Background: Pamamycins are a family of highly bioactive macrodiolide polyketides produced by Streptomyces alboniger as a complex mixture of derivatives with molecular weights ranging from 579 to 705 Daltons. The large derivatives are produced as a minor fraction, which has prevented their isolation and thus studies of chemical and biological properties.
Results: Herein, we describe the transcriptional engineering of the pamamycin biosynthetic gene cluster (pam BGC), which resulted in the shift in production profile toward high molecular weight derivatives. The pam BGC library was constructed by inserting randomized promoter sequences in front of key biosynthetic operons. The library was expressed in Streptomyces albus strain with improved resistance to pamamycins to overcome sensitivity-related host limitations. Clones with modified pamamycin profiles were selected and the properties of engineered pam BGC were studied in detail. The production level and composition of the mixture of pamamycins was found to depend on balance in expression of the corresponding biosynthetic genes. This approach enabled the isolation of known pamamycins and the discovery of three novel derivatives with molecular weights of 663 Da and higher. One of them, homopamamycin 677A, is the largest described representative of this family of natural products with an elucidated structure. The new pamamycin 663A shows extraordinary activity (IC50 2 nM) against hepatocyte cancer cells as well as strong activity (in the one-digit micromolar range) against a range of Gram-positive pathogenic bacteria.
Conclusion: By employing transcriptional gene cluster refactoring, we not only enhanced the production of known pamamycins but also discovered novel derivatives exhibiting promising biological activities. This approach has the potential for broader application in various biosynthetic gene clusters, creating a sustainable supply and discovery platform for bioactive natural products.
Keywords: Antibiotic; Gene cluster; Strain engineering; Streptomyces; Transcriptional refactoring.
© 2023. The Author(s).