Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses

Bioprocess development and optimization are still cost- and time-intensive due to the enormous number of experiments involved. In this study, the recently introduced model-assisted Design of Experiments (mDoE) concept (Möller et al. in Bioproc Biosyst Eng 42(5):867, https://doi.org/10.1007/s00449-019-02089-7, 2019) was extended and implemented into a software (“mDoE-toolbox”) to significantly reduce the number of required cultivations. The application of the toolbox is exemplary shown in two case studies with Saccharomyces cerevisiae. In the first case study, a fed-batch process was optimized with respect to the pH value and linearly rising feeding rates of glucose and nitrogen source. Using the mDoE-toolbox, the biomass concentration was increased by 30% compared to previously performed experiments. The second case study was the whole-cell biocatalysis of ethyl acetoacetate (EAA) to (S)-ethyl-3-hydroxybutyrate (E3HB), for which the feeding rates of glucose, nitrogen source, and EAA were optimized. An increase of 80% compared to a previously performed experiment with similar initial conditions was achieved for the E3HB concentration.

Schlagworte

Biocatalysis

Fed-batch strategy

Model-assisted design of experiments

Monte Carlo methods

Quality by design

DDC Class

570: Biowissenschaften, Biologie

600: Technik

Projekt(e)

Projekt DEAL

Funding Organisations

Bundesministerium für Bildung und Forschung (BMBF)

More Funding Information

The authors acknowledge partial funding by German Federal Ministry of Education and Research (BMBF, Grant 031B0577A-C).

Publication version

publishedVersion

Lizenz

https://creativecommons.org/licenses/by/4.0/

Name

Moser2021_Article_Model-assistedDoESoftwareOptim.pdf

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5.21 MB

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Adobe PDF

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Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses