerevisiae can be efficiently developed with the aid of in silico metabolic engineering. PMID:23300594

  10. Altered sucrose metabolism impacts plant biomass production and flower development.

    PubMed

    Coleman, Heather D; Beamish, Leigh; Reid, Anya; Park, Ji-Young; Mansfield, Shawn D

    2010-04-01

    Nicotiana tabacum (tobacco) was transformed with three genes involved in sucrose metabolism, UDP-glucose pyrophosphorylase (UGPase, EC 2.7.7.9), sucrose synthase (SuSy, EC 2.4.1.13) and sucrose phosphate synthase (SPS, EC 2.4.1.14). Plants harbouring the single transgenes were subsequently crossed to produce double and triple transgenic lines, including: 2 x 35S::UGPase x SPS, 4CL::UGPase x SPS, 2 x 35S::SuSy x SPS, 4CL::SuSy x SPS, 2 x 35S::UGPase x SuSy x SPS, and 4CL::UGPase x SuSy x SPS. The ultimate aim of the study was to examine whether it is possible to alter cellulose production through the manipulation of sucrose metabolism genes. While altering sucrose metabolism using UGPase, SuSy and SPS does not have an end effect on cellulose production, their simultaneous overexpression resulted in enhanced primary growth as seen in an increase in height growth, in some cases over 50%. Furthermore, the pyramiding strategy of simultaneously altering the expression of multiple genes in combination resulted in increased time to reproductive bud formation as well as altered flower morphology and foliar stipule formation in 4CL lines. Upregulation of these sucrose metabolism genes appears to directly impact primary growth and therefore biomass production in tobacco.

  11. Shift in metabolism towards ethanol production in Saccharomyces cerevisiae by addition of metabolic inhibitors

    SciTech Connect

    Hahn-Haegerdal, B.; Mattiasson, B.

    1982-01-01

    The future exploitation of fermentation processes for the production of bulk chemicals will very much depend on whether product yield and product concentration can be improved. At the present time the cost for the raw material and the product upgrading limits the competitiveness of fermentation processes in relation to petrochemical processes. Much effort is put into selecting microbial strains with higher product yields as well as improved tolerance towards increased product concentrations. This approach is rather laborious and time-consuming and the overall goal will be beneficial if it is complemented with other techniques. This investigation will describe how productivity migh be improved by addition of a specific metabolic inhibitor, sodium azide, which inhibits the cytochrome oxidase of the respiratory chain. As a model for these studies Saccaromyces cerevisiae fermenting glucose to ethanol was chosen.

  12. Metabolic engineering of Escherichia coli to improve recombinant protein production.

    PubMed

    Liu, Min; Feng, Xinjun; Ding, Yamei; Zhao, Guang; Liu, Huizhou; Xian, Mo

    2015-12-01

    Escherichia coli is one of the most widely used strains for recombinant protein production. However, obstacles also exist in both academic researches and industrial applications, such as the metabolic burden, the carbon source waste, and the cells' physiological deterioration. This article reviews recent approaches for improving recombinant protein production in metabolic engineering, including workhorse selection, stress factor application, and carbon flux regulation. Selecting a suitable host is the first key point for recombinant protein production. In general, it all depends on characteristics of the strains and the target proteins. It will be triggered cells physiological deterioration when the medium is significantly different from the cell's natural environment. Coexpression of stress factors can help proteins to fold into their native conformation. Carbon flux regulation is a direct approach for redirecting more carbon flux toward the desirable pathways and products. However, some undesirable consequences are usually found in metabolic engineering, such as glucose transport inhibition, cell growth retardation, and useless metabolite accumulation. More efficient regulators and platform cell factories should be explored to meet a variety of production demands.

  13. Metabolic engineering of microorganisms for the production of higher alcohols.

    PubMed

    Choi, Yong Jun; Lee, Joungmin; Jang, Yu-Sin; Lee, Sang Yup

    2014-09-02

    Due to the increasing concerns about limited fossil resources and environmental problems, there has been much interest in developing biofuels from renewable biomass. Ethanol is currently used as a major biofuel, as it can be easily produced by existing fermentation technology, but it is not the best biofuel due to its low energy density, high vapor pressure, hygroscopy, and incompatibility with current infrastructure. Higher alcohols, including 1-propanol, 1-butanol, isobutanol, 2-methyl-1-butanol, and 3-methyl-1-butanol, which possess fuel properties more similar to those of petroleum-based fuel, have attracted particular interest as alternatives to ethanol. Since microorganisms isolated from nature do not allow production of these alcohols at high enough efficiencies, metabolic engineering has been employed to enhance their production. Here, we review recent advances in metabolic engineering of microorganisms for the production of higher alcohols.

  14. Metabolic Engineering of Microorganisms for the Production of Higher Alcohols

    PubMed Central

    Choi, Yong Jun; Lee, Joungmin; Jang, Yu-Sin

    2014-01-01

    ABSTRACT Due to the increasing concerns about limited fossil resources and environmental problems, there has been much interest in developing biofuels from renewable biomass. Ethanol is currently used as a major biofuel, as it can be easily produced by existing fermentation technology, but it is not the best biofuel due to its low energy density, high vapor pressure, hygroscopy, and incompatibility with current infrastructure. Higher alcohols, including 1-propanol, 1-butanol, isobutanol, 2-methyl-1-butanol, and 3-methyl-1-butanol, which possess fuel properties more similar to those of petroleum-based fuel, have attracted particular interest as alternatives to ethanol. Since microorganisms isolated from nature do not allow production of these alcohols at high enough efficiencies, metabolic engineering has been employed to enhance their production. Here, we review recent advances in metabolic engineering of microorganisms for the production of higher alcohols. PMID:25182323

  15. Scaling metabolism from individuals to reef-fish communities at broad spatial scales.

    PubMed

    Barneche, D R; Kulbicki, M; Floeter, S R; Friedlander, A M; Maina, J; Allen, A P

    2014-09-01

    Fishes contribute substantially to energy and nutrient fluxes in reef ecosystems, but quantifying these roles is challenging. Here, we do so by synthesising a large compilation of fish metabolic-rate data with a comprehensive database on reef-fish community abundance and biomass. Individual-level analyses support predictions of Metabolic Theory after accounting for significant family-level variation, and indicate that some tropical reef fishes may already be experiencing thermal regimes at or near their temperature optima. Community-level analyses indicate that total estimated respiratory fluxes of reef-fish communities increase on average ~2-fold from 22 to 28 °C. Comparisons of estimated fluxes among trophic groups highlight striking differences in resource use by communities in different regions, perhaps partly reflecting distinct evolutionary histories, and support the hypothesis that piscivores receive substantial energy subsidies from outside reefs. Our study demonstrates one approach to synthesising individual- and community-level data to establish broad-scale trends in contributions of biota to ecosystem dynamics. © 2014 John Wiley & Sons Ltd/CNRS.

  16. Enhanced flavonoid production in Streptomyces venezuelae via metabolic engineering.

    PubMed

    Park, Sung Ryeol; Ahn, Mi Sun; Han, Ah Reum; Park, Je Won; Yoon, Yeo Joon

    2011-11-01

    Metabolic engineering of plant-specific phenylpropanoid biosynthesis has attracted an increasing amount of attention recently, owing to the vast potential of flavonoids as nutraceuticals and pharmaceuticals. Recently, we have developed a recombinant Streptomyces venezuelae as a heterologous host for the production of flavonoids. In this study, we successfully improved flavonoid production by expressing two sets of genes predicted to be involved in malonate assimilation. The introduction of matB and matC encoding for malonyl-CoA synthetase and the putative dicarboxylate carrier protein, respectively, from Streptomyces coelicolor into the recombinant S. venezuelae strains expressing flavanone and flavone biosynthetic genes resulted in enhanced production of both flavonoids.

  17. Metabolic engineering of natural product biosynthesis in actinobacteria.

    PubMed

    Bilyk, Oksana; Luzhetskyy, Andriy

    2016-12-01

    Actinomycetes are known to produce over two-thirds of all known secondary metabolites. We review here recent progress in the metabolic engineering of streptomycetes for natural product biosynthesis. Several examples of the yield improvement of polyketides (mithramycin and tylactone) and non-ribosomal peptides (balhimycin and daptomycin) demonstrate the power of precursor supply engineering. Another example is the manipulation of a regulatory network for increased production of nystatin and teicoplanin. The second part highlights new approaches in the derivatization of natural products via combination of mutasynthesis and genomic engineering.

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

    PubMed Central

    2011-01-01

    Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR) relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data. PMID:21943338

  19. The intraspecific scaling of metabolic rate with body mass in fishes depends on lifestyle and temperature.

    PubMed

    Killen, Shaun S; Atkinson, David; Glazier, Douglas S

    2010-02-01

    Metabolic energy fuels all biological processes, and therefore theories that explain the scaling of metabolic rate with body mass potentially have great predictive power in ecology. A new model, that could improve this predictive power, postulates that the metabolic scaling exponent (b) varies between 2/3 and 1, and is inversely related to the elevation of the intraspecific scaling relationship (metabolic level, L), which in turn varies systematically among species in response to various ecological factors. We test these predictions by examining the effects of lifestyle, swimming mode and temperature on intraspecific scaling of resting metabolic rate among 89 species of teleost fish. As predicted, b decreased as L increased with temperature, and with shifts in lifestyle from bathyal and benthic to benthopelagic to pelagic. This effect of lifestyle on b may be related to varying amounts of energetically expensive tissues associated with different capacities for swimming during predator-prey interactions.

  20. 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.

  1. New approach for phylogenetic tree recovery based on genome-scale metabolic networks.

    PubMed

    Gamermann, Daniel; Montagud, Arnaud; Conejero, J Alberto; Urchueguía, Javier F; de Córdoba, Pedro Fernández

    2014-07-01

    A wide range of applications and research has been done with genome-scale metabolic models. In this work, we describe an innovative methodology for comparing metabolic networks constructed from genome-scale metabolic models and how to apply this comparison in order to infer evolutionary distances between different organisms. Our methodology allows a quantification of the metabolic differences between different species from a broad range of families and even kingdoms. This quantification is then applied in order to reconstruct phylogenetic trees for sets of various organisms.

  2. Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

    PubMed Central

    Mendoza, Sebastián N.; Cañón, Pablo M.; Contreras, Ángela; Ribbeck, Magdalena; Agosín, Eduardo

    2017-01-01

    Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche. PMID:28424673

  3. Metabolic engineering for the production of 1,3-propanediol

    SciTech Connect

    Cameron, D.C.; Tong, I.T., Skraly, F.A.

    1993-12-31

    Metabolic engineering involves the use of recombinant DNA techniques for the modification of intermediary metabolic pathways. Microorganisms have recently been engineered to produce compounds such as indigo, ethanol, fatty acids and polyhydroxyalkanoates. As a model system for research in metabolic engineering, the authors have constructed a strain of the bacterium Escherichia coli, that is able to produce 1,3-propanediol (1,3-PD) from glycerol. This strain contains the genes for the glycerol deydratase and the 1,3-PD oxidoreductase from Klebsiella pneumoniae. The authors have also investigated genetic and environmental strategies for improving the yield and productivity of 1,3-PD by the engineered organism. In addition to being a useful model system, 1,3-PD production is of current practical interest. First 1,3-PD (also known as trimethylene glycol) and 1,4-butanediol, the more readily available diols. Second, the volume of feedstock (glycerol) is expected to grow, as it is a by-product of the production of polyglycoside surfactants and biodiesel fluids.

  4. Magnesium degradation products: effects on tissue and human metabolism.

    PubMed

    Seitz, J-M; Eifler, R; Bach, Fr-W; Maier, H J

    2014-10-01

    Owing to their mechanical properties, metallic materials present a promising solution in the field of resorbable implants. The magnesium metabolism in humans differs depending on its introduction. The natural, oral administration of magnesium via, for example, food, essentially leads to an intracellular enrichment of Mg(2+) . In contrast, introducing magnesium-rich substances or implants into the tissue results in a different decomposition behavior. Here, exposing magnesium to artificial body electrolytes resulted in the formation of the following products: magnesium hydroxide, magnesium oxide, and magnesium chloride, as well as calcium and magnesium apatites. Moreover, it can be assumed that Mg(2+) , OH(-) ions, and gaseous hydrogen are also present and result from the reaction for magnesium in an aqueous environment. With the aid of physiological metabolic processes, the organism succeeds in either excreting the above mentioned products or integrating them into the natural metabolic process. Only a burst release of these products is to be considered a problem. A multitude of general tissue effects and responses from the Mg's degradation products is considered within this review, which is not targeting specific implant classes. Furthermore, common alloying elements of magnesium and their hazardous potential in vivo are taken into account.

  5. Metabolic network architecture and carbon source determine metabolite production costs.

    PubMed

    Waschina, Silvio; D'Souza, Glen; Kost, Christian; Kaleta, Christoph

    2016-06-01

    Metabolism is essential to organismal life, because it provides energy and building block metabolites. Even though it is known that the biosynthesis of metabolites consumes a significant proportion of the resources available to a cell, the factors that determine their production costs remain less well understood. In this context, it is especially unclear how the nutritional environment affects the costs of metabolite production. Here, we use the amino acid metabolism of Escherichia coli as a model to show that the point at which a carbon source enters central metabolic pathways is a major determinant of individual metabolite production costs. Growth rates of auxotrophic genotypes, which in the presence of the required amino acid save biosynthetic costs, were compared to the growth rates that prototrophic cells achieved under the same conditions. The experimental results showed a strong concordance with computationally estimated biosynthetic costs, which allowed us, for the first time, to systematically quantify carbon source-dependent metabolite production costs. Thus, we demonstrate that the nutritional environment in combination with network architecture is an important but hitherto underestimated factor influencing biosynthetic costs and thus microbial growth. Our observations are highly relevant for the optimization of biotechnological processes as well as for understanding the ecology of microorganisms in their natural environments. © 2016 Federation of European Biochemical Societies.

  6. Metabolic pathway reconstruction strategies for central metabolism and natural product biosynthesis

    PubMed Central

    Kotera, Masaaki; Goto, Susumu

    2016-01-01

    Metabolic pathway reconstruction presents a challenge for understanding metabolic pathways in organisms of interest. Different strategies, i.e., reference-based vs. de novo, must be used for pathway reconstruction depending on the availability of well-characterized enzymatic reactions. If at least one enzyme is already known to catalyze a reaction, its amino acid sequence can be used as a reference for identifying homologous enzymes in the genome of an organism of interest. Where there is no known enzyme able to catalyze a corresponding reaction, however, the reaction and the corresponding enzyme must be predicted de novo from chemical transformations of the putative substrate-product pair. This review summarizes studies involving reference-based and de novo metabolic pathway reconstruction and discusses the importance of the classification and structure-function relationships of enzymes. PMID:27924274

  7. Metabolic pathway reconstruction strategies for central metabolism and natural product biosynthesis.

    PubMed

    Kotera, Masaaki; Goto, Susumu

    2016-01-01

    Metabolic pathway reconstruction presents a challenge for understanding metabolic pathways in organisms of interest. Different strategies, i.e., reference-based vs. de novo, must be used for pathway reconstruction depending on the availability of well-characterized enzymatic reactions. If at least one enzyme is already known to catalyze a reaction, its amino acid sequence can be used as a reference for identifying homologous enzymes in the genome of an organism of interest. Where there is no known enzyme able to catalyze a corresponding reaction, however, the reaction and the corresponding enzyme must be predicted de novo from chemical transformations of the putative substrate-product pair. This review summarizes studies involving reference-based and de novo metabolic pathway reconstruction and discusses the importance of the classification and structure-function relationships of enzymes.

  8. Patterns of metabolite changes identified from large-scale gene perturbations in Arabidopsis using a genome-scale metabolic network.

    PubMed

    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

    2015-04-01

    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.

  9. Genome-scale modeling of human metabolism - a systems biology approach.

    PubMed

    Mardinoglu, Adil; Gatto, Francesco; Nielsen, Jens

    2013-09-01

    Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

  10. Compartmentalizing metabolic pathway in Candida glabrata for acetoin production.

    PubMed

    Li, Shubo; Liu, Liming; Chen, Jian

    2015-03-01

    Acetoin, a valuable compound, has high potential as a biochemical building block. In this study, subcellular metabolic engineering was applied to engineer the mitochondrion of Candida glabrata for acetoin production. With the aid of mitochondrial targeting sequences, a heterologous acetoin pathway was targeted into the mitochondria to increase the enzyme concentrations and level of intermediate, followed by coupling with the mitochondrial pyruvate carrier (MPC) to increase the availability of mitochondrial pyruvate. As a result, the strain comprising the combination of the mitochondrial pathway and MPC could yield approximately 3.26 g/L of acetoin, which was about 59.8% higher than that produced by the cytoplasmic pathway. These results provided a new insight into the metabolic engineering of C. glabrata for acetoin production, and offered a potential platform to improve the performance of engineered pathways. Copyright © 2014. Published by Elsevier Inc.

  11. Dairy products on metabolic health: current research and clinical implications.

    PubMed

    Da Silva, Marine S; Rudkowska, Iwona

    2014-03-01

    Dairy products have been thought to have a beneficial role in the metabolic syndrome (MetS). MetS constitutes a cluster of risk factors for an increased mortality, including obesity, impaired glucose homeostasis, hypertension and atherogenic dyslipidemia. Individuals with MetS are also often in a chronic, low-grade inflammatory state. The objective of this review is to examine recent meta-analyses and clinical studies on the association between dairy products consumption and these MetS risk factors. Findings from studies demonstrate that weight loss related to dairy product intake is due to the combination of an energy-restricted diet with consumption of dairy products. Further, a limited number of studies have shown beneficial effects of dairy consumption on plasma lipids, blood pressure, glucose homeostasis or inflammatory and oxidative stress profiles. Overall, this review article suggests that adults should consume at least 2-3 servings of dairy products per day within a well-balanced diet and a healthy lifestyle for metabolic health. Yet, higher dairy product consumption may have additional beneficial effects, but more well-designed intervention studies are needed to ascertain these effects.

  12. Computational evaluation of Synechococcus sp. PCC 7002 metabolism for chemical production

    SciTech Connect

    Vu, Trang; Hill, Eric A.; Kucek, Leo A.; Konopka, Allan; Beliaev, Alex S.; Reed, Jennifer L.

    2013-05-24

    Cyanobacteria are ideal metabolic engineering platforms for carbon-neutral biotechnology because they directly convert CO2 to a range of valuable products. In this study, we present a computational assessment of biochemical production in Synechococcus sp. PCC 7002 (Synechococcus 7002), a fast growing cyanobacterium whose genome has been sequenced, and for which genetic modification methods have been developed. We evaluated the maximum theoretical yields (mol product per mol CO2 or mol photon) of producing various chemicals under photoautotrophic and dark conditions using a genome-scale metabolic model of Synechococcus 7002. We found that the yields were lower under dark conditions, compared to photoautotrophic conditions, due to the limited amount of energy and reductant generated from glycogen. We also examined the effects of photon and CO2 limitations on chemical production under photoautotrophic conditions. In addition, using various computational methods such as MOMA, RELATCH, and OptORF, we identified gene-knockout mutants that are predicted to improve chemical production under photoautotrophic and/or dark anoxic conditions. These computational results are useful for metabolic engineering of cyanobacteria to synthesize valueadded products.

  13. Symbolic flux analysis for genome-scale metabolic networks.

    PubMed

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

    2011-05-23

    With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  14. Symbolic flux analysis for genome-scale metabolic networks

    PubMed Central

    2011-01-01

    Background With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. Results A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. Conclusions We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition. PMID:21605414

  15. A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

    PubMed

    Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

    2013-04-01

    Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis

  16. A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

    PubMed Central

    Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

    2013-01-01

    Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical

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

    PubMed

    Puchałka, Jacek; Oberhardt, Matthew A; Godinho, Miguel; Bielecka, Agata; Regenhardt, Daniela; Timmis, Kenneth N; Papin, Jason A; Martins dos Santos, Vítor A P

    2008-10-01

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

  18. Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

    PubMed Central

    Godinho, Miguel; Bielecka, Agata; Regenhardt, Daniela; Timmis, Kenneth N.

    2008-01-01

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

  19. MapMaker and PathTracer for tracking carbon in genome-scale metabolic models.

    PubMed

    Tervo, Christopher J; Reed, Jennifer L

    2016-05-01

    Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites.

  20. MapMaker and PathTracer for tracking carbon in genome-scale metabolic models

    PubMed Central

    Tervo, Christopher J.; Reed, Jennifer L.

    2016-01-01

    Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites. PMID:26771089

  1. Evaluation of endogenous acidic metabolic products associated with carbohydrate metabolism in tumor cells.

    PubMed

    Mazzio, Elizabeth A; Smith, Bruce; Soliman, Karam F A

    2010-06-01

    Tumor cells have a high tolerance for acidic and hypoxic microenvironments, also producing abundant lactic acid through accelerated glycolysis in the presence or absence of O(2). While the accumulation of lactate is thought to be a major contributor to the reduction of pH-circumscribing aggressive tumors, it is not known if other endogenous metabolic products contribute this acidity. Furthermore, anaerobic metabolism in cancer cells bears similarity to homo-fermentative lactic acid bacteria, however very little is known about an alternative pathway that may drive adenosine triphosphate (ATP) production independent of glycolysis. In this study, we quantify over 40 end-products (amines, acids, alcohols, aldehydes, or ketones) produced by malignant neuroblastoma under accelerated glycolysis (+glucose (GLU) supply 1-10 mM) +/- mitochondrial toxin; 1-methyl-4-phenylpyridinium (MPP(+)) to abate aerobic respiration to delineate differences between anaerobic vs. aerobic cell required metabolic pathways. The data show that an acceleration of anaerobic glycolysis prompts an expected reduction in extracellular pH (pH(ex)) from neutral to 6.7 +/- 0.006. Diverse metabolic acids associated with this drop in acidity were quantified by ionic exchange liquid chromatography (LC), showing concomitant rise in lactate (Ctrls 7.5 +/- 0.5 mM; +GLU 12.35 +/- 1.3 mM; +GLU + MPP 18.1 +/- 1.8 mM), acetate (Ctrl 0.84 +/- 0.13 mM: +GLU 1.3 +/- 0.15 mM; +GLU + MPP 2.7 +/- 0.4 mM), fumarate, and a-ketoglutarate (<10 microM) while a range of other metabolic organic acids remained undetected. Amino acids quantified by o-phthalaldehyde precolumn derivatization/electrochemical detection-LC show accumulation of L: -alanine (1.6 +/- .052 mM), L: -glutamate (285 +/- 9.7 microM), L: -asparagine (202 +/- 2.1 microM), and L: -aspartate (84.2 +/- 4.9 microM) produced during routine metabolism, while other amino acids remain undetected. In contrast, the data show no evidence for accumulation of acetaldehyde

  2. Evaluation of endogenous acidic metabolic products associated with carbohydrate metabolism in tumor cells

    PubMed Central

    Mazzio, Elizabeth A.; Smith, Bruce

    2010-01-01

    Tumor cells have a high tolerance for acidic and hypoxic microenvironments, also producing abundant lactic acid through accelerated glycolysis in the presence or absence of O2. While the accumulation of lactate is thought to be a major contributor to the reduction of pH-circumscribing aggressive tumors, it is not known if other endogenous metabolic products contribute this acidity. Furthermore, anaerobic metabolism in cancer cells bears similarity to homo-fermentative lactic acid bacteria, however very little is known about an alternative pathway that may drive adenosine triphosphate (ATP) production independent of glycolysis. In this study, we quantify over 40 end-products (amines, acids, alcohols, aldehydes, or ketones) produced by malignant neuroblastoma under accelerated glycolysis (+glucose (GLU) supply 1–10 mM) ± mitochondrial toxin; 1-methyl-4-phenyl-pyridinium (MPP+) to abate aerobic respiration to delineate differences between anaerobic vs. aerobic cell required metabolic pathways. The data show that an acceleration of anaerobic glycolysis prompts an expected reduction in extracellular pH (pHex) from neutral to 6.7±0.006. Diverse metabolic acids associated with this drop in acidity were quantified by ionic exchange liquid chromatography (LC), showing concomitant rise in lactate (Ctrls 7.5±0.5 mM; +GLU 12.35±1.3 mM; +GLU + MPP 18.1±1.8 mM), acetate (Ctrl 0.84±0.13 mM: +GLU 1.3±0.15 mM; +GLU + MPP 2.7±0.4 mM), fumarate, and a-ketoglutarate (<10μM) while a range of other metabolic organic acids remained undetected. Amino acids quantified by o-phthalaldehyde precolumn derivatization/electrochemical detection–LC show accumulation of L-alanine (1.6±.052 mM), L-glutamate (285±9.7μM), L-asparagine (202±2.1μM), and L-aspartate (84.2±4.9μM) produced during routine metabolism, while other amino acids remain undetected. In contrast, the data show no evidence for accumulation of acetaldehyde, aldehydes, or ketones (Purpald/2

  3. Quantitative study of geometrical scaling in charm production at HERA

    NASA Astrophysics Data System (ADS)

    Stebel, Tomasz

    2013-07-01

    The method of ratios was applied to search for geometrical scaling in charm production in deep inelastic scattering. Recent combined data from the H1 and ZEUS experiments were used. Two forms of geometrical scaling were tested: an originally proposed scaling that results from the Golec-Biernat-Wusthoff model and scaling motivated by a dipole representation, which takes into account charm mass. It turns out that in both cases some residual scaling is present and charm mass inclusion improves scaling quality.

