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A roadmap for natural product discovery based on large-scale genomics and metabolomics

机译:基于大规模基因组学和代谢组学的天然产物发现路线图

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Actinobacteria encode a wealth of natural product biosynthetic gene clusters, whose systematic study is complicated by numerous repetitive motifs. By combining several metrics, we developed a method for the global classification of these gene clusters into families (GCFs) and analyzed the biosynthetic capacity of Actinobacteria in 830 genome sequences, including 344 obtained for this project. The GCF network, comprising 11,422 gene clusters grouped into 4,122 GCFs, was validated in hundreds of strains by correlating confident mass spectrometric detection of known small molecules with the presence or absence of their established biosynthetic gene clusters. The method also linked previously unassigned GCFs to known natural products, an approach that will enable de novo, bioassay-free discovery of new natural products using large data sets. Extrapolation from the 830-genome data set reveals that Actinobacteria encode hundreds of thousands of future drug leads, and the strong correlation between phylogeny and GCFs frames a roadmap to efficiently access them.
机译:放线菌编码大量天然产物生物合成基因簇,其系统研究因众多重复基序而复杂化。通过结合多种指标,我们开发了一种将这些基因簇全局分类为家族(GCF)的方法,并分析了放线菌在830个基因组序列中的生物合成能力,其中包括本项目获得的344个。通过将已知小分子的可信质谱检测与已建立的生物合成基因簇的存在或不存在相关联,在数百个菌株中验证了GCF网络,该网络包括分为4122个GCF的11422个基因簇。该方法还将以前未分配的GCF与已知的天然产物相关联,该方法将能够使用大数据集从头进行无生物测定的新天然产物发现。根据830个基因组数据集的推断,放线菌编码成千上万的未来药物前导,系统发育与GCF之间的紧密相关性为有效利用它们奠定了路线图。

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