Bandal J N, Tile V A, Sayyed R Z, Jadhav H P, Azelee N I Wan, Danish Subhan, Datta Rahul
Department of Microbiology, K.R.T. Arts, B.H. Commerce, and A.M. Science College, Nashik 422002, Maharashtra, India.
Department of Microbiology, PSGVP Mandal's, Arts, Science & Commerce College, Shahada 425409, Maharashtra, India.
Molecules. 2021 May 11;26(10):2833. doi: 10.3390/molecules26102833.
Amylase (EC 3.2.1.1) enzyme has gained tremendous demand in various industries, including wastewater treatment, bioremediation and nano-biotechnology. This compels the availability of enzyme in greater yields that can be achieved by employing potential amylase-producing cultures and statistical optimization. The use of Plackett-Burman design (PBD) that evaluates various medium components and having two-level factorial designs help to determine the factor and its level to increase the yield of product. In the present work, we are reporting the screening of amylase-producing marine bacterial strain identified as sp. H7 by 16S rRNA. The use of two-stage statistical optimization, i.e., PBD and response surface methodology (RSM), using central composite design (CCD) further improved the production of amylase. A 1.31-fold increase in amylase production was evident using a 5.0 L laboratory-scale bioreactor. Statistical optimization gives the exact idea of variables that influence the production of enzymes, and hence, the statistical approach offers the best way to optimize the bioprocess. The high catalytic efficiency (kcat/Km) of amylase from sp. H7 on soluble starch was estimated to be 13.73 mL/s/mg.
淀粉酶（EC 3.2.1.1）在包括废水处理、生物修复和纳米生物技术在内的各种行业中需求巨大。这就需要通过采用潜在的产淀粉酶培养物和统计优化来实现更高产量的酶。使用Plackett-Burman设计（PBD）评估各种培养基成分并采用二水平析因设计有助于确定提高产品产量的因素及其水平。在本研究中，我们报告了通过16S rRNA鉴定为H7菌株的产淀粉酶海洋细菌菌株的筛选。使用两阶段统计优化，即PBD和响应面方法（RSM），采用中心复合设计（CCD）进一步提高了淀粉酶的产量。使用5.0 L实验室规模的生物反应器，淀粉酶产量明显提高了1.31倍。统计优化给出了影响酶产生的变量的确切概念，因此，统计方法为优化生物过程提供了最佳途径。H7菌株的淀粉酶对可溶性淀粉的高催化效率（kcat/Km）估计为13.73 mL/s/mg。
