Integrated microbiome-metabolomics profiling reveals substrate-dependent variation in agricultural Jiaosu from fruit waste.

Agricultural Jiaosu (AJ), a novel biotechnology, is used to stably obtain beneficial microbiome and metabolites from organic waste. It is widely applied in agriculture and environmental remediation and is particularly suitable for the efficient treatment of fruit waste. However, the characteristics and differences in the microbiome and metabolome of AJ prepared from different substrates remain unclear. Herein, the substrate-dependent variations in microbial consortia and metabolomic profiles across six types of AJ prepared from different substrates were revealed through integrated microbiome and metabolomics analyses. Metabolomics analysis identified a total of 3,159 metabolites, and random forest machine learning analysis of differentially expressed metabolites indicated that 50% of the top 20 marker metabolites across the six AJ samples belonged to organoheterocyclic compounds, organic acids and derivatives, shikimates and phenylpropanoids. Microbial analysis revealed that Lactobacillus and Lentilactobacillus constituted the core microbiome in all six AJ, and that mixed fruit waste AJ exhibited the highest microbial diversity. Carbohydrate metabolism genes (19.57% of total metabolic genes) were predominant. Notably, genes encoding enzymes involved in pyruvate, propanoate, and butanoate metabolic pathways exhibited high expression in the mixed fruit waste AJ. Correlation and co-occurrence network analyses revealed robust interconnections among physicochemical properties, differential metabolites, and significant microorganisms within the AJ system. This study demonstrates how substrate selection shapes the functional microbiome and metabolic landscape of AJ through integrated multi-omics analysis, offering mechanistic insights for the engineered production of AJ.