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.

Potatoes are cultivated in southwest Greenland without the use of pesticides and with limited crop rotation. Despite the fact that plant-pathogenic fungi are present, no severe-disease outbreaks have yet been observed. In this report, we document that a potato soil at Inneruulalik in southern Greenland is suppressive against Rhizoctonia solani Ag3 and uncover the suppressive antifungal mechanism of a highly potent biocontrol bacterium, Pseudomonas fluorescens In5, isolated from the suppressive potato soil. A combination of molecular genetics, genomics, and matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) imaging mass spectrometry (IMS) revealed an antifungal genomic island in P. fluorescens In5 encoding two nonribosomal peptides, nunamycin and nunapeptin, which are key components for the biocontrol activity by strain In5 in vitro and in soil microcosm experiments. Furthermore, complex microbial behaviors were highlighted. Whereas nunamycin was demonstrated to inhibit the mycelial growth of R. solani Ag3, but not that of Pythium aphanidermatum, nunapeptin instead inhibited P. aphanidermatum but not R. solani Ag3. Moreover, the synthesis of nunamycin by P. fluorescens In5 was inhibited in the presence of P. aphanidermatum. Further characterization of the two peptides revealed nunamycin to be a monochlorinated 9-amino-acid cyclic lipopeptide with similarity to members of the syringomycin group, whereas nunapeptin was a 22-amino-acid cyclic lipopeptide with similarity to corpeptin and syringopeptin.

Pseudomonads are cosmopolitan microbes able to produce a wide array of specialized metabolites. These molecules allow Pseudomonas to scavenge nutrients, sense population density, and enhance or inhibit growth of competing microbes. However, these valuable metabolites are typically characterized one-molecule-one-microbe at a time instead of inventoried in large numbers. To index and map the diversity of molecules detected from these organisms, 260 strains of ecologically diverse origins were subjected to mass spectrometry-based molecular networking. Molecular networking not only enables dereplication of molecules, but also sheds light on their structural relationships. Moreover, it accelerates discovery of new molecules. Herein, through indexing the Pseudomonas specialized metabolome, we report the molecular networking-based discovery of four molecules and their evolutionary relationships: a poaeamide analog, and a molecular sub-family of cyclic lipopeptides, the bananamides 1, 2, and 3. Analysis of their biosynthetic gene cluster shows that it constitutes a distinct evolutionary branch of the Pseudomonas cyclic lipopeptides. Through analysis of an additional 370 extracts of wheat-associated Pseudomonas, we demonstrate how the detailed knowledge from our reference index can be efficiently propagated to annotate complex metabolomic data from other studies akin to the way newly generated genomic information can be compared to data from public databases.

While in nucleotide sequencing, the analysis of DNA from complex mixtures of organisms is common, this is not yet true for mass spectrometric data analysis of complex mixtures. The comparative analyses of mass spectrometry data of microbial communities at the molecular level is difficult to perform, especially in the context of a host. The challenge does not lie in generating the mass spectrometry data, rather much of the difficulty falls in the realm of how to derive relevant information from this data. The informatics based techniques to visualize and organize datasets are well established for metagenome sequencing; however, due to the scarcity of informatics strategies in mass spectrometry, it is currently difficult to cross correlate two very different mass spectrometry data sets from microbial communities and their hosts. We highlight that molecular networking can be used as an organizational tool of tandem mass spectrometry data, automated database search for rapid identification of metabolites, and as a workflow to manage and compare mass spectrometry data from complex mixtures of organisms. To demonstrate this platform, we show data analysis from hard corals and a human lung associated with cystic fibrosis.

New fungal metabolites, designated quinadolines A (1) and B (2), were isolated from culture broth of Aspergillus sp. FKI-1746, and their structures were elucidated by NMR spectroscopy. The complete relative and absolute stereochemistry of 2 was determined by X-ray crystallography and amino acid analysis using a chiral column. Quinadolines moderately inhibited lipid droplet synthesis in mouse macrophages.

A fungal strain FKI-2136 identified as genus Aspergillus was found to produce potentiators of imipenem activity against methicillin-resistant Staphylococcus aureus (MRSA). Two new compounds designated stemphones B and C were isolated along with a structurally related known compound cochlioquinone D from the fermentation broth of the producing strain by solvent extraction, silica gel column chromatography and preparative HPLC. These compounds have a common tetracyclic quinone skeleton. Stemphone C potentiated imipenem activity against the MRSA 512 fold by decreasing MIC value of imipenem from 16 mg/ml to 0.03 mg/ml.

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.

Clinically useful antibiotics, β-lactams and vancomycin, are known to inhibit bacterial cell wall peptidoglycan synthesis. Methicillin-resistant Staphylococcus aureus (MRSA) has a unique cell wall structure consisting of peptidoglycan and wall teichoic acid. In recent years, new anti-infectious agents (spirohexaline, tripropeptin C, DMPI, CDFI, cyslabdan, 1835F03, and BPH-652) targeting MRSA cell wall biosynthesis have been discovered using unique screening methods. These agents were found to inhibit important enzymes involved in cell wall biosynthesis such as undecaprenyl pyrophosphate (UPP) synthase, FemA, flippase, or UPP phosphatase. In this review, the discovery, the mechanism of action, and the future of these anti-infectious agents are described.