Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States.
Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, United States.
ACS Chem Biol. 2020 Oct 16;15(10):2766-2774. doi: 10.1021/acschembio.0c00558. Epub 2020 Sep 14.
The products of most secondary metabolite biosynthetic gene clusters (BGCs) have yet to be discovered, in part due to low expression levels in laboratory cultures. Reporter-guided mutant selection (RGMS) has recently been developed for this purpose: a mutant library is generated and screened, using genetic reporters to a chosen BGC, to select transcriptionally active mutants that then enable the characterization of the "cryptic" metabolite. The requirement for genetic reporters limits the approach to a single pathway within genetically tractable microorganisms. Herein, we utilize untargeted metabolomics in conjunction with transposon mutagenesis to provide a global read-out of secondary metabolism across large numbers of mutants. We employ self-organizing map analytics and imaging mass spectrometry to identify and characterize seven cryptic metabolites from mutant libraries of two different species. Applications of the methodologies reported can expand our understanding of the products and regulation of cryptic BGCs across phylogenetically diverse bacteria.
大多数次级代谢产物生物合成基因簇(BGC)的产物尚未被发现,部分原因是它们在实验室培养物中的表达水平较低。为此,最近开发了报告基因指导的突变体选择(RGMS):生成突变体文库,并使用遗传报告基因对选定的 BGC 进行筛选,以选择转录活跃的突变体,然后能够对“隐藏”代谢物进行特征分析。遗传报告基因的需求限制了该方法在遗传上可操作的微生物中单一路径的应用。本文中,我们利用非靶向代谢组学结合转座子诱变,为大量突变体的次级代谢提供了全局读数。我们采用自组织映射分析和成像质谱技术,从两种不同物种的突变体文库中鉴定和表征了七种隐藏代谢物。报告的方法学的应用可以扩展我们对隐藏 BGC 产物和调控的理解,这些 BGC 跨越了系统发育上多样化的细菌。