Oxygen supply and oxygen uptate rate (OUR) significantly influences both the physiological state of cells and nemadectin biosynthesis by Streptomyces cyaneogriseus ssp. noncyanogenus. In this study, a real-time monitoring approach for nemadectin fermentation was developed for the first time by an on-line OUR control strategy. The effect of OUR levels during the mycelium differentiation phase on nemadectin biosynthesis was studied and optimized by adjusting feeding rates of (NH4)2SO4. Results showed that controlling the OUR at approximately 17.5 mmol·L-1·h-1 during the mycelium differentiation phase effectively enhanced nemadectin production, reaching 2805.1 μg/mL, making 129.5% increase compared to the control. This OUR control strategy was successfully scaled-up to a 500 L pilot scale, achieving the highest ever nemadectin production of 2867.3 μg/mL. These findings demonstrate that this OUR control strategy provides an effective and scalable approach for industrial nemadectin production.

The ‘design-build-test-learn’ (DBTL) cycle has been adopted in rational high-throughput screening for obtaining high-yield industrial strains. However, the mismatch between build and test slows the DBTL cycle due to the lack of high-throughput analytical technologies. In this study, a highly-efficient, accurate, and non-invasive detection method of gentamicin (GM) was developed, which can provide timely feedback for the high-throughput screening of high-yield strains. Firstly, a self-made tool was established to obtain datasets in 24-well ​based on the coloring of cells. Subsequently, the random forest (RF) algorithm was found to have the highest prediction accuracy with 98.5% for the training and 91.3% for verification. Finally, a stable genetic high-yield strain (998U/mL) was successfully screened out in 3005 mutants, which was verified to improve the titer by 72.7% in a 5 L bioreactor. Moreover, the verified new datasets were updated to the model database in order to improve learning ability of DBTL cycle.