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Published on: February 1, 2015
A structured model for hyphal differentiation and penicillin production using Penicillium chrysogenum
1BBSRC Centre for Biochemical Engineering School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
Abstract:
A structured kinetic model describing growth, differentiation, and penicillin production in submerged Penicillium chrysogenum fermentations is reported. The filamentous hyphae are divided into four distinct regions on the basis of the activities and structure of hyphal compartments, viz., actively growing (mainly apical) regions, nongrowing or penicillin producing regions, vacuoles, and degenerated or metabolically inactive regions. A mechanistic approach is taken to give quantitative descriptions of differentiation and degeneration as a consequence of vacuolation. The growth and degeneration of vacuoles are expressed in the form of a population balance. The model assumes that newly generated vacuoles appear by differentiation of healthy regions, grow in size with limitation of available substrate, and eventually give rise to empty hyphal compartments. In the model the penicillin production is related to the amounts of the nongrowing regions of the hyphae. The model is used for successful predictions of the amounts of the four hyphal regions and the penicillin G production rate throughout the fed-batch fermentations of an industrial P. chrysogenum strain under different glucose feeding regimes. Quantitative information on proportions of the hyphal regions was obtained from image analysis measurements and the parameters of the kinetic model were identified. When the glucose feed rate to the production culture is switched between a high and a low value, the model can successfully predict the dynamic changes of differentiation and the resulting penicillin production caused by the variations in the nutrient conditions. The use of image analysis to characterize differentiation as a basis for structured modeling of the penicillin fermentation appears to be very powerful, and the method has great potential for use in process simulation and control of antibiotic fermentations.
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