Abstract
Streptomycetes represent an important reservoir of active secondary metabolites with potential applications in the pharmaceutical industry. The gene clusters responsible for their production are often cryptic under laboratory growth conditions. Characterization of these clusters is therefore essential for the discovery of new microbial pharmaceutical drugs. Here, we report the identification of the previously uncharacterized nybomycin gene cluster from the marine actinomycete Streptomyces albus subsp. chlorinus through its heterologous expression. Nybomycin has previously been reported to act against quinolone-resistant Staphylococcus aureus strains harboring a mutated gyrA gene but not against those with intact gyrA. The nybomycin-resistant mutants generated from quinolone-resistant mutants have been reported to be caused by a back-mutation in the gyrA gene that restores susceptibility to quinolones. On the basis of gene function assignment from bioinformatics analysis, we suggest a model for nybomycin biosynthesis.
Highlights
Actinobacteria represent a prominent source of natural products with potential industrial applications
We report the identification yields and enable characterization of the previously elucidation andnybomycin biological activity studies.from the marine strain Streptomyces albus subsp. chlorinus uncharacterized gene cluster this study, we report the identification and in characterization the Del14
In the course of systematic activation of cryptic secondary metabolite clusters from Streptomyces
Summary
Actinobacteria represent a prominent source of natural products with potential industrial applications. Dozens of various secondary metabolite clusters are encoded in their genomes. These clusters are often poorly expressed under standard cultivation conditions or even remain silent, preventing the isolation and characterization of the encoded compounds. Such uncharacterized clusters with unknown biosynthetic products are usually regarded as cryptic. Characterization of the cryptic gene clusters encoding natural products often relies on expression of their biosynthetic pathways in the optimized surrogate strains called heterologous hosts or chassis strains. The heterologous expression approach has a number of advantages compared to other cluster characterization methods
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