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In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation

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논문

In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation

학술지

Metabolic engineering

저자명

Chen, Jin; Henson, Michael A.

초록

<P><B>Abstract</B></P> <P>Synthesis gas fermentation is one of the most promising routes to convert synthesis gas (syngas; mainly comprised of H<SUB>2</SUB> and CO) to renewable liquid fuels and chemicals by specialized bacteria. The most commonly studied syngas fermenting bacterium is <I>Clostridium ljungdahlii</I>, which produces acetate and ethanol as its primary metabolic byproducts. Engineering of <I>C. ljungdahlii</I> metabolism to overproduce ethanol, enhance the synthesize of the native byproducts lactate and 2,3-butanediol, and introduce the synthesis of non-native products such as butanol and butyrate has substantial commercial value. We performed <I>in silico</I> metabolic engineering studies using a genome-scale reconstruction of <I>C. ljungdahlii</I> metabolism and the OptKnock computational framework to identify gene knockouts that were predicted to enhance the synthesis of these native products and non-native products, introduced through insertion of the necessary heterologous pathways. The OptKnock derived strategies were often difficult to assess because increase product synthesis was invariably accompanied by decreased growth. Therefore, the OptKnock strategies were further evaluated using a spatiotemporal metabolic model of a syngas bubble column reactor, a popular technology for large-scale gas fermentation. Unlike flux balance analysis, the bubble column model accounted for the complex tradeoffs between increased product synthesis and reduced growth rates of engineered mutants within the spatially varying column environment. The two-stage methodology for deriving and evaluating metabolic engineering strategies was shown to yield new <I>C. ljungdahlii</I> gene targets that offer the potential for increased product synthesis under realistic syngas fermentation conditions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Metabolic engineering strategies are studied <I>in silico</I> for <I>Clostridium ljungdahlii</I>. </LI> <LI> Gene deletions/insertions for metabolite overproduction are found with Optknock. </LI> <LI> Metabolic engineering strategies are further screened with a detailed reactor model. </LI> <LI> Sequential cellular/reactor engineering yields more realistic experimental targets. </LI> </UL> </P>

발행연도

2016

발행기관

Elsevier

ISSN

1096-7176

ISSN

1096-7184

38

페이지

pp.389-400

주제어

Gas fermentation; Clostridium ljungdahlii; In silico metabolic engineering; OptKnock; Spatiotemporal metabolic modeling

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논문; 2016-11-01

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