title: In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation.
abstract: Synthesis gas fermentation is one of the most promising routes to convert synthesis gas (syngas; mainly comprised of H2and CO) to renewable liquid fuels and chemicals by specialized bacteria. The most commonly studied syngas fermenting bacterium is Clostridium ljungdahlii, which produces acetate and ethanol as its primary metabolic byproducts. Engineering of C. ljungdahlii 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 in silico metabolic engineering studies using a genome-scale reconstruction of C. ljungdahlii 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 C. ljungdahlii gene targets that offer the potential for increased product synthesis under realistic syngas fermentation conditions.
authors.affiliation: Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003, United States.
authors.forename: Jin
authors.initials: J
authors.lastname: Chen
authors.affiliation: Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003, United States. Electronic address: henson@ecs.umass.edu.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Henson
mesh_terms: D001426:Bacterial Proteins / Q000235:genetics*; D056804:Biofuels / Q000382:microbiology*; D053898:Biosynthetic Pathways / Q000235:genetics; D002245:Carbon Dioxide / Q000378:metabolism; D003013:Clostridium / Q000502:physiology*; D003198:Computer Simulation; D005285:Fermentation / Q000235:genetics*; D024861:Genetic Enhancement / Q000379:methods; D006859:Hydrogen / Q000378:metabolism; D060847:Metabolic Engineering / Q000379:methods*; D064688:Metabolic Flux Analysis / Q000379:methods; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic; D058615:Synthetic Biology / Q000379:methods
chemical_list: D001426:Bacterial Proteins; D056804:Biofuels; D002245:Carbon Dioxide; D006859:Hydrogen
keywords: Clostridium ljungdahlii; Gas fermentation; In silico metabolic engineering; OptKnock; Spatiotemporal metabolic modeling