  4. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

    PubMed

    Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

    2015-03-07

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  5. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

    PubMed Central

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, David

    2015-01-01

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. PMID:25652833

  6. Metabolic engineering for advanced biofuels production from Escherichia coli.

    PubMed

    Atsumi, Shota; Liao, James C

    2008-10-01

    Global energy and environmental problems have stimulated increasing efforts toward synthesizing liquid biofuels as transportation energy. Compared to the traditional biofuel, ethanol, advanced biofuels should offer advantages such as higher energy density, lower hygroscopicity, lower vapor pressure, and compatibility with existing transportation infrastructure. However, these fuels are not synthesized economically using native organisms. Metabolic engineering offers an alternative approach in which synthetic pathways are engineered into user-friendly hosts for the production of these fuel molecules. These hosts could be readily manipulated to improve the production efficiency. This review summarizes recent progress in the engineering of Escherichia coli to produce advanced biofuels.

  7. Metabolic Engineering for Advanced Biofuels Production from Escherichia coli

    PubMed Central

    Atsumi, Shota; Liao, James C.

    2008-01-01

    Summary Global energy and environmental problems have stimulated increasing efforts towards synthesizing liquid biofuels as transportation energy. Compared to the traditional biofuel, ethanol, advanced biofuels should offer advantages such as higher energy density, lower hygroscopicity, lower vapor pressure, and compatibility with existing transportation infrastructure. However, these fuels are not synthesized economically using native organisms. Metabolic engineering offers an alternative approach in which synthetic pathways are engineered into user friendly hosts for the production of these fuel molecules. These hosts could be readily manipulated to improve the production efficiency. This review summarizes recent progress in the engineering of Escherichia coli to produce advanced biofuels. PMID:18761088

  8. Genome-Scale Metabolic Reconstructions and Theoretical Investigation of Methane Conversion in Methylomicrobium buryatense Strain 5G(B1)

    SciTech Connect

    de la Torre, Andrea; Metivier, Aisha; Chu, Frances; Laurens, Lieve M. L.; Beck, David A. C.; Pienkos, Philip T.; Lidstrom, Mary E.; Kalyuzhnaya, Marina G.

    2015-11-25

    Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration.

  9. Genome-Scale Metabolic Reconstructions and Theoretical Investigation of Methane Conversion in Methylomicrobium buryatense Strain 5G(B1)

    DOE PAGES

    de la Torre, Andrea; Metivier, Aisha; Chu, Frances; ...

    2015-11-25

    Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration.

  10. Intraspecific Scaling of the Resting and Maximum Metabolic Rates of the Crucian Carp (Carassius auratus)

    PubMed Central

    Huang, Qingda; Zhang, Yurong; Liu, Shuting; Wang, Wen; Luo, Yiping

    2013-01-01

    The question of how the scaling of metabolic rate with body mass (M) is achieved in animals is unresolved. Here, we tested the cell metabolism hypothesis and the organ size hypothesis by assessing the mass scaling of the resting metabolic rate (RMR), maximum metabolic rate (MMR), erythrocyte size, and the masses of metabolically active organs in the crucian carp (Carassius auratus). The M of the crucian carp ranged from 4.5 to 323.9 g, representing an approximately 72-fold difference. The RMR and MMR increased with M according to the allometric equations RMR = 0.212M0.776 and MMR = 0.753M0.785. The scaling exponents for RMR (br) and MMR (bm) obtained in crucian carp were close to each other. Thus, the factorial aerobic scope remained almost constant with increasing M. Although erythrocyte size was negatively correlated with both mass-specific RMR and absolute RMR adjusted to M, it and all other hematological parameters showed no significant relationship with M. These data demonstrate that the cell metabolism hypothesis does not describe metabolic scaling in the crucian carp, suggesting that erythrocyte size may not represent the general size of other cell types in this fish and the metabolic activity of cells may decrease as fish grows. The mass scaling exponents of active organs was lower than 1 while that of inactive organs was greater than 1, which suggests that the mass scaling of the RMR can be partly due to variance in the proportion of active/inactive organs in crucian carp. Furthermore, our results provide additional evidence supporting the correlation between locomotor capacity and metabolic scaling. PMID:24376588

  11. Intraspecific scaling of the resting and maximum metabolic rates of the crucian carp (Carassius auratus).

    PubMed

    Huang, Qingda; Zhang, Yurong; Liu, Shuting; Wang, Wen; Luo, Yiping

    2013-01-01

    The question of how the scaling of metabolic rate with body mass (M) is achieved in animals is unresolved. Here, we tested the cell metabolism hypothesis and the organ size hypothesis by assessing the mass scaling of the resting metabolic rate (RMR), maximum metabolic rate (MMR), erythrocyte size, and the masses of metabolically active organs in the crucian carp (Carassius auratus). The M of the crucian carp ranged from 4.5 to 323.9 g, representing an approximately 72-fold difference. The RMR and MMR increased with M according to the allometric equations RMR = 0.212M (0.776) and MMR = 0.753M (0.785). The scaling exponents for RMR (b r) and MMR (b m) obtained in crucian carp were close to each other. Thus, the factorial aerobic scope remained almost constant with increasing M. Although erythrocyte size was negatively correlated with both mass-specific RMR and absolute RMR adjusted to M, it and all other hematological parameters showed no significant relationship with M. These data demonstrate that the cell metabolism hypothesis does not describe metabolic scaling in the crucian carp, suggesting that erythrocyte size may not represent the general size of other cell types in this fish and the metabolic activity of cells may decrease as fish grows. The mass scaling exponents of active organs was lower than 1 while that of inactive organs was greater than 1, which suggests that the mass scaling of the RMR can be partly due to variance in the proportion of active/inactive organs in crucian carp. Furthermore, our results provide additional evidence supporting the correlation between locomotor capacity and metabolic scaling.

  12. Scale-down of the inactivated polio vaccine production process.

    PubMed

    Thomassen, Yvonne E; van 't Oever, Aart G; Vinke, Marian; Spiekstra, Arjen; Wijffels, René H; van der Pol, Leo A; Bakker, Wilfried A M

    2013-05-01

    The anticipated increase in the demand for inactivated polio vaccines resulting from the success in the polio eradication program requires an increase in production capacity and cost price reduction of the current inactivated polio vaccine production processes. Improvement of existing production processes is necessary as the initial process development has been done decades ago. An up-to-date lab-scale version encompassing the legacy inactivated polio vaccine production process was set-up. This lab-scale version should be representative of the large scale, meaning a scale-down model, to allow experiments for process optimization that can be readily applied. Initially the separate unit operations were scaled-down at setpoint. Subsequently, the unit operations were applied successively in a comparative manner to large-scale manufacturing. This allows the assessment of the effects of changes in one unit operation to the consecutive units at small-scale. Challenges in translating large-scale operations to lab-scale are discussed, and the concessions that needed to be made are described. The current scale-down model for cell and virus culture (2.3-L) presents a feasible model with its production scale counterpart (750-L) when operated at setpoint. Also, the current scale-down models for the DSP unit operations clarification, concentration, size exclusion chromatography, ion exchange chromatography, and inactivation are in agreement with the manufacturing scale. The small-scale units can be used separately, as well as sequentially, to study variations and critical product quality attributes in the production process. Finally, it is shown that the scale-down unit operations can be used consecutively to prepare trivalent vaccine at lab-scale with comparable characteristics to the product produced at manufacturing scale.

  13. Efficient estimation of the maximum metabolic productivity of batch systems

    DOE PAGES

    St. John, Peter C.; Crowley, Michael F.; Bomble, Yannick J.

    2017-01-31

    Production of chemicals from engineered organisms in a batch culture involves an inherent trade-off between productivity, yield, and titer. Existing strategies for strain design typically focus on designing mutations that achieve the highest yield possible while maintaining growth viability. While these methods are computationally tractable, an optimum productivity could be achieved by a dynamic strategy in which the intracellular division of resources is permitted to change with time. New methods for the design and implementation of dynamic microbial processes, both computational and experimental, have therefore been explored to maximize productivity. However, solving for the optimal metabolic behavior under the assumptionmore » that all fluxes in the cell are free to vary is a challenging numerical task. Here, previous studies have therefore typically focused on simpler strategies that are more feasible to implement in practice, such as the time-dependent control of a single flux or control variable.« less

  14. Metabolic heat production of neonatal calves during hypothermia and recovery.

    PubMed

    Robinson, J B; Young, B A

    1988-10-01

    Metabolic heat production and rectal temperature were measured in 19 newborn calves (41.8 +/- 3.7 kg) during hypothermia and recovery when four different means of assistance were provided. Hypothermia of 30 degrees C rectal temperature was induced by immersion in 18 degrees C water. Calves were rewarmed in a 20 to 25 degree C air environment where thermal assistance was provided by added thermal insulation or by supplemental heat from infrared lamps. Other calves were rewarmed by immersion in warm water (38 degrees C), with or without a 40-ml drench of 20% ethanol in water. Resting (prehypothermia) and cold-induced summit metabolism of the calves was 2.5 +/- .1 and 8.2 +/- .22 W/kg and occurred at rectal temperatures of 39.5 +/- .06 and 36.2 +/- .26 degrees C, respectively. During cooling, metabolic heat production declined at the rate of .65 W/kg per degrees C decline in rectal temperature. The time required to regain euthermia from a rectal temperature of 30 degrees C was longer for calves with added insulation and those exposed to heat lamps than for the calves in the warm water and warm water plus ethanol treatments (90 and 92 vs 59 and 63 +/- 6.4 min, respectively). During recovery, the calves rewarmed with the added insulation and heat lamps produced more heat metabolically than the calves rewarmed in warm water. Total heat production during recovery was 34.1, 31.1, 18.3, 16.9 +/- 1.07 kJ/kg for the calves with added insulation, exposed to the heat lamps, in warm water and in warm water plus an oral drench of ethanol, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

  15. Coupled Effects of Hyporheic Flow Structure and Metabolic Pattern on Reach-scale Nutrient Uptake

    NASA Astrophysics Data System (ADS)

    Li, A.; Aubeneau, A. F.; Bolster, D.; Tank, J. L.; Packman, A. I.

    2015-12-01

    Co-injections of conservative tracers and nutrients are commonly used to assess net reach-scale nutrient transformation rates and benthic/hyporheic uptake parameters. However, little information is available on spatial metabolic patterns in the benthic and hyporheic regions. Based on observations from real systems, we used particle tracking simulations to explore the effects of localized metabolism on estimates of reach-scale nutrient uptake rates. Metabolism locally depletes nutrient concentrations relative to conservative tracers, causing their concentration profiles of injected nutrients and conservative tracers to diverge. At slow rates of hyporheic exchange relative to rates of metabolism, overall hyporheic nutrient uptake is limited by delivery from the stream, and effective reach-scale nutrient uptake parameters will be controlled by the hyporheic exchange rate. At high rates of hyporheic exchange relative to rates of metabolism, the injected tracer can propagate beyond regions of high microbial activity, which commonly occur near the streambed surface. In this case, the injected tracer may not adequately capture timescales of nutrient replenishment in the most bioactive regions. Reach-scale nutrients uptake rate increases with increasing heterogeneity in local metabolic patterns, altering the shape of breakthrough curves downstream. More observations of hyporheic rates and metabolic patterns are needed to understand how flow heterogeneity and reaction heterogeneity interact to control nutrient dynamics at reach-scale.

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

    DTIC Science & Technology

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosametabolic network and gene expression...synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we

  17. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics

    NASA Astrophysics Data System (ADS)

    De Martino, Daniele

    2017-06-01

    In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions.

  18. MetaMerge: scaling up genome-scale metabolic reconstructions with application to Mycobacterium tuberculosis

    PubMed Central

    2012-01-01

    Reconstructed models of metabolic networks are widely used for studying metabolism in various organisms. Many different reconstructions of the same organism often exist concurrently, forcing researchers to choose one of them at the exclusion of the others. We describe MetaMerge, an algorithm for semi-automatically reconciling a pair of existing metabolic network reconstructions into a single metabolic network model. We use MetaMerge to combine two published metabolic networks for Mycobacterium tuberculosis into a single network, which allows many reactions that could not be active in the individual models to become active, and predicts essential genes with a higher positive predictive value. PMID:22292986

  19. Enhanced hydrogen production from glucose by metabolically engineered Escherichia coli.

    PubMed

    Maeda, Toshinari; Sanchez-Torres, Viviana; Wood, Thomas K

    2007-12-01

    To utilize fermentative bacteria for producing the alternative fuel hydrogen, we performed successive rounds of P1 transduction from the Keio Escherichia coli K-12 library to introduce multiple, stable mutations into a single bacterium to direct the metabolic flux toward hydrogen production. E. coli cells convert glucose to various organic acids (such as succinate, pyruvate, lactate, formate, and acetate) to synthesize energy and hydrogen from formate by the formate hydrogen-lyase (FHL) system that consists of hydrogenase 3 and formate dehydrogenase-H. We altered the regulation of FHL by inactivating the repressor encoded by hycA and by overexpressing the activator encoded by fhlA, removed hydrogen uptake activity by deleting hyaB (hydrogenase 1) and hybC (hydrogenase 2), redirected glucose metabolism to formate by using the fdnG, fdoG, narG, focA, focB, poxB, and aceE mutations, and inactivated the succinate and lactate synthesis pathways by deleting frdC and ldhA, respectively. The best of the metabolically engineered strains, BW25113 hyaB hybC hycA fdoG frdC ldhA aceE, increased hydrogen production 4.6-fold from glucose and increased the hydrogen yield twofold from 0.65 to 1.3 mol H(2)/mol glucose (maximum, 2 mol H(2)/mol glucose).

  20. Engineering nonphosphorylative metabolism to generate lignocellulose-derived products.

    PubMed

    Tai, Yi-Shu; Xiong, Mingyong; Jambunathan, Pooja; Wang, Jingyu; Wang, Jilong; Stapleton, Cole; Zhang, Kechun

    2016-04-01

    Conversion of lignocellulosic biomass into value-added products provides important environmental and economic benefits. Here we report the engineering of an unconventional metabolism for the production of tricarboxylic acid (TCA)-cycle derivatives from D-xylose, L-arabinose and D-galacturonate. We designed a growth-based selection platform to identify several gene clusters functional in Escherichia coli that can perform this nonphosphorylative assimilation of sugars into the TCA cycle in less than six steps. To demonstrate the application of this new metabolic platform, we built artificial biosynthetic pathways to 1,4-butanediol (BDO) with a theoretical molar yield of 100%. By screening and engineering downstream pathway enzymes, 2-ketoacid decarboxylases and alcohol dehydrogenases, we constructed E. coli strains capable of producing BDO from D-xylose, L-arabinose and D-galacturonate. The titers, rates and yields were higher than those previously reported using conventional pathways. This work demonstrates the potential of nonphosphorylative metabolism for biomanufacturing with improved biosynthetic efficiencies.

  1. Evaluating metabolic stress and plasmid stability in plasmid DNA production by Escherichia coli.

    PubMed

    Silva, Filomena; Queiroz, João A; Domingues, Fernanda C

    2012-01-01

    In the context of recombinant DNA technology, the development of feasible and high-yielding plasmid DNA production processes has regained attention as more evidence for its efficacy as vectors for gene therapy and DNA vaccination arise. When producing plasmid DNA in Escherichia coli, a number of biological restraints, triggered by plasmid maintenance and replication as well as culture conditions are responsible for limiting final biomass and product yields. This termed "metabolic burden" can also cause detrimental effects on plasmid stability and quality, since the cell machinery is no longer capable of maintaining an active metabolism towards plasmid synthesis and the stress responses elicited by plasmid maintenance can also cause increased plasmid instability. The optimization of plasmid DNA production bioprocesses is still hindered by the lack of information on the host metabolic responses as well as information on plasmid instability. Therefore, systematic and on-line approaches are required not only to characterise this "metabolic burden" and plasmid stability but also for the design of appropriate metabolic engineering and culture strategies. The monitoring tools described to date rapidly evolve from laborious, off-line and at-line monitoring to online monitoring, at a time-scale that enables researchers to solve these bioprocessing problems as they occur. This review highlights major E. coli biological alterations caused by plasmid maintenance and replication, possible causes for plasmid instability and discusses the ability of currently employed bioprocess monitoring techniques to provide information in order to circumvent metabolic burden and plasmid instability, pointing out the possible evolution of these methods towards online bioprocess monitoring.

  2. Genome-Scale Metabolic Modeling in the Simulation of Field-Scale Uranium Bioremediation

    NASA Astrophysics Data System (ADS)

    Yabusaki, S.; Wilkins, M.; Fang, Y.; Williams, K. H.; Waichler, S.; Long, P. E.

    2015-12-01

    Coupled variably saturated flow and biogeochemical reactive transport modeling is used to improve understanding of the processes, properties, and conditions controlling uranium bio-immobilization in a field experiment where uranium-contaminated groundwater was amended with acetate and bicarbonate. The acetate stimulates indigenous microorganisms that catalyze metal reduction, including the conversion of aqueous U(VI) to solid-phase U(IV), which effectively removes uranium from solution. The initiation of the bicarbonate amendment prior to biostimulation was designed to promote U(VI) desorption that would increase the aqueous U(VI) available for bioreduction. The three-dimensional simulations were able to largely reproduce the timing and magnitude of the physical, chemical and biological responses to the acetate and bicarbonate amendment in the context of changing water table elevation and gradient. A time series of groundwater proteomic samples exhibited correlations between the most abundant Geobacter metallireducens proteins and the genome-scale metabolic model-predicted fluxes of intra-cellular reactions associated with each of those proteins. The desorption of U(VI) induced by the bicarbonate amendment led to initially higher rates of bioreduction compared to locations with minimal bicarbonate exposure. After bicarbonate amendment ceased, bioreduction continued at these locations whereas U(VI) sorption was the dominant removal mechanism at the bicarbonate-impacted sites.

  3. Metabolic Engineering of Candida glabrata for Diacetyl Production

    PubMed Central

    Gao, Xiang; Xu, Nan; Li, Shubo; Liu, Liming

    2014-01-01

    In this study, Candida glabrata, an efficient pyruvate-producing strain, was metabolically engineered for the production of the food ingredient diacetyl. A diacetyl biosynthetic pathway was reconstructed based on genetic modifications and medium optimization. The former included (i) channeling carbon flux into the diacetyl biosynthetic pathway by amplification of acetolactate synthase, (ii) elimination of the branched pathway of α-acetolactate by deleting the ILV5 gene, and (iii) restriction of diacetyl degradation by deleting the BDH gene. The resultant strain showed an almost 1∶1 co-production of α-acetolactate and diacetyl (0.95 g L−1). Furthermore, addition of Fe3+ to the medium enhanced the conversion of α-acetolactate to diacetyl and resulted in a two-fold increase in diacetyl production (2.1 g L−1). In addition, increased carbon flux was further channeled into diacetyl biosynthetic pathway and a titer of 4.7 g L−1 of diacetyl was achieved by altering the vitamin level in the flask culture. Thus, this study illustrates that C. glabrata could be tailored as an attractive platform for enhanced biosynthesis of beneficial products from pyruvate by metabolic engineering strategies. PMID:24614328

  4. Metabolic determinants in Listeria monocytogenes anaerobic listeriolysin O production.

    PubMed

    Wallace, Nathan; Newton, Eric; Abrams, Elizabeth; Zani, Ashley; Sun, Yvonne

    2017-03-13

    Listeria monocytogenes is a human pathogen and a facultative anaerobe. To better understand how anaerobic growth affects L. monocytogenes pathogenesis, we first showed that anaerobic growth led to decreased growth and changes in surface morphology. Moreover, compared to aerobically grown bacteria, anaerobically grown L. monocytogenes established higher level of invasion but decreased intracellular growth and actin polymerization in cultured cells. The production of listeriolysin O (LLO) was significantly lower in anaerobic cultures-a phenotype observed in wild type and isogenic mutants lacking transcriptional regulators SigB or CodY or harboring a constitutively active PrfA. To explore potential regulatory mechanisms, we established that the addition of central carbon metabolism intermediates, such as acetate, citrate, fumarate, pyruvate, lactate, and succinate, led to an increase in LLO activity in the anaerobic culture supernatant. These results highlight the regulatory role of central carbon metabolism in L. monocytogenes pathogenesis under anaerobic conditions.

  5. Microbial production of antioxidant food ingredients via metabolic engineering.

    PubMed

    Lin, Yuheng; Jain, Rachit; Yan, Yajun

    2014-04-01

    Antioxidants are biological molecules with the ability to protect vital metabolites from harmful oxidation. Due to this fascinating role, their beneficial effects on human health are of paramount importance. Traditional approaches using solvent-based extraction from food/non-food sources and chemical synthesis are often expensive, exhaustive, and detrimental to the environment. With the advent of metabolic engineering tools, the successful reconstitution of heterologous pathways in Escherichia coli and other microorganisms provides a more exciting and amenable alternative to meet the increasing demand of natural antioxidants. In this review, we elucidate the recent progress in metabolic engineering efforts for the microbial production of antioxidant food ingredients - polyphenols, carotenoids, and antioxidant vitamins. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant products.

    PubMed

    Carinhas, Nuno; Bernal, Vicente; Teixeira, Ana P; Carrondo, Manuel Jt; Alves, Paula M; Oliveira, Rui

    2011-02-25

    Stoichiometric models constitute the basic framework for fluxome quantification in the realm of metabolic engineering. A recurrent bottleneck, however, is the establishment of consistent stoichiometric models for the synthesis of recombinant proteins or viruses. Although optimization algorithms for in silico metabolic redesign have been developed in the context of genome-scale stoichiometric models for small molecule production, still rudimentary knowledge of how different cellular levels are regulated and phenotypically expressed prevents their full applicability for complex product optimization. A hybrid framework is presented combining classical metabolic flux analysis with projection to latent structures to further link estimated metabolic fluxes with measured productivities. We first explore the functional metabolic decomposition of a baculovirus-producing insect cell line from experimental data, highlighting the TCA cycle and mitochondrial respiration as pathways strongly associated with viral replication. To reduce uncertainty in metabolic target identification, a Monte Carlo sampling method was used to select meaningful associations with the target, from which 66% of the estimated fluxome had to be screened out due to weak correlations and/or high estimation errors. The proposed hybrid model was then validated using a subset of preliminary experiments to pinpoint the same determinant pathways, while predicting the productivity of independent cultures. Overall, the results indicate our hybrid metabolic flux analysis framework is an advantageous tool for metabolic identification and quantification in incomplete or ill-defined metabolic networks. As experimental and computational solutions for constructing comprehensive global cellular models are in development, the contribution of hybrid metabolic flux analysis should constitute a valuable complement to current computational platforms in bridging the metabolic state with improved cell culture performance.

  7. Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

    PubMed

    Jiang, Zhenhong; He, Fei; Zhang, Ziding

    2017-07-01

    Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study

  8. The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

    PubMed Central

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

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

    PubMed

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

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

    PubMed Central

    Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

    2016-01-01

    The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

  11. Metabolic engineering for isoprenoid-based biofuel production.

    PubMed

    Gupta, P; Phulara, S C

    2015-09-01

    Sustainable economic and industrial growth is the need of the hour and it requires renewable energy resources having better performance and compatibility with existing fuel infrastructure from biological routes. Isoprenoids (C ≥ 5) can be a potential alternative due to their diverse nature and physiochemical properties similar to that of petroleum based fuels. In the past decade, extensive research has been done to utilize metabolic engineering strategies in micro-organisms primarily, (i) to overcome the limitations associated with their natural and non-natural production and (ii) to develop commercially competent microbial strain for isoprenoid-based biofuel production. This review briefly describes the engineered isoprenoid biosynthetic pathways in well-characterized microbial systems for the production of several isoprenoid-based biofuels and fuel precursors.

  12. Metabolic engineering strategies for improving xylitol production from hemicellulosic sugars.

    PubMed

    Su, Buli; Wu, Mianbin; Lin, Jianping; Yang, Lirong

    2013-11-01

    Xylitol is a five-carbon sugar alcohol with potential for use as a sweetener. Industrially, xylitol is currently produced by chemical hydrogenation of D-xylose using Raney nickel catalysts and this requires expensive separation and purification steps as well as high pressure and temperature that lead to environmental pollution. Highly efficient biotechnological production of xylitol using microorganisms is gaining more attention and has been proposed as an alternative process. Although the biotechnological method has not yet surpassed the advantages of chemical reduction in terms of yield and cost, various strategies offer promise for the biotechnological production of xylitol. In this review, the focus is on the most recent developments of the main metabolic engineering strategies for improving the production of xylitol.

  13. Metabolic engineering towards biotechnological production of carotenoids in microorganisms.

    PubMed

    Lee, P C; Schmidt-Dannert, C

    2002-10-01

    Carotenoids are important natural pigments produced by many microorganisms and plants. Traditionally, carotenoids have been used in the feed, food and nutraceutical industries. The recent discoveries of health-related beneficial properties attributed to carotenoids have spurred great interest in the production of structurally diverse carotenoids for pharmaceutical applications. The availability of a considerable number of microbial and plant carotenoid genes that can be functionally expressed in heterologous hosts has opened ways for the production of diverse carotenoid compounds in heterologous systems. In this review, we will describe the recent progress made in metabolic engineering of non-carotenogenic microorganisms for improved carotenoid productivity. In addition, we will discuss the application of combinatorial and evolutionary strategies to carotenoid pathway engineering to broaden the diversity of carotenoid structures synthesized in recombinant hosts.

  14. Toward systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels.

    PubMed

    Caspeta, Luis; Nielsen, Jens

    2013-05-01

    Recently genome sequence data have become available for Aspergillus and Pichia species of industrial interest. This has stimulated the use of systems biology approaches for large-scale analysis of the molecular and metabolic responses of Aspergillus and Pichia under defined conditions, which has resulted in much new biological information. Case-specific contextualization of this information has been performed using comparative and functional genomic tools. Genomics data are also the basis for constructing genome-scale metabolic models, and these models have helped in the contextualization of knowledge on the fundamental biology of Aspergillus and Pichia species. Furthermore, with the availability of these models, the engineering of Aspergillus and Pichia is moving from traditional approaches, such as random mutagenesis, to a systems metabolic engineering approach. Here we review the recent trends in systems biology of Aspergillus and Pichia species, highlighting the relevance of these developments for systems metabolic engineering of these organisms for the production of hydrolytic enzymes, biofuels and chemicals from biomass. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model.

