Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization. (16th January 2018)

• Record Type: Journal Article
• Authors: Haringa, Cees; Tang, Wenjun; Wang, Guan; Deshmukh, Amit T.; van Winden, Wouter A.; Chu, Ju; van Gulik, Walter M.; Heijnen, Joseph J.; Mudde, Robert F.; Noorman, Henk J.
• Is Part Of: Chemical engineering science. Volume 175(2018)
• Page Start: 12
• Page End: 24
• Publication Date: 2018-01-16
• Subjects: 76T10 -- 92-08; CFD -- Euler-Langrange -- Metabolic model -- Scale-down -- Industrial; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2017.09.020
• Languages: English
• ISSNs: 0009-2509

Abstract

Graphical abstract: Highlights: Metabolic-hydrodynamic simulation to predict yield loss due to substrate gradient. Novel design approach for representative scale-down simulators. Use of simulations to assess effect of reactor design on process yield. Experimental verification of penicillin production rate in fed-batch simulation. Prediction of emerging population heterogeneity in fed-batch simulation. Abstract: We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5 steps. (1) A model response study with a fixed spatial extra-cellular glucose concentration gradient, which reveals a drop in penicillin production rate q p of 18 – 50 % for the simulated reactor, depending on model setup. (2) CFD-based scale-down design, where we design a 1-vessel scale down simulator based on the organism lifelines. (3) Scale-down verification, numerically comparing the model response in the proposed scale-down simulator with large-scale CFD response. (4) Reactor design optimization, reducing the drop in penicillin production by a change of feed location. (5) Long-term fed-batch simulation, where we verify model predictions against experimental data, and discuss population heterogeneity. Overall, these steps present a coupled hydrodynamic-metabolic approach towards bioreactor evaluation, scale-down and optimization.