title: Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites.
abstract: The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realistic quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, USA.
authors.forename: Jimmy G
authors.initials: JG
authors.lastname: Lafontaine Rivera
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, USA; Department of Bioengineering, University of California, Los Angeles, USA.
authors.forename: Matthew K
authors.initials: MK
authors.lastname: Theisen
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, USA.
authors.forename: Po-Wei
authors.initials: PW
authors.lastname: Chen
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, USA; UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, USA; Academia Sinica, Taiwan. Electronic address: liaoj@ucla.edu.
authors.forename: James C
authors.initials: JC
authors.lastname: Liao
mesh_terms: D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological
keywords: Bioprocessing; Kinetic modeling; Systems biology; Yield calculation