    PubMed

    Cuevas, Daniel A; Edirisinghe, Janaka; Henry, Chris S; Overbeek, Ross; O'Connell, Taylor G; Edwards, Robert A

    2016-01-01

    Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe's entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Python-based open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe's metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models.

  16. From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model

    PubMed Central

    Cuevas, Daniel A.; Edirisinghe, Janaka; Henry, Chris S.; Overbeek, Ross; O’Connell, Taylor G.; Edwards, Robert A.

    2016-01-01

    Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe’s entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Python-based open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe’s metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models. PMID:27379044

  17. High-throughput generation, optimization and analysis of genome-scale metabolic models.

    SciTech Connect

    Henry, C. S.; DeJongh, M.; Best, A. A.; Frybarger, P. M.; Linsay, B.; Stevens, R. L.

    2010-09-01

    Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking {approx}48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.

  18. A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.

    PubMed

    Reimers, Alexandra-M; Lindhorst, Henning; Waldherr, Steffen

    2017-09-06

    In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now. This paper presents step-by-step instructions for building a (dynamic) resource allocation model, starting with prerequisites such as a genome-scale metabolic reconstruction, through building protein and noncatalytic biomass synthesis reactions and assigning turnover rates for each reaction. In addition, we explain how one can use SBML level 3 in combination with the flux balance constraints and our resource allocation modeling annotation to represent such models.

  19. Differentiating causality and correlation in allometric scaling: ant colony size drives metabolic hypometry.

    PubMed

    Waters, James S; Ochs, Alison; Fewell, Jennifer H; Harrison, Jon F

    2017-02-22

    Metabolic rates of individual animals and social insect colonies generally scale hypometrically, with mass-specific metabolic rates decreasing with increasing size. Although this allometry has wide ranging effects on social behaviour, ecology and evolution, its causes remain controversial. Because it is difficult to experimentally manipulate body size of organisms, most studies of metabolic scaling depend on correlative data, limiting their ability to determine causation. To overcome this limitation, we experimentally reduced the size of harvester ant colonies (Pogonomyrmex californicus) and quantified the consequent increase in mass-specific metabolic rates. Our results clearly demonstrate a causal relationship between colony size and hypometric changes in metabolic rate that could not be explained by changes in physical density. These findings provide evidence against prominent models arguing that the hypometric scaling of metabolic rate is primarily driven by constraints on resource delivery or surface area/volume ratios, because colonies were provided with excess food and colony size does not affect individual oxygen or nutrient transport. We found that larger colonies had lower median walking speeds and relatively more stationary ants and including walking speed as a variable in the mass-scaling allometry greatly reduced the amount of residual variation in the model, reinforcing the role of behaviour in metabolic allometry. Following the experimental size reduction, however, the proportion of stationary ants increased, demonstrating that variation in locomotory activity cannot solely explain hypometric scaling of metabolic rates in these colonies. Based on prior studies of this species, the increase in metabolic rate in size-reduced colonies could be due to increased anabolic processes associated with brood care and colony growth.

  20. Enhancing microbial production of biofuels by expanding microbial metabolic pathways.

    PubMed

    Yu, Ping; Chen, Xingge; Li, Peng

    2016-08-10

    Fatty acid, isoprenoid, and alcohol pathways have been successfully engineered to produce biofuels. By introducing three genes, atfA, adhE, and pdc, into Escherichia coli to expand fatty acid pathway, up to 1.28 g/L of fatty acid ethyl esters can be achieved. The isoprenoid pathway can be expanded to produce bisabolene with a high titer of 900 mg/L in Saccharomyces cerevisiae. Short- and long-chain alcohols can also be effectively biosynthesized by extending the carbon chain of ketoacids with an engineered "+1" alcohol pathway. Thus, it can be concluded that expanding microbial metabolic pathways has enormous potential for enhancing microbial production of biofuels for future industrial applications. However, some major challenges for microbial production of biofuels should be overcome to compete with traditional fossil fuels: lowering production costs, reducing the time required to construct genetic elements and to increase their predictability and reliability, and creating reusable parts with useful and predictable behavior. To address these challenges, several aspects should be further considered in future: mining and transformation of genetic elements related to metabolic pathways, assembling biofuel elements and coordinating their functions, enhancing the tolerance of host cells to biofuels, and creating modular subpathways that can be easily interconnected. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

  1. Metabolic flux analyses for serine alkaline protease production.

    PubMed

    Çalik; Çalik; Takaç; Özdamar

    2000-12-01

    The intracellular metabolic fluxes through the central carbon pathways in Bacillus licheniformis in serine alkaline protease (SAP) production were calculated to predict the potential strategies for increasing the performance of the bacilli, by using two optimization approaches, i.e. the theoretical data-based (TDA) and the theoretical data-based capacity (TDC) analyses based on respectively minimum in-vivo SAP accumulation rate and maximum SAP synthesis rate assumptions, at low-, medium-, and high-oxygen transfer conditions. At all periods of low-oxygen transfer condition, in lag and early exponential periods of medium-oxygen transfer (MOT) condition, and SAP synthesis period of high-oxygen transfer (HOT) condition, the TDA and TDC analyses revealed that SAP overproduction capacity is almost equal to the observed SAP production due to the regulation effect of the oxygen transfer. In the growth and early SAP synthesis period and in SAP synthesis period at MOT condition the calculated results of the two analyses reveal that SAP synthesis rate of the microorganism can be increased 7.2 and 16.7 folds, respectively; whereas, in the growth and early SAP synthesis period at HOT condition it can be increased 12.6 folds. The diversions in the biochemical reaction network and the influence of the oxygen transfer on the performance of the bacilli were also presented. The results encourage the application of metabolic engineering for lifting the rate limitations and for improving the genetic regulations in order to increase the SAP production.

  2. Evaluation of sludge reduction of three metabolic uncouplers in laboratory-scale anaerobic-anoxic-oxic process.

    PubMed

    Li, Ping; Li, Hechao; Li, Jin; Guo, Xuesong; Liu, Junxin; Xiao, Benyi

    2016-12-01

    To evaluate the sludge reduction of three metabolic uncouplers (3,3',4',5-tetrachlorosalicylanilide (TCS), 2,4-dichlorophenol (DCP), and tetrakis (hydroxymethyl) phosphonium sulfate (THPS)), we conducted continuous experiments on laboratory-scale anaerobic-anoxic-oxic processes. The three metabolic uncouplers were separately added in each oxic tank of the three systems, and a system without uncoupler addition was used as control. During the 85-day operation, sludge production and observed growth yields decreased to 38.6% and 16.98%, 43.4% and 17.55%, and 39.3% and 17.04% by the addition of TCS, DCP, and THPS, respectively. The addition of metabolic uncouplers slightly reduced the wastewater treatment efficiencies of the system (about 1.1-8.7%) and increased sludge SVIs (about 69.9-80.6%). Meanwhile, the differences among three metabolic uncouplers were little. Besides metabolic uncoupling and maintenance metabolism, which exist in the TCS- and DCP-added systems, lysis-cryptic growth also exists in the THPS-added system.

  3. Nutrient Uptake and Metabolism Along a Large Scale Tropical Physical-Chemical Gradient

    NASA Astrophysics Data System (ADS)

    Tromboni, F.; Neres-Lima, V.; Saltarelli, W. A.; Miwa, A. C. P.; Cunha, D. G. F.

    2016-12-01

    Nutrient spiraling is a whole-system approach for estimating nutrient uptake that can be used to assess aquatic ecosystems' responses to environmental change and anthropogenic impacts. Historically research on nutrient dynamic uptake in streams has focused on single nutrient dynamics and only rarely the stoichiometric uptake has been considered and linked to carbon metabolism driven by autotrophic and heterotrophic production. We investigated the relationship between uptake of phosphate (PO43-), nitrate (NO3-) ammonium (NH4+) and total dissolve nitrogen (DIN)/ PO43-; and gross primary production (GPP), respiration (R), and net ecosystem productivity (NEP) in six relatively pristine streams with differences regarding canopy cover and physical characteristics, located in a large scale gradient from tropical Atlantic Forest to an Atlantic forest/Cerrado (Brazilian Savanna) transition. We carried out whole stream instantaneous additions of PO43-, NO3- and NH4+ added to each stream in combination, using the TASCC (Tracer Additions for Spiraling Curve Characterization) method. Metabolism measurements were performed in the same streams right after uptake was measured, using one-station open channel method and re-aeration estimations for those sites. We found different background concentrations in the streams located in the Atlantic forest compared with the transition area with Cerrado. In general PO43- and NO3- uptake increased with the decreasing of canopy cover, while a positive relation with background concentration better explained NH4+uptake. DIN/PO43- uptake increased with increasing R and NEP. Little work on functional characteristics of pristine streams has been conducted in this region and this work provides an initial characterization on nitrogen and phosphorus dynamics as well as their stoichiometric uptake in streams.

  4. Metabolic modelling of polyhydroxyalkanoate copolymers production by mixed microbial cultures.

    PubMed

    Dias, João M L; Oehmen, Adrian; Serafim, Luísa S; Lemos, Paulo C; Reis, Maria A M; Oliveira, Rui

    2008-07-08

    This paper presents a metabolic model describing the production of polyhydroxyalkanoate (PHA) copolymers in mixed microbial cultures, using mixtures of acetic and propionic acid as carbon source material. Material and energetic balances were established on the basis of previously elucidated metabolic pathways. Equations were derived for the theoretical yields for cell growth and PHA production on mixtures of acetic and propionic acid as functions of the oxidative phosphorylation efficiency, P/O ratio. The oxidative phosphorylation efficiency was estimated from rate measurements, which in turn allowed the estimation of the theoretical yield coefficients. The model was validated with experimental data collected in a sequencing batch reactor (SBR) operated under varying feeding conditions: feeding of acetic and propionic acid separately (control experiments), and the feeding of acetic and propionic acid simultaneously. Two different feast and famine culture enrichment strategies were studied: (i) either with acetate or (ii) with propionate as carbon source material. Metabolic flux analysis (MFA) was performed for the different feeding conditions and culture enrichment strategies. Flux balance analysis (FBA) was used to calculate optimal feeding scenarios for high quality PHA polymers production, where it was found that a suitable polymer would be obtained when acetate is fed in excess and the feeding rate of propionate is limited to approximately 0.17 C-mol/(C-mol.h). The results were compared with published pure culture metabolic studies. Acetate was more conducive toward the enrichment of a microbial culture with higher PHA storage fluxes and yields as compared to propionate. The P/O ratio was not only influenced by the selected microbial culture, but also by the carbon substrate fed to each culture, where higher P/O ratio values were consistently observed for acetate than propionate. MFA studies suggest that when mixtures of acetate and propionate are fed to the

  5. Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling

    PubMed Central

    Wodke, Judith A H; Puchałka, Jacek; Lluch-Senar, Maria; Marcos, Josep; Yus, Eva; Godinho, Miguel; Gutiérrez-Gallego, Ricardo; dos Santos, Vitor A P Martins; Serrano, Luis; Klipp, Edda; Maier, Tobias

    2013-01-01

    Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms. PMID:23549481

  6. Production of diacetyl by metabolically engineered Enterobacter cloacae

    PubMed Central

    Zhang, Lijie; Zhang, Yingxin; Liu, Qiuyuan; Meng, Liying; Hu, Mandong; Lv, Min; Li, Kun; Gao, Chao; Xu, Ping; Ma, Cuiqing

    2015-01-01

    Diacetyl, a high value product that can be extensively used as a food ingredient, could be produced from the non-enzymatic oxidative decarboxylation of α-acetolactate during 2,3-butanediol fermentation. In this study, the 2,3-butanediol biosynthetic pathway in Enterobacter cloacae subsp. dissolvens strain SDM, a good candidate for microbial 2,3-butanediol production, was reconstructed for diacetyl production. To enhance the accumulation of the precursor of diacetyl, the α-acetolactate decarboxylase encoding gene (budA) was knocked out in strain SDM. Subsequently, the two diacetyl reductases DR-I (gdh) and DR-II (budC) encoding genes were inactivated in strain SDM individually or in combination to decrease the reduction of diacetyl. Although the engineered strain E. cloacae SDM (ΔbudAΔbudC) was found to have a good ability for diacetyl production, more α-acetolactate than diacetyl was produced simultaneously. In order to enhance the nonenzymatic oxidative decarboxylation of α-acetolactate to diacetyl, 20 mM Fe3+ was added to the fermentation broth at the optimal time. In the end, by using the metabolically engineered strain E. cloacae SDM (ΔbudAΔbudC), diacetyl at a concentration of 1.45 g/L was obtained with a high productivity (0.13 g/(L·h)). The method developed here may be a promising process for biotechnological production of diacetyl. PMID:25761989

  7. Membrane transporters in a human genome-scale metabolic knowledgebase and their implications for disease

    PubMed Central

    Sahoo, Swagatika; Aurich, Maike K.; Jonsson, Jon J.; Thiele, Ines

    2014-01-01

    Membrane transporters enable efficient cellular metabolism, aid in nutrient sensing, and have been associated with various diseases, such as obesity and cancer. Genome-scale metabolic network reconstructions capture genomic, physiological, and biochemical knowledge of a target organism, along with a detailed representation of the cellular metabolite transport mechanisms. Since the first reconstruction of human metabolism, Recon 1, published in 2007, progress has been made in the field of metabolite transport. Recently, we published an updated reconstruction, Recon 2, which significantly improved the metabolic coverage and functionality. Human metabolic reconstructions have been used to investigate the role of metabolism in disease and to predict biomarkers and drug targets. Given the importance of cellular transport systems in understanding human metabolism in health and disease, we analyzed the coverage of transport systems for various metabolite classes in Recon 2. We will review the current knowledge on transporters (i.e., their preferred substrates, transport mechanisms, metabolic relevance, and disease association for each metabolite class). We will assess missing coverage and propose modifications and additions through a transport module that is functional when combined with Recon 2. This information will be valuable for further refinements. These data will also provide starting points for further experiments by highlighting areas of incomplete knowledge. This review represents the first comprehensive overview of the transporters involved in central metabolism and their transport mechanisms, thus serving as a compendium of metabolite transporters specific for human metabolic reconstructions. PMID:24653705

  8. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    NASA Astrophysics Data System (ADS)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  9. Intraspecific variation in the metabolic scaling exponent in ectotherms: testing the effect of latitudinal cline, ontogeny and transgenerational change in the land snail Cornu aspersum.

    PubMed

    Gaitán-Espitia, Juan Diego; Bruning, Andrea; Mondaca, Fredy; Nespolo, Roberto F

    2013-06-01

    The strong dependence of metabolic rates on body mass has attracted the interest of ecological physiologists, as it has important implications to many aspects of biology including species variations in body size, the evolution of life history, and the structure and function of biological communities. The great diversity of observed scaling exponents has led some authors to conclude that there is no single universal scaling exponent, but instead it ranges from 2/3 to 1. Most of the telling evidence against the universality of power scaling exponents comes from ontogenetic changes. Nevertheless, there could be other sources of phenotypic variation that influence this allometric relationship at least at the intraspecific level. In order to explore the general concept of the metabolic scaling in terrestrial molluscs we tested the role of several biological and methodological sources of variation on the empirically estimated scaling exponent. Specifically, we measured a proxy of metabolic rate (CO(2) production) in 421 individuals, during three generations, in three different populations. Additionally, we measured this scaling relationship in 208 individuals at five developmental stages. Our results suggest that the metabolic scaling exponent at the intraspecific level does not have a single stationary value, but instead it shows some degree of variation across geographic distribution, transgenerational change and ontogenetic stages. The major differences in the metabolic scaling exponent that we found were at different developmental stages of snails, because ontogeny involves increases in size at different rates, which in turn, generate differential energy demands. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Size matters: plasticity in metabolic scaling shows body-size may modulate responses to climate change.

    PubMed

    Carey, Nicholas; Sigwart, Julia D

    2014-08-01

    Variability in metabolic scaling in animals, the relationship between metabolic rate ( R: ) and body mass ( M: ), has been a source of debate and controversy for decades. R: is proportional to MB: , the precise value of B: much debated, but historically considered equal in all organisms. Recent metabolic theory, however, predicts B: to vary among species with ecology and metabolic level, and may also vary within species under different abiotic conditions. Under climate change, most species will experience increased temperatures, and marine organisms will experience the additional stressor of decreased seawater pH ('ocean acidification'). Responses to these environmental changes are modulated by myriad species-specific factors. Body-size is a fundamental biological parameter, but its modulating role is relatively unexplored. Here, we show that changes to metabolic scaling reveal asymmetric responses to stressors across body-size ranges; B: is systematically decreased under increasing temperature in three grazing molluscs, indicating smaller individuals were more responsive to warming. Larger individuals were, however, more responsive to reduced seawater pH in low temperatures. These alterations to the allometry of metabolism highlight abiotic control of metabolic scaling, and indicate that responses to climate warming and ocean acidification may be modulated by body-size. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  11. Size matters: plasticity in metabolic scaling shows body-size may modulate responses to climate change

    PubMed Central

    Carey, Nicholas; Sigwart, Julia D.

    2014-01-01

    Variability in metabolic scaling in animals, the relationship between metabolic rate (R) and body mass (M), has been a source of debate and controversy for decades. R is proportional to Mb, the precise value of b much debated, but historically considered equal in all organisms. Recent metabolic theory, however, predicts b to vary among species with ecology and metabolic level, and may also vary within species under different abiotic conditions. Under climate change, most species will experience increased temperatures, and marine organisms will experience the additional stressor of decreased seawater pH (‘ocean acidification’). Responses to these environmental changes are modulated by myriad species-specific factors. Body-size is a fundamental biological parameter, but its modulating role is relatively unexplored. Here, we show that changes to metabolic scaling reveal asymmetric responses to stressors across body-size ranges; b is systematically decreased under increasing temperature in three grazing molluscs, indicating smaller individuals were more responsive to warming. Larger individuals were, however, more responsive to reduced seawater pH in low temperatures. These alterations to the allometry of metabolism highlight abiotic control of metabolic scaling, and indicate that responses to climate warming and ocean acidification may be modulated by body-size. PMID:25122741

  12. A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

    DOE PAGES

    Khodayari, Ali; Maranas, Costas D.

    2016-12-20

    Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less

  13. A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

    PubMed Central

    Khodayari, Ali; Maranas, Costas D.

    2016-01-01

    Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). The Pearson correlation coefficient between experimental data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47 (k-ecoli457 is available for download at http://www.maranasgroup.com). PMID:27996047

  14. Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement

    PubMed Central

    2010-01-01

    Background Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism. Results A fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified. Conclusion The genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized

  15. Improvement of lincomycin production by mutant selection and metabolic regulation.

    PubMed

    Pang, Xuewei; Zheng, Yitao; Qiao, Xianting; Mao, Quangui; Ma, Qian; Ye, Ruifang

    2017-08-09

    Lincomycin is a lincosamide antibiotic produced by Streptomyces lincolnensis. Through mutagenesis by ethylmethansulfonate (EMS) and ultraviolet (UV) irradiation repeatedly, M2 was picked out in plate with glutamine and propylproline orderly. In 50-L stirred bioreactor, the production of lincomycin, fermented by M2, was increased to 8136 u/ml under the optimal condition as compared to original strain S. lincolnensis 07-5 (6634 u/ml). Two-dimensional gel electrophoresis (2-D GE) and mass spectrometry (MS)-shown LmbG, LmbI, and acetohydroxy acid isomeroreductase were remarkably synthesized in M2. The gene lmbG and lmbI are responsible for methylation in the lincomycin biosynthetic cluster, while acetohydroxy acid isomeroreductase contributes to stronger metabolic capability. Finally, we obtained a better strain for industrial production.

  16. Metabolic Engineering of Escherichia coli for Production of Mixed-Acid Fermentation End Products

    PubMed Central

    Förster, Andreas H.; Gescher, Johannes

    2014-01-01

    Mixed-acid fermentation end products have numerous applications in biotechnology. This is probably the main driving force for the development of multiple strains that are supposed to produce individual end products with high yields. The process of engineering Escherichia coli strains for applied production of ethanol, lactate, succinate, or acetate was initiated several decades ago and is still ongoing. This review follows the path of strain development from the general characteristics of aerobic versus anaerobic metabolism over the regulatory machinery that enables the different metabolic routes. Thereafter, major improvements for broadening the substrate spectrum of E. coli toward cheap carbon sources like molasses or lignocellulose are highlighted before major routes of strain development for the production of ethanol, acetate, lactate, and succinate are presented. PMID:25152889

  17. Dietary fat quantity and quality modifies advanced glycation end products metabolism in patients with metabolic syndrome.

    PubMed

    Lopez-Moreno, Javier; Quintana-Navarro, Gracia M; Camargo, Antonio; Jimenez-Lucena, Rosa; Delgado-Lista, Javier; Marin, Carmen; Tinahones, Francisco J; Striker, Gary E; Roche, Helen M; Perez-Martinez, Pablo; Lopez-Miranda, Jose; Yubero-Serrano, Elena M

    2017-08-01

    Advanced glycation end products (AGEs) increase in dysmetabolic conditions. Lifestyle, including diet, has shown be effective in preventing the development of metabolic syndrome (MetS). We investigated whether AGE metabolism is affected by diets with different fat quantity and quality in MetS patients. A randomized, controlled trial assigned 75 MetS patients to one of four diets: high SFA (HSFA), high MUFA (HMUFA), and two low-fat, high-complex carbohydrate diets (LFHCC) supplemented with long-chain n-3 PUFA or placebo for 12-weeks each. Dietary and serum AGE [methylglyoxal (MG: lysine-MG-H1) and N-carboxymethyllysine] levels and gene expression related to AGE metabolism in peripheral blood mononuclear cells (AGER1, RAGE, GloxI, and Sirt1 mRNA) were determined. HMUFA diet reduced serum AGE (sAGE) and RAGE mRNA, increased AGER1 and GloxI mRNA levels compared to the other diets. LFHCC n-3 diet reduced sAGE levels and increased AGER1 mRNA levels compared to LFHCC and HSFA diets. Multiple regression analyses showed that sMG and AGER1 mRNA appeared as significant predictors of oxidative stress/inflammation-related parameters. Low AGE content in HMUFA diet reduces sAGEs and modulates the gene expression related to AGE metabolism in MetS patients, which may be used as a therapeutic approach to reduce the incidence of MetS and related chronic diseases. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. The components of crop productivity: measuring and modeling plant metabolism

    NASA Technical Reports Server (NTRS)

    Bugbee, B.

    1995-01-01

    Several investigators in the CELSS program have demonstrated that crop plants can be remarkably productive in optimal environments where plants are limited only by incident radiation. Radiation use efficiencies of 0.4 to 0.7 g biomass per mol of incident photons have been measured for crops in several laboratories. Some early published values for radiation use efficiency (1 g mol-1) were inflated due to the effect of side lighting. Sealed chambers are the basic research module for crop studies for space. Such chambers allow the measurement of radiation and CO2 fluxes, thus providing values for three determinants of plant growth: radiation absorption, photosynthetic efficiency (quantum yield), and respiration efficiency (carbon use efficiency). Continuous measurement of each of these parameters over the plant life cycle has provided a blueprint for daily growth rates, and is the basis for modeling crop productivity based on component metabolic processes. Much of what has been interpreted as low photosynthetic efficiency is really the result of reduced leaf expansion and poor radiation absorption. Measurements and models of short-term (minutes to hours) and long-term (days to weeks) plant metabolic rates have enormously improved our understanding of plant environment interactions in ground-based growth chambers and are critical to understanding plant responses to the space environment.

  19. The components of crop productivity: measuring and modeling plant metabolism

    NASA Technical Reports Server (NTRS)

    Bugbee, B.

    1995-01-01

    Several investigators in the CELSS program have demonstrated that crop plants can be remarkably productive in optimal environments where plants are limited only by incident radiation. Radiation use efficiencies of 0.4 to 0.7 g biomass per mol of incident photons have been measured for crops in several laboratories. Some early published values for radiation use efficiency (1 g mol-1) were inflated due to the effect of side lighting. Sealed chambers are the basic research module for crop studies for space. Such chambers allow the measurement of radiation and CO2 fluxes, thus providing values for three determinants of plant growth: radiation absorption, photosynthetic efficiency (quantum yield), and respiration efficiency (carbon use efficiency). Continuous measurement of each of these parameters over the plant life cycle has provided a blueprint for daily growth rates, and is the basis for modeling crop productivity based on component metabolic processes. Much of what has been interpreted as low photosynthetic efficiency is really the result of reduced leaf expansion and poor radiation absorption. Measurements and models of short-term (minutes to hours) and long-term (days to weeks) plant metabolic rates have enormously improved our understanding of plant environment interactions in ground-based growth chambers and are critical to understanding plant responses to the space environment.

