Improved flavonoid content in mulberry leaves by solid-state fermentation: Metabolic profile, activity, and mechanism

Abstract

This study was aimed at investigating the mechanisms of release and transformation of total flavonoids (TFs) from mulberry leaves (MLs) by solid-state fermentation (SSF) via Aspergillus cristatus. An intelligent model based on a back-propagation artificial neural network (BP–ANN) was established to predict the TFs in fungi co-fermented MLs. After prediction and experimental validation, the TFs released by SSF (72.55 mg rutin equivalents/g dry weight) were significantly higher than that of unfermented (24.42 mg rutin equivalents/g dry weight). In addition, the biotransformation mechanism of flavonoids during SSF was proposed by analyzing the untargeted metabolome, including the flavonoid and phenylpropanoid biosynthetic pathways. Pearson's correlation coefficient analysis indicated that the 29 up-regulated catabolites (especially loureirin D and arachidoside) after SSF contributed to increased ABTS (2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) radical scavenging activities and α-glucosidase inhibitory activities. Furthermore, structural characteristics (by scanning electron microscopy, thermogravimetric analysis, and FTIR spectroscopy) and analyses of dynamic changes in carbohydrate-hydrolyzing enzymes revealed that the destruction of hemicellulose was essential to releasing TFs by SFF. Industrial relevanceIn this study, a back-propagation artificial neural network (BP–ANN) was successfully used to establish a co-fermentation with Aspergillus cristatus for releasing and transforming flavonoids of mulberry leaves (MLs) through solid-state fermentation (SSF). The present study has immeasurable importance toward making maximum use of MLs. Moreover, the findings of this study also provide new insights into understanding the release and biotransformation mechanism of flavonoids from MLs by SSF.