GNPS is an open-access community-curated analysis platform for sharing natural product mass spectrometry data that enables continuous, automatic reanalysis of deposited 'living' data sets. The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu ), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

The human skin is an organ with a surface area of 1.5–2 m² that provides our interface with the environment. The molecular composition of this organ is derived from host cells, microbiota, and external molecules. The chemical makeup of the skin surface is largely undefined. Here we advance the technologies needed to explore the topographical distribution of skin molecules, using 3D mapping of mass spectrometry data and microbial 16S rRNA amplicon sequences. Our 3D maps reveal that the molecular composition of skin has diverse distributions and that the composition is defined not only by skin cells and microbes but also by our daily routines, including the application of hygiene products. The technological development of these maps lays a foundation for studying the spatial relationships of human skin with hygiene, the microbiota, and environment, with potential for developing predictive models of skin phenotypes tailored to individual health. Significance The paper describes the implementation of an approach to study the chemical makeup of human skin surface and correlate it to the microbes that live in the skin. We provide the translation of molecular information in high-spatial resolution 3D to understand the body distribution of skin molecules and bacteria. In addition, we use integrative analysis to interpret, at a molecular level, the large scale of data obtained from human skin samples. Correlations between molecules and microbes can be obtained to further gain insights into the chemical milieu in which these different microbial communities live.

Pfaffia glomerata contains high levels of β-ecdysone, which has shown a range of beneficial pharmacological effects. The present study demonstrated that inflorescences of P. glomerata contain other important bioactive compounds in addition to β-ecdysone. The identification of compounds from inflorescences using liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) was performed for the first time. The eight compounds identified were β-ecdysone, flavonoid glycosides such as quercetin-3-O-glucoside, kaempferol-3-O-glucoside and kaempferol-3-O-(6-p-coumaroyl)-glucoside, oleanane-type triterpenoid saponins such as ginsenoside Ro and chikusetsusaponin IV, in addition to oleanonic acid and gluconic acid. This study provided information on the phytochemicals contained in P. glomerata inflorescences revealing the potential application of this plant part as raw material for the phytotherapeutic and cosmetic industries.

Summary: Biosurfactant‐producing bacteria were isolated from samples collected in areas contaminated with crude oil. The isolates were screened for biosurfactant production using qualitative drop‐collapse test, oil‐spreading and emulsification assays, and measurement of their tensoactive properties. Five isolates tested positive for in the screening experiments and displayed decrease in the surface tension below 30 mN m ⁻¹ . The biosurfactants produced by these isolates were further investigated and their molecular identification revealed that they are bacteria related to the Bacillus genus. Additionally, the biosurfactants produced were chemically characterized via UHPLC ‐ HRMS experiments, indicating the production of surfactin homologues, including a new class of these molecules.

Phakopsora pachyrhizi is a biotrophic fungus, causer of the disease Asian Soybean Rust, a severe crop disease of soybean and one that demands greater investment from producers. Thus, research efforts to control this disease are still needed. We investigated the expression of metabolites in soybean plants presenting a resistant genotype inoculated with P. pachyrhizi through the untargeted metabolomics approach. The analysis was performed in control and inoculated plants with P. pachyrhizi using UHPLC-MS/MS. Principal component analysis (PCA) and the partial least squares discriminant analysis (PLS-DA), was applied to the data analysis. PCA and PLS-DA resulted in a clear separation and classification of groups between control and inoculated plants. The metabolites were putative classified and identified using the Global Natural Products Social Molecular Networking platform in flavonoids, isoflavonoids, lipids, fatty acyls, terpenes, and carboxylic acids. Flavonoids and isoflavonoids were up-regulation, while terpenes were down-regulated in response to the soybean–P. pachyrhizi interaction. Our data provide insights into the potential role of some metabolites as flavonoids and isoflavonoids in the plant resistance to ASR. This information could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen.