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Enhanced synthesis of S?adenosyl?L?methionine through combinatorial metabolic engineering and Bayesian optimization in Saccharomyces cerevisiae

Graphical Abstract and Lay SummaryIn order to effectively improve the SAM titer using Saccharomyces cerevisiae as a chassis cell, a method that include four metabolic strategies, which are enhancing SAM synthesis, enhancing ATP supply, disrupting SAM's further metabolism and downregulating SAM's competing pathway was established. Then, an algorism called Bayesian optimization was employed to optimize the culture medium, and its effect on SAM titer was verified.AbstractS?Adenosyl?L?methionine (SAM) is a substrate for many enzyme?catalyzed reactions and provides methyl groups in numerous biological methylations, and thus has vast applications in the agriculture and medical field. Saccharomyces cerevisiae has been engineered as a platform with significant potential for producing SAM, but the current production has room for improvement. Thus, a method that consists of a series of metabolic engineering strategies was established in this study. These strategies included enhancing SAM synthesis, increasing ATP supply, down?regulating SAM metabolism, and down?regulating competing pathway. After combinatorial metabolic engineering, Bayesian optimization was conducted on the obtained strain C262P6S to optimize the fermentation medium. A final yield of 2972.8 mg·L?1 at 36 h with 29.7% of the L?Met conversion rate in the shake flask was achieved, which was 26.3 times higher than that of its parent strain and the highest reported production in the shake flask to date. This paper establishes a feasible foundation for the construction of SAM?producing strains using metabolic engineering strategies and demonstrates the effectiveness of Bayesian optimization in optimizing fermentation medium to enhance the generation of SAM.

Publication date: 13/03/2024



This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.