Egyptian Petroleum Research Institute (EPRI), Nasr City, Cairo, Egypt.
Botany and Microbiology Department, Faculty of Science (Boys), Al-Azhar University, Nasr City, Cairo, Egypt.
J Appl Microbiol. 2018 Oct;125(4):1076-1093. doi: 10.1111/jam.14023. Epub 2018 Jul 24.
The aim of this study was to isolate and identify lipolytic bacteria. Perform a statistical stepwise physicochemical optimization for maximum production of extracellular lipase and its validation in a bioreactor.
Several lipolytic bacteria were isolated from petroleum hydrocarbon-polluted soil. The strain expressing the highest lipase activity (47 U ml ) was genetically identified as Gram-positive Bacillus stratosphericus PSP8 (NCBI GenBank accession no. MH120423). The response surface methodology (RSM)-central composite face centre (CCF) design of experiments was performed based on the preselected levels of the studied parameters obtained from the performed one-factor-at-a-time sequential experiments. A second-order polynomial model was predicted and improved the lipase production by approximately 1·6-fold. Preliminary scaling up of the validated optimized process was carried out in a batch 10-l stirred tank bioreactor, applying the optimum predicted operating conditions; pH 6·98, 34·8°C, 2·2 × 10 cells per ml, 200 rev min , 4·82 g l tributyrine concentration, 1% sucrose and 0·1% yeast extract. This yielded 89 U ml at the late log phase of bacterial growth (48 h). Logistic kinetic model effectively characterized the submerged fermentation process, and the maximum specific growth and lipase production rates were estimated to be 0·338 and 0·164 h respectively.
The mesophilic and neutrophilic B. stratosphericus PSP8 isolated from petroleum hydrocarbon-contaminated soil is a proper source of lipase. The closeness of the predicted response with that of the experimental value and the enhancement of lipase productivity in fermenter scale by approximately 1·9-fold, showed that statistically optimized design can be used in order to improve the lipase production to meet the increasing demand.
The RSM-CCF statistical optimization is useful for optimizing a large number of variables and studying their interactive effects on extracellular lipase production.
本研究旨在分离和鉴定脂肪酶产生菌。通过逐步物理化学优化方法，实现最大产胞外脂肪酶，并在生物反应器中进行验证。
从石油烃污染土壤中分离出数株脂肪酶产生菌。其中，酶活最高（47 U/ml）的菌株经鉴定为革兰氏阳性芽孢杆菌（Bacillus stratosphericus）PSP8（NCBI GenBank 登录号：MH120423）。在单因素试验基础上，根据所选参数水平，采用响应面法（RSM）-中心复合面中心（CCF）设计实验。建立的二次多项式模型可使脂肪酶产量提高约 1.6 倍。在批式 10 升搅拌槽生物反应器中对验证后的优化工艺进行初步放大，采用最佳预测操作条件：pH 6.98、34.8°C、2.2×10 个细胞/ml、200 转/分、4.82 g/l 丁酸丁酯浓度、1%蔗糖和 0.1%酵母提取物。在细菌生长对数末期（48 h）可获得 89 U/ml 的酶活。对数生长阶段的发酵过程可通过 logistic 动力学模型有效描述，最大比生长速率和脂肪酶比生产速率分别估计为 0.338 和 0.164 h。
从石油烃污染土壤中分离得到的中温嗜中性芽孢杆菌 PSP8 是脂肪酶的合适来源。预测值与实验值的接近以及发酵罐中脂肪酶产量提高约 1.9 倍，表明统计优化设计可用于提高脂肪酶产量以满足日益增长的需求。
RSM-CCF 统计优化方法可用于优化大量变量，并研究它们对胞外脂肪酶生产的交互影响。
