Black‐box kinetic modeling of growth and citric acid production and estimation of ATP maintenance parameters for Candida oleophila ATCC20177. (14th April 2020)

• Record Type: Journal Article
• Authors: Tanıl, Ezgi; Nikerel, Emrah
• Is Part Of: Biotechnology and applied biochemistry. Volume 68:Number 1(2021)
• Page Start: 148
• Page End: 156
• Publication Date: 2020-04-14
• Subjects: black‐box kinetic modeling -- Candida oleophila, citric acid production -- energetics ATP parameters -- parameter identifiability; Biotechnology -- Periodicals; Biochemical engineering -- Periodicals; Biochemistry -- Periodicals; Biochemistry -- Periodicals; Genetic Techniques -- Periodicals; Microbiological Techniques -- Periodicals; 660.6
• DOI: 10.1002/bab.1905
• Languages: English
• ISSNs: 0885-4513

Abstract

Abstract: Mathematical modeling represents and predicts biological systems, explains underlying mechanisms, constituting one of the key focus points for fundamental and applied research to improve our understanding and to decrease costs. Organic acids are used in several industries such as monomers for bioplastics, food preservatives and additives, pharmaceuticals, and agriculture. Nonpetrochemical, sustainable production of organic acids is therefore of great interest. An important step in production of organic acids is the determination of growth and acid production dynamics, as the product itself may have direct and indirect inhibitory effects on the host's metabolism. The aim of this study it twofold: (i) to determine the parameters related to energetics of growth and production as growth ( K x ) and nongrowth associated ( m ATP ) maintenance constants and (ii) to set up and analyze an unstructured, black‐box kinetic model to describe the dynamics of the growth and production of citric acid by Candida oleophila ATCC20177 using published batch fermentation data. K x and m ATP were found to be 2.3 ± 1.7 and 5.25 ± 2.75, respectively, for the published P/O ratio of 1.45. The parameter sensitivities and correlations are determined using the Monte Carlo approach, and the final model is tested using chemostat data.