title: Genome-scale analysis of Mannheimia succiniciproducens metabolism.
abstract: Mannheimia succiniciproducens MBEL55E isolated from bovine rumen is a capnophilic gram-negative bacterium that efficiently produces succinic acid, an industrially important four carbon dicarboxylic acid. In order to design a metabolically engineered strain which is capable of producing succinic acid with high yield and productivity, it is essential to optimize the whole metabolism at the systems level. Consequently, in silico modeling and simulation of the genome-scale metabolic network was employed for genome-scale analysis and efficient design of metabolic engineering experiments. The genome-scale metabolic network of M. succiniciproducens consisting of 686 reactions and 519 metabolites was constructed based on reannotation and validation experiments. With the reconstructed model, the network structure and key metabolic characteristics allowing highly efficient production of succinic acid were deciphered; these include strong PEP carboxylation, branched TCA cycle, relative weak pyruvate formation, the lack of glyoxylate shunt, and non-PTS for glucose uptake. Constraints-based flux analyses were then carried out under various environmental and genetic conditions to validate the genome-scale metabolic model and to decipher the altered metabolic characteristics. Predictions based on constraints-based flux analysis were mostly in excellent agreement with the experimental data. In silico knockout studies allowed prediction of new metabolic engineering strategies for the enhanced production of succinic acid. This genome-scale in silico model can serve as a platform for the systematic prediction of physiological responses of M. succiniciproducens to various environmental and genetic perturbations and consequently for designing rational strategies for strain improvement.
authors.affiliation: Department of Chemical and Biomolecular Engineering (BK21 Program), Metabolic and Biomolecular Engineering National Research Laboratory, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
authors.forename: Tae Yong
authors.initials: TY
authors.lastname: Kim
authors.forename: Hyun Uk
authors.initials: HU
authors.lastname: Kim
authors.forename: Jong Myoung
authors.initials: JM
authors.lastname: Park
authors.forename: Hyohak
authors.initials: H
authors.lastname: Song
authors.forename: Jin Sik
authors.initials: JS
authors.lastname: Kim
authors.forename: Sang Yup
authors.initials: SY
authors.lastname: Lee
mesh_terms: D000818:Animals; D018533:Biomass; D002417:Cattle; D003198:Computer Simulation; D005285:Fermentation; D016680:Genome, Bacterial; D031121:Mannheimia / Q000235:genetics* / Q000378:metabolism*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D009154:Mutation; D010802:Phylogeny; D015203:Reproducibility of Results; D012417:Rumen / Q000382:microbiology