MetaboLights

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were annotated using the KEGG database (https://www.genome.jp/kegg/pathway.html), the HMDB database (https://hmdb.ca/metabolites), and the LIPIDMaps database (http://www.lipidmaps.org/).MetaboLightsPublicLiquid Chromatography MS - negative - reverse-phaseLiquid Chromatography MS - positive - reverse-phaseChromatographic separation was performed on a Vanquish UHPLC system (Thermo Fisher, Germany) equipped with a Hypesil Gold column (C18, 100 × 2.1 mm, 1.9 μm; Thermo Fisher, USA). The column temperature was maintained at 40 °C, and the flow rate was 0.2 mL/min.For positive ionization mode, mobile phase A was 0.1% formic acid in water and mobile phase B was methanol. For negative ionization mode, mobile phase A was 5 mM ammonium acetate (pH 9.0) and mobile phase B was methanol. The gradient elution program was as follows: 0–1.5 min, 98% A; 1.5–3 min, 98–85% A; 3–10 min, 85–100% B; 10–10.1 min, 100–98% A; 10.1–12 min, 98% A; 12–12.1 min, 98% A (re-equilibration).Integrated microbiome and metabolome profiling reveals rhizosphere responses to chitosan application in tobacco.liu xinyuHubei Universityrhizospheremass spectrometry assayApproximately 100 mg of liquid-nitrogen-ground tissue was placed in an EP tube, and 500 μL of 80% methanol–water was added. The mixture was vortexed, incubated on ice for 5 min, and centrifuged at 15,000 × g for 20 min at 4 °C. An aliquot of the supernatant was diluted with MS-grade water to a final methanol content of 53%. The diluted supernatant was centrifuged again at 15,000 × g for 20 min at 4 °C, and the supernatant was collected for LC–MS analysisNicotiana tabacumhttps://www.ebi.ac.uk/metabolights/MTBLS15706liu xinyu. Hubei University. liuxinyu0904@163.com.Raw data files (.raw) were imported into CD 3.1 software for processing. Parameters including retention time and mass-to-charge ratio (m/z) were initially screened for each metabolite. Peak alignment across different samples was performed with a retention time deviation of 0.2 min and a mass deviation of 5 ppm to improve identification accuracy. Peak extraction was then conducted using a mass deviation of 5 ppm, a signal intensity deviation of 30%, a signal-to-noise ratio of 3, a minimum signal intensity threshold, and adduct ion information. Peak areas were quantified, and target ions were integrated. Molecular formulas were predicted based on molecular ion peaks and fragment ions and compared against the mzCloud (https://www.mzcloud.org/), mzVault, and MassList databases.Treatmentliuxinyu0904@163.comBiological samples were prepared by the customer and transported to the company on dry ice. Upon receipt, all samples were immediately stored at -80 °C until analysis. A pooled quality control (QC) sample was prepared by mixing equal volumes of all experimental samples; this QC sample was used to equilibrate the LC-MS system and to monitor instrument stability throughout the run. A blank sample was also prepared by substituting 53% methanol-water for the experimental sample and was subjected to the same pretreatment procedure as the experimental samples; the blank was used to remove background ions.MetabolomicsMetabolomicsProteoWizard msconvertuntargeted analysisThermo Scientific Q Exactive HF-XThermo Scientific Vanquish Flex UHPLC SystemOpenMSNicotiana tabacumrhizosphereexperimental sampleMetabolomicsProteoWizard msconvertuntargeted analysisThermo Scientific Q Exactive HF-XThermo Scientific Vanquish Flex UHPLC SystemOpenMSNicotiana tabacumexperimental samplerhizosphereMass spectrometric detection was performed on a Q Exactive™ HF-X mass spectrometer (Thermo Fisher, Germany). The scan range was set to m/z 100–1500. The ESI source parameters were as follows: spray voltage, 3.5 kV; sheath gas flow rate, 35 psi; auxiliary gas flow rate, 10 L/min; capillary temperature, 320 °C; S-lens RF level, 60; auxiliary gas heater temperature, 350 °C. Polarity was set to positive and negative. MS/MS secondary scans were acquired in data-dependent scan (DDS) mode.falseIntegrated microbiome and metabolome profiling reveals rhizosphere responses to chitosan application in tobaccoChitosan is widely investigated as a plant biostimulant, but its effects on the rhizosphere microbiome and metabolome under field conditions remain poorly understood. Here, we evaluated the response of the tobacco (Nicotiana tabacum L.) rhizosphere to chitosan root-drench treatment by integrating bacterial 16S rRNA and fungal ITS amplicon sequencing with untargeted LC–MS/MS metabolomics. Chitosan had limited effects on the overall structure of rhizosphere bacterial and fungal communities, as indicated by Bray–Curtis-based community analyses, but was associated with selective changes in specific microbial taxa. Several bacterial biomarkers differed between treatments, while fungal community richness and predicted trophic profiles also showed treatment-associated changes. In contrast to the relatively modest changes in overall microbial community structure, rhizosphere metabolite profiles showed clear treatment-associated differences. Differential metabolites were mainly related to carbon metabolism, amino acid metabolism, phenylpropanoid biosynthesis, vitamin metabolism, alkaloid biosynthesis, and other secondary metabolic pathways. Functional prediction further suggested changes in the metabolic and ecological potential of bacterial and fungal communities following chitosan application. Correlation analysis identified associations between differential metabolites and specific bacterial and fungal taxa, providing candidate links between microbial community composition and rhizosphere chemical variation. Together, our results suggest that chitosan acts primarily as a selective modulator of the rhizosphere microbiome and chemical environment rather than as a broad-spectrum driver of microbial community restructuring. The integrated microbiome–metabolome framework used here provides a basis for understanding how chitosan application may influence plant–soil–microbe interactions under field conditions.2026-09-172026-09-17MTBLS15706