title: Using flux balance analysis to guide microbial metabolic engineering.
abstract: Metabolic engineers modify biological systems through the use of modern molecular biology tools in order to obtain desired phenotypes. However, due to the extreme complexity and interconnectedness of metabolism in all organisms, it is often difficult to a priori predict which changes will yield the optimal results. Flux balance analysis (FBA) is a mathematical approach that uses a genomic-scale metabolic network models to afford in silico prediction and optimization of metabolic changes. In particular, a genome-scale approach can help select gene targets for knockout and overexpression. This approach can be used to help expedite the strain engineering process. Here, we give an introduction to the use of FBA and provide details for its implementation in a microbial metabolic engineering context.
authors.affiliation: Department of Chemical Engineering, The University of Texas at Austin, Austin, TX, USA.
authors.forename: Kathleen A
authors.initials: KA
authors.lastname: Curran
authors.forename: Nathan C
authors.initials: NC
authors.lastname: Crook
authors.forename: Hal S
authors.initials: HS
authors.lastname: Alper
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D060847:Metabolic Engineering / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D015203:Reproducibility of Results; D012984:Software