A simple mathematical model capable of describing the microbial production of poly(hydroxyalkanoates) under carbon‐ and nitrogen‐limiting growth conditions. Issue 9 (14th April 2018)

• Record Type: Journal Article
• Authors: Vega, Roberto; Castillo, Augusto
• Is Part Of: Journal of chemical technology & biotechnology. Volume 93:Issue 9(2018)
• Page Start: 2564
• Page End: 2575
• Publication Date: 2018-04-14
• Subjects: polyhydroxyalkanoates -- mathematical model -- kinetics -- Pseudomonas putida -- Cupriavidus necator -- batch culture -- continuous culture; Biotechnology -- Periodicals; Chemistry, Technical -- Periodicals; Chemical engineering -- Periodicals; Industries -- Environmental aspects -- Periodicals; 660
• DOI: 10.1002/jctb.5610
• Languages: English
• ISSNs: 0268-2575

Abstract

Abstract: BACKGROUND: Poly(hydroxyalkanoates) (PHAs) are biodegradable polymers that can replace conventional plastics, but microbial production of PHAs must be optimized for commercial success. The aim of this study is to provide a simple mathematical model based on previous studies in the literature to represent the production of PHAs in chemostat and batch cultures by Pseudomonas putida GPo1 (ATCC 29347) and Cupriavidus necator (DSM 545) grown on octanoate and glucose, respectively. RESULTS: Kinetic and stoichiometric equations, dependent on the specific growth rate of residual biomass (µR ), were developed for carbon‐ and nitrogen‐limiting growth conditions. The parameters have biochemical significance and are independent of the biomass concentration. The results revealed that the Luedeking–Piret model is growth‐associated for both fermentations under carbon limitation. In addition, the PHA content increases with µR . Meanwhile, the PHA content is amplified under nitrogen limitation but decreases as μR increases. Also, the Luedeking–Piret model exhibits a profile that depends on the synthesized polyhydroxyalkanoate. CONCLUSION: This study demonstrates that strategies for the production of PHAs require an in‐depth understanding of the process kinetics. This model gives satisfactory predictions, may be extended to fed batch cultures and may be adapted to other fermentations. © 2018 Society of Chemical Industry