1Key Laboratory of Biomass Chemical Engineering of Ministry of Education & State Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, 310027, China
2Zhejiang Key Laboratory of Intelligent Manufacturing for Functional Chemicals, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310000, China
3State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210093, China
4These two authors contributed equally to this work
| Received 19 Jul 2025 |
Accepted 23 Sep 2025 |
Published 18 Dec 2025 |
Isoflavonoids, such as calycosin-7-glucoside, possess significant pharmaceutical value but are typically sourced from plants, where production is limited by slow growth and complex isolation process. Here, we engineered Saccharomyces cerevisiae for heterologous production of calycosin-7-glucoside. First, via the introduction of isoflavone 4′-O-methyltransferase from Pueraria montana var. lobata (PlOMT9), isoflavone-3′-hydroxylase from Astragalus membranaceus (AmI3′H), and calycosin 7'-O-glucosyltransferase from A. membranaceus (AmUCGT) into our previously constructed daidzein-producing strain, we achieved de novo biosynthesis of calycosin-7-glucoside for the first time. Then, we disrupted the endogenous glucoside hydrolase (EXG1 knockout), enhanced UDP-glucose supply (UGP1 overexpression), and screened a glycosyltransferase (AmUGT88E29 from A. membranaceus) with higher catalytic activity to substantially improve the production of our target compound. Using LC-MS-based metabolomics, we analyzed pathway intermediates and metabolic flux distribution, revealing PlOMT9 as the major bottleneck. Subsequent optimization of PlOMT9 gene copy number further enhanced bioproduction of calycosin-7-glucoside, achieving a final titer of 0.22 mg/L. This study establishes a yeast-based platform for high-value isoflavonoid biosynthesis and provides a foundation for future pathway optimization.
