ABSTRACT:
Lee2010 - Genome-scale metabolic network of
Zymomonas mobilis (iZmobMBEL601)
This model is described in the article:
The genome-scale metabolic
network analysis of Zymomonas mobilis ZM4 explains
physiological features and suggests ethanol and succinic acid
production strategies.
Lee KY, Park JM, Kim TY, Yun H, Lee
SY.
Microb. Cell Fact. 2010; 9: 94
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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