MetaboLights

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QI software (version 3.0, Waters Corp., Milford, MA, United States) was used to process the data, encompassing import, peak extraction, and deconvolution. Compound identification involved screening the TCM Pro 2.0 reference database (Beijing Hexin Technology Co., Ltd.) alongside a theoretical database constructed from literature and public data. Reliable identification was established based on retention time and mass errors, daughter ion matching degrees, isotope distribution, and peak area.Identified metabolites were annotated using the following databases:• KEGG Pathway Database (https://www.genome.jp/kegg/pathway.html)• HMDB (Human Metabolome Database) (https://hmdb.ca/metabolites)• LIPID MAPS Lipidomics Gateway (http://www.lipidmaps.org/)MetaboLightsPublicLiquid Chromatography MS - negative - reverse-phaseLiquid Chromatography MS - positive - reverse-phaseSeparation was performed on a Hypersil Gold C18 column (Thermo Fisher Scientific; 100 × 2.1 mm, 1.9 μm) maintained at 40°C. The mobile phase consisted of A: 0.1% formic acid in water and B: methanol, delivered at a flow rate of 0.2 mL/min. The gradient program was: 0–1.5 min (98% A, 2% B), 1.5–3 min (98 15% A), 3–10 min (15 0% A), 10–10.1 min (0 98% A), 10.1–12 min (98% A). Injections of 5 μL were made using an autosampler cooled to 4°C. Following each run, the column was reset for 2 min at initial conditions to ensure system stabilization prior to subsequent analyses.Synergistic modulation of the gutmicrobiome-liver-hostmetabolome axis associates withthe therapeutic efficacy ofDanlou tablet against metabolicsyndrome.Henan University of Chinese MedicineMinghe Yaoserummass spectrometry assay1. Sample Preparation: 100 μL of serum was aliquoted into a sterile microcentrifuge tube. 400 μL of ice-cold 80% methanol/water solution (v/v) was added.2. Protein Precipitation: Samples were vortexed thoroughly for homogenization. Incubated on ice for 5 min. Centrifuged at 15,000 × g for 20 min at 4°C.3. Dilution for LC-MS Compatibility: A measured volume of supernatant was transferred to a new tube. Diluted with mass spectrometry-grade water to achieve 53% methanol content. Example: For 100 μL supernatant, add 41.5 μL water (final methanol conc. = 53%)4. Final Clarification: The diluted mixture was centrifuged again at 15,000 × g for 20 min at 4°C. The clarified supernatant was collected for LC-MS injection.Mus musculushttps://www.ebi.ac.uk/metabolights/MTBLS14750Lingling Li. Henan University of Chinese Medicine. openleeling@163.com.Minghe Yao. Henan University of Chinese Medicine. yaominghe@hactcm.edu.cn.Raw data files were converted to the mzXML format using ProteoWizard (version 3.0.8789). Peak extraction and quantification were performed using XCMS. Peaks were aligned across samples based on retention time, mass-to-charge ratio (m/z), and other parameters. Peak area correction was applied using the first sample as the reference to enhance quantification accuracy. Metabolite identification was conducted by comparing data against high-quality MS/MS spectral databases with a mass tolerance of 10 ppm and consideration of adduct ions. Background ions were removed using blank samples, and raw quantification results were normalized to obtain relative peak areas using the formula: (original quantification value of a sample) ÷ [(sum of metabolite quantification values for the sample) ÷ (sum of metabolite quantification values for the first sample)].Groupyaominghe@hactcm.edu.cn1. Sample Source• Species: Male C57BL/6N mice (6 weeks old)• Groups: Control (Con): Standard chow diet (25% protein, 60% carbohydrate, 15% fat) + sterile water gavage High-Fat Diet (HFD): HFD (20% protein, 20% carbohydrate, 60% fat) + sterile water gavage Intervention Groups: Metformin (MET): HFD + metformin (100 mg/kg/day) Low-Dose Danlou Tablet (DLT-L): HFD + DLT (680 mg/kg/day) High-Dose Danlou Tablet (DLT-H): HFD + DLT (1,360 mg/kg/day)• Sample Size: n = 10 per group2. Collection Time Point• Serum samples were collected at the endpoint of the 22-week intervention period.