Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures
the need of a biological systems response analysis
Guan Wang (East China University of Science and Technology)
Junfei Zhao (East China University of Science and Technology)
Cees Haringa (TU Delft - ChemE/Transport Phenomena)
Wenjun Tang (East China University of Science and Technology)
Jianye Xia (East China University of Science and Technology)
Ju Chu (East China University of Science and Technology)
Yingping Zhuang (East China University of Science and Technology)
Siliang Zhang (East China University of Science and Technology)
Amit T. Deshmukh (DSM)
Walter van Gulik (TU Delft - OLD BT/Cell Systems Engineering)
Joseph J. Heijnen (TU Delft - OLD BT/Cell Systems Engineering)
Henk J. Noorman (DSM, TU Delft - BT/Bioprocess Engineering)
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Abstract
In a 54 m3 large-scale penicillin fermentor, the cells experience substrate gradient cycles at the timescales of global mixing time about 20–40 s. Here, we used an intermittent feeding regime (IFR) and a two-compartment reactor (TCR) to mimic these substrate gradients at laboratory-scale continuous cultures. The IFR was applied to simulate substrate dynamics experienced by the cells at full scale at timescales of tens of seconds to minutes (30 s, 3 min and 6 min), while the TCR was designed to simulate substrate gradients at an applied mean residence time ((Formula presented.)) of 6 min. A biological systems analysis of the response of an industrial high-yielding P. chrysogenum strain has been performed in these continuous cultures. Compared to an undisturbed continuous feeding regime in a single reactor, the penicillin productivity (qPenG) was reduced in all scale-down simulators. The dynamic metabolomics data indicated that in the IFRs, the cells accumulated high levels of the central metabolites during the feast phase to actively cope with external substrate deprivation during the famine phase. In contrast, in the TCR system, the storage pool (e.g. mannitol and arabitol) constituted a large contribution of carbon supply in the non-feed compartment. Further, transcript analysis revealed that all scale-down simulators gave different expression levels of the glucose/hexose transporter genes and the penicillin gene clusters. The results showed that qPenG did not correlate well with exposure to the substrate regimes (excess, limitation and starvation), but there was a clear inverse relation between qPenG and the intracellular glucose level.