Analysis of Aerobic-to-Anaerobic and Anaerobic-to-Aerobic Switches in E. coli Using Large-Scale Dynamic Metabolic Models

Dynamic nonlinear models of metabolism offer significant advantages as compared to traditional steady-state counterparts for the analysis of metabolic networks and identification of metabolic engineering strategies. Uncertainties in the metabolic network structure, kinetic rate laws, and their corresponding parameters are limiting the development of systematic methodologies for construction of large-scale, dynamic metabolic models. In this study, we employed a novel methodology to construct dynamic, large-scale, nonlinear models of E.coli metabolism. The parameters of these models were computed in two steps: (i) the ORACLE framework is used to integrate thermodynamics, available omics, and kinetic data and construct a population of log-linear kinetic models; (ii) the log-linear models are used to compute kinetic parameters of nonlinear enzymatic mechanisms in the network and we developed a population of nonlinear kinetic models. We used a metabolic network composed of 140 metabolites and 225 reactions, and we  analyzed the dynamic responses of E.coli upon switch from aerobic respiration to anaerobic, and vice versa. This analysis allowed us to characterize the time constants of the different functional parts of E.coli  metabolism such as glycolysis, TCA, and oxidative phosphorylation. Furthermore, we analyzed the network responses upon various perturbations of the network components to explore the robustness and sensitivity of the operational states. The methodology presented here is independent of the organism and the physiological conditions and it can be used for the design of any metabolic network of interest.