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Metabolic engineering for improved microbial pentose fermentation.

ABSTRACT: Global concern over the depletion of fossil fuel reserves, and the detrimental impact that combustion of these materials has on the environment, is focusing attention on initiatives to create sustainable approaches for the production and use of biofuels from various biomass substrates. The development of a low-cost, safe and eco-friendly process for the utilization of renewable resources to generate value-added products with biotechnological potential as well as robust microorganisms capable of efficient fermentation of all types of sugars are essential to underpin the economic production of biofuels from biomass feedstocks. Saccharomyces cerevisiae, the most established fermentation yeast used in large scale bioconversion strategies, does not however metabolise the pentose sugars, xylose and arabinose and bioengineering is required for introduction of efficient pentose metabolic pathways and pentose sugar transport proteins for bioconversion of these substrates. Our approach provided a basis for future experiments that may ultimately lead to the development of industrial S. cerevisiae strains engineered to express pentose metabolising proteins from thermophilic fungi living on decaying plant material and here we expand our original article and discuss the strategies implemented to improve pentose fermentation.

SUBMITTER: Fernandes S

PROVIDER: S-EPMC3056094 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundComputational modeling and analysis of metabolic networks has been successful in metabolic engineering of microbial strains for valuable biochemical production. Limitations of currently available computational methods for metabolic engineering are that they are often based on reaction deletions rather than gene deletions and do not consider the regulatory networks that control metabolism. Due to the presence of multi-functional enzymes and isozymes, computational designs based on reaction deletions can sometimes result in strategies that are genetically complicated or infeasible. Additionally, strains might not be able to grow initially due to regulatory restrictions. To overcome these limitations, we have developed a new approach (OptORF) for identifying metabolic engineering strategies based on gene deletion and overexpression.ResultsHere we propose an effective method to systematically integrate transcriptional regulatory networks and metabolic networks. This allows for the formulation of linear optimization problems that search for metabolic and/or regulatory perturbations that couple biomass and biochemical production, thus proposing adaptive evolutionary strain designs. Using genome-scale models of Escherichia coli, we have implemented the OptORF algorithm (which considers gene deletions and transcriptional regulation) and compared its metabolic engineering strategies for ethanol production to those found using OptKnock (which considers reaction deletions). Our results found that the reaction-based strategies often require more gene deletions to remove the identified reactions (2 more genes than reactions), and result in lethal growth phenotypes when transcriptional regulation is considered (162 out of 200 cases). Finally, we present metabolic engineering strategies for producing ethanol and higher alcohols (e.g. isobutanol) in E. coli using our OptORF approach. We have found common genetic modifications such as deletion of pgi and overexpression of edd, as well as chemical specific strategies for producing different alcohols.ConclusionsBy taking regulatory effects into account, OptORF can propose changes such as the overexpression of metabolic genes or deletion of transcriptional factors, in addition to the deletion of metabolic genes, that may lead to faster evolutionary trajectories. While biofuel production in E. coli is evaluated here, the developed OptORF approach is general and can be applied to optimize the production of different compounds in other biological systems.

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Metabolic engineering for improved microbial pentose fermentation.

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