In large scale fermentors the cultivated cells are exposed to dynamic changes in the nutrient concentrations due to imperfect mixing. Based on the characterization of these nutrient gradients in space and time, a rational scale down design can be obtained. This study focuses on the combined gradients of dissolved sugar and oxygen concentrations. Based on a recent computational fluid dynamics (CFD) study, firstly a scale-down design was developed. From intracellular metabolite measurements during these scale-down experiments, the metabolic behavior of the cells under highly dynamic conditions was revealed. Under the combined influence of oscillating glucose and oxygen concentrations, the penicillin production declined to 50 % of the value under steady state conditions. This decline was similar as observed during glucose oscillations alone. The influence of oxygen oscillations on the levels of the majority of the intracellular metabolites analyzed was negligible, although these metabolites were strongly affected by the varying oxygen levels under solely oxygen oscillations. Additionally, a metabolic structured kinetic model was developed and validated with data from glucose and oxygen oscillation experiments. This model can be coupled to CFD simulations to obtain an accurate prediction of the performance of industrial strains in space and time in large industrial scale bioreactors.

In large-scale bioreactors, there is often insufficient mixing and as a consequence, cells experience uneven substrate and oxygen levels that influence product formation. In this study, the influence of dissolved oxygen (DO) gradients on the primary and secondary metabolism of a high producing industrial strain of Penicillium chrysogenum was investigated. Within a wide range of DO concentrations, obtained under chemostat conditions, we observed different responses from P. chrysogenum: (i) no influence on growth or penicillin production (>0.025 mmol L⁻¹); (ii) reduced penicillin production, but no growth limitation (0.013–0.025 mmol L⁻¹); and (iii) growth and penicillin production limitations (<0.013 mmol L⁻¹). In addition, scale down experiments were performed by oscillating the DO concentration in the bioreactor. We found that during DO oscillation, the penicillin production rate decreased below the value observed when a constant DO equal to the average oscillating DO value was used. To understand and predict the influence of oxygen levels on primary metabolism and penicillin production, we developed a black box model that was linked to a detailed kinetic model of the penicillin pathway. The model simulations represented the experimental data during the step experiments; however, during the oscillation experiments the predictions deviated, indicating the involvement of the central metabolism in penicillin production.