• Mice were fasted prior to blood collection (fasting duration not specified; refer to lab SOP if applicable).3. Processing Protocol1. Blood Collection: Whole blood was drawn via appropriate methods (e.g., cardiac puncture or retro-orbital bleeding under anesthesia). Detailed procedures are described in Supplementary Methods S3.2. Clotting & Centrifugation: Blood samples were kept at 4°C for 30 minutes to allow clotting.3. Serum Isolation: Centrifuged at 3,000 rpm for 10 minutes at 4°C to separate serum.4. Aliquoting: Supernatant (serum) was transferred to sterile tubes and immediately snap-frozen.4. Storage Conditions• Serum aliquots were stored at -80°C until analysis.• No freeze-thaw cycles were permitted prior to metabolomic profiling.MetabolomicsMetabolomicsMus musculusSerum Samplesuntargeted analysisThermo Scientific Vanquish UHPLC Systemgut microbiomegut-liver axisDanlou tablettranscriptomicsThermo Scientific Q Exactive HFseruminsulin resistanceobesityMetabolomicsMus musculusSerum Samplesuntargeted analysisThermo Scientific Vanquish UHPLC Systemgut microbiomegut-liver axisDanlou tablettranscriptomicsThermo Scientific Q Exactive HFseruminsulin resistanceobesityScan Range: m/z 100–1500• ESI Ionization Settings: Spray Voltage: 3.5 kV (positive/negative polarity switching) Sheath Gas Flow Rate: 35 psi Auxiliary Gas Flow Rate: 10 L/min Capillary Temperature: 320 °C S-lens RF Level: 60 Aux Gas Heater Temperature: 350 °C Scan Polarity: Positive and negative modes• MS/MS Acquisition: Data-dependent scanning (DDA) triggered based on precursor ion intensity.falseSynergistic modulation of the gutmicrobiome-liver-hostmetabolome axis associates withthe therapeutic efficacy ofDanlou tablet against metabolicsyndromeBackground: Obesity drives chronic diseases such as cardiovascular disease anddiabetes. Danlou tablet (DLT), a traditional Chinese medicine formula, is used totreat coronary heart disease by regulating lipid metabolism, suggesting potentialfor addressing obesity-related metabolic dysfunction. However, its role in obesityand insulin resistance remains unexplored. Objectives: We investigated the efficacy and mechanisms of DLT against high-fatdiet (HFD)-induced obesity and insulin resistance. Methods: C57BL/6N mice were fed an HFD for 22 weeks and treated with DLT. Acomprehensive phenotypic assessment was conducted, including body weight,glucose tolerance, insulin sensitivity, serum biochemistry, and histopathologyof key tissues. To elucidate the therapeutic mechanism, we integrated 16S rRNAgene sequencing of gut microbiota, serum metabolomics (UPLC-Q-TOF- MS),and hepatic transcriptomics. Results: DLT treatment counteracted HFD-induced metabolic dysfunction,reducing body weight, adiposity, dyslipidemia, and insulin resistance, while ame-liorating hepatic steatosis, inflammation, and oxidative stress. At the microbiallevel, DLT restored gut microbial diversity, corrected the Firmicutes/Bacteroidotaratio, and modulated key genera. Metabolomics linked these changes to restoredfatty acid B-oxidation. In the liver, transcriptomics showed that DLT reversed HFDinduced gene expression, suppressed inflammatory pathways and enhancedfatty acid oxidation and xenobiotic metabolism. Integrated multi-omics analy-sis revealed a strong correlative relationship that DLT's therapeutic benefits areassociated with the modulation of the gut-liver axis, where remodeling of thegut microbiome is closely linked to the reprogramming of hepatic metabolicpathways. Conclusion: DLT counteracts HFD-induced obesity and insulin resistance via amulti-level regulatory mechanism that is closely associated with the modulationof the gut-liver axis, which involves suppressing pathogenic gut microbes, restor-ing fatty acid metabolism, and enhancing hepatic lipid catabolism and antioxidantdefense. This comprehensive preclinical evidence supports the clinical translationof DLT as a novel therapeutic option for obesity and type 2 diabetes mellitus.2026-06-122026-06-12MTBLS14750