A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies. Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases. This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods. Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogs, a challenge for many other dereplication strategies. To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of marine and terrestrial microbial samples, illustrating the dereplication of 58 molecules including analogs.

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The composition of the skin microbiota varies widely among individuals when sampled at the same body site. A key question is which molecular factors determine strain-level variability within sub-ecosystems of the skin microbiota. Here, we used a genomics-guided approach to identify an antibacterial biosynthetic gene cluster in Cutibacterium acnes (formerly Propionibacterium acnes), a human skin commensal bacterium that is widely distributed across individuals and skin sites. Experimental characterization of this biosynthetic gene cluster resulted in identification of a new thiopeptide antibiotic, cutimycin. Analysis of individual human skin hair follicles revealed that cutimycin contributed to the ecology of the skin hair follicle microbiota and helped to reduce colonization of skin hair follicles by Staphylococcus species.

Despite recognition of the looming antibiotic crisis by healthcare professionals, the number of new antibiotics reaching the clinic continues to decline sharply. This study aimed to establish an antibiotic profiling strategy using a panel of clinically relevant bacterial strains to create unique biological fingerprints for all major classes of antibiotics. Antibiotic mode of action profile (BioMAP) screening has been shown to effectively cluster antibiotics by structural class based on these fingerprints. Using this approach, we have accurately predicted the presence of known antibiotics in natural product extracts and have discovered a naphthoquinone-based antibiotic from our marine natural product library that possesses a unique carbon skeleton. We have demonstrated that bioactivity fingerprinting is a successful strategy for profiling antibiotic lead compounds and that BioMAP can be applied to the discovery of new natural product antibiotics leads.

Most (75%) of the anti-infectives that save countless lives and enormously improve quality of life originate from microbes found in nature. Herein, we described a global visualization of the detectable molecules produced from a single microorganism, which we define as the ‘molecular network’ of that organism, followed by studies to characterize the cellular effects of antibacterial molecules. We demonstrate that Streptomyces roseosporus produces at least four non-ribosomal peptide synthetase-derived molecular families and their gene subnetworks (daptomycin, arylomycin, napsamycin and stenothricin) were identified with different modes of action. A number of previously unreported analogs involving truncation, glycosylation, hydrolysis and biosynthetic intermediates and/or shunt products were also captured and visualized by creation of a map through MS/MS networking. The diversity of antibacterial compounds produced by S. roseosporus highlights the importance of developing new approaches to characterize the molecular capacity of an organism in a more global manner. This allows one to more deeply interrogate the biosynthetic capacities of microorganisms with the goal to streamline the discovery pipeline for biotechnological applications in agriculture and medicine. This is a contribution to a special issue to honor Chris Walsh’s amazing career.