Multi-Omics Characterization of Temporal Microbial and Metabolic Dynamics During Solid-State Fermentation of Mulberry Branch Residue

Abstract

The microbial fermentation of mulberry branch residues offers a potential strategy for sustainable lignocellulosic biomass valorization. This study integrated 16S rRNA gene sequencing and untargeted LC–MS metabolomics to characterize temporal microbial and metabolic changes during a 12-day solid-state fermentation at 35 °C using a defined consortium of lactic acid bacteria, Bacillus subtilis, and Saccharomyces cerevisiae. Microbial community analysis revealed distinct temporal succession, with Bacillus accounting for 19.5% of the bacterial community during early fermentation, followed by increasingly diverse assemblages. Exploratory machine learning analysis ranked Azotobacter and Kyrpidia among the genera contributing most strongly to temporal differentiation. FAPROTAX-based predictions indicated that chemoheterotrophy-related functions remained prevalent across fermentation stages, although these predictions do not represent direct functional activity. Untargeted metabolomics detected 2782 putatively annotated features, dominated by lipids (15.1%), organic acids (13.8%), and phenylpropanoids (13.2%). Correlation analysis identified temporal associations between bacterial genera and metabolite classes, including associations of Geobacillus with alkaloids and glycerophospholipids. Exploratory OPLS-DA further highlighted pseudouridine and 3-methylxanthine as discriminatory features across fermentation stages. These findings provide a descriptive multi-omics overview of microbial succession and metabolic variation during mulberry branch residue fermentation.