  20. Metabolic engineering of Escherichia coli for the production of cinnamaldehyde.

    PubMed

    Bang, Hyun Bae; Lee, Yoon Hyeok; Kim, Sun Chang; Sung, Chang Keun; Jeong, Ki Jun

    2016-01-19

    Plant parasitic nematodes are harmful to agricultural crops and plants, and may cause severe yield losses. Cinnamaldehyde, a volatile, yellow liquid commonly used as a flavoring or food additive, is increasingly becoming a popular natural nematicide because of its high nematicidal activity and, there is a high demand for the development of a biological platform to produce cinnamaldehyde. We engineered Escherichia coli as an eco-friendly biological platform for the production of cinnamaldehyde. In E. coli, cinnamaldehyde can be synthesized from intracellular L-phenylalanine, which requires the activities of three enzymes: phenylalanine-ammonia lyase (PAL), 4-coumarate:CoA ligase (4CL), and cinnamoyl-CoA reductase (CCR). For the efficient production of cinnamaldehyde in E. coli, we first examined the activities of enzymes from different sources and a gene expression system for the selected enzymes was constructed. Next, the metabolic pathway for L-phenylalanine biosynthesis was engineered to increase the intracellular pool of L-phenylalanine, which is a main precursor of cinnamaldehyde. Finally, we tried to produce cinnamaldehyde with the engineered E. coli. According to this result, cinnamaldehyde production as high as 75 mg/L could be achieved, which was about 35-fold higher compared with that in the parental E. coli W3110 harboring a plasmid for cinnamaldehyde biosynthesis. We also confirmed that cinnamaldehyde produced by our engineered E. coli had a nematicidal activity similar to the activity of commercial cinnamaldehyde by nematicidal assays against Bursaphelenchus xylophilus. As a potential natural pesticide, cinnamaldehyde was successfully produced in E. coli by construction of the biosynthesis pathway and, its production titer was also significantly increased by engineering the metabolic pathway of L-phenylalanine.

  1. Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

    PubMed Central

    Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

    2016-01-01

    Motivation Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. Results In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In

  2. Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism.

    PubMed

    Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

    2016-01-01

    Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the

  3. Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling.

    PubMed

    Gutierrez, Jahir M; Lewis, Nathan E

    2015-07-01

    Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Redirecting reductant flux into hydrogen production via metabolic engineering of fermentative carbon metabolism in a cyanobacterium.

    PubMed

    McNeely, Kelsey; Xu, Yu; Bennette, Nick; Bryant, Donald A; Dismukes, G Charles

    2010-08-01

    Some aquatic microbial oxygenic photoautotrophs (AMOPs) make hydrogen (H(2)), a carbon-neutral, renewable product derived from water, in low yields during autofermentation (anaerobic metabolism) of intracellular carbohydrates previously stored during aerobic photosynthesis. We have constructed a mutant (the ldhA mutant) of the cyanobacterium Synechococcus sp. strain PCC 7002 lacking the enzyme for the NADH-dependent reduction of pyruvate to D-lactate, the major fermentative reductant sink in this AMOP. Both nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS) metabolomic methods have shown that autofermentation by the ldhA mutant resulted in no D-lactate production and higher concentrations of excreted acetate, alanine, succinate, and hydrogen (up to 5-fold) compared to that by the wild type. The measured intracellular NAD(P)(H) concentrations demonstrated that the NAD(P)H/NAD(P)(+) ratio increased appreciably during autofermentation in the ldhA strain; we propose this to be the principal source of the observed increase in H(2) production via an NADH-dependent, bidirectional [NiFe] hydrogenase. Despite the elevated NAD(P)H/NAD(P)(+) ratio, no decrease was found in the rate of anaerobic conversion of stored carbohydrates. The measured energy conversion efficiency (ECE) from biomass (as glucose equivalents) converted to hydrogen in the ldhA mutant is 12%. Together with the unimpaired photoautotrophic growth of the ldhA mutant, these attributes reveal that metabolic engineering is an effective strategy to enhance H(2) production in AMOPs without compromising viability.

  5. Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiological constraints.

    PubMed

    Chakrabarti, Anirikh; Miskovic, Ljubisa; Soh, Keng Cher; Hatzimanikatis, Vassily

    2013-09-01

    Mathematical modeling is an essential tool for the comprehensive understanding of cell metabolism and its interactions with the environmental and process conditions. Recent developments in the construction and analysis of stoichiometric models made it possible to define limits on steady-state metabolic behavior using flux balance analysis. However, detailed information on enzyme kinetics and enzyme regulation is needed to formulate kinetic models that can accurately capture the dynamic metabolic responses. The use of mechanistic enzyme kinetics is a difficult task due to uncertainty in the kinetic properties of enzymes. Therefore, the majority of recent works considered only mass action kinetics for reactions in metabolic networks. Herein, we applied the optimization and risk analysis of complex living entities (ORACLE) framework and constructed a large-scale mechanistic kinetic model of optimally grown Escherichia coli. We investigated the complex interplay between stoichiometry, thermodynamics, and kinetics in determining the flexibility and capabilities of metabolism. Our results indicate that enzyme saturation is a necessary consideration in modeling metabolic networks and it extends the feasible ranges of metabolic fluxes and metabolite concentrations. Our results further suggest that enzymes in metabolic networks have evolved to function at different saturation states to ensure greater flexibility and robustness of cellular metabolism.

  6. Redesigning Escherichia coli metabolism for anaerobic production of isobutanol.

    PubMed

    Trinh, Cong T; Li, Johnny; Blanch, Harvey W; Clark, Douglas S

    2011-07-01

    Fermentation enables the production of reduced metabolites, such as the biofuels ethanol and butanol, from fermentable sugars. This work demonstrates a general approach for designing and constructing a production host that uses a heterologous pathway as an obligately fermentative pathway to produce reduced metabolites, specifically, the biofuel isobutanol. Elementary mode analysis was applied to design an Escherichia coli strain optimized for isobutanol production under strictly anaerobic conditions. The central metabolism of E. coli was decomposed into 38,219 functional, unique, and elementary modes (EMs). The model predictions revealed that during anaerobic growth E. coli cannot produce isobutanol as the sole fermentative product. By deleting 7 chromosomal genes, the total 38,219 EMs were constrained to 12 EMs, 6 of which can produce high yields of isobutanol in a range from 0.29 to 0.41 g isobutanol/g glucose under anaerobic conditions. The remaining 6 EMs rely primarily on the pyruvate dehydrogenase enzyme complex (PDHC) and are typically inhibited under anaerobic conditions. The redesigned E. coli strain was constrained to employ the anaerobic isobutanol pathways through deletion of 7 chromosomal genes, addition of 2 heterologous genes, and overexpression of 5 genes. Here we present the design, construction, and characterization of an isobutanol-producing E. coli strain to illustrate the approach. The model predictions are evaluated in relation to experimental data and strategies proposed to improve anaerobic isobutanol production. We also show that the endogenous alcohol/aldehyde dehydrogenase AdhE is the key enzyme responsible for the production of isobutanol and ethanol under anaerobic conditions. The glycolytic flux can be controlled to regulate the ratio of isobutanol to ethanol production.

  7. High Production of 3-Hydroxypropionic Acid in Klebsiella pneumoniae by Systematic Optimization of Glycerol Metabolism

    PubMed Central

    Li, Ying; Wang, Xi; Ge, Xizhen; Tian, Pingfang

    2016-01-01

    3-Hydroxypropionic acid (3-HP) is an important platform chemical proposed by the United States Department of Energy. 3-HP can be converted to a series of bulk chemicals. Biological production of 3-HP has made great progress in recent years. However, low yield of 3-HP restricts its commercialization. In this study, systematic optimization was conducted towards high-yield production of 3-HP in Klebsiella pneumoniae. We first investigated appropriate promoters for the key enzyme (aldehyde dehydrogenase, ALDH) in 3-HP biosynthesis, and found that IPTG-inducible tac promoter enabled overexpression of an endogenous ALDH (PuuC) in K. pneumoniae. We optimized the metabolic flux and found that blocking the synthesis of lactic acid and acetic acid significantly increased the production of 3-HP. Additionally, fermentation conditions were optimized and scaled-up cultivation were investigated. The highest 3-HP titer was observed at 83.8 g/L with a high conversion ratio of 54% on substrate glycerol. Furthermore, a flux distribution model of glycerol metabolism in K. pneumoniae was proposed based on in silico analysis. To our knowledge, this is the highest 3-HP production in K. pneumoniae. This work has significantly advanced biological production of 3-HP from renewable carbon sources. PMID:27230116

  8. Engineering electron metabolism to increase ethanol production in Clostridium thermocellum

    DOE PAGES

    Lo, Jonathan; Olson, Daniel G.; Murphy, Sean Jean-Loup; ...

    2016-10-28

    Here, the NfnAB (NADH-dependent reduced ferredoxin:NADP+ oxidoreductase) and Rnf (Rhodobacter nitrogen fixation) complexes are thought to catalyze electron transfer between reduced ferredoxin and NAD(P)+. Efficient electron flux is critical for engineering fuel production pathways, but little is known about the relative importance of these enzymes in vivo. In this study we investigate the importance of the NfnAB and Rnf complexes in Clostridium thermocellum for growth on cellobiose and Avicel using gene deletion, enzyme assays, and fermentation product analysis. The NfnAB complex does not seem to play a major role in metabolism, since deletion of nfnAB genes had little effect onmore » the distribution of fermentation products. By contrast, the Rnf complex appears to play an important role in ethanol formation. Deletion of rnf genes resulted in a decrease in ethanol formation. Overexpression of rnf genes resulted in an increase in ethanol production of about 30%, but only in strains where the hydG hydrogenase maturation gene was also deleted.« less

  9. Engineering electron metabolism to increase ethanol production in Clostridium thermocellum

    SciTech Connect

    Lo, Jonathan; Olson, Daniel G.; Murphy, Sean Jean-Loup; Tian, Liang; Hon, Shuen; Lanahan, Anthony; Guss, Adam M.; Lynd, Lee R.

    2016-10-28

    Here, the NfnAB (NADH-dependent reduced ferredoxin:NADP+ oxidoreductase) and Rnf (Rhodobacter nitrogen fixation) complexes are thought to catalyze electron transfer between reduced ferredoxin and NAD(P)+. Efficient electron flux is critical for engineering fuel production pathways, but little is known about the relative importance of these enzymes in vivo. In this study we investigate the importance of the NfnAB and Rnf complexes in Clostridium thermocellum for growth on cellobiose and Avicel using gene deletion, enzyme assays, and fermentation product analysis. The NfnAB complex does not seem to play a major role in metabolism, since deletion of nfnAB genes had little effect on the distribution of fermentation products. By contrast, the Rnf complex appears to play an important role in ethanol formation. Deletion of rnf genes resulted in a decrease in ethanol formation. Overexpression of rnf genes resulted in an increase in ethanol production of about 30%, but only in strains where the hydG hydrogenase maturation gene was also deleted.

  10. Metabolic engineering of biocatalysts for carboxylic acids production

    PubMed Central

    Liu, Ping; Jarboe, Laura R.

    2012-01-01

    Fermentation of renewable feedstocks by microbes to produce sustainable fuels and chemicals has the potential to replace petrochemical-based production. For example, carboxylic acids produced by microbial fermentation can be used to generate primary building blocks of industrial chemicals by either enzymatic or chemical catalysis. In order to achieve the titer, yield and productivity values required for economically viable processes, the carboxylic acid-producing microbes need to be robust and well-performing. Traditional strain development methods based on mutagenesis have proven useful in the selection of desirable microbial behavior, such as robustness and carboxylic acid production. On the other hand, rationally-based metabolic engineering, like genetic manipulation for pathway design, has becoming increasingly important to this field and has been used for the production of several organic acids, such as succinic acid, malic acid and lactic acid. This review investigates recent works on Saccharomyces cerevisiae and Escherichia coli, as well as the strategies to improve tolerance towards these chemicals. PMID:24688671

  11. Metabolic engineering of Bacillus subtilis for terpenoid production.

    PubMed

    Guan, Zheng; Xue, Dan; Abdallah, Ingy I; Dijkshoorn, Linda; Setroikromo, Rita; Lv, Guiyuan; Quax, Wim J

    2015-11-01

    Terpenoids are the largest group of small-molecule natural products, with more than 60,000 compounds made from isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP). As the most diverse group of small-molecule natural products, terpenoids play an important role in the pharmaceutical, food, and cosmetic industries. For decades, Escherichia coli (E. coli) and Saccharomyces cerevisiae (S. cerevisiae) were extensively studied to biosynthesize terpenoids, because they are both fully amenable to genetic modifications and have vast molecular resources. On the other hand, our literature survey (20 years) revealed that terpenoids are naturally more widespread in Bacillales. In the mid-1990s, an inherent methylerythritol phosphate (MEP) pathway was discovered in Bacillus subtilis (B. subtilis). Since B. subtilis is a generally recognized as safe (GRAS) organism and has long been used for the industrial production of proteins, attempts to biosynthesize terpenoids in this bacterium have aroused much interest in the scientific community. This review discusses metabolic engineering of B. subtilis for terpenoid production, and encountered challenges will be discussed. We will summarize some major advances and outline future directions for exploiting the potential of B. subtilis as a desired "cell factory" to produce terpenoids.

  12. Metabolic Engineering of Oleaginous Yeasts for Fatty Alcohol Production

    SciTech Connect

    Wang, Wei; Wei, Hui; Knoshaug, Eric; Van Wychen, Stefanie; Xu, Qi; Himmel, Michael E.; Zhang, Min

    2016-04-25

    To develop pathways for advanced biological upgrading of sugars to hydrocarbons, we are seeking biological approaches to produce high carbon efficiency intermediates amenable to separations and catalytic upgrading to hydrocarbon fuels. In this study, we successfully demonstrated fatty alcohol production by oleaginous yeasts Yarrowia lipolytica and Lipomyces starkeyi by expressing a bacteria-derived fatty acyl-CoA reductase (FAR). Moreover, we find higher extracellular distribution of fatty alcohols produced by FAR-expressing L. starkeyi strain as compared to Y. lipolytica strain, which would benefit the downstream product recovery process. In both oleaginous yeasts, long chain length saturated fatty alcohols were predominant, accounting for more than 85% of the total fatty alcohols produced. To the best of our knowledge, this is the first report of fatty alcohol production in L. starkeyi. Taken together, our work demonstrates that in addition to Y. lipolytica, L. starkeyi can also serve as a platform organism for production of fatty acid-derived biofuels and bioproducts via metabolic engineering. We believe strain and process development both will significantly contribute to our goal of producing scalable and cost-effective fatty alcohols from renewable biomass.

  13. EColiCore2: a reference network model of the central metabolism of Escherichia coli and relationships to its genome-scale parent model.

    PubMed

    Hädicke, Oliver; Klamt, Steffen

    2017-01-03

    Genome-scale metabolic modeling has become an invaluable tool to analyze properties and capabilities of metabolic networks and has been particularly successful for the model organism Escherichia coli. However, for several applications, smaller metabolic (core) models are needed. Using a recently introduced reduction algorithm and the latest E. coli genome-scale reconstruction iJO1366, we derived EColiCore2, a model of the central metabolism of E. coli. EColiCore2 is a subnetwork of iJO1366 and preserves predefined phenotypes including optimal growth on different substrates. The network comprises 486 metabolites and 499 reactions, is accessible for elementary-modes analysis and can, if required, be further compressed to a network with 82 reactions and 54 metabolites having an identical solution space as EColiCore2. A systematic comparison of EColiCore2 with its genome-scale parent model iJO1366 reveals that several key properties (flux ranges, reaction essentialities, production envelopes) of the central metabolism are preserved in EColiCore2 while it neglects redundancies along biosynthetic routes. We also compare calculated metabolic engineering strategies in both models and demonstrate, as a general result, how intervention strategies found in a core model allow the identification of valid strategies in a genome-scale model. Overall, EColiCore2 holds promise to become a reference model of E. coli's central metabolism.

  14. EColiCore2: a reference network model of the central metabolism of Escherichia coli and relationships to its genome-scale parent model

    PubMed Central

    Hädicke, Oliver; Klamt, Steffen

    2017-01-01

    Genome-scale metabolic modeling has become an invaluable tool to analyze properties and capabilities of metabolic networks and has been particularly successful for the model organism Escherichia coli. However, for several applications, smaller metabolic (core) models are needed. Using a recently introduced reduction algorithm and the latest E. coli genome-scale reconstruction iJO1366, we derived EColiCore2, a model of the central metabolism of E. coli. EColiCore2 is a subnetwork of iJO1366 and preserves predefined phenotypes including optimal growth on different substrates. The network comprises 486 metabolites and 499 reactions, is accessible for elementary-modes analysis and can, if required, be further compressed to a network with 82 reactions and 54 metabolites having an identical solution space as EColiCore2. A systematic comparison of EColiCore2 with its genome-scale parent model iJO1366 reveals that several key properties (flux ranges, reaction essentialities, production envelopes) of the central metabolism are preserved in EColiCore2 while it neglects redundancies along biosynthetic routes. We also compare calculated metabolic engineering strategies in both models and demonstrate, as a general result, how intervention strategies found in a core model allow the identification of valid strategies in a genome-scale model. Overall, EColiCore2 holds promise to become a reference model of E. coli’s central metabolism. PMID:28045126

  15. Body shape shifting during growth permits tests that distinguish between competing geometric theories of metabolic scaling.

    PubMed

    Hirst, Andrew G; Glazier, Douglas S; Atkinson, David

    2014-10-01

    Metabolism fuels all of life's activities, from biochemical reactions to ecological interactions. According to two intensely debated theories, body size affects metabolism via geometrical influences on the transport of resources and wastes. However, these theories differ crucially in whether the size dependence of metabolism is derived from material transport across external surfaces, or through internal resource-transport networks. We show that when body shape changes during growth, these models make opposing predictions. These models are tested using pelagic invertebrates, because these animals exhibit highly variable intraspecific scaling relationships for metabolic rate and body shape. Metabolic scaling slopes of diverse integument-breathing species were significantly positively correlated with degree of body flattening or elongation during ontogeny, as expected from surface area theory, but contradicting the negative correlations predicted by resource-transport network models. This finding explains strong deviations from predictions of widely adopted theory, and underpins a new explanation for mass-invariant metabolic scaling during ontogeny in animals and plants. © 2014 John Wiley & Sons Ltd/CNRS.

  16. GEMSiRV: a software platform for GEnome-scale metabolic model simulation, reconstruction and visualization.

    PubMed

    Liao, Yu-Chieh; Tsai, Ming-Hsin; Chen, Feng-Chi; Hsiung, Chao A

    2012-07-01

    Genome-scale metabolic network models have become an indispensable part of the increasingly important field of systems biology. Metabolic systems biology studies usually include three major components-network model construction, objective- and experiment-guided model editing and visualization, and simulation studies based mainly on flux balance analyses. Bioinformatics tools are required to facilitate these complicated analyses. Although some of the required functions have been served separately by existing tools, a free software resource that simultaneously serves the needs of the three major components is not yet available. Here we present a software platform, GEMSiRV (GEnome-scale Metabolic model Simulation, Reconstruction and Visualization), to provide functionalities of easy metabolic network drafting and editing, amenable network visualization for experimental data integration and flux balance analysis tools for simulation studies. GEMSiRV comes with downloadable, ready-to-use public-domain metabolic models, reference metabolite/reaction databases and metabolic network maps, all of which can be input into GEMSiRV as the starting materials for network construction or simulation analyses. Furthermore, all of the GEMSiRV-generated metabolic models and analysis results, including projects in progress, can be easily exchanged in the research community. GEMSiRV is a powerful integrative resource that may facilitate the development of systems biology studies. The software is freely available on the web at http://sb.nhri.org.tw/GEMSiRV.

  17. l-Malate Production by Metabolically Engineered Escherichia coli▿ †

    PubMed Central

    Zhang, X.; Wang, X.; Shanmugam, K. T.; Ingram, L. O.

    2011-01-01

    Escherichia coli strains (KJ060 and KJ073) that were previously developed for succinate production have now been modified for malate production. Many unexpected changes were observed during this investigation. The initial strategy of deleting fumarase isoenzymes was ineffective, and succinate continued to accumulate. Surprisingly, a mutation in fumarate reductase alone was sufficient to redirect carbon flow into malate even in the presence of fumarase. Further deletions were needed to inactivate malic enzymes (typically gluconeogenic) and prevent conversion to pyruvate. However, deletion of these genes (sfcA and maeB) resulted in the unexpected accumulation of d-lactate despite the prior deletion of mgsA and ldhA and the absence of apparent lactate dehydrogenase activity. Although the metabolic source of this d-lactate was not identified, lactate accumulation was increased by supplementation with pyruvate and decreased by the deletion of either pyruvate kinase gene (pykA or pykF) to reduce the supply of pyruvate. Many of the gene deletions adversely affected growth and cell yield in minimal medium under anaerobic conditions, and volumetric rates of malate production remained low. The final strain (XZ658) produced 163 mM malate, with a yield of 1.0 mol (mol glucose−1), half of the theoretical maximum. Using a two-stage process (aerobic cell growth and anaerobic malate production), this engineered strain produced 253 mM malate (34 g liter−1) within 72 h, with a higher yield (1.42 mol mol−1) and productivity (0.47 g liter−1 h−1). This malate yield and productivity are equal to or better than those of other known biocatalysts. PMID:21097588

  18. Solar photocatalytic oxidation of recalcitrant natural metabolic by-products of amoxicillin biodegradation.

    PubMed

    Pereira, João H O S; Reis, Ana C; Homem, Vera; Silva, José A; Alves, Arminda; Borges, Maria T; Boaventura, Rui A R; Vilar, Vítor J P; Nunes, Olga C

    2014-11-15

    The contamination of the aquatic environment by non-metabolized and metabolized antibiotic residues has brought the necessity of alternative treatment steps to current water decontamination technologies. This work assessed the feasibility of using a multistage treatment system for amoxicillin (AMX) spiked solutions combining: i) a biological treatment process using an enriched culture to metabolize AMX, with ii) a solar photocatalytic system to achieve the removal of the metabolized transformation products (TPs) identified via LC-MS, recalcitrant to further biological degradation. Firstly, a mixed culture (MC) was obtained through the enrichment of an activated sludge sample collected in an urban wastewater treatment plant (WWTP). Secondly, different aqueous matrices spiked with AMX were treated with the MC and the metabolic transformation products were identified. Thirdly, the efficiency of two solar assisted photocatalytic processes (TiO2/UV or Fe(3+)/Oxalate/H2O2/UV-Vis) was assessed in the degradation of the obtained TPs using a lab-scale prototype photoreactor equipped with a compound parabolic collector (CPC). Highest AMX specific biodegradation rates were obtained in buffer and urban wastewater (WW) media (0.10 ± 0.01 and 0.13 ± 0.07 g(AMX) g(biomass)(-1) h(-1), respectively). The resulting TPs, which no longer presented antibacterial activity, were identified as amoxicilloic acid (m/z = 384). The performance of the Fe(3+)/Oxalate/H2O2/UV-Vis system in the removal of the TPs from WW medium was superior to the TiO2/UV process (TPs no longer detected after 40 min (QUV = 2.6 kJ L(-1)), against incomplete TPs removal after 240 min (QUV = 14.9 kJ L(-1)), respectively). Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Computing the shortest elementary flux modes in genome-scale metabolic networks.

    PubMed

    de Figueiredo, Luis F; Podhorski, Adam; Rubio, Angel; Kaleta, Christoph; Beasley, John E; Schuster, Stefan; Planes, Francisco J

    2009-12-01

    Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity. In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A detailed analysis of the biological significance of the K-shortest EFMs was conducted, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted. The work presented here represents an important step forward in the analysis and computation of EFMs for large-scale metabolic networks, where traditional methods fail for networks of even moderate size. Supplementary data are available at Bioinformatics online.

  20. Metabolic engineering strategies to bio-adipic acid production.

    PubMed

    Kruyer, Nicholas S; Peralta-Yahya, Pamela

    2017-06-01

    Adipic acid is the most industrially important dicarboxylic acid as it is a key monomer in the synthesis of nylon. Today, adipic acid is obtained via a chemical process that relies on petrochemical precursors and releases large quantities of greenhouse gases. In the last two years, significant progress has been made in engineering microbes for the production of adipic acid and its immediate precursors, muconic acid and glucaric acid. Not only have the microbial substrates expanded beyond glucose and glycerol to include lignin monomers and hemicellulose components, but the number of microbial chassis now goes further than Escherichia coli and Saccharomyces cerevisiae to include microbes proficient in aromatic degradation, cellulose secretion and degradation of multiple carbon sources. Here, we review the metabolic engineering and nascent protein engineering strategies undertaken in each of these chassis to convert different feedstocks to adipic, muconic and glucaric acid. We also highlight near term prospects and challenges for each of the metabolic routes discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Engineered Fluorine Metabolism and Fluoropolymer Production in Living Cells.

    PubMed

    Thuronyi, Benjamin W; Privalsky, Thomas M; Chang, Michelle C Y

    2017-08-31

    Fluorine has become an important element for the design of synthetic molecules for use in medicine, agriculture, and materials. Despite the many advantages provided by fluorine for tuning key molecular properties, it is rarely found in natural metabolism. We seek to expand the molecular space available for discovery through the development of new biosynthetic strategies that cross synthetic with natural compounds. Towards this goal, we engineered a microbial host for organofluorine metabolism and show that we can achieve the production of the fluorinated diketide 2-fluoro-3-hydroxybutyrate at approximately 50 % yield. This fluorinated diketide can be used as a monomer in vivo to produce fluorinated poly(hydroxyalkanoate) (PHA) bioplastics with fluorine substitutions ranging from around 5-15 %. This system provides a platform to produce mm flux through the key fluoromalonyl coenzyme A (CoA) building block, thereby offering the potential to generate a broad range of fluorinated small-molecule targets in living cells. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Metabolic engineering of higher plants and algae for isoprenoid production.

    PubMed

    Kempinski, Chase; Jiang, Zuodong; Bell, Stephen; Chappell, Joe

    2015-01-01

    Isoprenoids are a class of compounds derived from the five carbon precursors, dimethylallyl diphosphate, and isopentenyl diphosphate. These molecules present incredible natural chemical diversity, which can be valuable for humans in many aspects such as cosmetics, agriculture, and medicine. However, many terpenoids are only produced in small quantities by their natural hosts and can be difficult to generate synthetically. Therefore, much interest and effort has been directed toward capturing the genetic blueprint for their biochemistry and engineering it into alternative hosts such as plants and algae. These autotrophic organisms are attractive when compared to traditional microbial platforms because of their ability to utilize atmospheric CO2 as a carbon substrate instead of supplied carbon sources like glucose. This chapter will summarize important techniques and strategies for engineering the accumulation of isoprenoid metabolites into higher plants and algae by choosing the correct host, avoiding endogenous regulatory mechanisms, and optimizing potential flux into the target compound. Future endeavors will build on these efforts by fine-tuning product accumulation levels via the vast amount of available "-omic" data and devising metabolic engineering schemes that integrate this into a whole-organism approach. With the development of high-throughput transformation protocols and synthetic biology molecular tools, we have only begun to harness the power and utility of plant and algae metabolic engineering.

