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In silico screening of triple reaction knockout Escherichia coli strains for overproduction of useful metabolites.

Journal of bioscience and bioengineering (2012-10-09)
Satoshi Ohno, Chikara Furusawa, Hiroshi Shimizu
ABSTRACT

For efficient production of industrially useful metabolites by microorganisms, it is important to design metabolic networks suitable for production. For this purpose, constraint-based metabolic flux simulation is a powerful tool to predict the effect of reaction knockouts on target productivity. In this study, using constraint-based metabolic simulation, in silico screening was performed to identify knockout candidate sets that increase the productivity of 1-butanol, 1-propanol, and 1,3-propanediol by engineered Escherichia coli. Metabolic changes caused by all possible sets of triple reaction knockouts were evaluated using a reduced metabolic model, which was constructed to significantly reduce the computational cost. The results demonstrated the strategies to improve target productivity by gene disruption; some of them could not be achieved by previous screening methods. Such knockout strategies can support further improvements of the target productivity.

MATERIALS
Product Number
Brand
Product Description

Sigma-Aldrich
1,3-Propanediol, 98%
Sigma-Aldrich
1-Propanol, purum, ≥99.0% (GC)
Supelco
1-Propanol, analytical standard
Sigma-Aldrich
1-Propanol, anhydrous, 99.7%
Sigma-Aldrich
1-Propanol, ≥99%, FG
Sigma-Aldrich
1-Propanol, natural, ≥98%, FG
Sigma-Aldrich
1-Propanol, suitable for HPLC, ≥99.9%
Sigma-Aldrich
1-Propanol, ≥99% (GC), purum
Sigma-Aldrich
1-Propanol, ACS reagent, ≥99.5%