Background
Macrolactins, a type of macrolide antibiotic, are toxic to the producer strains. As such, its level is usually maintained below the lethal concentration during the fermentation process. To improve the production of macrolactins, we applied adaptive laboratory evolution technology to engineer a saline-resistant mutant strain. The hypothesis that strains with saline resistance show improved macrolactins production was investigated.
Results
Using saline stress as a selective pressure, we engineered a mutant strain with saline resistance coupled with enhanced macrolactins production within 60 days using a self-made device. As compared with the parental strain, the evolved strain produced macrolactins with 11.93% improvement in non-saline stress fermentation medium containing 50 g/L glucose, when the glucose concentration increased to 70 g/L, the evolved strain produced macrolactins with 71.04% improvement. RNA sequencing and metabolomics results revealed that amino acid metabolism was involved in the production of macrolactins in the evolved strain. Furthermore, genome sequencing of the evolved strain revealed a candidate mutation, hisDD41Y, that was causal for the improved MLNs production, it was 3.42 times higher than the control in the overexpression hisDD41Y strain. Results revealed that saline resistance protected the producer strain from feedback inhibition of end-product (macrolide antibiotic), resulting in enhanced MLNs production.
Conclusions
In the present work, we successfully engineered a mutant strain with enhanced macrolactins production by adaptive laboratory evolution using saline stress as a selective pressure. Based on physiological, transcriptomic and genetic analysis, amino acid metabolism was found to benefit macrolactins production improvement. Our strategy might be applicable to improve the production of other kinds of macrolide antibiotics and other toxic compounds. The identification of the hisD mutation will allow for the deduction of metabolic engineering strategies in future research.