Open AccessUnlocking Cryptic Metabolites with Mass Spectrometry-Guided Transposon Mutant Selection
Author(s) -
Aya Yoshimura,
Brett C. Covington,
Étienne Gallant,
Chen Zhang,
Anran Li,
Mohammad R. Seyedsayamdost
Publication year - 2020
Publication title -
acs chemical biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.899
H-Index - 111
eISSN - 1554-8937
pISSN - 1554-8929
DOI - 10.1021/acschembio.0c00558
Subject(s) - mutant , transposable element , biology , mutagenesis , transposon mutagenesis , computational biology , metabolomics , genetics , metabolite , selection (genetic algorithm) , gene , biochemistry , bioinformatics , artificial intelligence , computer science
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 Burkholderia species. Applications of the methodologies reported can expand our understanding of the products and regulation of cryptic BGCs across phylogenetically diverse bacteria.