In our next public ATeam group presentation, Shipei Xing from Pieter Dorrestein lab at UC San Diego will present on how one can annotate metabolites in imaging MS beyond molecular formula. This is a ...

Nature Protocols - In this reverse metabolomics protocol, a tandem mass spectrometry spectrum is used as a search term to probe public metabolomic data. Analysis of the metadata connected with...

Rapid advances in mass spectrometry (MS) data analysis have accelerated the identification of natural products from complex mixtures such as natural product extracts. However, limitations in MS data in metabolite libraries and dereplication strategies are still lacking for assigning structures to known compounds and searching for unidentified compounds. To overcome these limitations, we present an approach that combines molecular networking with MS database-derived mass defect analysis to preferentially discover new compounds with high structural novelty in the initial stage of a discovery workflow. Specifically, unknown metabolites or clusters generated from molecular networking are assigned to a compound class based on their relative mass defects (RMDs) calculated using open-source databases. If ancillary data such as ultraviolet and MS/MS spectra of the unknown clusters are incongruent with the RMD-assigned compound class, metabolites are considered to have a new skeleton that exhibits a large difference in RMD value due to structural changes. Here, we applied this RMD-assisted method to a desert-derived bacterial strain library and validated it through the discovery of brasiliencin A (1), a new 18-membered macrolide from Nocardia brasiliensis. A putative biosynthetic pathway of brasiliencin A was proposed through whole-genome sequence analysis, and an additional 29 analogs were detected using absolute mass defect filtering (AMDF) based on plausible biosynthetic products. This led to the isolation of three additional macrolides, brasiliencins B–D (2–4). The structures of the brasiliencins (1–4) were fully elucidated through spectroscopic data analysis and quantum chemical calculations including ROE distance and 13C NMR chemical shift calculations, and experimental and theoretical electronic circular dichroism (ECD). Brasiliencin A showed strong activity against Mycobacterium smegmatis and Streptococcus australis (MIC = 31.3 nM and 7.81 μM, respectively) compared to brasiliencin B (MIC = 1000 nM and 62.5 μM, respectively) that differs at a single stereocenter.

PFAS are a wide class of ubiquitous chemically persistent environmental pollutants. Here the authors combine nontarget screening with a two-layer network approach to identify large numbers of PFAS fro...

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based...