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.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present Feature-Based Molecular Networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. The FBMN method brings quantitative analyses, isomeric resolution, including from ion-mobility spectrometry, into molecular networks.

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Rapid advances in DNA sequencing, metabolomics, proteomics and computational tools are dramatically increasing access to the microbiome and identification of its links with disease. In particular, time-series studies and multiple molecular perspectives are facilitating microbiome-wide association studies, which are analogous to genome-wide association studies. Early findings point to actionable outcomes of microbiome-wide association studies, although their clinical application has yet to be approved. An appreciation of the complexity of interactions among the microbiome and the host's diet, chemistry and health, as well as determining the frequency of observations that are needed to capture and integrate this dynamic interface, is paramount for developing precision diagnostics and therapies that are based on the microbiome.

The microbiota, and the genes that comprise its microbiome, play key roles in human health. Host-microbe interactions affect immunity, metabolism, development, and behavior, and dysbiosis of gut bacteria contributes to disease. Despite advances in correlating changes in the microbiota with various conditions, specific mechanisms of host-microbiota signaling remain largely elusive. We discuss the synthesis of microbial metabolites, their absorption, and potential physiological effects on the host. We propose that the effects of specialized metabolites may explain present knowledge gaps linking the gut microbiota to biological host mechanisms during initial colonization, and in health and disease.

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families known to be produced by the microbiome have a profound impact on the balance between health and disease 1-9. Considering the diversity of the human microbiome, numbering over 40,000 operational taxonomic units 10 , the impact of the microbiome on the chemistry of an entire animal remains underexplored. In this study, mass spectrometry informatics and data visualization approaches 11-13 were used to provide an assessment of the impacts of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free (GF) and specific pathogen Reprints and/or permissions can be provided by R. Quinn or P.C. Dorrestein.

1Molecular networking has become a key method used to visualize and annotate the chemical space in 2 non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and

Lantipeptides are ribosomally synthesized and posttranslationally modified peptides containing thioether cross-links. We describe the preparation of seven different lantipeptides in Escherichia coli and demonstrate that this methodology can be used to incorporate nonproteinogenic amino acids.