A metabolomics guided exploration of marine natural product chemical space

Abstract

Introduction Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Objective Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. Method In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to Result This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Conclusion Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

Mass Spectrometry Based Molecular 3D-Cartography of Plant Metabolites

“…Matches to library data are present all along this distribution ( Figure 3C ), providing evidence that the untargeted metabolomics equally sampled a wide range of compounds and that these were represented within the library. Molecular networking performs especially well in identifying uniquely expressed metabolites in a survey (Floros et al, 2016; Nguyen et al, 2016). It is clear that in our molecular network ( Figure 3A ), with background spectra removed, are multiple molecular families (connected network components) which are either unique to or dominated by samples from specific tissue types.…”

Metabolomics‐based chemotaxonomy of root endophytic fungi for natural products discovery

“…This step, however, only provided an overall direct and indirect (‘level‐two’) dereplication of 307 metabolites, representing a total of 3.8% of those in a spectral family. This annotation rate is similar to those achieved in studies from bacterial and human sources (Floros et al ., ; Quinn et al ., ), which achieved annotations for 2.5%–3.5% of all metabolites using the same workflow, and it did not increase noticeably when using high resolution MS/MS spectra, indicating that the precision of measurements is not a major factor affecting identifications. Altogether, the relatively low annotation rate highlights an insufficient coverage of fungal chemistries in GNPS libraries rather than an actual lack of knowledge on fungal natural products.…”

“…The GNPS‐based dereplication of chemical space reduced by 10‐fold the number of detected MS/MS spectra to be examined (from 172 708 to 17 809), and the number was further reduced when considering only metabolites assigned to a spectral family (7951), as done elsewhere (Floros et al ., ; Crüsemann et al ., ). GNPS also automatically annotated compounds via comparisons against reference libraries of natural products.…”

Omics-based natural product discovery and the lexicon of genome mining

“…While these methods have proven useful, it’s also possible that many BGCs are active yet their small molecule products are simply missed due to the extraction methods or analytical techniques employed (Figure 1). For example, recent metabolomics analyses have shown that extraction solvents had a major impact on the metabolites detected[59,60]. As we learn more about the relationships between orphan BGCs and their products, it is likely that much of the apparent biosynthetic potential observed in microbial genomes will ultimately be linked to compounds that are in fact produced but simply missed or ignored because they do not possess the properties that allow them to be detected or make them attractive targets for discovery.…”