Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters.

Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters.
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DOI:
10.1093/bib/bbx146
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发表时间:
2019-07-19
影响因子:
9.5
通讯作者:
Weber T
Weber T
中科院分区:
生物学2区
文献类型:
--
作者:
Blin K;Kim HU;Medema MH;Weber T

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许多药物是从微生物和植物产生的小分子中提取的,即所谓的天然产物。天然产物具有不同的化学结构,但产生这些化合物的生物合成途径通常被组织为生物合成基因簇(BGC),并遵循高度保守的生物合成逻辑。这允许使用基于所涉及的酶/基因的序列相似性的基因组挖掘策略来鉴定核心生物合成酶。然而,对各种BGC的挖掘很快接近复杂程度,手动分析不再可能,需要使用自动化基因组挖掘管道,如antiSMASH软件。在这篇综述中,我们讨论了antiSMASH和其他工具预测的基本原理,并为其应用提供了实用的建议。此外,我们还讨论了重要的警告,如基于规则的BGC检测,序列和注释质量和聚类边界预测,这些都必须考虑,同时规划,执行和分析基因组挖掘研究的结果。
Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies.
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