Modeling and tuning of glucose oxidase-catalase system incorporating dissolved oxygen concentration

Abstract

BACKGROUND: Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx-CAT system is modeled considering a continuous oxygen supply at a bioreactor lab scale. Initially, experiments and modeling for parameter estimations of (Formula presented.) and the individual enzymes were conducted. Then, experiments and modeling for the GOx-CAT system were performed for final model tuning. Additionally, the model quality was evaluated, allowing for a deeper understanding of the system phenomenology. RESULTS: From the oxygen transport model tuning, a highly accurate (Formula presented.) estimation was obtained ((Formula presented.) >0.98 and confidence interval <2%). The highest oxygen transport rate was obtained for the combined system Buffer-antifoam-GOx-CAT that was 2.5 times larger than that obtained for DI water. Kinetic models for the individual enzymes were very accurate and the parameters were fully identifiable. For the integrated system, the gluconic acid evolution was properly predicted and there was a loss of predictive power for the oxygen model. Parameter identifiability analysis showed that (Formula presented.) and (Formula presented.) interpretability was compromised. However, the sensitivity analysis indicated that the model must not be simplified. CONCLUSION: Herein its has been demonstrated that (Formula presented.) is a complex parameter to be estimated for multi-enzymatic systems due to its dependency on medium composition, particularly with GOx. Nonetheless, based on the acceptable model predictive power, the calculated parameters could be used for studies on the process design phase. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).