Insight into endophytic microbiota-driven geographical and bioactive signatures toward a novel quality assessment model for Codonopsis Radix

Codonopsis Radix, a medicinal and dietary herb in traditional Chinese medicine, largely owes its pharmacological efficacy to both intrinsic phytochemistry and symbiotic interactions with plant-associated microbes. Here, we deciphered the geo-environmental regulation of Codonopsis Radix's endophytic microbiota across four major production regions using 16S rRNA/ITS sequencing and bioactive compound profiling. Results demonstrated that the planting environment significantly shaped the endophytic community of Codonopsis Radix, where Bifidobacteriaceae and Muribaculaceae exhibited the strongest correlations with its bioactive components. Monolobus and Bradyrhizobium not only exhibit distinct associations with Lobetyolin and Atractylenolide III respectively, but also demonstrate significant correlations with the key biosynthetic pathways of these compounds. Leveraging machine learning, we developed the first microbiota-driven quality assessment model, achieving 100.0% and 85.7% prediction accuracies for Lobetyolin and Atractylenolide III respectively, using Random Forest algorithms. This dual-metric framework-integrating microbial signatures with chemical profiles-establishes a novel paradigm for Codonopsis Radix quality control, bridging ecological insights with precision agriculture. Our findings illuminate the microbiota's role as a biosynthetic orchestrator in geoherbalism, offering actionable strategies for sustainable cultivation and standardized production of Codonopsis Radix.