Abstract
To combat escalating levels of antibiotic resistance, novel strategies are developed to address the everlasting demand for new antibiotics. This study aimed at investigating amicoumacin antibiotics from the desert-derived Bacillus subtilis PJS by using the modern MS/MS-based molecular networking approach. Two new amicoumacins, namely hetiamacin E (1) and hetiamacin F (2), were finally isolated. The planar structures were determined by analysis of extensive NMR spectroscopic and HR–ESI–MS data, and the absolute configurations were concluded by analysis of the CD spectrum. Hetiamacin E (1) showed strong antibacterial activities against methicillin-sensitive and resistant Staphylococcus epidermidis at 2–4 µg/mL, and methicillin-sensitive and resistant Staphylococcus aureus at 8–16 µg/mL. Hetiamacin F (2) exhibited moderate antibacterial activities against Staphylococcus sp. at 32 µg/mL. Both compounds were inhibitors of protein biosynthesis demonstrated by a double fluorescent protein reporter system.
Highlights
With increasing concerns over the continuous development of bacterial resistance to antibiotic drugs, there is an urgent need to develop efficient antibiotics
This concept has been integrated as a central component of the Global Natural Products Social (GNPS) molecular networking platform, where compound class identification is performed against a large, community-acquired reference library of spectra, and novel chemical entities related to known molecules can be efficiently affiliated with characteristic chemical families in clusters, thereby expediting the discovery and characterization process [6]
The UPLC–MS/MS data were performed on the GNPS platform and displayed in Cytoscape
Summary
With increasing concerns over the continuous development of bacterial resistance to antibiotic drugs, there is an urgent need to develop efficient antibiotics. The molecular networking enables the visualization of large datasets and the grouping of fragmented ions into clusters, using an algorithm to compare the similarity of the fragmentation spectra. This concept has been integrated as a central component of the Global Natural Products Social (GNPS) molecular networking platform, where compound class identification is performed against a large, community-acquired reference library of spectra, and novel chemical entities related to known molecules can be efficiently affiliated with characteristic chemical families in clusters, thereby expediting the discovery and characterization process [6]. One successful application was the isolation of new monoterpene indole alkaloids obtained from the bark of Geissospermum leave, guided by a molecular networking-based dereplication strategy using an in-house database of monoterpene indole alkaloids [10]
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