Abstract

Empedopeptins—eight amino acid cyclic lipopeptides—are calcium-dependent antibiotics that act against Gram-positive bacteria such as Staphylococcus aureus by inhibiting cell wall biosynthesis. However, to date, the biosynthetic mechanism of the empedopeptins has not been well identified. Through comparative genomics and metabolomics analysis, we identified empedopeptin and its new analogs from a marine bacterium, Massilia sp. YMA4. We then unveiled the empedopeptin biosynthetic gene cluster. The core nonribosomal peptide gene null-mutant strains (ΔempC, ΔempD, and ΔempE) could not produce empedopeptin, while dioxygenase gene null-mutant strains (ΔempA and ΔempB) produced several unique empedopeptin analogs. However, the antibiotic activity of ΔempA and ΔempB was significantly reduced compared with the wild-type, demonstrating that the hydroxylated amino acid residues of empedopeptin and its analogs are important to their antibiotic activity. Furthermore, we found seven bacterial strains that could produce empedopeptin-like cyclic lipopeptides using a genome mining approach. In summary, this study demonstrated that an integrated omics strategy can facilitate the discovery of potential bioactive metabolites from microbial sources without further isolation and purification.

Highlights

  • The production of secondary metabolites is regulated by several genes that are responsible for modifying their chemical structure, transporting substrates and products, and other specific regulatory functions

  • Knowledge about the potential natural antibiotics related to nonribosomal peptides in the Massilia remains scarce

  • YMA4 effectively inhibited the growth of S. aureus ATCC

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Summary

Introduction

The production of secondary metabolites is regulated by several genes that are responsible for modifying their chemical structure, transporting substrates and products, and other specific regulatory functions. These genes, named secondary metabolite biosynthesis gene clusters (BGCs), are contiguously aligned in the genome [1]. Comparative genomics analysis and BGC mining have been applied to the natural product studies to discover new sources of bioactive natural products [3]. Molecular Networking (GNPS), have been utilized to monitor the production of specific molecules [4]. Molecular networking groups similar molecules as a cluster by comparing vector correlations between tandem mass fragment ions of molecules [5].

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