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Article Abstract
Liquid fermentation is the primary method for GA production using. However, production capacity is limited due to unknown metabolic pathways. To address this, we constructed a genome-scale metabolic model (CY1235) with 1753 reactions, 1979 metabolites, and 1235 genes to understand the GA regulation mechanisms. The model was validated by analyzing growth rates under different glucose uptake rates and identifying essential genes. We used the model to optimize fermentation conditions, including carbon sources and dissolved oxygen. Through the OptForce algorithm, we identified 20 reactions as targets. Overexpressing FFUJ_02053 and FFUJ_14337 resulted in a 37.5 and 75% increase in GA3 titers, respectively. These targets enhance carbon flux toward GA production. Our model holds promise for guiding the metabolic engineering of to achieve targeted overproduction. In summary, our study utilizes the CY1235 model to understand GA regulation, optimize fermentation conditions, and identify specific targets for enhancing GA production through metabolic engineering.
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