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Discovery of (hemi-) cellulase genes in a metagenomic library from a biogas digester using 454 pyrosequencing
Authors:Xing Yan  Alei Geng  Jun Zhang  Yongjun Wei  Lei Zhang  Changli Qian  Qianfu Wang  Shengyue Wang  Zhihua Zhou
Institution:1. Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Fenglin Rd 300, Shanghai, 200032, China
2. Biofuels institute, School of the Environment, Jiangsu University, Zhenjiang, 212013, Jiangsu, China
3. The College of Life Sciences, Northwest University, Xi’an, 710069, China
4. Chinese National Human Genome Center at Shanghai, Shanghai, 201203, China
Abstract:In this study, 341, 246, and 386 positive clones with endo-β-1,4-glucanase, β-glucosidase, and endo-β-1,4-xylanase activities, respectively, were identified by screening from a metagenomic fosmid library constructed from a biogas digester. Subsequently, pools of 4, 10, and 16 positive clones were subjected to 454 pyrosequencing in different subruns. In total, 21 unique glycosyl hydrolase (GH) genes were predicted by bioinformatic analysis, which showed similarities to their nearest neighbors from 39 % to 72 %. In addition to bioinformatics prediction, nine GH genes were expressed and purified to identify their activity with four kinds of substrates. The activities of the most expressed proteins were consistent with their annotation based on bioinformatics prediction; however, three GH genes belonging to the GH5 family showed different activities from their annotation. An efficient acidic cellulase En1 had an optimal condition at 55 °C, pH 5.5, with a specific activity toward carboxymethylcellulose at 118 U/mg and K m at 12.8 g/L. This study demonstrated that there are diverse GHs in the biogas digester system with potential industrial application in lignocellulose hydrolysis, and their activities should be investigated with different substrates before their application. Additionally, pool sequencing of positive fosmid clones might be a cost-effective approach to obtain functional genes from metagenomic libraries.
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