Abstract
Ganoderma lucidum (GL), a traditional Chinese medicinal fungus, is rich in triterpenoids and phenols with antioxidant properties. Nevertheless, current extraction techniques limit the efficient utilization of bioactive components from GL. This study aims to optimize the extraction process of triterpenoids and phenols, enhance their antioxidant activities, and assess their neuroprotective activities against oxidative damage. Here, we used response surface methodology (RSM) coupled with artificial neural network-genetic algorithm (ANN-GA) modeling to optimize ultrasound-assisted extraction (UAE) parameters for simultaneous extraction of triterpenoids and phenols. Following extraction, the microstructures of the GL powder were examined using scanning electron microscopy (SEM). UPLC-Q-TOF MS/MS was utilized to qualitatively analyze triterpenoid and phenolic compositions of GL extracts. We then investigated the neuroprotective effects of these extracts using an H(2)O(2)-induced oxidative stress model in PC12 cells. We found that the optimized extraction conditions were 320 W ultrasonic power, 74 % ethanol, 61 mL/g liquid-solid ratio, and 69 min duration. Yields of the extracts per gram of GL were: TTC 4.61 ± 0.08 mg, TPC 4.53 ± 0.09 mg, DPPH scavenging 93.96 ± 4.62 %, and 1.225 ± 0.008 mM Fe(2+), with SEM confirming the effectiveness of UAE. UPLC-Q-TOF MS/MS analysis identified 20 triterpenoids (9 newly reported) and 8 phenols (7 newly reported). These extracts safeguarded PC12 cells from H(2)O(2)-induced oxidative injury by restoring cell morphology, enhancing cell viability, reducing LDH release, intracellular calcium, ROS and MDA, and increasing antioxidant enzyme activities. These findings support the use of GL extracts in functional foods and pharmaceuticals.