Prioritizing natural product diversity in a collection of 146 bacterial strains based on growth and extraction protocols

Crusemann, M, O'Neill EC, Larson CB, Melnik AV, Floros DJ, da Silva RR, Jensen PR, Dorrestein PC, Moore BS.  2017.  Prioritizing natural product diversity in a collection of 146 bacterial strains based on growth and extraction protocols. Journal of Natural Products. 80:588-597.

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actinomycete, biosynthetic gene clusters, cyanobacteria, discovery, mass-spectrometry, molecular networking, osmac method, polyketide synthase, Salinispora, secondary metabolomics


In order to expedite the rapid and efficient discovery and isolation of novel specialized metabolites, while minimizing the waste of resources on rediscovery of known compounds, it is crucial to develop efficient approaches for strain prioritization, rapid dereplication, and the assessment of favored cultivation and extraction conditions. Herein we interrogated bacterial strains by systematically evaluating cultivation and extraction parameters with LC-MS/MS analysis and subsequent dereplication through the Global Natural Product Social Molecular Networking (GNPS) platform. The developed method is fast, requiring minimal time and sample material, and is compatible with high throughput extract analysis, thereby streamlining strain prioritization and evaluation of culturing parameters. With this approach, we analyzed 146 marine Salinispora and Streptomyces strains that were grown and extracted using multiple different protocols. In total, 603 samples were analyzed, generating approximately 1.8 million mass spectra. We constructed a comprehensive molecular network and identified 15 molecular families of diverse natural products and their analogues. The size and breadth of this network shows statistically supported trends in molecular diversity when comparing growth and extraction conditions. The network provides an extensive survey of the biosynthetic capacity of the strain collection and a method to compare strains based on the variety and novelty of their metabolites. This approach allows us to quickly identify patterns in metabolite production that can be linked to taxonomy, culture conditions, and extraction methods, as well as informing the most valuable growth and extraction conditions.