Functional characterization of HMG_9 and C2H2.07 as positive regulators of ganoderic acid biosynthesis in Ganoderma lucidum
摘要
Ganoderic acids (GAs) are high-value lanostane-type triterpenoids produced by Ganoderma lucidum (G. lucidum) and are responsible for its diverse pharmacological activities. Previous studies have elucidated key enzymatic steps of the mevalonate pathway leading to lanosterol formation. However, the transcriptional regulatory mechanisms controlling the extensive downstream oxidation and modification reactions required for GA biosynthesis remain poorly understood.
ResultsIn this study, two transcription factors, GlHMG_9 and GlC2H2.07, were systematically identified and functionally characterized as positive regulators of GA biosynthesis. Overexpression of either transcription factor significantly increased total triterpenoid content, whereas RNAi-mediated silencing resulted in pronounced reductions in total triterpenoids and multiple individual GAs at both mycelial and primordia stages. LC–MS analysis revealed marked decreases in representative GAs upon gene silencing. Subcellular localization confirmed nuclear localization of both proteins. Transcriptome profiling demonstrated that GlHMG_9 and GlC2H2.07 coordinately regulate genes involved in the mevalonate pathway and downstream lanosterol-derived modification steps, including cytochrome P450–mediated oxidation. Notably, GlC2H2.07 influenced a broader spectrum of biosynthesis-related genes than GlHMG_9, as evidenced by a greater number of differentially expressed genes (266 vs. 157, respectively).
ConclusionsThese findings establish GlHMG_9 and GlC2H2.07 as key transcriptional regulators controlling GA biosynthesis in G. lucidum. This study provides mechanistic insights into transcription factor–mediated metabolic regulation and identifies promising regulatory targets for transcription factor–guided strain optimization, thereby providing foundational knowledge for the future development of high-yield G. lucidum cell factories through further optimization and validation.