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基于胆酸氧化与辅因子再生的机理模型对生物催化过程进行优化。

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

机构信息

Institute of Biochemical Engineering, Technische Universität München, Boltzmannstr. 15, 85748 Garching, Germany.

出版信息

Biotechnol Bioeng. 2011 Jun;108(6):1307-17. doi: 10.1002/bit.23047. Epub 2011 Jan 28.

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.

摘要

类固醇在人类肠道中的还原和氧化是由微生物的羟甾脱氢酶催化的。为了从胆酸生产 12-酮去氧胆酸(12-Keto-CDCA),可以替代化学合成,应用 Clostridium 组 P 菌株 C 48-50(HSDH)的 12α-羟甾脱氢酶进行生物催化。然而,由于成本高昂,有必要再生必要的辅酶(NADP(+))。应用嗜热厌氧菌(Thermoanaerobacter ethanolicus)的醇脱氢酶(ADH-TE)来催化丙酮的还原,同时再生 NADP(+)。通过对 HSDH 和 ADH-TE 进行广泛浓度范围内的批处理过程的进展曲线测量,分别为两个酶模型确定参数,并考虑到基础有序双生物机制,开发了用于胆酸氧化过程开发的机理动力学模型。通过质量平衡将两个独立推导的动力学模型耦合起来,以预测使用 HSDH 生产 12-Keto-CDCA,并与 ADH-TE 和丙酮作为共底物集成辅酶再生。推导模型的预测适合于描述具有不同初始反应物和酶浓度的制备 12-Keto-CDCA 分批生产的动力学。这些数据集再次用于参数识别。这导致了一个组合模型,该模型可以出色地描述在宽浓度范围内的生物催化批处理过程的反应动力学。基于识别的过程模型,成功地进行了批处理过程的计算机模拟优化,以最小化酶成本。通过使用 0.1 mM NADP(+),可以将 HSDH 浓度降低至 3-4 µM,将 ADH 浓度降低至 0.4-0.6 µM,从而在 48 h 内达到 100 mM 胆酸的最大转化率。总之,所识别的机理模型为经济高效的工艺设计提供了有力的工具。

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