Classification and sensitivity analysis of a proposed primary metabolic reaction network for Streptomyces lividans.

Constructing a metabolic flux analysis model is in principle fairly straightforward. However, there are a number of mathematical pitfalls. First, dependent reactions are a recurring problem and, second, the choice of reactions to measure may not be straight-forward. A method for systematic identification of dependent reactions and a thorough reactions classification procedure is presented. A well-defined stoichiometric presentation can provide significant insight into metabolic control mechanisms. Two methods for analyzing the impact of perturbations in the measured fluxes on the remaining metabolism and the impact of changes in biomass composition on the calculated metabolic reactions is developed. A metabolic reaction network proposed for Streptomyces lividans is used as an example to demonstrate the outlined analysis. It is concluded that oxygen utilization has the highest influence on the pathway fluxes and that realistic perturbations in the biomass composition do not significantly alter the flux patterns.

Metabolic modeling as a tool for evaluating polyhydroxyalkanoate copolymer production in plants.

The production of polyhydroxyalkanoates in plants is an interesting commercial prospect due to lower carbon feedstock costs and capital investments. The production of poly-(3-hydroxybutyrate) has already been successfully demonstrated in plant plastids, and the production of more complex polymers is under investigation. Using a mathematical simulation model this paper outlines the theoretical prospects of producing the copolymer poly-(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-3HV)] in plant plastids. The model suggests that both the 3HV/3HB ratio and the copolymer production rate will vary considerably between dark and light conditions. Using metabolic control analysis we predict that the beta-ketothiolase predominately controls the copolymer production rate, but that the activity of all three enzymes influence the copolymer ratio. Dynamic simulations further suggest that controlled expression of the three enzymes at different levels may enable desirable changes in both the copolymer production rate and the 3HV/3HB ratio. Finally, we illustrate that natural variations in substrate and cofactor levels may have a considerable impact on both the production rate and the copolymer ratio, which must be taken into account when constructing a production system.

A simple structured model describing the growth of Streptomyces lividans.

The growth of Streptomyces lividans in defined media was modeled using a simple structured growth model. Conventional unstructured models like Monod kinetics, substrate inhibition kinetics, and the logistic equation were also used in an attempt to fit the data, but the results were all unsatisfactory. The main reason for failure in applying simple unstructured models is that they cannot describe the long lag phases sometimes observed during growth of S. lividans. The simple structured growth model was derived along similar principles to cybernetic growth models. This model quite accurately describes the growth of S. lividans. It assumes that the rate of assimilation of a substrate depends on the concentration of a specific key enzyme. This key enzyme is only produced in the presence of the substrate, and it is broken down at a steady rate. An enzyme synthesis allocation variable, w, similar to the cybernetic variable, u, described in cybernetic growth models, is proposed to control enzyme synthesis. Until the key enzyme concentration approaches its maximum level, very little substrate is consumed. And consequently, the lag phase is sustained.