Reference: Yin MQ, et al. (2024) Metabolic engineering for compartmentalized biosynthesis of the valuable compounds in Saccharomyces cerevisiae. Microbiol Res 286:127815

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Abstract


Saccharomyces cerevisiae is commonly used as a microbial cell factory to produce high-value compounds or bulk chemicals due to its genetic operability and suitable intracellular physiological environment. The current biosynthesis pathway for targeted products is primarily rewired in the cytosolic compartment. However, the related precursors, enzymes, and cofactors are frequently distributed in various subcellular compartments, which may limit targeted compounds biosynthesis. To overcome above mentioned limitations, the biosynthesis pathways are localized in different subcellular organelles for product biosynthesis. Subcellular compartmentalization in the production of targeted compounds offers several advantages, mainly relieving competition for precursors from side pathways, improving biosynthesis efficiency in confined spaces, and alleviating the cytotoxicity of certain hydrophobic products. In recent years, subcellular compartmentalization in targeted compound biosynthesis has received extensive attention and has met satisfactory expectations. In this review, we summarize the recent advances in the compartmentalized biosynthesis of the valuable compounds in S. cerevisiae, including terpenoids, sterols, alkaloids, organic acids, and fatty alcohols, etc. Additionally, we describe the characteristics and suitability of different organelles for specific compounds, based on the optimization of pathway reconstruction, cofactor supplementation, and the synthesis of key precursors (metabolites). Finally, we discuss the current challenges and strategies in the field of compartmentalized biosynthesis through subcellular engineering, which will facilitate the production of the complex valuable compounds and offer potential solutions to improve product specificity and productivity in industrial processes.

Reference Type
Journal Article | Review
Authors
Yin MQ, Xu K, Luan T, Kang XL, Yang XY, Li HX, Hou YH, Zhao JZ, Bao XM
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