  3. Metabolic engineering of Escherichia coli for the production of riboflavin

    PubMed Central

    2014-01-01

    Background Riboflavin (vitamin B2), the precursor of the flavin cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), is used commercially as an animal feed supplement and food colorant. E. coli is a robust host for various genetic manipulations and has been employed for efficient production of biofuels, polymers, amino acids, and bulk chemicals. Thus, the aim of this study was to understand the metabolic capacity of E. coli for the riboflavin production by modification of central metabolism, riboflavin biosynthesis pathway and optimization of the fermentation conditions. Results The basic producer RF01S, in which the riboflavin biosynthesis genes ribABDEC from E. coli were overexpressed under the control of the inducible trc promoter, could accumulate 229.1 mg/L of riboflavin. Further engineering was performed by examining the impact of expression of zwf (encodes glucose 6-phosphate dehydrogenase) and gnd (encodes 6-phosphogluconate dehydrogenase) from Corynebacterium glutamicum and pgl (encodes 6-phosphogluconolactonase) from E. coli on riboflavin production. Deleting pgi (encodes glucose-6-phosphate isomerase) and genes of Entner-Doudoroff (ED) pathway successfully redirected the carbon flux into the oxidative pentose phosphate pathway, and overexpressing the acs (encodes acetyl-CoA synthetase) reduced the acetate accumulation. These modifications increased riboflavin production to 585.2 mg/L. By further modulating the expression of ribF (encodes riboflavin kinase) for reducing the conversion of riboflavin to FMN in RF05S, the final engineering strain RF05S-M40 could produce 1036.1 mg/L riboflavin in LB medium at 37°C. After optimizing the fermentation conditions, strain RF05S-M40 produced 2702.8 mg/L riboflavin in the optimized semi-defined medium, which was a value nearly 12-fold higher than that of RF01S, with a yield of 137.5 mg riboflavin/g glucose. Conclusions The engineered strain RF05S-M40 has the highest yield among all

  4. Double and multiple knockout simulations for genome-scale metabolic network reconstructions.

    PubMed

    Goldstein, Yaron Ab; Bockmayr, Alexander

    2015-01-01

    Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results. A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC.

  5. Biodiesel: Small Scale Production and Quality Requirements

    NASA Astrophysics Data System (ADS)

    van Gerpen, Jon

    Biodiesel is produced by reacting vegetable oils or animal fats with alcohol in the presence of an alkaline catalyst. The resulting methyl esters, which are the biodiesel fuel, are separated from the by-product glycerin, and then washed with water and dehydrated to produce fuel that must meet standardized specifications. Degraded oils containing high levels of free fatty acids can also be converted to biodiesel, but pretreatment with acid-catalyzed esterification is required. The resulting fuel is suitable for use as a neat fuel in diesel engines or blended with conventional diesel fuel.

  6. Biodiesel: small scale production and quality requirements.

    PubMed

    Van Gerpen, Jon

    2009-01-01

    Biodiesel is produced by reacting vegetable oils or animal fats with alcohol in the presence of an alkaline catalyst. The resulting methyl esters, which are the biodiesel fuel, are separated from the by-product glycerin, and then washed with water and dehydrated to produce fuel that must meet standardized specifications. Degraded oils containing high levels of free fatty acids can also be converted to biodiesel, but pretreatment with acid-catalyzed esterification is required. The resulting fuel is suitable for use as a neat fuel in diesel engines or blended with conventional diesel fuel.

  7. Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

    PubMed

    Vivek-Ananth, R P; Samal, Areejit

    2016-09-01

    A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.

  8. Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

    PubMed

    Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

    2016-05-01

    We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02.

  9. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    NASA Astrophysics Data System (ADS)

    Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2013-09-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  10. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    NASA Astrophysics Data System (ADS)

    Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2012-12-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  11. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    SciTech Connect

    Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.; Fang, Yilin; Mahadevan, Radhakrishnan; Lovley, Derek R.

    2013-09-07

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under

  12. CO2 production as an indicator of biofilm metabolism.

    PubMed

    Kroukamp, Otini; Wolfaardt, Gideon M

    2009-07-01

    Biofilms are important in aquatic nutrient cycling and microbial proliferation. In these structures, nutrients like carbon are channeled into the production of extracellular polymeric substances or cell division; both are vital for microbial survival and propagation. The aim of this study was to assess carbon channeling into cellular or noncellular fractions in biofilms. Growing in tubular reactors, biofilms of our model strain Pseudomonas sp. strain CT07 produced cells to the planktonic phase from the early stages of biofilm development, reaching pseudo steady state with a consistent yield of approximately 10(7) cells.cm(-2).h(-1) within 72 h. Total direct counts and image analysis showed that most of the converted carbon occurred in the noncellular fraction, with the released and sessile cells accounting for <10% and <2% of inflowing carbon, respectively. A CO(2) evolution measurement system (CEMS) that monitored CO(2) in the gas phase was developed to perform a complete carbon balance across the biofilm. The measurement system was able to determine whole-biofilm CO(2) production rates in real time and showed that gaseous CO(2) production accounted for 25% of inflowing carbon. In addition, the CEMS made it possible to measure biofilm response to changing environmental conditions; changes in temperature or inflowing carbon concentration were followed by a rapid response in biofilm metabolism and the establishment of new steady-state conditions.

  13. Metabolic modeling of mixed substrate uptake for polyhydroxyalkanoate (PHA) production.

    PubMed

    Jiang, Yang; Hebly, Marit; Kleerebezem, Robbert; Muyzer, Gerard; van Loosdrecht, Mark C M

    2011-01-01

    Polyhydroxyalkanoate (PHA) production by mixed microbial communities can be established in a two-stage process, consisting of a microbial enrichment step and a PHA accumulation step. In this study, a mathematical model was constructed for evaluating the influence of the carbon substrate composition on both steps of the PHA production process. Experiments were conducted with acetate, propionate, and acetate propionate mixtures. Microbial community analysis demonstrated that despite the changes in substrate composition the dominant microorganism was Plasticicumulans acidivorans in all experiments. A metabolic network model was established to investigate the processes observed. The model based analysis indicated that adaptation of the acetate and propionate uptake rate as a function of acetate and propionate concentrations in the substrate during cultivation occurred. The monomer composition of the PHA produced was found to be directly related to the composition of the substrate. Propionate induced mainly polyhydroxyvalerate (PHV) production whereas only polyhydroxybutyrate (PHB) was produced on acetate. Accumulation experiments with acetate-propionate mixtures yielded PHB/PHV mixtures in ratios directly related to the acetate and propionate uptake rate. The model developed can be used as a useful tool to predict the PHA composition as a function of the substrate composition for acetate-propionate mixtures.

  14. A Global-Scale Distributed Geomorphologic Product

    NASA Astrophysics Data System (ADS)

    Shen, X.; Hong, Y.; Wang, D.; Vergara, H. J.; Anagnostou, E. N.

    2015-12-01

    In response to the vital role of geomorphological analysis in natural hazards study, geomorphology, distributed hydrology and other related disciplines, we present the first global basin morphometric product of 30 characteristics, 9 archived elementary including stream order, stream number, stream length, basin relief, basin length, basin perimeter, maximal flow length, down valley length and overland flow length, and 21 derivable from these elementary morphometric characteristics. As a distributed product, characteristics of basins discharging to every grid-cell of the global earth surface are computed at 1km resolution strictly following their definitions. We introduce in this paper an efficient framework to reduce the algorithm complexity to O(N), which results in efficiency improvement in the order of 50-100 times the traditional way. We find that, spatially, 1) the relief ratio reaches its peak values along both sides of the ridges; 2) the fitness ratio of the main stream value often has a sharp decrease at the joint of large tributaries; statistically, 3) only the basin relief exhibits strong discrepancy of distribution among different continents while all others show unexpected homogeneity of distribution in spite of the size (number of cells) difference of continents; 4) the distributions of the main flow length/down valley length and basin length/basin perimeter resemble each other respectively; and 5) the distributions of the two pairs are quite different thus neither the main flow length nor down valley length should be used as substitutions of the basin length as done by some previous studies.

  15. Metabolic engineering of Streptomyces coelicolor for enhanced prodigiosins (RED) production.

    PubMed

    Liu, Panpan; Zhu, Hong; Zheng, Guosong; Jiang, Weihong; Lu, Yinhua

    2017-09-01

    Bacterial prodigiosins are red-colored secondary metabolites with multiple activities, such as anticancer, antimalarial and immunosuppressive, which hold great potential for medical applications. In this study, dramatically enhanced prodigiosins (RED) production in Streptomyces coelicolor was achieved by combinatorial metabolic engineering, including inactivation of the repressor gene ohkA, deletion of the actinorhodin (ACT) and calcium-dependent antibiotic (CDA) biosynthetic gene clusters (BGCs) and multi-copy chromosomal integration of the RED BGC. The results showed that ohkA deletion led to a 1-fold increase of RED production over the wild-type strain M145. Then, the ACT and CDA BGCs were deleted successively based on the ΔohkA mutant (SBJ101). To achieve multi-copy RED BGC integration, artificial ΦC31 attB site(s) were inserted simultaneously at the position where the ACT and CDA BGCs were deleted. The resulting strains SBJ102 (with a single deletion of the ACT BGC and insertion of one artificial attB site) and SBJ103 (with the deletion of both BGCs and insertion of two artificial attB sites) produced 1.9- and 6-fold higher RED titers than M145, respectively. Finally, the entire RED BGC was introduced into mutants from SBJ101 to SBJ103, generating three mutants (from SBJ104 to SBJ106) with chromosomal integration of one to three copies of the RED BGC. The highest RED yield was from SBJ106, which produced a maximum level of 96.8 mg g(-1) cell dry weight, showing a 12-fold increase relative to M145. Collectively, the metabolic engineering strategies employed in this study are very efficient for the construction of high prodigiosin-producing strains.

  16. Characterization of proton production and consumption associated with microbial metabolism

    PubMed Central

    2010-01-01

    Background Production or consumption of protons in growth medium during microbial metabolism plays an important role in determining the pH of the environment. Such pH changes resulting from microbial metabolism may influence the geochemical speciation of many elements in subsurface environments. Protons produced or consumed during microbial growth were measured by determining the amount of acid or base added in a 5 L batch bioreactor equipped with pH control for different species including Escherichia coli, Geobacter sulfurreducens, and Geobacter metallireducens. Results An in silico model was used to predict the proton secretion or consumption rates and the results were compared with the data. The data was found to confirm predictions of proton consumption during aerobic growth of E. coli with acetate as the carbon source. However, in contrast to proton consumption observed during aerobic growth of E. coli with acetate, proton secretion was observed during growth of Geobacter species with acetate as the donor and Fe(III) as the extracellular electron acceptor. Conclusions In this study, we have also shown that the final pH of the medium can be either acidic or basic depending on the choice of the electron acceptor for the same electron donor. In all cases, the in silico model could predict qualitatively the proton production/consumption rates obtained from the experimental data. Therefore, measurements of pH equivalents generated or consumed during growth can help characterize the microbial physiology further and can be valuable for optimizing practical applications such as microbial fuel cells, where growth associated pH changes can limit current generation rates. PMID:20089195

  17. A metabolite-centric view on flux distributions in genome-scale metabolic models

    PubMed Central

    2013-01-01

    Background Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. Results We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. Conclusions The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens

  18. A metabolite-centric view on flux distributions in genome-scale metabolic models.

    PubMed

    Riemer, S Alexander; Rex, René; Schomburg, Dietmar

    2013-04-12

    Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological

  19. Synechocystis sp. PCC6803 metabolic models for the enhanced production of hydrogen.

    PubMed

    Montagud, Arnau; Gamermann, Daniel; Fernández de Córdoba, Pedro; Urchueguía, Javier F

    2015-06-01

    In the present economy, difficulties to access energy sources are real drawbacks to maintain our current lifestyle. In fact, increasing interests have been gathered around efficient strategies to use energy sources that do not generate high CO2 titers. Thus, science-funding agencies have invested more resources into research on hydrogen among other biofuels as interesting energy vectors. This article reviews present energy challenges and frames it into the present fuel usage landscape. Different strategies for hydrogen production are explained and evaluated. Focus is on biological hydrogen production; fermentation and photon-fuelled hydrogen production are compared. Mathematical models in biology can be used to assess, explore and design production strategies for industrially relevant metabolites, such as biofuels. We assess the diverse construction and uses of genome-scale metabolic models of cyanobacterium Synechocystis sp. PCC6803 to efficiently obtain biofuels. This organism has been studied as a potential photon-fuelled production platform for its ability to grow from carbon dioxide, water and photons, on simple culture media. Finally, we review studies that propose production strategies to weigh this organism's viability as a biofuel production platform. Overall, the work presented in this review unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean biofuel production platform.

  20. A model for allometric scaling of mammalian metabolism with ambient heat loss.

    PubMed

    Kwak, Ho Sang; Im, Hong G; Shim, Eun Bo

    2016-03-01

    Allometric scaling, which represents the dependence of biological traits or processes on body size, is a long-standing subject in biological science. However, there has been no study to consider heat loss to the ambient and an insulation layer representing mammalian skin and fur for the derivation of the scaling law of metabolism. A simple heat transfer model is proposed to analyze the allometry of mammalian metabolism. The present model extends existing studies by incorporating various external heat transfer parameters and additional insulation layers. The model equations were solved numerically and by an analytic heat balance approach. A general observation is that the present heat transfer model predicted the 2/3 surface scaling law, which is primarily attributed to the dependence of the surface area on the body mass. External heat transfer effects introduced deviations in the scaling law, mainly due to natural convection heat transfer, which becomes more prominent at smaller mass. These deviations resulted in a slight modification of the scaling exponent to a value < 2/3. The finding that additional radiative heat loss and the consideration of an outer insulation fur layer attenuate these deviation effects and render the scaling law closer to 2/3 provides in silico evidence for a functional impact of heat transfer mode on the allometric scaling law in mammalian metabolism.

  1. Metabolic engineering of Synechocystis sp. PCC 6803 for enhanced ethanol production based on flux balance analysis.

    PubMed

    Yoshikawa, Katsunori; Toya, Yoshihiro; Shimizu, Hiroshi

    2017-05-01

    Synechocystis sp. PCC 6803 is an attractive host for bio-ethanol production due to its ability to directly convert atmospheric carbon dioxide into ethanol using photosystems. To enhance ethanol production in Synechocystis sp. PCC 6803, metabolic engineering was performed based on in silico simulations, using the genome-scale metabolic model. Comprehensive reaction knockout simulations by flux balance analysis predicted that the knockout of NAD(P)H dehydrogenase enhanced ethanol production under photoautotrophic conditions, where ammonium is the nitrogen source. This deletion inhibits the re-oxidation of NAD(P)H, which is generated by ferredoxin-NADP(+) reductase and imposes re-oxidation in the ethanol synthesis pathway. The effect of deleting the ndhF1 gene, which encodes NADH dehydrogenase subunit 5, on ethanol production was experimentally evaluated using ethanol-producing strains of Synechocystis sp. PCC 6803. The ethanol titer of the ethanol-producing ∆ndhF1 strain increased by 145%, compared with that of the control strain.

  2. Expanded bed absorption from laboratory to production scale

    SciTech Connect

    Johansson, S.; Akervall, A.; Hagel, L.

    1995-12-01

    Expanded bed adsorption is a new technique using stable homogeneous fluidization for initial recovery of a product from crude fermentation broth. The technique makes it possible to combine clarification, concentration and product capture in one unit operation. This study shows a 144 fold scale-up from laboratory to production scale. The column sizes used are 50 mm I.D. and 600 mm I.D. respectively. Residence time distribution (RTD), the response from an injected step, was used to evaluate the scale up. This reflects the hydrodynamics of the system. Adsorption kinetics was determined from a breakthrough curve of bovine serum albumine and the binding capacity was calculated. The results show that expanded bed adsorption is scaleable from laboratory to production scale with retained properties.

  3. Temporal and spatial simulation of production-scale irrigated cotton

    USDA-ARS?s Scientific Manuscript database

    Site-specific management of cotton (Gossypium hirsutum) cropping systems at the production-scale requires information regarding interactions between soil, plant, weather, and agronomic inputs. Management decisions regarding the spatially and temporally variable addition of agronomic inputs are most ...

  4. Metabolic Engineering toward Sustainable Production of Nylon-6.

    PubMed

    Turk, Stefan C H J; Kloosterman, Wigard P; Ninaber, Dennis K; Kolen, Karin P A M; Knutova, Julia; Suir, Erwin; Schürmann, Martin; Raemakers-Franken, Petronella C; Müller, Monika; de Wildeman, Stefaan M A; Raamsdonk, Leonie M; van der Pol, Ruud; Wu, Liang; Temudo, Margarida F; van der Hoeven, Rob A M; Akeroyd, Michiel; van der Stoel, Roland E; Noorman, Henk J; Bovenberg, Roel A L; Trefzer, Axel C

    2016-01-15

    Nylon-6 is a bulk polymer used for many applications. It consists of the non-natural building block 6-aminocaproic acid, the linear form of caprolactam. Via a retro-synthetic approach, two synthetic pathways were identified for the fermentative production of 6-aminocaproic acid. Both pathways require yet unreported novel biocatalytic steps. We demonstrated proof of these bioconversions by in vitro enzyme assays with a set of selected candidate proteins expressed in Escherichia coli. One of the biosynthetic pathways starts with 2-oxoglutarate and contains bioconversions of the ketoacid elongation pathway known from methanogenic archaea. This pathway was selected for implementation in E. coli and yielded 6-aminocaproic acid at levels up to 160 mg/L in lab-scale batch fermentations. The total amount of 6-aminocaproic acid and related intermediates generated by this pathway exceeded 2 g/L in lab-scale fed-batch fermentations, indicating its potential for further optimization toward large-scale sustainable production of nylon-6.

  5. Subjective responses to oral tobacco products: scale validation.

    PubMed

    Hatsukami, Dorothy K; Zhang, Yan; O'Connor, Richard J; Severson, Herb H

    2013-07-01

    Several noncombusted oral tobacco products have been introduced that are primarily marketed to cigarette smokers. An important component of evaluating these products involves assessment of subjective responses to the product. To date, few studies have been undertaken to examine the validity of subjective response questionnaires for oral tobacco products. The goal of this study is to examine the extent subjective responses to a product are related to product preference and extent of product use. Data from a study examining oral tobacco product preference were used. Smokers were asked to sample a variety of oral tobacco products that differed in formulation (snus versus dissolvables) and dose of nicotine. At the end of the sampling period, subjects were asked to choose the product that they would use to completely substitute for cigarettes for the next 2 weeks. During the sampling period, subjects completed a Product Evaluation Scale (PES) that describes subjective responses to the product. During the treatment phase, they kept record of amount of product use. Subjective responses to the product on the PES were related to product choice and to some extent, the amount of product use. Product choice was associated with different characteristics of the product and smoker needs. The PES may be a useful tool for the evaluation or oral tobacco products.

  6. Multiscale Metabolic Modeling of C4 Plants: Connecting Nonlinear Genome-Scale Models to Leaf-Scale Metabolism in Developing Maize Leaves

    PubMed Central

    Bogart, Eli; Myers, Christopher R.

    2016-01-01

    C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve the efficiency of carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and oxygen levels and reaction rates are key to their physiology but cannot be handled with standard techniques of constraint-based metabolic modeling. We demonstrate that incorporating these relationships as constraints on reaction rates and solving the resulting nonlinear optimization problem yields realistic predictions of the response of C4 systems to environmental and biochemical perturbations. Using a new genome-scale reconstruction of maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll and bundle sheath cells in 15 segments of the developing maize leaf, interacting via metabolite exchange, and use RNA-seq and enzyme activity measurements to predict spatial variation in metabolic state by a novel method that optimizes correlation between fluxes and expression data. Though such correlations are known to be weak in general, we suggest that developmental gradients may be particularly suited to the inference of metabolic fluxes from expression data, and we demonstrate that our method predicts fluxes that achieve high correlation with the data, successfully capture the experimentally observed base-to-tip transition between carbon-importing tissue and carbon-exporting tissue, and include a nonzero growth rate, in contrast to prior results from similar methods in other systems. PMID:26990967

  7. Genome-scale metabolic reconstructions and theoretical investigation of methane conversion in Methylomicrobium buryatense strain 5G(B1).

    PubMed

    de la Torre, Andrea; Metivier, Aisha; Chu, Frances; Laurens, Lieve M L; Beck, David A C; Pienkos, Philip T; Lidstrom, Mary E; Kalyuzhnaya, Marina G

    2015-11-25

    Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration. A stoichiometric flux balance model of Methylomicrobium buryatense strain 5G(B1) was constructed and used for evaluating metabolic engineering strategies for biofuels and chemical production with a methanotrophic bacterium as the catalytic platform. The initial metabolic reconstruction was based on whole-genome predictions. Each metabolic step was manually verified, gapfilled, and modified in accordance with genome-wide expression data. The final model incorporates a total of 841 reactions (in 167 metabolic pathways). Of these, up to 400 reactions were recruited to produce 118 intracellular metabolites. The flux balance simulations suggest that only the transfer of electrons from methanol oxidation to methane oxidation steps can support measured growth and methane/oxygen consumption parameters, while the scenario employing NADH as a possible source of electrons for particulate methane monooxygenase cannot. Direct coupling between methane oxidation and methanol oxidation accounts for most of the membrane-associated methane monooxygenase activity. However the best fit to experimental results is achieved only after assuming that the efficiency of direct coupling depends on growth conditions and additional NADH input (about 0.1-0.2 mol of incremental NADH per one mol of methane oxidized). The additional input is proposed to cover loss of electrons through inefficiency and to sustain methane oxidation at perturbations or support uphill electron transfer. Finally, the model was used for testing the carbon conversion

  8. Metabolic scaling theory in plant biology and the three oxygen paradoxa of aerobic life.

    PubMed

    Kutschera, Ulrich; Niklas, Karl J

    2013-12-01

    Alfred Russell Wallace was a field naturalist with a strong interest in general physiology. In this vein, he wrote that oxygen (O2), produced by green plants, is "the food of protoplasm, without which it cannot continue to live". Here we summarize current models relating body size to respiration rates (in the context of the metabolic scaling theory) and show that oxygen-uptake activities, measured at 21 vol.% O2, correlate closely with growth patterns at the level of specific organs within the same plant. Thus, whole plant respiration can change ontogenetically, corresponding to alterations in the volume fractions of different tissues. Then, we describe the evolution of cyanobacterial photosynthesis during the Paleoarchean, which changed the world forever. By slowly converting what was once a reducing atmosphere to an oxidizing one, microbes capable of O2-producing photosynthesis modified the chemical nature and distribution of the element iron (Fe), slowly drove some of the most ancient prokaryotes to extinction, created the ozone (O3) layer that subsequently shielded the first terrestrial plants and animals from harmful UV radiation, but also made it possible for Earth's forest to burn, sometimes with catastrophic consequences. Yet another paradox is that the most abundant protein (i.e., the enzyme Rubisco, Ribulose-1,5-biphosphate carboxylase/oxygenase) has a greater affinity for oxygen than for carbon dioxide (CO2), even though its function is to bind with the latter rather than the former. We evaluate this second "oxygen paradox" within the context of photorespiratory carbon loss and crop yield reduction in C3 vs. C4 plants (rye vs. maize). Finally, we analyze the occurrence of reactive oxygen species (ROS) as destructive by-products of cellular metabolism, and discuss the three "O2-paradoxa" with reference to A. R. Wallace's speculations on "design in nature".

  9. 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.

  10. M13 bacteriophage production for large-scale applications.

    PubMed

    Warner, Christopher M; Barker, Natalie; Lee, Seung-Wuk; Perkins, Edward J

    2014-10-01

    Bacteriophage materials have the potential to revolutionize medicine, energy production and storage, agriculture, solar cells, optics and many other fields. To fulfill these needs, this study examined critical process parameters during phage propagation to increase phage production capability. A representative scale-down system was created in tube spin reactors to allow parallel experimentation with single- and multi-variable analysis. Temperature, harvest time, media composition, feed regime, bacteriophage, and bacteria concentration were analyzed in the scale-down system. Temperature, media composition, and feeding regimens were found to affect phage production more than other factors. Temperature affected bacterial growth and phage production inversely. Multi-variate analysis identified an optimal parameter space which provided a significant improvement over the base line method. This method should be useful in scaled production of bacteriophage for biotechnology.

  11. Generation of 2,000 breast cancer metabolic landscapes reveals a poor prognosis group with active serotonin production

    PubMed Central

    Leoncikas, Vytautas; Wu, Huihai; Ward, Lara T.; Kierzek, Andrzej M.; Plant, Nick J.

