Shinfuku, al. Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum. Microb. Cell Fact.8, 43

Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan. .
Microbial Cell Factories (Impact Factor: 4.22). 09/2009; 8(1):43. DOI: 10.1186/1475-2859-8-43
Source: PubMed


In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates.
The reconstructed genome-scale metabolic model of C. glutamicum contains 502 reactions and 423 metabolites. We collected the reactions and biomass components from the database and literatures, and made the model available for the flux balance analysis by filling gaps in the reaction networks and removing inadequate loop reactions. Using the framework of FBA and our genome-scale metabolic model, we first simulated the changes in the metabolic flux profiles that occur on changing the oxygen uptake rate. The predicted production yields of carbon dioxide and organic acids agreed well with the experimental data. The metabolic profiles of amino acid production phases were also investigated. A comprehensive gene deletion study was performed in which the effects of gene deletions on metabolic fluxes were simulated; this helped in the identification of several genes whose deletion resulted in an improvement in organic acid production.
The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities and prediction of the metabolic characteristics of C. glutamicum. This can form a basis for the in silico design of C. glutamicum metabolic networks for improved bioproduction of desirable metabolites.

    • "These databases are critical to improve the accuracy of the prediction of cellular phenotypes . More than 100 genome-scale metabolic network models were constructed for a wide range of different microorganisms, including Saccharomyces cerevisiae (Förster et al., 2003), Corynebacterium glutamicum (Shinfuku et al., 2009), Mannheimia succiniciproducens (Kim et al., 2007), Bacillus subtilis (Henry et al., 2009), Clostridium acetobutylicum (Lee et al., 2008), Clostridium beijerinckii (Milne et al., 2011), Lactococcus lactis (Flahaut et al., 2013), Pichia pastoris (Sohn et al., 2010), Pseudomonas putida (Puchałka et al., 2008), and so on. Recently, the ensemble modeling (EM) approach has shown promise in capturing kinetic and regulatory effects in the modeling of metabolic networks in comparison to FBA (Tran et al., 2008). "
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    ABSTRACT: 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.
    No preview · Article · Oct 2015 · Metabolic Engineering
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    • "Recently, in silico metabolic simulation has been developed to consider whole metabolic networks. A genome-scale metabolic model, which includes most of the metabolic reactions of the cell [21-23], can estimate the flux distribution of the whole metabolic network using flux balance analysis (FBA) [24,25] by assuming the steady states of metabolic reactions and maximizing objective functions such as cell growth [26,27]. This method can be used to simulate the effects of gene modifications on target production and identify candidate genes for metabolic engineering [28-30]. "
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    ABSTRACT: Background 3-hydroxypropionic acid (3HP) is an important chemical precursor for the production of bioplastics. Microbial production of 3HP from glycerol has previously been developed through the optimization of culture conditions and the 3HP biosynthesis pathway. In this study, a novel strategy for improving 3HP production in Escherichia coli was investigated by the modification of central metabolism based on a genome-scale metabolic model and experimental validation. Results Metabolic simulation identified the double knockout of tpiA and zwf as a candidate for improving 3HP production. A 3HP-producing strain was constructed by the expression of glycerol dehydratase and aldehyde dehydrogenase. The double knockout of tpiA and zwf increased the percentage carbon-molar yield (C-mol%) of 3HP on consumed glycerol 4.4-fold (20.1 ± 9.2 C-mol%), compared to the parental strain. Increased extracellular methylglyoxal concentrations in the ΔtpiA Δzwf strain indicated that glycerol catabolism was occurring through the methylglyoxal pathway, which converts dihydroxyacetone phosphate to pyruvate, as predicted by the metabolic model. Since the ΔtpiA Δzwf strain produced abundant 1,3-propanediol as a major byproduct (37.7 ± 13.2 C-mol%), yqhD, which encodes an enzyme involved in the production of 1,3-propanediol, was disrupted in the ΔtpiA Δzwf strain. The 3HP yield of the ΔtpiA Δzwf ΔyqhD strain (33.9 ± 1.2 C-mol%) was increased 1.7-fold further compared to the ΔtpiA Δzwf strain and by 7.4-fold compared to the parental strain. Conclusion This study successfully increased 3HP production by 7.4-fold in the ΔtpiA Δzwf ΔyqhD E. coli strain by the modification of the central metabolism, based on metabolic simulation and experimental validation of engineered strains.
    Full-text · Article · May 2014 · Microbial Cell Factories
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    • "Substrate uptake could be identified by decreasing glucose concentrations between plug flow ports, with a biomass-specific uptake rate of qGLC = 0.90 (± 0.17) g g-1 h-1, i.e. 5.0 (± 1.0) mmol g-1 h-1 during the feed phase. This value is higher than the typical aerobic substrate uptake capacity of C. glutamicum (own data) and reported microaerobic uptake rates [26] (both ca. 3 mmol g-1 h-1). Interestingly, in the PFR there was also a significant pH difference between the different ports, as is shown for the longer residence time (τ = 87 s) in Figure 4A. "
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    ABSTRACT: Corynebacterium glutamicum has large scale industrial applications in the production of amino acids and the potential to serve as a platform organism for new products. This means the demand for industrial process development is likely to increase. However, large scale cultivation conditions differ from laboratory bioreactors, mostly due to the formation of concentration gradients at the industrial scale. This leads to an oscillating supply of oxygen and nutrients for microorganisms with uncertain impact on metabolism. Scale-down bioreactors can be applied to study robustness and physiological reactions to oscillating conditions at a laboratory scale. In this study, C. glutamicum ATCC13032 was cultivated by glucose limited fed-batch cultivation in a two-compartment bioreactor consisting of an aerobic stirred tank and a connected non-aerated plug flow reactor with optional feeding. Continuous flow through both compartments generated oscillating profiles with estimated residence times of 45 and 87 seconds in the non-aerated plug flow compartment. Oscillation of oxygen supply conditions at substrate excess and oscillation of both substrate and dissolved oxygen concentration were compared to homogeneous reference cultivations. The dynamic metabolic response of cells within the anaerobic plug flow compartment was monitored throughout the processes, detecting high turnover of substrate into metabolic side products and acidification within oxygen depleted zones. It was shown that anaerobic secretion of lactate into the extracellular culture broth, with subsequent reabsorption in the aerobic glucose-limited environment, leads to mixed-substrate growth in fed-batch processes. Apart from this, the oscillations had only a minor impact on growth and intracellular metabolite characteristics. Carbon metabolism of C. glutamicum changes at oscillating oxygen supply conditions, leading to a futile cycle over extracellular side products and back into oxidative pathways. This phenomenon facilitates a dynamic and flexible shift of oxygen uptake at inhomogeneous process conditions. There is no loss of process characteristics at oscillation times in the minute range, which emphasizes the robustness of C. glutamicum in comparison to other industrial microorganisms. Therefore, the metabolic phenotype of C. glutamicum seems to be particularly well-suited for cultivation at inhomogeneous process conditions for large-scale fed-batch application, which is in good accordance with the respective industrial experiences.
    Full-text · Article · Jan 2014 · Microbial Cell Factories
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