Model-based analysis of biocatalytic processes and performance of microbioreactors with integrated optical sensors
Language English Country Netherlands Media print-electronic
Document type Journal Article
PubMed
31704414
DOI
10.1016/j.nbt.2019.11.001
PII: S1871-6784(18)31977-0
Knihovny.cz E-resources
- Keywords
- Bioprocess modeling, Computational fluid dynamics, Enzymatic biocatalysis, Mechanistic modeling, Microbioreactor, Oxygen monitoring,
- MeSH
- Biocatalysis MeSH
- Models, Biological * MeSH
- Bioreactors * MeSH
- Glucose Oxidase metabolism MeSH
- Catalase metabolism MeSH
- Microfluidic Analytical Techniques * MeSH
- Optical Fibers * MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Glucose Oxidase MeSH
- Catalase MeSH
Design and development of scale-down approaches, such as microbioreactor (μBR) technologies with integrated sensors, are an adequate solution for rapid, high-throughput and cost-effective screening of valuable reactions and/or production strains, with considerably reduced use of reagents and generation of waste. A significant challenge in the successful and widespread application of μBRs in biotechnology remains the lack of appropriate software and automated data interpretation of μBR experiments. Here, it is demonstrated how mathematical models can be usedas helpful tools, not only to exploit the capabilities of microfluidic platforms, but also to reveal the critical experimental conditions when monitoring cascade enzymatic reactions. A simplified mechanistic model was developed to describe the enzymatic reaction of glucose oxidase and glucose in the presence of catalase inside a commercial microfluidic platform with integrated oxygen sensor spots. The proposed model allowed an easy and rapid identification of the reaction mechanism, kinetics and limiting factors. The effect of fluid flow and enzyme adsorption inside the microfluidic chip on the optical sensor response and overall monitoring capabilities of the presented platform was evaluated via computational fluid dynamics (CFD) simulations. Remarkably, the model predictions were independently confirmed for μL- and mL- scale experiments. It is expected that the mechanistic models will significantly contribute to the further promotion of μBRs in biocatalysis research and that the overall study will create a framework for screening and evaluation of critical system parameters, including sensor response, operating conditions, experimental and microbioreactor designs.
Process and Systems Engineering Center Allée Emile Monso 4 31030 Toulouse France
Process and Systems Engineering Center Søltofts Plads Building 229 2800 Kgs Lyngby Denmark
Process and Systems Engineering Center Technicka 5 166 28 Prague Czech Republic
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