    2016-01-01

    A major roadblock in the effective treatment of cancers is their heterogeneity, whereby multiple molecular landscapes are classified as a single disease. To explore the contribution of cellular metabolism to cancer heterogeneity, we analyse the Metabric dataset, a landmark genomic and transcriptomic study of 2,000 individual breast tumours, in the context of the human genome-scale metabolic network. We create personalized metabolic landscapes for each tumour by exploring sets of active reactions that satisfy constraints derived from human biochemistry and maximize congruency with the Metabric transcriptome data. Classification of the personalized landscapes derived from 997 tumour samples within the Metabric discovery dataset reveals a novel poor prognosis cluster, reproducible in the 995-sample validation dataset. We experimentally follow mechanistic hypotheses resulting from the computational study and establish that active serotonin production is a major metabolic feature of the poor prognosis group. These data support the reconsideration of concomitant serotonin-specific uptake inhibitors treatment during breast cancer chemotherapy. PMID:26813959

  12. Both respiration and photosynthesis determine the scaling of plankton metabolism in the oligotrophic ocean

    PubMed Central

    Serret, Pablo; Robinson, Carol; Aranguren-Gassis, María; García-Martín, Enma Elena; Gist, Niki; Kitidis, Vassilis; Lozano, José; Stephens, John; Harris, Carolyn; Thomas, Rob

    2015-01-01

    Despite its importance to ocean–climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for >15 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including 14C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean's metabolic state. PMID:25908109

  13. Both respiration and photosynthesis determine the scaling of plankton metabolism in the oligotrophic ocean.

    PubMed

    Serret, Pablo; Robinson, Carol; Aranguren-Gassis, María; García-Martín, Enma Elena; Gist, Niki; Kitidis, Vassilis; Lozano, José; Stephens, John; Harris, Carolyn; Thomas, Rob

    2015-04-24

    Despite its importance to ocean-climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for >15 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including (14)C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean's metabolic state.

  14. Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

    PubMed

    Dao, Tien Tuan

    2016-09-16

    Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

  15. Do Performance-Safety Tradeoffs Cause Hypometric Metabolic Scaling in Animals?

    PubMed

    Harrison, Jon F

    2017-09-01

    Hypometric scaling of aerobic metabolism in animals has been widely attributed to constraints on oxygen (O2) supply in larger animals, but recent findings demonstrate that O2 supply balances with need regardless of size. Larger animals also do not exhibit evidence of compensation for O2 supply limitation. Because declining metabolic rates (MRs) are tightly linked to fitness, this provides significant evidence against the hypothesis that constraints on supply drive hypometric scaling. As an alternative, ATP demand might decline in larger animals because of performance-safety tradeoffs. Larger animals, which typically reproduce later, exhibit risk-reducing strategies that lower MR. Conversely, smaller animals are more strongly selected for growth and costly neurolocomotory performance, elevating metabolism. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Metingear: a development environment for annotating genome-scale metabolic models.

    PubMed

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  17. Thermoneutral zone and scaling of metabolic rate on body mass in small mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.

    1983-01-01

    A 4-species animal model suitable for experimental study of the effect of change in gravitational loading on the scale relationship between metabolic rate and total body mass is used to study the effect of temperature on metabolic rate in six male animals, 8-10 months of age, of each of the four species in the ambient temperature range 20-36 C. The measurements taken permitted partitioning of total body heat output into sensible heat loss by radiation, conduction and convection, and into latent heat loss by evaporation of water from the body surface. It is shown that the condition of thermoneutrality is important for metabolic scale effect studies, and that the thermoneutral zone for the species considered here is a narrow one.

  18. Thermoneutral zone and scaling of metabolic rate on body mass in small mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.

    1983-01-01

    A 4-species animal model suitable for experimental study of the effect of change in gravitational loading on the scale relationship between metabolic rate and total body mass is used to study the effect of temperature on metabolic rate in six male animals, 8-10 months of age, of each of the four species in the ambient temperature range 20-36 C. The measurements taken permitted partitioning of total body heat output into sensible heat loss by radiation, conduction and convection, and into latent heat loss by evaporation of water from the body surface. It is shown that the condition of thermoneutrality is important for metabolic scale effect studies, and that the thermoneutral zone for the species considered here is a narrow one.

  19. D-lactic acid production by metabolically engineered Saccharomyces cerevisiae.

    PubMed

    Ishida, Nobuhiro; Suzuki, Tomiko; Tokuhiro, Kenro; Nagamori, Eiji; Onishi, Toru; Saitoh, Satoshi; Kitamoto, Katsuhiko; Takahashi, Haruo

    2006-02-01

    Poly D-lactic acid is an important polymer because it improves the thermostability of poly L-lactic acid by the stereo complex formation. We constructed a metabolically engineered Saccharomyces cerevisiae that produces D-lactic acid efficiently. In this recombinant, the coding region of pyruvate decarboxylase 1 (PDC1) was completely deleted, and two copies of the D-lactate dehydrogenase (D-LDH) gene from Leuconostoc mesenteroides subsp. mesenteroides strain NBRC3426 were introduced into the genome. The D-lactate production reached 61.5 g/l, the amount of glucose being transformed into D-lactic acid being 61.2% under neutralizing conditions. Additionally, the yield of free D-lactic acid was also shown to be 53.0% under non-neutralizing conditions. It was confirmed that D-lactic acid of extremely high optical purity of 99.9% or higher. Our finding obtained the possibility of a new approach for pure d-lactic acid production without a neutralizing process compared with other techniques involving lactic acid bacteria and transgenic Escherichia coli.

  20. Response of white peach scale to metabolic stress disinfection and disinfestation (MSDD) treatment

    USDA-ARS?s Scientific Manuscript database

    Metabolic stress disinfection and disinfestation (MSDD) is a postharvest treatment that combines short periods of low pressure (vacuum) and high CO2 with ethanol vapor to control pathogens and arthropod pests on commodities. The system was tested against white peach scale, Pseudaulacaspis pentagona ...

  1. Metabolic Engineering and Modeling of Metabolic Pathways to Improve Hydrogen Production by Photosynthetic Bacteria

    SciTech Connect

    Jiao, Y.; Navid, A.

    2014-12-19

    traits act as the biocatalysts of the process designed to both enhance the system efficiency of CO2 fixation and the net hydrogen production rate. Additionally we applied metabolic engineering approaches guided by computational modeling for the chosen model microorganisms to enable efficient hydrogen production.

  2. Reconstruction and analysis of the industrial strain Bacillus megaterium WSH002 genome-scale in silico metabolic model.

    PubMed

    Zou, Wei; Zhou, Maoda; Liu, Liming; Chen, Jian

    2013-04-15

    A genome-scale metabolic model of Bacillus megaterium WSH002, an industrial bacterium widely used in the vitamin C industry, was reconstructed on the basis of the genome annotation and data from the literature and biochemical databases. It comprises 1112 reactions, 993 metabolites, and 1055 genes, including 43 new annotated genes. This model was able to predict qualitatively and quantitatively the growth of B. megaterium on a range of carbon and nitrogen sources, and the results agreed well with experimental data. A gene essentiality analysis predicted a core metabolic essential gene set of 57 genes on three different media. Furthermore, constraint-based analysis revealed that B. megaterium WSH002 is capable of producing and exporting several key metabolites, which could promote the growth of Ketogulonicigenium vulgare and 2-keto-l-gulonic acid (2-KLG) production. Here, the model represents a helpful tool for understanding and exploring this important industrial organism.

  3. Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering

    PubMed Central

    2012-01-01

    Background 2,3-Butanediol is a chemical compound of increasing interest due to its wide applications. It can be synthesized via mixed acid fermentation of pathogenic bacteria such as Enterobacter aerogenes and Klebsiella oxytoca. The non-pathogenic Saccharomyces cerevisiae possesses three different 2,3-butanediol biosynthetic pathways, but produces minute amount of 2,3-butanediol. Hence, we attempted to engineer S. cerevisiae strain to enhance 2,3-butanediol production. Results We first identified gene deletion strategy by performing in silico genome-scale metabolic analysis. Based on the best in silico strategy, in which disruption of alcohol dehydrogenase (ADH) pathway is required, we then constructed gene deletion mutant strains and performed batch cultivation of the strains. Deletion of three ADH genes, ADH1, ADH3 and ADH5, increased 2,3-butanediol production by 55-fold under microaerobic condition. However, overproduction of glycerol was observed in this triple deletion strain. Additional rational design to reduce glycerol production by GPD2 deletion altered the carbon fluxes back to ethanol and significantly reduced 2,3-butanediol production. Deletion of ALD6 reduced acetate production in strains lacking major ADH isozymes, but it did not favor 2,3-butanediol production. Finally, we introduced 2,3-butanediol biosynthetic pathway from Bacillus subtilis and E. aerogenes to the engineered strain and successfully increased titer and yield. Highest 2,3-butanediol titer (2.29 g·l-1) and yield (0.113 g·g-1) were achieved by Δadh1 Δadh3 Δadh5 strain under anaerobic condition. Conclusions With the aid of in silico metabolic engineering, we have successfully designed and constructed S. cerevisiae strains with improved 2,3-butanediol production. PMID:22640729

  4. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    DOE PAGES

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; ...

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions andmore » possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.« less

  5. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    SciTech Connect

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  6. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    PubMed Central

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-01-01

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes. PMID:25806041

  7. Improved Evidence-Based Genome-scale Metabolic Models for Maize Leaf, Embryo, and Endosperm

    SciTech Connect

    Seaver, Samuel M.D.; Frelin, Oceane; Bradbury, Louis M.T.; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  8. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm.

    PubMed

    Seaver, Samuel M D; Bradbury, Louis M T; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D; Henry, Christopher S

    2015-01-01

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

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

    PubMed Central

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

    2015-01-01

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

  10. Association of Lipid Accumulation Product with Cardio-Metabolic Risk Factors in Postmenopausal Women.

    PubMed

    Namazi Shabestari, Alireza; Asadi, Mojgan; Jouyandeh, Zahra; Qorbani, Mostafa; Kelishadi, Roya

    2016-06-01

    The lipid accumulation product is a novel, safe and inexpensive index of central lipid over accumulation based on waist circumference and fasting concentration of circulating triglycerides. This study was designed to investigate the ability of lipid accumulation product to predict Cardio-metabolic risk factors in postmenopausal women. In this Cross-sectional study, 264 postmenopausal women by using convenience sampling method were selected from menopause clinic in Tehran. Cardio-metabolic risk factors were measured, and lipid accumulation product (waist-58×triglycerides [nmol/L]) was calculated. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was estimated by ROC (Receiver-operating characteristic) curve analysis. Metabolic syndrome was diagnosed in 41.2% of subjects. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was 47.63 (sensitivity:75%; specificity:77.9%). High lipid accumulation product increases risk of all Cardio-metabolic risk factors except overweight, high Total Cholesterol, high Low Density Lipoprotein Cholesterol and high Fasting Blood Sugar in postmenopausal women. Our findings show that lipid accumulation product is associated with metabolic syndrome and some Cardio-metabolic risk factors Also lipid accumulation product may have been a useful tool for predicting cardiovascular disease and metabolic syndrome risk in postmenopausal women.

  11. Metabolic Engineering for Advanced Biofuels Production and Recent Advances Toward Commercialization.

    PubMed

    Meadows, Corey W; Kang, Aram; Lee, Taek S

    2017-07-21

    Research on renewable biofuels produced by microorganisms has enjoyed considerable advances in academic and industrial settings. As the renewable ethanol market approaches maturity, the demand is rising for the commercialization of more energy-dense fuel targets. Many strategies implemented in recent years have considerably increased the diversity and number of fuel targets that can be produced by microorganisms. Moreover, strain optimization for some of these fuel targets has ultimately led to their production at industrial scale. In this review, the recent metabolic engineering approaches for augmenting biofuel production derived from alcohols, isoprenoids, and fatty acids in several microorganisms are discussed. In addition, the successful commercialization ventures for each class of biofuel targets are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production.

    PubMed

    Baroukh, Caroline; Muñoz-Tamayo, Rafael; Bernard, Olivier; Steyer, Jean-Philippe

    2015-06-01

    The conversion of microalgae lipids and cyanobacteria carbohydrates into biofuels appears to be a promising source of renewable energy. This requires a thorough understanding of their carbon metabolism, supported by mathematical models, in order to optimize biofuel production. However, unlike heterotrophic microorganisms that utilize the same substrate as sources of energy and carbon, photoautotrophic microorganisms require light for energy and CO2 as carbon source. Furthermore, they are submitted to permanent fluctuating light environments due to outdoor cultivation or mixing inducing a flashing effect. Although, modeling these nonstandard organisms is a major challenge for which classical tools are often inadequate, this step remains a prerequisite towards efficient optimization of outdoor biofuel production at an industrial scale.

  13. Metabolic engineering of Arabidopsis for butanetriol production using bacterial genes.

    PubMed

    Abdel-Ghany, Salah E; Day, Irene; Heuberger, Adam L; Broeckling, Corey D; Reddy, Anireddy S N

    2013-11-01

    1,2,4-butanetriol (butanetriol) is a useful precursor for the synthesis of the energetic material butanetriol trinitrate and several pharmaceutical compounds. Bacterial synthesis of butanetriol from xylose or arabinose takes place in a pathway that requires four enzymes. To produce butanetriol in plants by expressing bacterial enzymes, we cloned native bacterial or codon optimized synthetic genes under different promoters into a binary vector and stably transformed Arabidopsis plants. Transgenic lines expressing introduced genes were analyzed for the production of butanetriol using gas chromatography coupled to mass spectrometry (GC-MS). Soil-grown transgenic plants expressing these genes produced up to 20 µg/g of butanetriol. To test if an exogenous supply of pentose sugar precursors would enhance the butanetriol level, transgenic plants were grown in a medium supplemented with either xylose or arabinose and the amount of butanetriol was quantified. Plants expressing synthetic genes in the arabinose pathway showed up to a forty-fold increase in butanetriol levels after arabinose was added to the medium. Transgenic plants expressing either bacterial or synthetic xylose pathways, or the arabinose pathway showed toxicity symptoms when xylose or arabinose was added to the medium, suggesting that a by-product in the pathway or butanetriol affected plant growth. Furthermore, the metabolite profile of plants expressing arabinose and xylose pathways was altered. Our results demonstrate that bacterial pathways that produce butanetriol can be engineered into plants to produce this chemical. This proof-of-concept study for phytoproduction of butanetriol paves the way to further manipulate metabolic pathways in plants to enhance the level of butanetriol production.

  14. Debottlenecking recombinant protein production in Bacillus megaterium under large-scale conditions--targeted precursor feeding designed from metabolomics.

    PubMed

    Korneli, Claudia; Bolten, Christoph Josef; Godard, Thibault; Franco-Lara, Ezequiel; Wittmann, Christoph

    2012-06-01

    In the present work the impact of large production scale was investigated for Bacillus megaterium expressing green fluorescent protein (GFP). Specifically designed scale-down studies, mimicking the intermittent and continuous nutrient supply of large- and small-scale processes, were carried out for this purpose. The recombinant strain revealed a 40% reduced GFP yield for the large-scale conditions. In line with extended carbon loss via formation of acetate and carbon dioxide, this indicated obvious limitations in the underlying metabolism of B. megaterium under the large-scale conditions. Quantitative analysis of intracellular amino acids via validated fast filtration protocols revealed that their level strongly differed between the two scenarios. During cultivation in large-scale set-up, the availability of most amino acids, serving as key building blocks of the recombinant protein, was substantially reduced. This was most pronounced for tryptophan, aspartate, histidine, glutamine, and lysine. In contrast alanine was increased, probably related to a bottleneck at the level of pyruvate which also triggered acetate overflow metabolism. The pre-cursor quantifications could then be exploited to verify the presumed bottlenecks and improve recombinant protein production under large-scale conditions. Addition of only 5 mM tryptophan, aspartate, histidine, glutamine, and lysine to the feed solution increased the GFP yield by 100%. This rational concept of driving the lab scale productivity of recombinant microorganisms under suboptimal feeding conditions emulating large scale can easily be extended to other processes and production hosts.

  15. Metabolic modelling of full-scale enhanced biological phosphorus removal sludge.

    PubMed

    Lanham, Ana B; Oehmen, Adrian; Saunders, Aaron M; Carvalho, Gilda; Nielsen, Per H; Reis, Maria A M

    2014-12-01

    This study investigates, for the first time, the application of metabolic models incorporating polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) towards describing the biochemical transformations of full-scale enhanced biological phosphorus removal (EBPR) activated sludge from wastewater treatment plants (WWTPs). For this purpose, it was required to modify previous metabolic models applied to lab-scale systems by incorporating the anaerobic utilisation of the TCA cycle and the aerobic maintenance processes based on sequential utilisation of polyhydroxyalkanoates, followed by glycogen and polyphosphate. The abundance of the PAO and GAO populations quantified by fluorescence in situ hybridisation served as the initial conditions of each biomass fraction, whereby the models were able to describe accurately the experimental data. The kinetic rates were found to change among the four different WWTPs studied or even in the same plant during different seasons, either suggesting the presence of additional PAO or GAO organisms, or varying microbial activities for the same organisms. Nevertheless, these variations in kinetic rates were largely found to be proportional to the difference in acetate uptake rate, suggesting a viable means of calibrating the metabolic model. The application of the metabolic model to full-scale sludge also revealed that different Accumulibacter clades likely possess different acetate uptake mechanisms, as a correlation was observed between the energetic requirement for acetate transport across the cell membrane with the diversity of Accumulibacter present. Using the model as a predictive tool, it was shown that lower acetate concentrations in the feed as well as longer aerobic retention times favour the dominance of the TCA metabolism over glycolysis, which could explain why the anaerobic TCA pathway seems to be more relevant in full-scale WWTPs than in lab-scale systems. Copyright © 2014 Elsevier Ltd. All

  16. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    PubMed Central

    Gürgan, Muazzez; Afşar Erkal, Nilüfer; Özgür, Ebru; Gündüz, Ufuk; Eroglu, Inci; Yücel, Meral

    2015-01-01

    Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C) and heat (42 °C) stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F). The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS) bacteria under temperature stress. PMID:26086826

  17. 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.

  18. C4GEM, a Genome-Scale Metabolic Model to Study C4 Plant Metabolism1[W][OA

    PubMed Central

    de Oliveira Dal’Molin, Cristiana Gomes; Quek, Lake-Ee; Palfreyman, Robin William; Brumbley, Stevens Michael; Nielsen, Lars Keld

    2010-01-01

    Leaves of C4 grasses (such as maize [Zea mays], sugarcane [Saccharum officinarum], and sorghum [Sorghum bicolor]) form a classical Kranz leaf anatomy. Unlike C3 plants, where photosynthetic CO2 fixation proceeds in the mesophyll (M), the fixation process in C4 plants is distributed between two cell types, the M cell and the bundle sheath (BS) cell. Here, we develop a C4 genome-scale model (C4GEM) for the investigation of flux distribution in M and BS cells during C4 photosynthesis. C4GEM, to our knowledge, is the first large-scale metabolic model that encapsulates metabolic interactions between two different cell types. C4GEM is based on the Arabidopsis (Arabidopsis thaliana) model (AraGEM) but has been extended by adding reactions and transporters responsible to represent three different C4 subtypes (NADP-ME [for malic enzyme], NAD-ME, and phosphoenolpyruvate carboxykinase). C4GEM has been validated for its ability to synthesize 47 biomass components and consists of 1,588 unique reactions, 1,755 metabolites, 83 interorganelle transporters, and 29 external transporters (including transport through plasmodesmata). Reactions in the common C4 model have been associated with well-annotated C4 species (NADP-ME subtypes): 3,557 genes in sorghum, 11,623 genes in maize, and 3,881 genes in sugarcane. The number of essential reactions not assigned to genes is 131, 135, and 156 in sorghum, maize, and sugarcane, respectively. Flux balance analysis was used to assess the metabolic activity in M and BS cells during C4 photosynthesis. Our simulations were consistent with chloroplast proteomic studies, and C4GEM predicted the classical C4 photosynthesis pathway and its major effect in organelle function in M and BS. The model also highlights differences in metabolic activities around photosystem I and photosystem II for three different C4 subtypes. Effects of CO2 leakage were also explored. C4GEM is a viable framework for in silico analysis of cell cooperation between M and BS

  19. Convergence of trophic interaction strengths in grassland food webs through metabolic scaling of herbivore biomass.

    PubMed

    Schmitz, Oswald J; Price, Jessica R

    2011-11-01

    1. Food web theory hypothesizes that trophic interaction strengths of consumers should vary with consumer metabolic body mass (mass(0·75) ) rather than simply with consumer body mass (mass(1·0) ) owing to constraints on consumption imposed by metabolic demand for and metabolic capacity to process nutrients and energy. Accordingly, species with similar metabolic body masses should have similar trophic interaction strengths. 2. We experimentally tested this hypothesis by assembling food webs comprised of species of arthropod predators, small sap-feeding and large leaf-chewing insect herbivores and herbaceous plants in a New England, USA meadow grassland. The experiment comprised of a density-matching treatment where herbivore species were stocked into field mesocosms at equal densities to quantify baseline species identity and metabolic body mass effects. The experiment also comprised of a metabolic biomass-matching treatment where smaller sap-feeding herbivore (SH) species were stocked into mesocosms such that the product of their density and metabolic body mass (metabolic biomass) was equal to the large herbivore (LH) species. We compared the magnitude of the direct effects of herbivore species on plants in the different treatments. We also compared the magnitude of indirect effects between predators and plants mediated by herbivores in the different treatments. 3. Consistent with the hypothesis, we found that increasing metabolic biomass translated into a 9-14-fold increase in magnitude of herbivore direct effects and up to a fivefold increase in indirect effects on plants. Moreover, metabolic biomass matching caused interaction strengths among herbivore species to converge. This result came about through increases in the herbivore mean effects as well as decreases in variation in effects among treatment replicates as herbivore metabolic biomass increased. 4. We found, however, that herbivore feeding mode rather than herbivore metabolic biomass explained

  20. A sperm-specific proteome-scale metabolic network model identifies non-glycolytic genes for energy deficiency in asthenozoospermia.

    PubMed

    Asghari, Arvand; Marashi, Sayed-Amir; Ansari-Pour, Naser

    2017-04-01

    About 15% of couples experience difficulty in conceiving a child, of which half of the cases are thought to be male-related. Asthenozoospermia, or low sperm motility, is one of the frequent types of male infertility. Although energy metabolism is suggested to be central to the etiology of asthenozoospermia, very few attempts have been made to identify its underlying metabolic pathways. Here, we reconstructed SpermNet, the first proteome-scale model of the sperm cell by using whole-proteome data and the mCADRE algorithm. The reconstructed model was then analyzed using the COBRA toolbox. Genes were knocked-out in the model to investigate their effect on ATP production. A total of 78 genes elevated ATP production rate considerably of which most encode components of oxidative phosphorylation, fatty acid oxidation, the Krebs cycle, and members of the solute carrier 25 family. Among them, we identified 11 novel genes which have previously not been associated with sperm cell energy metabolism and may thus be implicated in asthenozoospermia. We further examined the reconstructed model by in silico knock out of currently known asthenozoospermia implicated-genes that were not predicted by our model. The pathways affected by knocking out these genes were also related to energy metabolism, confirming previous findings. Therefore, our model not only predicts the known pathways, it also identifies several non-glycolytic genes for deficient energy metabolism in asthenozoospermia. Finally, this model supports the notion that metabolic pathways besides glycolysis such as oxidative phosphorylation and fatty acid oxidation are essential for sperm energy metabolism and if validated, may form a basis for fertility recovery. mCADRE: metabolic context-specificity assessed by deterministic reaction evaluation; ATP: adenosine triphosphate; RNA: ribonucleic acid; FBA: flux balance analysis; FVA: flux variability analysis; DAVID: database for annotation, visualization and integrated

  1. High-Throughput Tissue Bioenergetics Analysis Reveals Identical Metabolic Allometric Scaling for Teleost Hearts and Whole Organisms.

    PubMed

    Jayasundara, Nishad; Kozal, Jordan S; Arnold, Mariah C; Chan, Sherine S L; Di Giulio, Richard T

    2015-01-01

    Organismal metabolic rate, a fundamental metric in biology, demonstrates an allometric scaling relationship with body size. Fractal-like vascular distribution networks of biological systems are proposed to underlie metabolic rate allometric scaling laws from individual organisms to cells, mitochondria, and enzymes. Tissue-specific metabolic scaling is notably absent from this paradigm. In the current study, metabolic scaling relationships of hearts and brains with body size were examined by improving on a high-throughput whole-organ oxygen consumption rate (OCR) analysis method in five biomedically and environmentally relevant teleost model species. Tissue-specific metabolic scaling was compared with organismal routine metabolism (RMO2), which was measured using whole organismal respirometry. Basal heart OCR and organismal RMO2 scaled identically with body mass in a species-specific fashion across all five species tested. However, organismal maximum metabolic rates (MMO2) and pharmacologically-induced maximum cardiac metabolic rates in zebrafish Danio rerio did not show a similar relationship with body mass. Brain metabolic rates did not scale with body size. The identical allometric scaling of heart and organismal metabolic rates with body size suggests that hearts, the power generator of an organism's vascular distribution network, might be crucial in determining teleost metabolic rate scaling under routine conditions. Furthermore, these findings indicate the possibility of measuring heart OCR utilizing the high-throughput approach presented here as a proxy for organismal metabolic rate-a useful metric in characterizing organismal fitness. In addition to heart and brain OCR, the current approach was also used to measure whole liver OCR, partition cardiac mitochondrial bioenergetic parameters using pharmacological agents, and estimate heart and brain glycolytic rates. This high-throughput whole-organ bioenergetic analysis method has important applications in

  2. High-Throughput Tissue Bioenergetics Analysis Reveals Identical Metabolic Allometric Scaling for Teleost Hearts and Whole Organisms

    PubMed Central

    Jayasundara, Nishad; Kozal, Jordan S.; Arnold, Mariah C.; Chan, Sherine S. L.; Di Giulio, Richard T.

    2015-01-01

    Organismal metabolic rate, a fundamental metric in biology, demonstrates an allometric scaling relationship with body size. Fractal-like vascular distribution networks of biological systems are proposed to underlie metabolic rate allometric scaling laws from individual organisms to cells, mitochondria, and enzymes. Tissue-specific metabolic scaling is notably absent from this paradigm. In the current study, metabolic scaling relationships of hearts and brains with body size were examined by improving on a high-throughput whole-organ oxygen consumption rate (OCR) analysis method in five biomedically and environmentally relevant teleost model species. Tissue-specific metabolic scaling was compared with organismal routine metabolism (RMO2), which was measured using whole organismal respirometry. Basal heart OCR and organismal RMO2 scaled identically with body mass in a species-specific fashion across all five species tested. However, organismal maximum metabolic rates (MMO2) and pharmacologically-induced maximum cardiac metabolic rates in zebrafish Danio rerio did not show a similar relationship with body mass. Brain metabolic rates did not scale with body size. The identical allometric scaling of heart and organismal metabolic rates with body size suggests that hearts, the power generator of an organism’s vascular distribution network, might be crucial in determining teleost metabolic rate scaling under routine conditions. Furthermore, these findings indicate the possibility of measuring heart OCR utilizing the high-throughput approach presented here as a proxy for organismal metabolic rate—a useful metric in characterizing organismal fitness. In addition to heart and brain OCR, the current approach was also used to measure whole liver OCR, partition cardiac mitochondrial bioenergetic parameters using pharmacological agents, and estimate heart and brain glycolytic rates. This high-throughput whole-organ bioenergetic analysis method has important applications in

  3. Comparing Scales of Environmental Effects from Gasoline and Ethanol Production

    SciTech Connect

    Parish, Esther S; Kline, Keith L; Dale, Virginia H; Efroymson, Rebecca Ann; McBride, Allen; Johnson, Timothy L; Hilliard, Michael R; Bielicki, Dr Jeffrey M

    2013-01-01

    Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the scales (i.e., spatial extent and temporal duration) of ethanol and gasoline production processes and environmental effects based on a literature review, and then synthesize the scale differences on space-time diagrams. Comprehensive assessment of any fuel-production system is a moving target, and our analysis shows that decisions regarding the selection of spatial and temporal boundaries of analysis have tremendous influences on the comparisons. Effects that strongly differentiate gasoline and ethanol supply chains in terms of scale are associated with when and where energy resources are formed and how they are extracted. Although both gasoline and ethanol production may result in negative environmental effects, this study indicates that ethanol production traced through a supply chain may impact less area and result in more easily reversed effects of a shorter duration than gasoline production.

  4. Genome-scale metabolic modeling of a clostridial co-culture for consolidated bioprocessing.

    PubMed

    Salimi, Fahimeh; Zhuang, Kai; Mahadevan, Radhakrishnan

    2010-07-01

    An alternative consolidated bioprocessing approach is the use of a co-culture containing cellulolytic and solventogenic clostridia. It has been demonstrated that the rate of cellulose utilization in the co-culture of Clostridium acetobutylicum and Clostridium cellulolyticum is improved compared to the mono-culture of C. cellulolyticum, suggesting the presence of syntrophy between these two species. However, the metabolic interactions in the co-culture are not well understood. To understand the metabolic interactions in the co-culture, we developed a genome-scale metabolic model of C. cellulolyticum comprising of 431 genes, 621 reactions, and 603 metabolites. The C. cellulolyticum model can successfully predict the chemostat growth and byproduct secretion with cellulose as the substrate. However, a growth arrest phenomenon, which occurs in batch cultures of C. cellulolyticum at cellulose concentrations higher than 6.7 g/L, cannot be predicted by dynamic flux balance analysis due to the lack of understanding of the underlying mechanism. These genome-scale metabolic models of the pure cultures have also been integrated using a community modeling framework to develop a dynamic model of metabolic interactions in the co-culture. Co-culture simulations suggest that cellobiose inhibition cannot be the main factor that is responsible for improved cellulose utilization relative to mono-culture of C. cellulolyticum.

  5. Metabolic versatility in full-scale wastewater treatment plants performing enhanced biological phosphorus removal.

    PubMed

    Lanham, Ana B; Oehmen, Adrian; Saunders, Aaron M; Carvalho, Gilda; Nielsen, Per H; Reis, Maria A M

    2013-12-01

    This study analysed the enhanced biological phosphorus removal (EBPR) microbial community and metabolic performance of five full-scale EBPR systems by using fluorescence in situ hybridisation combined with off-line batch tests fed with acetate under anaerobic-aerobic conditions. The phosphorus accumulating organisms (PAOs) in all systems were stable and showed little variability between each plant, while glycogen accumulating organisms (GAOs) were present in two of the plants. The metabolic activity of each sludge showed the frequent involvement of the anaerobic tricarboxylic acid cycle (TCA) in PAO metabolism for the anaerobic generation of reducing equivalents, in addition to the more frequently reported glycolysis pathway. Metabolic variability in the use of the two pathways was also observed, between different systems and in the same system over time. The metabolic dynamics was linked to the availability of glycogen, where a higher utilisation of the glycolysis pathway was observed in the two systems employing side-stream hydrolysis, and the TCA cycle was more active in the A(2)O systems. Full-scale plants that showed higher glycolysis activity also exhibited superior P removal performance, suggesting that promotion of the glycolysis pathway over the TCA cycle could be beneficial towards the optimisation of EBPR systems. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    PubMed

    Vinay-Lara, Elena; Hamilton, Joshua J; Stahl, Buffy; Broadbent, Jeff R; Reed, Jennifer L; Steele, James L

    2014-01-01

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

  7. GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism

    PubMed Central

    Beste, Dany JV; Hooper, Tracy; Stewart, Graham; Bonde, Bhushan; Avignone-Rossa, Claudio; Bushell, Michael E; Wheeler, Paul; Klamt, Steffen; Kierzek, Andrzej M; McFadden, Johnjoe

    2007-01-01

    Background An impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis. Results GSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available. Conclusion The GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism. PMID:17521419

  8. Genome –Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

    PubMed Central

    Vinay-Lara, Elena; Hamilton, Joshua J.; Stahl, Buffy; Broadbent, Jeff R.; Reed, Jennifer L.; Steele, James L.

    2014-01-01

    Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications. PMID:25365062

  9. Rational medium optimization based on comparative metabolic profiling analysis to improve fumaric acid production.

    PubMed

    Wang, Guanyi; Huang, Di; Qi, Haishan; Wen, Jianping; Jia, Xiaoqiang; Chen, Yunlin

    2013-06-01

    To rationally guide fumaric acid production improvement, metabolic profiling approach was performed to analyze metabolite changes of Rhizopus oryzae FM19 under different fermentation conditions. A correlation between the metabolic profiling and fumaric acid production was revealed by principal component analysis as well as partial least squares. Citric acid, oxaloacetic acid, 2-oxoglutarate, lactic acid, proline, alanine, valine, leucine were identified to be mainly responsible for the metabolism difference, which were involved in the Embden-Meyerhof-Parnas, tricarboxylic acid cycle, amino acid metabolism and fatty acid metabolism. Through the further analysis of metabolites changes together with the above pathways, exogenous addition strategies were developed, which resulted in 14% increase of fumaric acid (up to 56.5 g/L) and less by-products. These results demonstrated that metabolic profiling analysis could be successfully applied to the rational guidance of medium optimization and the productivity improvement of value-added compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Metabolic engineering of Corynebacterium glutamicum aimed at alternative carbon sources and new products

    PubMed Central

    Zahoor, Ahmed; Lindner, Steffen N.; Wendisch, Volker F.

    2012-01-01

    Corynebacterium glutamicum is well known as the amino acid-producing workhorse of fermentation industry, being used for multi-million-ton scale production of glutamate and lysine for more than 60 years. However, it is only recently that extensive research has focused on engineering it beyond the scope of amino acids. Meanwhile, a variety of corynebacterial strains allows access to alternative carbon sources and/or allows production of a wide range of industrially relevant compounds. Some of these efforts set new standards in terms of titers and productivities achieved whereas others represent a proof-of-principle. These achievements manifest the position of C. glutamicum as an important industrial microorganism with capabilities far beyond the traditional amino acid production. In this review we focus on the state of the art of metabolic engineering of C. glutamicum for utilization of alternative carbon sources, (e.g. coming from wastes and unprocessed sources), and construction of C. glutamicum strains for production of new products such as diamines, organic acids and alcohols PMID:24688664

  11. Metabolic engineering of Corynebacterium glutamicum aimed at alternative carbon sources and new products.

    PubMed

    Zahoor, Ahmed; Lindner, Steffen N; Wendisch, Volker F

    2012-01-01

    Corynebacterium glutamicum is well known as the amino acid-producing workhorse of fermentation industry, being used for multi-million-ton scale production of glutamate and lysine for more than 60 years. However, it is only recently that extensive research has focused on engineering it beyond the scope of amino acids. Meanwhile, a variety of corynebacterial strains allows access to alternative carbon sources and/or allows production of a wide range of industrially relevant compounds. Some of these efforts set new standards in terms of titers and productivities achieved whereas others represent a proof-of-principle. These achievements manifest the position of C. glutamicum as an important industrial microorganism with capabilities far beyond the traditional amino acid production. In this review we focus on the state of the art of metabolic engineering of C. glutamicum for utilization of alternative carbon sources, (e.g. coming from wastes and unprocessed sources), and construction of C. glutamicum strains for production of new products such as diamines, organic acids and alcohols.

  12. Advanced glycation end products: possible link between metabolic syndrome and periodontal diseases.

    PubMed

    Pietropaoli, D; Monaco, A; Del Pinto, R; Cifone, M G; Marzo, G; Giannoni, M

    2012-01-01

    On a planetary scale, Metabolic Syndrome (MetS)is the third cause of inability after malnutrition and nicotinism, even higher than water shortage and sedentariness. In the USA, the prevalence is estimated at over 25 percent of the population; in Italy, it involves approximately 25 percent of men and even 27 percent of women. These are very high figures, corresponding to approximately 14 million affected individuals. The prevalence is alarming and must not be underestimated, particularly in the dental field, where more than one patient out of four sitting in a dentist chair is affected. The etiology of periodontal disease has not yet been clarified, and recently the idea to consider it as a multifactor pathology has been developed. Cofactors such as the formation of free radicals of oxygen (ROS), oxidative stress, lipid peroxidation, and formation of glycation end-products (AGEs) probably play an important role in the onset of periodontal disease. The AGEs are compounds physiologically produced by the cells. However, they accumulate and cause pro-inflammatory conditions, when the cellular clearance fails, or in hyperglycemic and oxidative states. All these conditions can be clinically summarized as Metabolic Syndrome. The purpose of this literature review is to establish a relationship between two pathologies with very high prevalence: Metabolic Syndrome and Periodontal Disorder. The literature seems to have clarified that MetS involves a pro-oxidation status, which induces AGE formation. AGEs play a very important role in the course and severity of periodontal diseases.

  13. 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

  14. 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.

  15. Intraspecific scaling in frog calls: the interplay of temperature, body size and metabolic condition.

    PubMed

    Ziegler, Lucia; Arim, Matías; Bozinovic, Francisco

    2016-07-01

    Understanding physiological and environmental determinants of strategies of reproductive allocation is a pivotal aim in biology. Because of their high metabolic cost, properties of sexual acoustic signals may correlate with body size, temperature, and an individual's energetic state. A quantitative theory of acoustic communication, based on the metabolic scaling with temperature and mass, was recently proposed, adding to the well-reported empirical patterns. It provides quantitative predictions for frequencies, call rate, and durations. Here, we analysed the mass, temperature, and body condition scaling of spectral and temporal attributes of the advertisement call of the treefrog Hypsiboas pulchellus. Mass dependence of call frequency followed metabolic expectations (f~M (-0.25), where f is frequency and M is mass) although non-metabolic allometry could also account for the observed pattern. Temporal variables scaled inversely with mass contradicting metabolic expectations (d~M (0.25), where d is duration), supporting instead empirical patterns reported to date. Temperature was positively associated with call rate and negatively with temporal variables, which is congruent with metabolic predictions. We found no significant association between temperature and frequencies, adding to the bulk of empirical evidence. Finally, a result of particular relevance was that body condition consistently determined call characteristics, in interaction with temperature or mass. Our intraspecific study highlights that even if proximate determinants of call variability are rather well understood, the mechanisms through which they operate are proving to be more complex than previously thought. The determinants of call characteristics emerge as a key topic of research in behavioural and physiological biology, with several clear points under debate which need to be analysed on theoretical and empirical grounds.

  16. Ecophysiological influence on scaling of aerobic and anaerobic metabolism of pelagic gonatid squids.

    PubMed

    Rosa, Rui; Trueblood, Lloyd; Seibel, Brad A

    2009-01-01

    We examined the oxygen consumption rates and activity levels of respiratory enzymes involved in the aerobic (citrate synthase [CS]) and anaerobic (octopine dehydrogenase [ODH]) metabolism of gonatid squids (Gonatus onyx and Gonatus pyrus) as a function of body size. The energy expenditure rates of gonatids (ranging from 2.51 to 8.79 micromol O(2) g(-1) h(-1) at 5 degrees C) are among the highest in Animalia when mass and temperature are taken into account. They reflect the low efficiency of jet propulsion and the animals' active life strategy as diel vertical migrants in the pelagic environment. Both metabolic rate and aerobic muscle potential (CS activity) were size independent across a size range of four orders of magnitude, which may be a result of their unusual body geometric allometry, extensive cutaneous respiration, and decreased energy-saving opportunities at larger sizes. Anaerobic metabolic potential (ODH activity) revealed a shift from positive scaling in juveniles to negative scaling among larger sizes. Juveniles are found in shallow water, where they are more susceptible to visually cued predators and require quicker size-specific escape responses and higher burst swimming capacities. Conversely, adults have reduced requirements for predator/prey interactions in the light-limited deep sea. Anaerobic metabolic scaling reflects an adaptive response to the changing physical and ecological demands across a depth gradient during this species's ontogenetic vertical migration.

  17. Pantograph: A template-based method for genome-scale metabolic model reconstruction.

    PubMed

    Loira, Nicolas; Zhukova, Anna; Sherman, David James

    2015-04-01

    Genome-scale metabolic models are a powerful tool to study the inner workings of biological systems and to guide applications. The advent of cheap sequencing has brought the opportunity to create metabolic maps of biotechnologically interesting organisms. While this drives the development of new methods and automatic tools, network reconstruction remains a time-consuming process where extensive manual curation is required. This curation introduces specific knowledge about the modeled organism, either explicitly in the form of molecular processes, or indirectly in the form of annotations of the model elements. Paradoxically, this knowledge is usually lost when reconstruction of a different organism is started. We introduce the Pantograph method for metabolic model reconstruction. This method combines a template reaction knowledge base, orthology mappings between two organisms, and experimental phenotypic evidence, to build a genome-scale metabolic model for a target organism. Our method infers implicit knowledge from annotations in the template, and rewrites these inferences to include them in the resulting model of the target organism. The generated model is well suited for manual curation. Scripts for evaluating the model with respect to experimental data are automatically generated, to aid curators in iterative improvement. We present an implementation of the Pantograph method, as a toolbox for genome-scale model reconstruction, curation and validation. This open source package can be obtained from: http://pathtastic.gforge.inria.fr.

  18. Comparative Study of Laboratory-Scale and Prototypic Production-Scale Fuel Fabrication Processes and Product Characteristics

    SciTech Connect

    Douglas W. Marshall

    2014-10-01

    An objective of the High Temperature Gas Reactor fuel development and qualification program for the United States Department of Energy has been to qualify fuel fabricated in prototypic production-scale equipment. The quality and characteristics of the tristructural isotropic coatings on fuel kernels are influenced by the equipment scale and processing parameters. Some characteristics affecting product quality were suppressed while others have become more significant in the larger equipment. Changes to the composition and method of producing resinated graphite matrix material has eliminated the use of hazardous, flammable liquids and enabled it to be procured as a vendor-supplied feed stock. A new method of overcoating TRISO particles with the resinated graphite matrix eliminates the use of hazardous, flammable liquids, produces highly spherical particles with a narrow size distribution, and attains product yields in excess of 99%. Compact fabrication processes have been scaled-up and automated with relatively minor changes to compact quality to manual laboratory-scale processes. The impact on statistical variability of the processes and the products as equipment was scaled are discussed. The prototypic production-scale processes produce test fuels that meet fuel quality specifications.

  19. Genome-scale Metabolic Reaction Modeling: a New Approach to Geomicrobial Kinetics

    NASA Astrophysics Data System (ADS)

    McKernan, S. E.; Shapiro, B.; Jin, Q.

    2014-12-01

    Geomicrobial rates, rates of microbial metabolism in natural environments, are a key parameter of theoretical and practical problems in geobiology and biogeochemistry. Both laboratory- and field-based approaches have been applied to study rates of geomicrobial processes. Laboratory-based approaches analyze geomicrobial kinetics by incubating environmental samples under controlled laboratory conditions. Field methods quantify geomicrobial rates by observing the progress of geomicrobial processes. To take advantage of recent development in biogeochemical modeling and genome-scale metabolic modeling, we suggest that geomicrobial rates can also be predicted by simulating metabolic reaction networks of microbes. To predict geomicrobial rates, we developed a genome-scale metabolic model that describes enzyme reaction networks of microbial metabolism, and simulated the network model by accounting for the kinetics and thermodynamics of enzyme reactions. The model is simulated numerically to solve cellular enzyme abundance and hence metabolic rates under the constraints of cellular physiology. The new modeling approach differs from flux balance analysis of system biology in that it accounts for the thermodynamics and kinetics of enzymatic reactions. It builds on subcellular metabolic reaction networks, and hence also differs from classical biogeochemical reaction modeling. We applied the new approach to Methanosarcina acetivorans, an anaerobic, marine methanogen capable of disproportionating acetate to carbon dioxide and methane. The input of the new model includes (1) enzyme reaction network of acetoclastic methanogenesis, and (2) representative geochemical conditions of freshwater sedimentary environments. The output of the simulation includes the proteomics, metabolomics, and energy and matter fluxes of M. acetivorans. Our simulation results demonstrate the predictive power of the new modeling approach. Specifically, the results illustrate how methanogenesis rates vary

  20. Potential of lipid metabolism in marine diatoms for biofuel production.

    PubMed

    d'Ippolito, Giuliana; Sardo, Angela; Paris, Debora; Vella, Filomena Monica; Adelfi, Maria Grazia; Botte, Pierpaolo; Gallo, Carmela; Fontana, Angelo

    2015-01-01

    Diatoms are an ecologically relevant group of microalgae that are not commonly considered for bio-oil production even if they are responsible for massive blooms at sea. Seventeen diatom species were screened for their capacity to produce biomass and lipids, in relation to their growth rate. Triglyceride levels were also assessed as a preferential source of biofuels. Using statistical analysis, two centric diatoms, Thalassiosira weissflogii and Cyclotella cryptica, were selected as good candidates for oil production. Lipid levels significantly increased when the two diatoms were cultivated in a two-stage process under nitrogen limitation. The effect was less pronounced in cultures where silicon was reduced to 20% of the standard supply. Nitrogen limitation did not affect growth rates but led to lipid remodeling and de novo synthesis of triacylglycerols. Triacylglycerols in T. weissflogii and C. cryptica can account for up to 82% and 88% of total glycerolipids, thereby suggesting that the two species are promising candidates for large-scale experimentation for biofuel production.

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

    PubMed Central

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

    2016-01-01

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

  2. 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.

  3. Precursors and metabolic pathway for guaiacol production by Alicyclobacillus acidoterrestris.

    PubMed

    Cai, Rui; Yuan, Yahong; Wang, Zhouli; Guo, Chunfeng; Liu, Bin; Liu, Laping; Wang, Yutang; Yue, Tianli

    2015-12-02

    Alicyclobacillus acidoterrestris has recently received much attention due to its implication in the spoilage of pasteurized fruit juices, which was manifested by the production of guaiacol. Vanillic acid and vanillin have been accepted as the biochemical precursors of guaiacol in fruit juices. The purpose of this study was to try to find other precursors and elucidate details about the conversion of vanillic acid and vanillin to guaiacol by A. acidoterrestris. Four potential substrates including ferulic acid, catechol, phenylalanine and tyrosine were analyzed, but they could not be metabolized to guaiacol by all the thirty A. acidoterrestris strains tested. Resting cell studies and enzyme assays demonstrated that vanillin was reduced to vanillyl alcohol by NADPH-dependent vanillin reductase and oxidized to vanillic acid by NAD(P)(+)-dependent vanillin dehydrogenases in A. acidoterrestris DSM 3923. Vanillic acid underwent a nonoxidative decarboxylation to guaiacol. The reversible vanillic acid decarboxylase involved was oxygen insensitive and pyridine nucleotide-independent. Copyright © 2015. Published by Elsevier B.V.

  4. Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

    PubMed Central

    2011-01-01

    Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925) for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test). Inhibition of the

  5. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

    SciTech Connect

    Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C.; McConnell, Brian O.; Long, Christopher P.; Knoshaug, Eric P.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Betenbaugh, Michael J.; Zengler, Karsten

    2016-07-02

    The green microalgae Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Moreover, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.

  6. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    PubMed Central

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  7. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

    DOE PAGES

    Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler; ...

    2016-07-02

    The green microalgae Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organismmore » to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Moreover, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.« less

  8. Do insect metabolic rates at rest and during flight scale with body mass?

    PubMed

    Niven, Jeremy E; Scharlemann, Jörn P W

    2005-09-22

    Energetically costly behaviours, such as flight, push physiological systems to their limits requiring metabolic rates (MR) that are highly elevated above the resting MR (RMR). Both RMR and MR during exercise (e.g. flight or running) in birds and mammals scale allometrically, although there is little consensus about the underlying mechanisms or the scaling relationships themselves. Even less is known about the allometric scaling of RMR and MR during exercise in insects. We analysed data on the resting and flight MR (FMR) of over 50 insect species that fly to determine whether RMR and FMR scale allometrically. RMR scaled with body mass to the power of 0.66 (M0.66), whereas FMR scaled with M1.10. Further analysis suggested that FMR scaled with two separate relationships; insects weighing less than 10mg had fourfold lower FMR than predicted from the scaling of FMR in insects weighing more than 10mg, although both groups scaled with M0.86. The scaling exponents of RMR and FMR in insects were not significantly different from those of birds and mammals, suggesting that they might be determined by similar factors. We argue that low FMR in small insects suggests these insects may be making considerable energy savings during flight, which could be extremely important for the physiology and evolution of insect flight.

  9. Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease.

    PubMed

    Hyötyläinen, Tuulia; Jerby, Livnat; Petäjä, Elina M; Mattila, Ismo; Jäntti, Sirkku; Auvinen, Petri; Gastaldelli, Amalia; Yki-Järvinen, Hannele; Ruppin, Eytan; Orešič, Matej

    2016-02-03

    Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. Here we chart liver metabolic activity and functionality in NAFLD by integrating global transcriptomic data, from human liver biopsies, and metabolic flux data, measured across the human splanchnic vascular bed, within a genome-scale model of human metabolism. We show that an increased amount of liver fat induces mitochondrial metabolism, lipolysis, glyceroneogenesis and a switch from lactate to glycerol as substrate for gluconeogenesis, indicating an intricate balance of exacerbated opposite metabolic processes in glycemic regulation. These changes were associated with reduced metabolic adaptability on a network level in the sense that liver fat accumulation puts increasing demands on the liver to adaptively regulate metabolic responses to maintain basic liver functions. We propose that failure to meet excessive metabolic challenges coupled with reduced metabolic adaptability may lead to a vicious pathogenic cycle leading to the co-morbidities of NAFLD.

  10. Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease

    PubMed Central

    Hyötyläinen, Tuulia; Jerby, Livnat; Petäjä, Elina M.; Mattila, Ismo; Jäntti, Sirkku; Auvinen, Petri; Gastaldelli, Amalia; Yki-Järvinen, Hannele; Ruppin, Eytan; Orešič, Matej

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. Here we chart liver metabolic activity and functionality in NAFLD by integrating global transcriptomic data, from human liver biopsies, and metabolic flux data, measured across the human splanchnic vascular bed, within a genome-scale model of human metabolism. We show that an increased amount of liver fat induces mitochondrial metabolism, lipolysis, glyceroneogenesis and a switch from lactate to glycerol as substrate for gluconeogenesis, indicating an intricate balance of exacerbated opposite metabolic processes in glycemic regulation. These changes were associated with reduced metabolic adaptability on a network level in the sense that liver fat accumulation puts increasing demands on the liver to adaptively regulate metabolic responses to maintain basic liver functions. We propose that failure to meet excessive metabolic challenges coupled with reduced metabolic adaptability may lead to a vicious pathogenic cycle leading to the co-morbidities of NAFLD. PMID:26839171

  11. Fermentative Production of the Diamine Putrescine: System Metabolic Engineering of Corynebacterium Glutamicum

    PubMed Central

    Nguyen, Anh Q. D.; Schneider, Jens; Reddy, Gajendar Komati; Wendisch, Volker F.

