Preprint Article Version 1 This version is not peer-reviewed

Insights into the Diversity of Secondary Metabolites of Planktothrix Using a Biphasic Approach Combining Global Genomics and Metabolomics

Version 1 : Received: 29 June 2019 / Approved: 30 June 2019 / Online: 30 June 2019 (10:42:22 CEST)

A peer-reviewed article of this Preprint also exists.

Kim Tiam, S.; Gugger, M.; Demay, J.; Le Manach, S.; Duval, C.; Bernard, C.; Marie, B. Insights into the Diversity of Secondary Metabolites of Planktothrix Using a Biphasic Approach Combining Global Genomics and Metabolomics. Toxins 2019, 11, 498. Kim Tiam, S.; Gugger, M.; Demay, J.; Le Manach, S.; Duval, C.; Bernard, C.; Marie, B. Insights into the Diversity of Secondary Metabolites of Planktothrix Using a Biphasic Approach Combining Global Genomics and Metabolomics. Toxins 2019, 11, 498.

Journal reference: Toxins 2019, 11, 498
DOI: 10.3390/toxins11090498

Abstract

Cyanobacteria are an ancient lineage of slow-growing photosynthetic bacteria and a prolific source of natural products with diverse chemical structures and potent biological activities and toxicities. The chemical identification of these compounds remains a major bottleneck. Strategies that can prioritize the most prolific strains and novel compounds are of great interest. Here, we combine chemical analysis and genomics to investigate the chemodiversity of secondary metabolites based on their pattern of distribution within some cyanobacteria. Planktothrix being a cyanobacterial genus known to form blooms worldwide and to produce a broad spectrum of toxins and other bioactive compounds, we applied this combined approach on four closely related strains of Planktothrix. The chemical diversity of the metabolites produced by the four strains was evaluated using an untargeted metabolomics strategy with high-resolution LC-MS. Metabolite profiles were correlated with the potential of metabolite production identified by genomics for the different strains. Although, the Planktothrix strains present a global similarity in term biosynthetic cluster gene for microcystin, aeruginosin and prenylagaramide for example, we found remarkable strain-specific chemo-diversity. Only few of the chemical features were common to the four studied strains. Additionally, the MS/MS data were analyzed using Global Natural Products Social Molecular Networking (GNPS) to identify molecular families of the same biosynthetic origin. In conclusion, we present an efficient integrative strategy for elucidating the chemical diversity of a given genus and link the data obtained from analytical chemistry to biosynthetic genes of cyanobacteria.

Subject Areas

cyanobacteria; secondary metabolite; genome mining; molecular networking

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