Enhanced synthesis of S-adenosyl-L-methionine through Combinatorial
metabolic engineering and Bayesian optimization in Saccharomyces
cerevisiae
Abstract
S-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, although the
current production has room for improvement. Thus, a method that
consists of a series of metabolic engineering strategies was established
this study. These strategies included enhancing SAM synthesis,
increasing ATP supply, and down-regulating SAM metabolism and
downregulating competing pathway. After combinatorial metabolic
engineering, Bayesian optimization was conducted on the obtained strain
C262P6 to optimize the fermentation medium. A final yield of 2972.8 mg/L
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.