(504f) Flux Balance Analysis of Dynamic Metabolism in Shewanella for Sequential Utilization of Carbon Sources

Abstract An environmentally important strain for metal reduction, Shewanella oneidensis MR-1 can grow and co-metabolize numerous toxic compounds and metals. The capabilities of S. oneidensis MR-1 to utilize diverse electron acceptors make it of great value in microbial fuel cells (MFC). One of the unique characteristics of the carbon metabolism in S. oneidensis MR-1 is the sequential production and utilization of different carbon sources during its growth. In general, lactate is first used, and less energy favorable extracellular metabolites (i.e., acetate and pyruvate) are secreted. When lactate is depleted, S. oneidensis MR-1 can uptake acetate and pyruvate for its growth. To decipher time-variant metabolic fluxes under different carbon-source utilization conditions, a non-stationary framework was proposed by dividing the flux model into two major components: 1) a Monod based kinetic model to describe the dynamic growth and metabolite production, and 2) a steady state flux model (incorporated over 260 reactions) embedded within the dynamic model. Our solution of this system generally followed the Static Optimization Approach (SOA) taken by Mahadevan et al. (2002). This approach involved dividing the growth period into several time intervals and solving the instantaneous optimization problem at the beginning of each time interval by traditional flux balance analysis approaches (e,g. using objective functions for maximization of biomass). This method avoided dynamic fluxes via nonlinear ordinary difference equations (ODE). The model results show that two metabolic statuses through the entire growth period. In the first metabolic status, fluxes through key central pathways were fully operated in the early growth phase when lactate was mainly utilized as the carbon source. It was followed by a continuous decrease of intracellular fluxes when the lactate was depleted. Then the fluxes of the central pathways were up-regulated after carbon sources switched to pyruvate and acetate. To validate the model, we measured the gene expression levels at multiple time points in the central metabolic pathways. The experimental data agree with model predictions. Such a framework can be a useful tool for dynamic metabolism analysis in other biological systems. Key words: dFBA, Shewanella, gene expression

Reference: Mahadevan R, Edwards JS, Doyle FJ. 2002. Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli. Biophysical Journal, 83(3), 1331-1340