β-半乳糖苷酶催化合成 3-O-β-D-吡喃半乳糖基-sn-甘油：响应面法优化,Biocatalysis and Biotransformation

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β-半乳糖苷酶催化合成 3-O-β-D-吡喃半乳糖基-sn-甘油：响应面法优化
Biocatalysis and Biotransformation ( IF 1.4 ) Pub Date : 2016-07-03 , DOI: 10.1080/10242422.2016.1247815
Wei Wei ₁ , Danping Qi ₁ , Mingming Diao ₁ , Lu Zhaoxin ₁ , Fengxia Lv ₁ , Haizhen Zhao ₁

Affiliation

摘要在本研究中，3-O-β-D-吡喃半乳糖基-sn-甘油 (GG) 的合成是通过使用乳酸克鲁维酵母的 β-半乳糖苷酶对 D-半乳糖和甘油进行反向水解来进行的。四个过程变量，反应温度 (30.0–45.0 °C)、反应时间 (24–48 h)、酶浓度 (150.00–350.00 U/mL) 和底物摩尔比（甘油：D-半乳糖，7.5:12.5 mmol/ mmol) 通过响应面方法 (RSM) 进行研究和优化，以获得最佳 GG 合成。建立了二次方程和最佳反应条件。结果表明，四个变量，即反应温度、反应时间、酶浓度和底物摩尔比对GG的合成具有显着(p < 0.0001)影响。最佳反应条件确定为350。00 U/mL β-半乳糖苷酶浓度和 8.65:1.00 的底物摩尔浓度比（甘油：D-半乳糖）在 39.8 °C 和 48 小时的反应。在这些条件下，GG浓度为140.03 g/L，GG产率为55.71%，均接近预测值（143.26 g/L和56.73%）。这一发现证明 RSM 是优化 GG 合成工艺条件的有用工具。

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β-galactosidase-catalyzed synthesis of 3-O-β-D-galactopyranosyl-sn-glycerol: Optimization by response surface methodology

Abstract In this study, the synthesis of 3-O-β-D-galactopyranosyl-sn-glycerol (GG) was performed by the reverse hydrolysis of D-galactose and glycerol using β-galactosidase from Kluyveromyces lactis. Four process variables, reaction temperature (30.0–45.0 °C), reaction time (24–48 h), enzyme concentration (150.00–350.00 U/mL), and substrate molar ratio (glycerol:D-galactose, 7.5:12.5 mmol/mmol) were investigated and optimized via response surface methodology (RSM) for optimal GG synthesis. Both quadratic equations and the optimal reaction conditions were established. Results showed that the four variables, i.e., reaction temperature, reaction time, enzyme concentration, and substrate molar ratio had significant (p < 0.0001) effects on the synthesis of GG. The optimal reaction conditions were identified as 350.00 U/mL of β-galactosidase concentration and 8.65:1.00 of substrate molar concentration ratio (glycerol: D-galactose) at 39.8 °C and 48 h of reaction. Under these conditions, the GG concentration was 140.03 g/L and GG yield was 55.71%, which both were close to the predicted values (143.26 g/L and 56.73%). This finding proves the RSM to be a useful tool in optimizing process conditions for GG synthesis.

更新日期：2016-07-03

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