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 techniques are well-suited to high-throughput characterization of natural products, 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 m 2 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.human skin | 3D mapping | mass spectrometry | 16S rRNA T he skin provides the interface between our internal molecular processes and the external environment. The stratum corneum (SC), the outer layer of the epidermis, is the most exposed organ of the human body and is composed of molecules derived from our own skin cells, our microbiota, and the environment (1). In addition, it may be possible that personal hygiene products, the clothing we wear, and the food we eat can affect the chemical composition of the skin (2, 3). The chemical environment of the skin is also critical for the development of microbial communities, yet there are no systematic workflows that can be used to correlate skin chemistry and microbes. Human skin microbiome inventories are changing our views of commensal organisms and their roles in establishing and maintaining the immune system and general epithelial health (4-7), but their role in biotransformation of skin molecules is as yet poorly characterized.Understanding the molecular topography of the surface of the SC will provide insights into the chemical environment in which microbes reside on the skin and how in turn they modify this environment. To understand the relationship between the chemical milieu and the microbial communities, we must develop workflows that map the chemistry and microbiology of the human skin and that determine the associations between them. The composition of the human skin microbiota has been correlated with skin anatomy, dividing into moist, dry, and sebaceous microenvironments, and can be influenced by beauty and hygiene products (2-9). Regions such as the face, chest, and back, areas with a high density of sebaceous glands, promote growth of lipophilic microorganisms such as Propionibacterium and Malassezia. In contrast, less exposed regions, such as the groin, axilla, and toe web, which are higher in temperature and moisture content, are colonized by Staphylococcus and Corynebacterium (7, 10, 11). Previous studies have reported mass spectrometry (MS) methods to identify compounds from human skin (12, 13). However, th...

SummaryBiosurfactant‐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.

Asian Soybean Rust (ASR), caused by the biotrophic fungus Phakopsora pachyrhizi, is a devastating disease with an estimated crop yield loss of up to 90%. Yet, there is a nerf of information on the metabolic response of soybean plants to the pathogen Untargeted metabolomics and Global natural products Social Molecular networking platform approach was used to explore soybean metabolome modulation to P. pachyrhizi infection. Soybean plants susceptible to ASR was inoculated with P. pachyrhizi spore suspension and non-inoculated plants were used as controls. Leaves from both groups were collected 14 days post-inoculation and extracted using different extractor solvent mixtures. The extracts were analyzed on an ultra-high performance liquid chromatography system coupled to high-definition electrospray ionization-mass spectrometry. There was a significant production of defense secondary metabolites (phenylpropanoids, terpenoids and flavonoids) when P. pachyrhizi infected soybean plants, such as putatively identified liquiritigenin, coumestrol, formononetin, pisatin, medicarpin, biochanin A, glyoceollidin i, glyoceollidin ii, glyoceollin i, glyoceolidin ii, glyoceolidin III, glyoceolidin IV, glyoceolidin VI. Primary metabolites (amino acids, peptides and lipids) also were putatively identified. This is the first report using untargeted metabolomics and GNPS-Molecular Networking approach to explore ASR in soybean plants. Our data provide insights into the potential role of some metabolites in the plant resistance to ASR, which could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen. The soybean (Glycine max (L.) Merrill) is prominent among crops due to its agro-economic and nutritional value, used mainly as a source of proteins and oils for human consumption, in animal feeds and for biofuel production 1,2. However, estimates indicate a necessity to double global agricultural output by 2050 to feed a rising population, hence soybean productivity needs to be increased by 2.4% per annum 3. Yet, soybean diseases were estimated to reduce crop yield by 11% in the United States 4 and 50% or greater in the southeastern United States 5. The Asian Soybean Rust (ASR) was registered for the first time in Brazil during the 2001/2002 harvest 6. Recently, Brazilian soybean farmers spent US$ 2.16 billion with fungicides during the 2016/2017 harvest, and 96% of the sum was used for ASR control. Another US$ 1.62 billion was invested on insecticides, totaling US$ 3.78 billion. This amount represented 12.4% of the production costs for the harvest 7. Despite increasing costs, disease management practices are needed as yield losses of up to 90% have already been reported when control measures were absent 4 .

Aspergillus flavus is a filamentous fungus found in nature and characterized by the production of bright and colourful colonies. It grows on different substrates, producing secondary metabolites and, if present in foodstuffs, can be a source of health problems for humans and animals, as well as causing economic losses. Traditional methods for fungal identification are based on morphological characteristics, requiring specialists and being very time-consuming. The development of analytical alternatives might have advantages such as greater efficiency, more reproducibility and be less time-consuming. Thus, a qualitative analytical method to detect Aspergillus flavus in food samples, based on the identification of fungal chemical markers by HPLC-MS, was developed. The method comprises methanol extraction followed by HPLC-MS analysis, and was able to identify 14 fungus secondary metabolites, namely aflatoxin B1, aflatoxin G1, aspergillic acid, aspyrone, betaine, chrysogine, deacetyl parasiticolide A, flufuran, gregatin B, hydroxysydonic acid, nicotinic acid, phomaligin A, spinulosin and terrein.

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-pcoumaroyl)-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.

The rumen primary and secondary metabolite content is intimately related to its community of bacteria, protozoa, fungi, archaea and bacteriophages, ingested feed and the host. Despite the myriad of interactions and novel compounds to be discovered, few studies have explored the rumen metabolome. Here, we present the first study using ultra-high performance liquid chromatography tandem mass-spectrometry and Molecular Networking approach, and various extraction methods on the cell-free rumen fluid of a non-lactating Holstein cow. Putative molecules were annotated based on accurate fragmentation matching the Global Natural Products Social Molecular Networking library, public spectral libraries, or annotated manually. The combination of five extraction methods resulted on 1,882 molecular features observed. Liquid-liquid extraction resulted on the highest molecular features abundance, 1,166 (61.96% of total). Sixty-seven compounds were annotated using Global Natural Products Social Molecular Networking library and public libraries, such as hydrocinnamic and azelaic acid, and monensin. Only 3.56% of molecular features (67) observed had positive match with available libraries, which shows the potential of the rumen as reservoir of novel compounds. The use of untargeted metabolomics in this study provided a snapshot of the rumen fluid metabolome. The complexity of the rumen will remain long unknown, but the use of new tools should be encouraged to foster advances on the rumen metabolome.

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.