Untargeted LC-QToF-MS profiling of the soybean (

Introduction: Compartment-resolved metabolite baselines for legumes grown under field conditions are notably scarce. Most root exudate data are obtained from hydroponic or pot systems using targeted assays. These methods fail to accurately represent the soil-borne and microbially derived chemical environments surrounding roots Methods: We employed untargeted liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QToF-MS) to analyze four compartments of a field-grown soybean system in Hadoti, southeastern Rajasthan, India. These included non-rhizospheric bulk soil (NRBS), rhizospheric soil (RS), surface-sterilized (SRS), and unsterilized (SRU) roots, with three replicates each. We aimed to identify compartment-specific metabolic signatures and potential plant-microbe interaction mediators. As data were obtained at the MS1 level without tandem-MS confirmation, all annotations are putative, in accordance with Metabolomics Standards Initiative Levels 2-3. Results: Principal component analysis distinguished the root compartments, whereas the soil compartments were differentiated along the first component with overlapping confidence regions. Set analyses revealed 43 features exclusive to RS and 120 features exclusive to SRU. Soil chemistry differed markedly between NRBS and RS: available phosphorus, potassium, zinc, and manganese were lower in the rhizosphere, whereas exchangeable aluminium was approximately 15 times higher and was the sole element accumulating in the root zone. Among the ecological features, root colonization correlated with reduced abundance of jasmonic acid features and increased abundance of isoflavonoid features (including daidzein) and microbial siderophores. Although substantial, these differences did not withstand false discovery rate correction and are reported as candidate observations. Discussion: The observed patterns align with established models of nutrient mobilization, symbiotic signalling, and iron competition. However, targeted MS/MS validation and independent quantification are required before drawing mechanistic conclusions. The dataset serves as a hypothesis-generating baseline and provides a prioritized set of candidate features for subsequent targeted investigations of soybean root-microbe chemical interactions.