An Integrated Metabolomic and Genomic Mining Workflow To Uncover the Biosynthetic Potential of Bacteria

• DOI: 10.1128/msystems.00028-15
• Publication Date: 2016-05-04T02:34:42Z
• Authors: Maria Maansson; Nikolaj G. Vynne; Andreas Klitgaard; Jane L. Nybo; Jette Melchiorsen; Don D. Nguyen; Laura M. Sanchez; Nadine Ziemert; Pieter C. Dorrestein; Mikael R. Andersen; Lone Gram
• Keywords: Comparative Genomics

Microorganisms are a rich source of bioactives; however, chemical identification is major bottleneck. Strategies that can prioritize the most prolific microbial strains and novel compounds great interest. Here, we present an integrated approach to evaluate biosynthetic richness in bacteria mine associated diversity. Thirteen closely related Pseudoalteromonas luteoviolacea isolated from all over Earth were analyzed using untargeted metabolomics strategy, metabolomic profiles correlated with whole-genome sequences strains. We found considerable diversity: only 2% features 7% genes common strains, while 30% 24% unique single The list was reduced 50 discriminating genetic algorithm support vector machines. Features dereplicated by tandem mass spectrometry (MS/MS) networking identify molecular families same origin, pathways probed comparative genomics. Most antibacterial compounds, including thiomarinols reported P. here for first time. By genomics, identified cluster responsible production antibiotic indolmycin, which could not be predicted standard methods. In conclusion, efficient, integrative strategy elucidating given set link chemistry genes. IMPORTANCE combine analysis genomics probe new bioactive secondary metabolites based on their pattern distribution within bacterial species. demonstrate usefulness this combined group marine Gram-negative luteoviolacea, species known produce broad spectrum chemicals. allowed us antibiotics pathways. Combining genetics efficient "mining" workflow identifying diverse pharmaceutical candidates range microorganisms therefore use bioprospecting.