Dynamic regulation of secondary metabolites and agarwood aroma compounds in Aquilaria sinensis by the endophytic fungus NSZJ-CX-22 revealed through metabolomics and GC–MS

Background: species, is prized for its distinctive fragrance and medicinal properties. However, natural agarwood formation is slow, and the quality of artificially induced agarwood remains unstable. While endophytic fungi can stimulate resin accumulation by activating metabolic pathways, the temporal dynamics of metabolite synthesis, the mechanisms of pathway convergence, and the quantitative relationships between precursor consumption and aromatic compound production remain poorly understood, limiting the development of standardized bioinduction systems. Methods: sawdust medium and inoculated the high-efficiency agarwood-inducing endophytic fungus NSZJ-CX-22 to construct a controllable model system. We systematically evaluated the dynamic variation patterns of metabolite profiles at four culture time points (7th, 14th, 21st, and 28th days post-inoculation) using widely targeted metabolomics (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS). We applied multivariate statistical approaches, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), to decipher the metabolic dynamics. Additionally, we performed KEGG enrichment analysis to identify key metabolic pathways. Results: We identified 14,784 metabolites, including 118 agarwood-characteristic sesquiterpene skeletons and 2-(2-phenylethyl)chromones (PECs). Three core biosynthetic pathways-flavonoid, phenylpropanoid, and terpenoid-converge through shared precursors (acetyl-CoA and malonyl-CoA) and branch-point enzymes (CHS, TPS, PKS), orchestrated by jasmonic acid (JA)-like signals. The metabolic trajectory exhibited a triphasic pattern: nutrient mobilization (0-7d), biosynthetic burst with peak sesquiterpene/chromone accumulation at day 14, and defensive restructuring (21-28d) with P450-mediated modifications. Quantitative correlation analysis revealed significant negative relationships (|r| ≈ 0.63-0.74, FDR<0.05) between precursor depletion and agarwood compound synthesis. Volatile profiling identified 116 compounds, with aromatic compounds (42) and sesquiterpenes (5) as key odorants, accumulating in stage-specific patterns aligned with precursor flux redirection. Conclusion: This study establishes a "precursor pool-pathway convergence-temporal programming" framework for fungal agarwood biogenesis. The integrated multi-omics approach quantitatively links substrate consumption to product synthesis. It provides actionable guidance for optimized bioproduction: segmented harvesting (sesquiterpenes at 7-14d, chromones avoiding the day-21 energy trough), JA-signal priming in the early phase, and P450-enhancement strategies in the late phase for structural diversification. These findings advance mechanistic understanding and enable scalable, quality-controlled agarwood biomanufacturing.