Mathematical Modeling of Growth Kinetics and Recombinant Butyrylcholinesterase Production of Transgenic Rice Cell Suspension Cultures

Conference proceedings article


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Publication Details

Author listParadon Sakornpanich, Kantharakorn Macharoen

Publication year2022

Title of seriesThe 31st Thai Institute of Chemical Engineering and Applied Chemistry Conference

Start page128

End page139

Number of pages12

URLhttps://drive.google.com/file/d/1STEnd1BYqjw0mrXOIWmRkCjxbz8YhDk1/view

LanguagesEnglish-United States (EN-US)


Abstract

Recombinant human butyrylcholinesterase (rBChE), a bioscavenger hydrolase enzyme against organophosphate nerve agents, has been expressed in several host systems, including mammalian cell cultures, transgenic animals, transient and transgenic whole plants, and transgenic plant cells using biotechnological techniques. Transgenic plant cell suspension cultures have been gaining more attention due to their simple and low-cost medium and intrinsic safe from human virus contamination. However, there are some challenges in this platform, such as labor-intensive in cell line development, low-throughput production, and time-consuming experiments. Therefore, in this study, mathematical modeling was developed to predict growth kinetics, substrate uptake, and rBChE production from transgenic rice cell suspension cultures grown in a conventional 5-L stirred tank bioreactor. The proposed model has considered a dynamic heterogeneous population of metabolic active viable cells and non-metabolic active viable cells. The ordinary differential equations (ODEs) of cell growth kinetics, sucrose utilization, intracellular rBChE production were solved simultaneously with kinetic parameters estimation in MATLAB using minimizing sum of squared errors between the model and experimental data. By comparing several growth kinetic models, the Moser model is likely to be the best fit model for this transgenic rice cell suspension culture. Finally, by using another set of experimental data for validation, the proposed model shows a relatively good prediction of cell growth, sucrose utilization, and product synthesis.


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Last updated on 2022-27-07 at 23:05