    2015-01-01

    Corynebacterium glutamicum shows great potential for the production of the glutamate-derived diamine putrescine, a monomeric compound of polyamides. A genome-scale stoichiometric model of a C. glutamicum strain with reduced ornithine transcarbamoylase activity, derepressed arginine biosynthesis, and an anabolic plasmid-addiction system for heterologous expression of E. coli ornithine decarboxylase gene speC was investigated by flux balance analysis with respect to its putrescine production potential. Based on these simulations, enhancing glycolysis and anaplerosis by plasmid-borne overexpression of the genes for glyceraldehyde 3-phosphate dehydrogenase and pyruvate carboxylase as well as reducing 2-oxoglutarate dehydrogenase activity were chosen as targets for metabolic engineering. Changing the translational start codon of the chromosomal gene for 2-oxoglutarate dehydrogenase subunit E1o to the less preferred TTG and changing threonine 15 of OdhI to alanine reduced 2-oxoglutarate dehydrogenase activity about five fold and improved putrescine titers by 28%. Additional engineering steps improved further putrescine production with the largest contributions from preventing the formation of the by-product N-acetylputrescine by deletion of spermi(di)ne N-acetyltransferase gene snaA and from overexpression of the gene for a feedback-resistant N-acetylglutamate kinase variant. The resulting C. glutamicum strain NA6 obtained by systems metabolic engineering accumulated two fold more putrescine than the base strain, i.e., 58.1 ± 0.2 mM, and showed a specific productivity of 0.045 g·g−1·h−1 and a yield on glucose of 0.26 g·g−1. PMID:25919117

  12. Genome-Scale NAD(H/+) Availability Patterns as a Differentiating Feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in Relation to Fermentative Metabolism

    PubMed Central

    Acevedo, Alejandro; Aroca, German; Conejeros, Raul

    2014-01-01

    Scheffersomyces stipitis is a yeast able to ferment pentoses to ethanol, unlike Saccharomyces cerevisiae, it does not present the so-called overflow phenomenon. Metabolic features characterizing the presence or not of this phenomenon have not been fully elucidated. This work proposes that genome-scale metabolic response to variations in NAD(H/+) availability characterizes fermentative behavior in both yeasts. Thus, differentiating features in S. stipitis and S. cerevisiae were determined analyzing growth sensitivity response to changes in available reducing capacity in relation to ethanol production capacity and overall metabolic flux span. Using genome-scale constraint-based metabolic models, phenotypic phase planes and shadow price analyses, an excess of available reducing capacity for growth was found in S. cerevisiae at every metabolic phenotype where growth is limited by oxygen uptake, while in S. stipitis this was observed only for a subset of those phenotypes. Moreover, by using flux variability analysis, an increased metabolic flux span was found in S. cerevisiae at growth limited by oxygen uptake, while in S. stipitis flux span was invariant. Therefore, each yeast can be characterized by a significantly different metabolic response and flux span when growth is limited by oxygen uptake, both features suggesting a higher metabolic flexibility in S. cerevisiae. By applying an optimization-based approach on the genome-scale models, three single reaction deletions were found to generate in S. stipitis the reducing capacity availability pattern found in S. cerevisiae, two of them correspond to reactions involved in the overflow phenomenon. These results show a close relationship between the growth sensitivity response given by the metabolic network and fermentative behavior. PMID:24489927

  13. Comparing scales of environmental effects from gasoline and ethanol production.

    PubMed

    Parish, Esther S; Kline, Keith L; Dale, Virginia H; Efroymson, Rebecca A; McBride, Allen C; Johnson, Timothy L; Hilliard, Michael R; Bielicki, Jeffrey M

    2013-02-01

    Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams. Comprehensive assessment of any fuel-production system is a moving target, and our analysis shows that decisions regarding the selection of spatial and temporal boundaries of analysis have tremendous influences on the comparisons. Effects that strongly differentiate gasoline and ethanol-supply chains in terms of scale are associated with when and where energy resources are formed and how they are extracted. Although both gasoline and ethanol production may result in negative environmental effects, this study indicates that ethanol production traced through a supply chain may impact less area and result in more easily reversed effects of a shorter duration than gasoline production.

  14. Comparing Scales of Environmental Effects from Gasoline and Ethanol Production

    NASA Astrophysics Data System (ADS)

    Parish, Esther S.; Kline, Keith L.; Dale, Virginia H.; Efroymson, Rebecca A.; McBride, Allen C.; Johnson, Timothy L.; Hilliard, Michael R.; Bielicki, Jeffrey M.

    2013-02-01

    Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams. Comprehensive assessment of any fuel-production system is a moving target, and our analysis shows that decisions regarding the selection of spatial and temporal boundaries of analysis have tremendous influences on the comparisons. Effects that strongly differentiate gasoline and ethanol-supply chains in terms of scale are associated with when and where energy resources are formed and how they are extracted. Although both gasoline and ethanol production may result in negative environmental effects, this study indicates that ethanol production traced through a supply chain may impact less area and result in more easily reversed effects of a shorter duration than gasoline production.

  15. Lipid metabolism and potentials of biofuel and high added-value oil production in red algae.

    PubMed

    Sato, Naoki; Moriyama, Takashi; Mori, Natsumi; Toyoshima, Masakazu

    2017-04-01

    Biomass production is currently explored in microalgae, macroalgae and land plants. Microalgal biofuel development has been performed mostly in green algae. In the Japanese tradition, macrophytic red algae such as Pyropia yezoensis and Gelidium crinale have been utilized as food and industrial materials. Researches on the utilization of unicellular red microalgae such as Cyanidioschyzon merolae and Porphyridium purpureum started only quite recently. Red algae have relatively large plastid genomes harboring more than 200 protein-coding genes that support the biosynthetic capacity of the plastid. Engineering the plastid genome is a unique potential of red microalgae. In addition, large-scale growth facilities of P. purpureum have been developed for industrial production of biofuels. C. merolae has been studied as a model alga for cell and molecular biological analyses with its completely determined genomes and transformation techniques. Its acidic and warm habitat makes it easy to grow this alga axenically in large scales. Its potential as a biofuel producer is recently documented under nitrogen-limited conditions. Metabolic pathways of the accumulation of starch and triacylglycerol and the enzymes involved therein are being elucidated. Engineering these regulatory mechanisms will open a possibility of exploiting the full capability of production of biofuel and high added-value oil. In the present review, we will describe the characteristics and potential of these algae as biotechnological seeds.

  16. Scale-down of penicillin production in Penicillium chrysogenum.

    PubMed

    de Jonge, Lodewijk P; Buijs, Nicolaas A A; ten Pierick, Angela; Deshmukh, Amit; Zhao, Zheng; Kiel, Jan A K W; Heijnen, Joseph J; van Gulik, Walter M

    2011-08-01

    In large-scale production reactors the combination of high broth viscosity and large broth volume leads to insufficient liquid-phase mixing, resulting in gradients in, for example, the concentrations of substrate and oxygen. This often leads to differences in productivity of the full-scale process compared with laboratory scale. In this scale-down study of penicillin production, the influence of substrate gradients on process performance and cell physiology was investigated by imposing an intermittent feeding regime on a laboratory-scale culture of a high yielding strain of Penicillium chrysogenum. It was found that penicillin production was reduced by a factor of two in the intermittently fed cultures relative to constant feed cultivations fed with the same amount of glucose per hour, while the biomass yield was the same. Measurement of the levels of the intermediates of the penicillin biosynthesis pathway, along with the enzyme levels, suggested that the reduction of the flux through the penicillin pathway is mainly the result of a lower influx into the pathway, possibly due to inhibitory levels of adenosine monophosphate and pyrophosphate and lower activating levels of adenosine triphosphate during the zero-substrate phase of each cycle of intermittent feeding.

  17. Semi industrial scale RVNRL preparation, products manufacturing and properties

    NASA Astrophysics Data System (ADS)

    Zin, Wan Manshol Bin W.

    1998-06-01

    Natural rubber latex vulcanisation by radiation aims towards the preparation of prevulcanised natural rubber latex in the name of RVNRL for use to produce chemical-free and environment-friendly latex products. Scale up RVNRL preparation is proven possible when a semi-commercial latex irradiator was commissioned in MINT in March 1996. The plant is designed to irradiate up to 6 000 cubic meters per annum of natural rubber latex. RVNRL has the required properties and successfully used on industrial scale production of quality gloves and balloons.

  18. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis

    NASA Astrophysics Data System (ADS)

    De Martino, D.

    2016-02-01

    In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.

  19. Scale-up of a new bacterial mannitol production process.

    PubMed

    von Weymarn, F Niklas W; Kiviharju, Kristiina J; Jääskeläinen, Seppo T; Leisola, Matti S A

    2003-01-01

    D-Mannitol is a sugar alcohol with applications in chemistry, food and pharmaceutical industries, and medicine. Commercially, mannitol is produced by catalytic hydrogenation. Although this process is widely used, it is not optimal for mannitol production. New processes, including chemical, enzymatic, and microbial processes, are frequently developed and evaluated against the existing hydrogenation processes. In earlier papers, we have described the identification of a food-grade lactic acid bacterium strain, Leuconostoc mesenteroides ATCC-9135, with efficient mannitol production capabilities and the development and optimization of a new bioprocess in which the strain was applied. The new bioprocess is simple. It requires a reduced bioreactor with the following features: sterilization, pH and T control (at mild conditions), and slow mixing. The contamination risk of the new bioprocess is low, and the downstream processing protocol comprises simple, widely used unit operations: evaporation, crystallization, crystal separation, and drying. On a 2-L laboratory scale, high mannitol yields from fructose (93-97%) and volumetric mannitol productivities (>20 g L(-1) h(-1)) were achieved. In this paper, the scalability of the new bioprocess was tested on a small pilot scale (100 L). In the pilot plant, production levels were achieved similar to those in the laboratory. Also, high-purity mannitol crystals were obtained at similar yield levels. The results presented in this paper indicate that the new bioprocess can easily be scaled-up to an industrial scale and that the production levels achieved with it are comparable to the catalytic hydrogenation processes.

  20. Metabolic engineering strategies for acetoin and 2,3-butanediol production: advances and prospects.

    PubMed

    Yang, Taowei; Rao, Zhiming; Zhang, Xian; Xu, Meijuan; Xu, Zhenghong; Yang, Shang-Tian

    2017-12-01

    Acetoin and 2,3-butanediol (2,3-BD) have a large number of industrial applications. The production of acetoin and 2,3-BD has traditionally relied on oil supplies. Microbial production of acetoin and 2,3-BD will alleviate the dependence on oil. Acetoin and 2,3-BD are neighboring metabolites in the 2,3-BD metabolic pathway of bacteria. This review summarizes metabolic engineering strategies for improvement of microbial acetoin and 2,3-BD production. We also propose enhancements to current acetoin and 2,3-BD production strategies, by offering a metabolic engineering approach that is guided by systems biology and synthetic biology.

  1. Process optimization of large-scale production of recombinant adeno-associated vectors using dielectric spectroscopy.

    PubMed

    Negrete, Alejandro; Esteban, Geoffrey; Kotin, Robert M

    2007-09-01

    A well-characterized manufacturing process for the large-scale production of recombinant adeno-associated vectors (rAAV) for gene therapy applications is required to meet current and future demands for pre-clinical and clinical studies and potential commercialization. Economic considerations argue in favor of suspension culture-based production. Currently, the only feasible method for large-scale rAAV production utilizes baculovirus expression vectors and insect cells in suspension cultures. To maximize yields and achieve reproducibility between batches, online monitoring of various metabolic and physical parameters is useful for characterizing early stages of baculovirus-infected insect cells. In this study, rAAVs were produced at 40-l scale yielding ~1 x 10(15) particles. During the process, dielectric spectroscopy was performed by real time scanning in radio frequencies between 300 kHz and 10 MHz. The corresponding permittivity values were correlated with the rAAV production. Both infected and uninfected reached a maximum value; however, only infected cell cultures permittivity profile reached a second maximum value. This effect was correlated with the optimal harvest time for rAAV production. Analysis of rAAV indicated the harvesting time around 48 h post-infection (hpi), and 72 hpi produced similar quantities of biologically active rAAV. Thus, if operated continuously, the 24-h reduction in the production process of rAAV gives sufficient time for additional 18 runs a year corresponding to an extra production of ~2 x 10(16) particles. As part of large-scale optimization studies, this new finding will facilitate the bioprocessing scale-up of rAAV and other bioproducts.

  2. Elucidating and reprogramming Escherichia coli metabolisms for obligate anaerobic n-butanol and isobutanol production.

    PubMed

    Trinh, Cong T

    2012-08-01

    Elementary mode (EM) analysis based on the constraint-based metabolic network modeling was applied to elucidate and compare complex fermentative metabolisms of Escherichia coli for obligate anaerobic production of n-butanol and isobutanol. The result shows that the n-butanol fermentative metabolism was NADH-deficient, while the isobutanol fermentative metabolism was NADH redundant. E. coli could grow and produce n-butanol anaerobically as the sole fermentative product but not achieve the maximum theoretical n-butanol yield. In contrast, for the isobutanol fermentative metabolism, E. coli was required to couple with either ethanol- or succinate-producing pathway to recycle NADH. To overcome these "defective" metabolisms, EM analysis was implemented to reprogram the native fermentative metabolism of E. coli for optimized anaerobic production of n-butanol and isobutanol through multiple gene deletion (~8-9 genes), addition (~6-7 genes), up- and downexpression (~6-7 genes), and cofactor engineering (e.g., NADH, NADPH). The designed strains were forced to couple both growth and anaerobic production of n-butanol and isobutanol, which is a useful characteristic to enhance biofuel production and tolerance through metabolic pathway evolution. Even though the n-butanol and isobutanol fermentative metabolisms were quite different, the designed strains could be engineered to have identical metabolic flux distribution in "core" metabolic pathways mainly supporting cell growth and maintenance. Finally, the model prediction in elucidating and reprogramming the native fermentative metabolism of E. coli for obligate anaerobic production of n-butanol and isobutanol was validated with published experimental data.

  3. A20 modulates lipid metabolism and energy production to promote liver regeneration.

    PubMed

    Damrauer, Scott M; Studer, Peter; da Silva, Cleide G; Longo, Christopher R; Ramsey, Haley E; Csizmadia, Eva; Shrikhande, Gautam V; Scali, Salvatore T; Libermann, Towia A; Bhasin, Manoj K; Ferran, Christiane

    2011-03-17

    Liver regeneration is clinically of major importance in the setting of liver injury, resection or transplantation. We have demonstrated that the NF-κB inhibitory protein A20 significantly improves recovery of liver function and mass following extended liver resection (LR) in mice. In this study, we explored the Systems Biology modulated by A20 following extended LR in mice. We performed transcriptional profiling using Affymetrix-Mouse 430.2 arrays on liver mRNA retrieved from recombinant adenovirus A20 (rAd.A20) and rAd.βgalactosidase treated livers, before and 24 hours after 78% LR. A20 overexpression impacted 1595 genes that were enriched for biological processes related to inflammatory and immune responses, cellular proliferation, energy production, oxidoreductase activity, and lipid and fatty acid metabolism. These pathways were modulated by A20 in a manner that favored decreased inflammation, heightened proliferation, and optimized metabolic control and energy production. Promoter analysis identified several transcriptional factors that implemented the effects of A20, including NF-κB, CEBPA, OCT-1, OCT-4 and EGR1. Interactive scale-free network analysis captured the key genes that delivered the specific functions of A20. Most of these genes were affected at basal level and after resection. We validated a number of A20's target genes by real-time PCR, including p21, the mitochondrial solute carriers SLC25a10 and SLC25a13, and the fatty acid metabolism regulator, peroxisome proliferator activated receptor alpha. This resulted in greater energy production in A20-expressing livers following LR, as demonstrated by increased enzymatic activity of cytochrome c oxidase, or mitochondrial complex IV. This Systems Biology-based analysis unravels novel mechanisms supporting the pro-regenerative function of A20 in the liver, by optimizing energy production through improved lipid/fatty acid metabolism, and down-regulated inflammation. These findings support pursuit of A

  4. Variation of foraging rate and wing loading, but not resting metabolic rate scaling, of insect pollinators

    NASA Astrophysics Data System (ADS)

    Terblanche, John S.; Anderson, Bruce

    2010-08-01

    Morphological, physiological and behavioural variation with body size (i.e. scaling) may affect costs of living in a particular environment for insects and, ultimately, pollination or foraging success. However, few studies have directly assessed the scaling of these traits at the species level. Using two similar-sized pollinator species (the hawkmoth Macroglossum trochilus and the fly Moegistorhynchus longirostrus), we compare intraspecific scaling relationships of resting metabolic rate (RMR), foraging rate (FR) and wing loading (WL) to address this paucity of data. Scaling of RMR was similar for both taxa although the intercepts for the relationships differed. However, these two species showed variation in WL scaling relationships and fundamentally different FR scaling. For M. longirostrus, FR scaling was positive but non-significantly related to body mass while for M. trochilus FR scaling was negative. This suggests that variation in FR and WL, but not RMR scaling, among these flies and hawkmoths may impose significant energetic costs which could affect animal-plant interactions in the wild.

  5. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom

    PubMed Central

    Broddrick, Jared; Dupont, Christopher L.; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A.; Allen, Andrew E.; Palsson, Bernhard O.; Zengler, Karsten

    2016-01-01

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications. PMID:27152931

  6. An Experimentally-Supported Genome-Scale Metabolic Network Reconstruction for Yersinia pestis CO92

    SciTech Connect

    Charusanti, Pep; Chauhan, Sadhana; Mcateer, Kathleen; Lerman, Joshua A.; Hyduke, Daniel R.; Motin, Vladimir L.; Ansong, Charles; Adkins, Joshua N.; Palsson, Bernhard O.

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, thus provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  7. An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92.

    PubMed

    Charusanti, Pep; Chauhan, Sadhana; McAteer, Kathleen; Lerman, Joshua A; Hyduke, Daniel R; Motin, Vladimir L; Ansong, Charles; Adkins, Joshua N; Palsson, Bernhard O

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  8. Genome-scale model reveals metabolic basis of biomass partitioning in a model diatom

    DOE PAGES

    Levering, Jennifer; Broddrick, Jared; Dupont, Christopher L.; ...

    2016-05-06

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curatedmore » reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. Furthermore, the model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.« less

  9. Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri

    SciTech Connect

    Feist, Adam; Scholten, Johannes C.; Palsson, Bernard O.; Brockman, Fred J.; Ideker, Trey

    2006-01-31

    We present a genome-scale metabolic reconstruction for the archaeal methanogen Methanosarcina barkeri. This reconstruction represents the first large-scale, predictive model of a methanogen and an archael species. We characterize this reconstruction and compare it to those from the prokaryotic, eukaryotic, and archael domains. We further apply constraint-based methods to stimulate the metabolic fluxes and resulting phenotypes under different environmental and genetic conditions. These results are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for mutants of the methanogenic pathway were found to have a high level of agreement with experimental findings. The active reactions and pathways under selected growth conditions are presented and characterized. We also examined the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an in silico analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation, and further uncover the metabolic characteristics of methanogenesis.

  10. 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.

  11. Genome-scale metabolic reconstruction for the insidious bacterium in aquaculture Piscirickettsia salmonis.

    PubMed

    Fuentealba, Pablo; Aros, Camila; Latorre, Yesenia; Martínez, Irene; Marshall, Sergio; Ferrer, Pau; Albiol, Joan; Altamirano, Claudia

    2017-01-01

    Piscirickettsia salmonis is a fish bacterium that causes the disease piscirickettsiosis in salmonids. This pathology is partially controlled by vaccines. The lack of knowledge has hindered its culture on laboratory and industrial scale. The study describes the metabolic phenotype of P. salmonis in culture. This study presents the first genome-scale model (iPF215) of the LF-89 strain of P. salmonis, describing the central metabolic pathway, biosynthesis and molecule degradation and transport mechanisms. The model was adjusted with experiment data, allowing the identification of the capacities that were not predicted by the automatic annotation of the genome sequences. The iPF215 model is comprised of 417 metabolites, 445 reactions and 215 genes, was used to reproduce the growth of P. salmonis (μmax 0.052±0.005h(-1)). The metabolic reconstruction of the P. salmonis LF-89 strain obtained in this research provides a baseline that describes the metabolic capacities of the bacterium and is the basis for developing improvements to its cultivation for vaccine formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Is the scaling of swim speed in sharks driven by metabolism?

    PubMed Central

    Jacoby, David M. P.; Siriwat, Penthai; Freeman, Robin; Carbone, Chris

    2015-01-01

    The movement rates of sharks are intrinsically linked to foraging ecology, predator–prey dynamics and wider ecosystem functioning in marine systems. During ram ventilation, however, shark movement rates are linked not only to ecological parameters, but also to physiology, as minimum speeds are required to provide sufficient water flow across the gills to maintain metabolism. We develop a geometric model predicting a positive scaling relationship between swim speeds in relation to body size and ultimately shark metabolism, taking into account estimates for the scaling of gill dimensions. Empirical data from 64 studies (26 species) were compiled to test our model while controlling for the influence of phylogenetic similarity between related species. Our model predictions were found to closely resemble the observed relationships from tracked sharks, providing a means to infer mobility in particularly intractable species. PMID:26631246

  13. Is the scaling of swim speed in sharks driven by metabolism?

    PubMed

    Jacoby, David M P; Siriwat, Penthai; Freeman, Robin; Carbone, Chris

    2015-12-01

    The movement rates of sharks are intrinsically linked to foraging ecology, predator-prey dynamics and wider ecosystem functioning in marine systems. During ram ventilation, however, shark movement rates are linked not only to ecological parameters, but also to physiology, as minimum speeds are required to provide sufficient water flow across the gills to maintain metabolism. We develop a geometric model predicting a positive scaling relationship between swim speeds in relation to body size and ultimately shark metabolism, taking into account estimates for the scaling of gill dimensions. Empirical data from 64 studies (26 species) were compiled to test our model while controlling for the influence of phylogenetic similarity between related species. Our model predictions were found to closely resemble the observed relationships from tracked sharks, providing a means to infer mobility in particularly intractable species. © 2015 The Author(s).

  14. Metabolic glycoengineering bacteria for therapeutic, recombinant protein, and metabolite production applications.

    PubMed

    Saeui, Christopher T; Urias, Esteban; Liu, Lingshu; Mathew, Mohit P; Yarema, Kevin J

    2015-10-01

    Metabolic glycoengineering is a specialization of metabolic engineering that focuses on using small molecule metabolites to manipulate biosynthetic pathways responsible for oligosaccharide and glycoconjugate production. As outlined in this article, this technique has blossomed in mammalian systems over the past three decades but has made only modest progress in prokaryotes. Nevertheless, a sufficient foundation now exists to support several important applications of metabolic glycoengineering in bacteria based on methods to preferentially direct metabolic intermediates into pathways involved in lipopolysaccharide, peptidoglycan, teichoic acid, or capsule polysaccharide production. An overview of current applications and future prospects for this technology are provided in this report.

  15. Slow swimming, fast strikes: effects of feeding behavior on scaling of anaerobic metabolism in epipelagic squid.

    PubMed

    Trueblood, Lloyd A; Seibel, Brad A

    2014-08-01

    Many pelagic fishes engage prey at high speeds supported by high metabolic rates and anaerobic metabolic capacity. Epipelagic squids are reported to have among the highest metabolic rates in the oceans as a result of demanding foraging strategies and the use of jet propulsion, which is inherently inefficient. This study examined enzymatic proxies of anaerobic metabolism in two species of pelagic squid, Dosidicus gigas and Doryteuthis pealeii (Lesueur 1821), over a size range of six orders of magnitude. We hypothesized that activity of the anaerobically poised enzymes would be high and increase with size as in ecologically similar fishes. In contrast, we demonstrate that anaerobic metabolic capacity in these organisms scales negatively with body mass. We explored several cephalopod-specific traits, such as the use of tentacles to capture prey, body morphology and reduced relative prey size of adult squids, that may create a diminished reliance on anaerobically fueled burst activity during prey capture in large animals. © 2014. Published by The Company of Biologists Ltd.

  16. 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.

  17. Temporal Changes in Microbial Metabolic Characteristics in Field-Scale Biopiles Composed of Aged Oil Sludge

    PubMed Central

    Wang, Xiang; Li, Fasheng; Guo, Guanlin; Wang, Shijie; Boronin, Alexander; Wang, Qunhui

    2014-01-01

    Abstract Disposal of oil sludge, a hazardous waste, is currently a prevalent environmental issue. In this study, two field-scale biopiles were constructed to explore the temporal changes of microbial metabolic characteristics during the biotreatment of aged oil sludge. Bulking agent was mixed thoroughly with oily sludge to form a treated pile. The BIOLOG™ system was used to analyze the community level physiological parameters, including microbial metabolic activity, diversity, and variance. In comparison with the control, the community level physiological parameters of the treated pile were dramatically improved. Microbial metabolic activity of the treated pile was improved by 25.06% calculated from the maximums during the treatment. Microbial diversity index (Shannon index) ranges were improved from 1.64–3.02 (control pile) to 2.34–3.14 (treated pile). The numbers of petroleum-degrading bacteria and the total heterotrophic bacteria were correlated with the environmental temperature, and microbial metabolic characteristics in the treated pile revealed the distinctive carbon resources selection with the addition of cotton stalk. Temporal microbial metabolic characteristics, which have important effect on bioremediation, were revealed in this study. PMID:25228785

  18. Temporal Changes in Microbial Metabolic Characteristics in Field-Scale Biopiles Composed of Aged Oil Sludge.

    PubMed

    Wang, Xiang; Li, Fasheng; Guo, Guanlin; Wang, Shijie; Boronin, Alexander; Wang, Qunhui

    2014-09-01

    Disposal of oil sludge, a hazardous waste, is currently a prevalent environmental issue. In this study, two field-scale biopiles were constructed to explore the temporal changes of microbial metabolic characteristics during the biotreatment of aged oil sludge. Bulking agent was mixed thoroughly with oily sludge to form a treated pile. The BIOLOG™ system was used to analyze the community level physiological parameters, including microbial metabolic activity, diversity, and variance. In comparison with the control, the community level physiological parameters of the treated pile were dramatically improved. Microbial metabolic activity of the treated pile was improved by 25.06% calculated from the maximums during the treatment. Microbial diversity index (Shannon index) ranges were improved from 1.64-3.02 (control pile) to 2.34-3.14 (treated pile). The numbers of petroleum-degrading bacteria and the total heterotrophic bacteria were correlated with the environmental temperature, and microbial metabolic characteristics in the treated pile revealed the distinctive carbon resources selection with the addition of cotton stalk. Temporal microbial metabolic characteristics, which have important effect on bioremediation, were revealed in this study.

  19. Metabolic engineering approaches for production of biochemicals in food and medicinal plants.