Data-mechanism integrated optimization and preliminary scale-up study of feeding process in penicillin fermentation

Abstract:

With the advancement of online monitoring and automation in industrial fermentation, large volumes of production operation data have been accumulated, while their potential value in fermentation regulation and process optimization has not been fully exploited. This study aims to investigate the key causes of titer variation in industrial-scale penicillin fermentation, thereby guiding the optimization of the feeding process. To this end, industrial historical data was analyzed to elucidate the relationships between key process variables and production performance, and to further investigate and validate their physiological regulatory significance. The production titer at harvest, maximum specific production rate (qP,max), and initiation timing of secondary metabolism were selected as characterization indicators. Curve similarity and correlation analyses were performed for staged screening of the data of 325 production batches from a 156 m³ industrial fermenter. The results indicated that cumulative glucose feeding amount and dilution rate were the key factors contributing to variations in fermentation performance. Further analysis revealed that a high dilution rate during the late fermentation stage maintained a high specific growth rate (μ), thereby limiting the accumulation of penicillin, a typical secondary metabolite. In contrast, low glucose feeding and reduced dilution rates promoted a decline in μ and enhanced production capacity, quantitatively demonstrating, at the industrial scale, the regulatory role of μ in secondary metabolism. On the basis of these findings, a viable cell electrode was introduced into a 50-L fermentation system to enable online biomass monitoring, and physiological metabolic parameters were used to reproduce industrial fermentation states. Subsequently, dynamic regulation of μ during the production phase was achieved by increasing the feed glucose concentration and optimizing the feeding rate to reduce late-stage dilution rate. Laboratory-scale experiments showed that the glucose conversion efficiency, titer, and fermentation index increased by 22.06%, 16.10%, and 16.42%, respectively. Preliminary scale-up results based solely on increasing feed glucose concentration demonstrated a 6.56% increase in titer, a 4%-5% improvement in overall production, and a 2.20% increase in fermentation index. This study developed a data–mechanism integrated strategy for fermentation process optimization, providing a new approach for precise regulation and optimization of large-scale biomanufacturing processes.