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The Genome-scale Metabolic Network Analysis of Zymomonas Mobilis ZM4 Explains Physiological Features and Suggests Ethanol and Succinic Acid Production Strategies

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Publisher Biomed Central
Date 2010 Nov 25
PMID 21092328
Citations 28
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Abstract

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 experiments and literature information. This reconstructed metabolic model will allow better understanding of Z. mobilis metabolism and consequently designing metabolic engineering strategies for various biotechnological applications.

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References
1.
David H, Ozcelik I, Hofmann G, Nielsen J . Analysis of Aspergillus nidulans metabolism at the genome-scale. BMC Genomics. 2008; 9:163. PMC: 2386489. DOI: 10.1186/1471-2164-9-163. View

2.
Tsantili I, Karim M, Klapa M . Quantifying the metabolic capabilities of engineered Zymomonas mobilis using linear programming analysis. Microb Cell Fact. 2007; 6:8. PMC: 1831482. DOI: 10.1186/1475-2859-6-8. View

3.
Seo J, Chong H, Park H, Yoon K, Jung C, Kim J . The genome sequence of the ethanologenic bacterium Zymomonas mobilis ZM4. Nat Biotechnol. 2004; 23(1):63-8. PMC: 6870993. DOI: 10.1038/nbt1045. View

4.
Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel R, Bairoch A . ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003; 31(13):3784-8. PMC: 168970. DOI: 10.1093/nar/gkg563. View

5.
Schilling C, Covert M, Famili I, Church G, Edwards J, Palsson B . Genome-scale metabolic model of Helicobacter pylori 26695. J Bacteriol. 2002; 184(16):4582-93. PMC: 135230. DOI: 10.1128/JB.184.16.4582-4593.2002. View