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基于基因组的聚酮化合物发现的最新进展。

Recent advances in genome-based polyketide discovery.

作者信息

Helfrich Eric J N, Reiter Silke, Piel Jörn

机构信息

Institute of Microbiology, Swiss Federal Institute of Technology Zurich (ETH), Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland.

Institute of Microbiology, Swiss Federal Institute of Technology Zurich (ETH), Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland.

出版信息

Curr Opin Biotechnol. 2014 Oct;29:107-15. doi: 10.1016/j.copbio.2014.03.004. Epub 2014 Apr 22.

Abstract

Polyketides are extraordinarily diverse secondary metabolites of great pharmacological value and with interesting ecological functions. The post-genomics era has led to fundamental changes in natural product research by inverting the workflow of secondary metabolite discovery. As opposed to traditional bioactivity-guided screenings, genome mining is an in silico method to screen and analyze sequenced genomes for natural product biosynthetic gene clusters. Since genes for known compounds can be recognized at the early computational stage, genome mining presents an opportunity for dereplication. This review highlights recent progress in bioinformatics, pathway engineering and chemical analytics to extract the biosynthetic secrets hidden in the genome of both well-known natural product sources as well as previously neglected bacteria.

摘要

聚酮化合物是一类极其多样的次生代谢产物,具有很高的药理价值和有趣的生态功能。后基因组时代通过颠倒次生代谢产物发现的工作流程,给天然产物研究带来了根本性的变化。与传统的生物活性导向筛选相反,基因组挖掘是一种计算机方法,用于筛选和分析已测序基因组中的天然产物生物合成基因簇。由于已知化合物的基因可以在早期计算阶段被识别,基因组挖掘为重复数据去除提供了机会。本文综述了生物信息学、途径工程和化学分析方面的最新进展,以揭示隐藏在著名天然产物来源以及先前被忽视的细菌基因组中的生物合成奥秘。

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