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宏基因组文库中隐藏土壤酶的恢复和功能验证。

Recovery and functional validation of hidden soil enzymes in metagenomic libraries.

机构信息

Molecular Biotechnology Research Group, Corporación CorpoGen, Bogotá, Colombia.

Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Friedrich-Schiller Universität, Jena, Germany.

出版信息

Microbiologyopen. 2019 Apr;8(4):e00572. doi: 10.1002/mbo3.572. Epub 2019 Mar 9.

Abstract

The vast microbial diversity on the planet represents an invaluable source for identifying novel activities with potential industrial and therapeutic application. In this regard, metagenomics has emerged as a group of strategies that have significantly facilitated the analysis of DNA from multiple environments and has expanded the limits of known microbial diversity. However, the functional characterization of enzymes, metabolites, and products encoded by diverse microbial genomes is limited by the inefficient heterologous expression of foreign genes. We have implemented a pipeline that combines NGS and Sanger sequencing as a way to identify fosmids within metagenomic libraries. This strategy facilitated the identification of putative proteins, subcloning of targeted genes and preliminary characterization of selected proteins. Overall, the in silico approach followed by the experimental validation allowed us to efficiently recover the activity of previously hidden enzymes derived from agricultural soil samples. Therefore, the methodology workflow described herein can be applied to recover activities encoded by environmental DNA from multiple sources.

摘要

地球上丰富的微生物多样性代表了一个宝贵的资源库,可用于鉴定具有潜在工业和治疗应用价值的新活性物质。在这方面,宏基因组学已经成为一组策略,这些策略极大地促进了对来自多种环境的 DNA 的分析,并扩展了已知微生物多样性的界限。然而,不同微生物基因组编码的酶、代谢物和产物的功能表征受到异源基因表达效率低下的限制。我们实施了一个结合 NGS 和 Sanger 测序的策略,用于识别宏基因组文库中的 fosmid。该策略有助于鉴定可能的蛋白质、目标基因的亚克隆和选定蛋白质的初步特征。总的来说,通过计算机方法进行的初步预测,然后进行实验验证,使我们能够有效地从农业土壤样本中恢复以前隐藏的酶的活性。因此,本文所述的方法学工作流程可用于从多种来源恢复环境 DNA 编码的活性。

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