Chennupati Subhakar, Potumarthi Ravichandra, Gopal Rao M, Manga P Lakshmi, Sridevi M, Jetty Annapurna
Bioengineering and Environmental Centre, Indian Institute of Chemical Technology (CSIR), Tarnaka, Hyderabad 500607, India.
Appl Biochem Biotechnol. 2009 Nov;159(2):317-29. doi: 10.1007/s12010-009-8547-6. Epub 2009 Feb 4.
Response surface methodology was employed to optimize culture medium for production of lipase with Rhodotorula sp. MTCC 8737. In the first step, a Plackett-Burman design was used to evaluate the effects of different inducers qualitatively. Of all the seven inducers tested, soybean oil showed significant influence on the lipase production. Further, response surface studies were conducted to quantitatively optimize by considering linear, interactive, and quadratic effects of test variables. A novel approach was proposed to optimize the lipase production system by optimizing the responses in terms of yield kinetics rather than optimizing the direct responses like lipase titer and biomass growth. The coefficient of determination (R(2)) calculated for Y (P/S) (0.769), Y (P/X) (0.799), and Y (X/S) (0.847) indicated that the statistical model could explain 76.9%, 79.99%, and 84.7% of variability in the response.
采用响应面法优化红酵母MTCC 8737产脂肪酶的培养基。第一步,采用Plackett-Burman设计定性评估不同诱导剂的影响。在所有测试的7种诱导剂中,大豆油对脂肪酶的产生有显著影响。此外,通过考虑测试变量的线性、交互和二次效应进行响应面研究以进行定量优化。提出了一种新方法,通过优化产率动力学方面的响应而不是像脂肪酶效价和生物量生长等直接响应来优化脂肪酶生产系统。针对Y(P/S)(0.769)、Y(P/X)(0.799)和Y(X/S)(0.847)计算的决定系数(R²)表明,统计模型可以解释响应中76.9%、79.99%和84.7%的变异性。