摘要
l -Histidine is an essential amino acid with important applications in pharmaceuticals and nutrition, highlighting the demand for efficient microbial production platforms. This study developed a high-performance Escherichia coli cell factory through systematic metabolic engineering. First, we mined a feedback-resistant hisG∗ smar and the entire mutant his operon from a previously obtained high l -histidine-producing mutant of Serratia marcescens , offering novel enzymatic parts beyond conventional sources. Combined with precursor supply enhancement and redox balancing, the engineered strain yielded 4.46 g/L l -histidine. Second, a machine learning-based platform (TransDW) was utilized to predict and validate a novel efflux transporter, Cgl1374, increasing titer to 4.82 g/L. Third, we implemented a growth phase-dependent system to dynamically regulate pgi expression, redirecting carbon flux and achieving 5.49 g/L in shake flasks. Finally, applying a novel carbon evolution rate (CER)-based control strategy in fed-batch fermentation, the optimized strain achieved 49.8 g/L of l -histidine in a 5-L bioreactor, with a yield of 0.265 g/g glucose, which is the highest yield reported for engineered E. coli . This work establishes a synergistic framework combining non-model gene discovery, computational transport engineering, and real-time physiological feedback control, providing a versatile blueprint for next-generation microbial cell factories.
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