Statistical Optimization of the Content Composition Precursors Using Response Surface Methodology to Enhance Agaricoglyceride A Production from the Shaggy Ink Cap Medicinal Mushroom, Coprinus comatus (Higher Basidiomycetes) Mycelia

Abstract

Coprinus comatus, a novel cultivated edible mushroom, has a various of pharmacological effects due to its many active components. In this study, agaricoglycerides, a new class of fungal secondary metabolites that have strong activity against neurolysin, were isolated from C. comatus mycelia. Simultaneously, a 3-level Box-Behnken factorial design was used, combined with response surface methodology, to optimize the precursor composition of agaricoglycerides for the production of agaricoglyceride A. The model estimated that a maximal yield of agaricoglyceride A (20.105 mg/L) could be obtained when the concentrations of 4-hydroxybenzoic acid, glycerol, and methanol (MeOH) were set at 75 mg/L, 0.75 mL/L, and 0.75 mL/L, respectively. The verified experiments showed that the model was significantly consistent with the model prediction. These results showed that appropriately adding the precursors could increase the production of agaricoglyceride A.

Optimization of Fermentation Condition for Echinacoside Yield Improvement with Penicillium sp. H1, an Endophytic Fungus Isolated from Ligustrum lucidum Ait Using Response Surface Methodology

“…The predicted response Y for ECH production in terms of coded factors is expressed as follow: Y = 36.98 − 1.76 X 1 − 0.46 X 2 + 1.54 X 3 − 0.42 X 1 X 2 − 1.99 X 1 X 3 + 0.50 X 2 X 3 − 9.62 X 1 2 − 10.13 X 2 2 − 8.17 X 3 2 where Y is the response variable of ECH, and X 1 , X 2 and X 3 are independent variable in coded units. The regression model was statistically detected in the shape of an F -test, and ANOVA, which was utilized to evaluate the significance and adequacy of the model ( Table 2 ) [ 38 ].…”