Heavy metal-contaminated soil metabolomics dataset

This dataset contains untargeted metabolomics data of Cd-Pb co-contaminated soil under the synergistic remediation system of "Astragalus residue biochar (ARBC)-Enterobacter mori XJ10-king grass (Pennisetum purpureum × Pennisetum glaucum)", aiming to reveal the response mechanisms of soil metabolites to heavy metal remediation and functional metabolic pathways. The study set up five treatment groups (3 biological replicates per group): ① CK-1: uncontaminated original soil + king grass; ② CK-2: Cd-Pb co-contaminated soil + king grass; ③ T1: contaminated soil + king grass + Enterobacter mori XJ10; ④ T2: contaminated soil + king grass + brown sugar-modified ARBC; ⑤ T3: contaminated soil + king grass + ARBC-loaded Enterobacter mori XJ10. After a 90-day remediation period, rhizosphere soil samples were collected and subjected to metabolomic analysis using reverse-phase high-performance liquid chromatography-tandem mass spectrometry (RP-LC-MS) in both positive and negative ion modes.The data were acquired using a Thermo Scientific UltiMate 3000 chromatographic system (equipped with an Agilent ZORBAX Eclipse Plus C18 column, 2.1×100 mm, 1.8 μm) coupled with a Thermo Scientific Q Exactive mass spectrometer, with a scan range of 50-1200 m/z, an ESI ion source, and an Orbitrap mass analyzer. The dataset includes: ① raw mass spectrometry data (mzML format, including positive and negative ion modes); ② preprocessed peak table data (containing metabolite retention time, m/z value, and peak intensity); ③ metabolite annotation results (linked to HMDB, ChEBI, and NIST spectral libraries, including MS/MS matching information); ④ sample metadata (including soil pH, organic matter content, total and bioavailable Cd/Pb concentrations, enzyme activities, and other physicochemical parameters).The dataset was preprocessed via median normalization and Log2 transformation, resulting in the identification of 927 metabolites in positive ion mode and 449 metabolites in negative ion mode. Core functional metabolites include metal-chelating compounds (flavonoids, organic acids), nutrient cycling-related substances (amino acids, vitamins), and detoxification-related metabolites. This data can directly support the following research: ① screening and functional verification of differential metabolites during the remediation of Cd-Pb co-contaminated soil; ② regulatory mechanisms of soil metabolic pathways mediated by biochar-microbe synergy; ③ correlation analysis between soil metabolome, physicochemical properties, and microbial communities. The data have been organized in accordance with MetaboLights standards and complement the transcriptomic and metagenomic data in the associated research, providing comprehensive data support for the development of synergistic remediation technologies and metabolic mechanism studies of heavy metal-contaminated soil.