The rapid emergence of multidrug-resistant (MDR) bacterial pathogens poses a major threat for human health. In recent years, genome sequencing has unveiled many poorly expressed antibiotic clusters in actinomycetes. Here, we report a well-defined ecological collection of >800 actinomycetes obtained from sites in the Himalaya and Qinling mountains, and we used these in a concept study to see how efficiently antibiotics can be elicited against MDR pathogens isolated recently from the clinic. Using 40 different growth conditions, 96 actinomycetes were identified – predominantly Streptomyces – that produced antibiotics with efficacy against the MDR clinical isolates referred to as ESKAPE pathogens: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and/or Enterobacter cloacae. Antimicrobial activities that fluctuated strongly with growth conditions were correlated with specific compounds, including borrelidin, resistomycin, carbomethoxy-phenazine, and 6,7,8- and 5,6,8-trimethoxy-3-methylisocoumarin, of which the latter was not described previously. Our work provided insights into the potential of actinomycetes as producers of drugs with efficacy against clinical isolates that have emerged recently and also underlined the importance of targeting a specific pathogen.

Metabolomics is a high throughput analytical technique used to globally measure low molecular weight metabolites, allowing simultaneous metabolic comparison of different biological samples and thus highlighting differentially produced compounds as potential biomarkers. Although microbes are renowned as prolific sources of antibiotics, the traditional approach for new anti-infectives discovery is time-consuming and labor-intensive. In this review, the use of NMR- or MS-based metabolomics is proposed as an efficient approach to find antimicrobials in microbial single- or co-cultures.

Actinomycetes are a major source of antimicrobials, anticancer compounds, and other medically important products, and their genomes harbor extensive biosynthetic potential. Major challenges in the screening of these microorganisms are to activate the expression of cryptic biosynthetic gene clusters and the development of technologies for efficient dereplication of known molecules. Here we report the identification of a previously unidentified isatin-type antibiotic produced by Streptomyces sp. MBT28, following a strategy based on NMR-based metabolomics combined with the introduction of streptomycin resistance in the producer strain. NMR-guided isolation by tracking the target proton signal resulted in the characterization of 7-prenylisatin (1) with antimicrobial activity against Bacillus subtilis. The metabolite-guided genome mining of Streptomyces sp. MBT28 combined with proteomics identified a gene cluster with an indole prenyltransferase that catalyzes the conversion of tryptophan into 7-prenylisatin. This study underlines the applicability of NMR-based metabolomics in facilitating the discovery of novel antibiotics.

Metabolomics is an analytical technique that allows scientists to globally profile low molecular weight metabolites between samples in a medium- or high-throughput environment. Different biological samples are statistically analyzed and correlated to a bioactivity of interest, highlighting differentially produced compounds as potential biomarkers. Here, we review NMR- and MS-based metabolomics as technologies to facilitate the identification of novel antimicrobial natural products from microbial sources. Approaches to elicit the production of poorly expressed (cryptic) molecules are thereby a key to allow statistical analysis of samples to identify bioactive markers, while connection of compounds to their biosynthetic gene cluster is a determining step in elucidating the biosynthetic pathway and allows downstream process optimization and upscaling. The review focuses on approaches built around NMR-based metabolomics, which enables efficient dereplication and guided fractionation of (antimicrobial) compounds.

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