Biocatalytic process optimization based on mechanistic modeling of cholic acid oxidation with cofactor regeneration

Authors

  • Michael Braun,

    1. Institute of Biochemical Engineering, Technische Universität München, Boltzmannstr. 15, 85748 Garching, Germany; tel.: +49-0-89-289-15712; fax: +49-0-89-289-15714
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  • Hannes Link,

    1. Institute of Biochemical Engineering, Technische Universität München, Boltzmannstr. 15, 85748 Garching, Germany; tel.: +49-0-89-289-15712; fax: +49-0-89-289-15714
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  • Luo Liu,

    1. Institute of Technical Biochemistry, Universität Stuttgart, Stuttgart, Germany
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  • Rolf D. Schmid,

    1. Institute of Technical Biochemistry, Universität Stuttgart, Stuttgart, Germany
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  • Dirk Weuster-Botz

    Corresponding author
    1. Institute of Biochemical Engineering, Technische Universität München, Boltzmannstr. 15, 85748 Garching, Germany; tel.: +49-0-89-289-15712; fax: +49-0-89-289-15714
    • Institute of Biochemical Engineering, Technische Universität München, Boltzmannstr. 15, 85748 Garching, Germany; tel.: +49-0-89-289-15712; fax: +49-0-89-289-15714.
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Abstract

Reduction and oxidation of steroids in the human gut are catalyzed by hydroxysteroid dehydrogenases of microorganisms. For the production of 12-ketochenodeoxycholic acid (12-Keto-CDCA) from cholic acid the biocatalytic application of the 12α-hydroxysteroid dehydrogenase of Clostridium group P, strain C 48–50 (HSDH) is an alternative to chemical synthesis. However, due to the intensive costs the necessary cofactor (NADP+) has to be regenerated. The alcohol dehydrogenase of Thermoanaerobacter ethanolicus (ADH-TE) was applied to catalyze the reduction of acetone while regenerating NADP+. A mechanistic kinetic model was developed for the process development of cholic acid oxidation using HSDH and ADH-TE. The process model was derived by identifying the parameters for both enzymatic models separately using progress curve measurements of batch processes over a broad range of concentrations and considering the underlying ordered bi–bi mechanism. Both independently derived kinetic models were coupled via mass balances to predict the production of 12-Keto-CDCA with HSDH and integrated cofactor regeneration with ADH-TE and acetone as co-substrate. The prediction of the derived model was suitable to describe the dynamics of the preparative 12-Keto-CDCA batch production with different initial reactant and enzyme concentrations. These datasets were used again for parameter identification. This led to a combined model which excellently described the reaction dynamics of biocatalytic batch processes over broad concentration ranges. Based on the identified process model batch process optimization was successfully performed in silico to minimize enzyme costs. By using 0.1 mM NADP+ the HSDH concentration can be reduced to 3–4 µM and the ADH concentration to 0.4–0.6 µM to reach the maximal possible conversion of 100 mM cholic acid within 48 h. In conclusion, the identified mechanistic model offers a powerful tool for a cost-efficient process design. Biotechnol. Bioeng. 2011; 108:1307–1317. © 2010 Wiley Periodicals, Inc.

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