Improvement of FK506 production via metabolic engineering-guided combinational strategies in Streptomyces tsukubaensis

MICROBIAL CELL FACTORIES(2021)

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摘要
Background FK506, a macrolide mainly with immunosuppressive activity, can be produced by various Streptomyces strains. However, one of the major challenges in the fermentation of FK506 is its insufficient production, resulting in high fermentation costs and environmental burdens. Herein, we tried to improve its production via metabolic engineering-guided combinational strategies in Streptomyces tsukubaensis . Results First, basing on the genome sequencing and analysis, putative competitive pathways were deleted. A better parental strain L19-2 with increased FK506 production from 140.3 to 170.3 mg/L and a cleaner metabolic background was constructed. Subsequently, the FK506 biosynthetic gene cluster was refactored by in-situ promoter-substitution strategy basing on the regulatory circuits. This strategy enhanced transcription levels of the entire FK506 biosynthetic gene cluster in a fine-tuning manner and dramatically increased the FK506 production to 410.3 mg/mL, 1.41-fold higher than the parental strain L19-2 (170.3 mg/L). Finally, the FK506 production was further increased from 410.3 to 603 mg/L in shake-flask culture by adding L-isoleucine at a final concentration of 6 g/L. Moreover, the potential of FK506 production capacity was also evaluated in a 15-L fermenter, resulting in the FK506 production of 830.3 mg/L. Conclusion From the aspects of competitive pathways, refactoring of the FK506 biosynthetic gene cluster and nutrients-addition, a strategy for hyper-production and potentially industrial application of FK506 was developed and a hyper-production strain L19-9 was constructed. The strategy presented here can be generally applicable to other Streptomyces for improvement of FK506 production and streamline hyper-production of other valuable secondary metabolites.
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关键词
Streptomyces tsukubaensis, FK506, Hyper-production, Metabolic engineering, Biosynthetic gene cluster refactoring, Regulatory circuits
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