Instabilities of product formation in a fed-batch culture ofPenicillium chrysogenum

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Computing the various pathways of penicillin synthesis and their molar yields

More than 80 years after its discovery, penicillin is still a widely used and commercially highly important antibiotic. Here, we analyse the metabolic network of penicillin synthesis in Penicillium chrysogenum based on the concept of elementary flux modes. In particular, we consider the synthesis of the invariant molecular core of the various subtypes of penicillin and the two major ways of incorporating sulfur: transsulfuration and direct sulfhydrylation. 66 elementary modes producing this invariant core are obtained. These show four different yields with respect to glucose, notably ½, 2/5, 1/3, and 2/7, with the highest yield of ½ occurring only when direct sulfhydrylation is used and α-aminoadipate is completely recycled. In the case of no recycling of this intermediate, we find the maximum yield to be 2/7. We compare these values with earlier literature values. Our analysis provides a systematic overview of the redundancy in penicillin synthesis and a detailed insight into the corresponding routes. Moreover, we derive suggestions for potential knockouts that could increase the average yield.

Mathematical modelling of industrial pilot-plant penicillin-G fed-batch fermentations

Penicillin-G fermentation with industrial media in 1 m3 stirred tank bioreactors was studied. A model based on the Bajpai-Reuss model structure was developed. Under typical production conditions catabolite repression is nonidentifiable and extensive mycelium differentiation occurs. Thus, the original model was reformulated, neglecting glucose repression of penicillin production and including biomass autolysis. The multi-substrate nature of industrial media was critically analysed. By combining the two most important carbon substrates present, a simple and applicable model was obtained. Model predictions agreed well with experimental data and reproduced the general characteristics observed in the fermentations. The predictive power of the model was tested for fermentations with different sugar feed rate profiles and raw materials (corn-steep liquor and sugar syrup). Several aspects of parameter estimation and model development are discussed on the basis of direct experimental data inspection and a sensitivity analysis of model parameters.