Microbiome–metabolome interaction reveals rhizosphere ecological, bioactive, and antioxidant responses of Paeonia lactiflora Pall. to intercropping and harvest timing

Abstract

Paeonia lactiflora Pall. (P. lactiflora) is a medicinal plant with considerable economic value. During its growth, root secondary metabolism and rhizosphere microbes interact closely; however, no systematic study has examined microbiome and metabolome dynamics under different planting systems and harvest times. To address this, we employed amplicon sequencing for microbial diversity and untargeted metabolomics for metabolite profiling. The datasets were then integrated, and correlation analysis was performed. We measured paeoniflorin by high-performance liquid chromatography (HPLC), total phenolic content by the Folin–Ciocalteu method, total flavonoid content by the NaNO2−Al(NO3)3 method, and antioxidant activity by DPPH, ABTS, hydroxyl radical scavenging, and FRAP assays. The results revealed that Proteobacteria was the most abundant phylum in the bacterial community, and among classified genera, Subgroup_2 exhibited the highest relative abundance. In the fungal community, Ascomycota dominated at the phylum level, while Coniosporium was the most abundant genus. Metabolomic analysis revealed clear separation among sample groups by principal component analysis. Four pairwise comparisons identified differential metabolites predominantly classified as lipids, phenylpropanoids, and polyketides. Functional enrichment analysis indicated that these differences were mainly associated with metabolic pathways, particularly amino acid metabolism, secondary metabolite biosynthesis, and ABC transporters. Furthermore, monoculture with late-stage harvest (CS-4) represented the optimal strategy for maximizing medicinal quality. Under intercropping, mid-stage harvest (TZ-2/TZ-3), with adjustments based on annual climatic conditions, is recommended to balance quality and ecological benefits. Collectively, these findings reveal differences in P. lactiflora across planting systems and harvest periods, providing a theoretical basis for the optimization of cultivation strategies.