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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14873/m_MTBLS14873_LC-MS_negative_reversed-phase-chromatography_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14873/s_MTBLS14873.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14873/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14873/a_MTBLS14873_LC-MS_negative_reversed-phase-chromatography.txtprimary200OKftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14873MultiQuant 3.0.3 software was used to extract the original MRM data of metabolitesMetaboLightsPublicLiquid Chromatography MS - negative - reversed-phase-chromatographyThe LC/MS platform is based on the Shimadzu Nexera X2 LC-30AD system equipped with an ACQUITY UPLC BEH C18 (1.7um 2.1 X 100mm) and a triple quadruple mass spectrometer (QTRAP 6500+, AB SCIEX). Metabolites were detected in electrospray positive-ionization mode. The 5 μL samples are injected sequentially with LC autosampler. The ACQUITY UPLC BEH C18 (1.7um 2.1 X 100mm) was heated to 40°C under a flow rate of 300 μL/min. Mobile phase: A solution: 0.1% formic acid water, B solution: 0.1% formic acid -70% acetonitrile -30% isopropanol. The sample is placed in a 4℃ automatic sampler, with a column temperature of 40℃, a flow rate of 300 µL/min, and an injection volume of 5 µL. The relevant liquid phase gradient is as follows: 0-1 min, with liquid B maintained at 0%; 1-8 minutes, liquid B changes linearly from 0% to 100%; 8-14 minutes, B solution maintained at 100%; From 14.1 to 16 minutes, liquid B changes linearly from 100% to 0%.targeted metabolomics detemination of SCFA.Xuejiao LiThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technologyfecesmass spectrometry assayInitially, 50 µL of the sample was transferred into a reaction vessel, followed by the addition of 250 µL of Dole reagent (isopropanol: heptane: sulfuric acid, 40:10:1, v/v/v). The mixture was thoroughly vortexed to ensure complete homogenization and then allowed to stand at room temperature for 10 minutes. Subsequently, 100 µL of heptane and 150 µL of water were added to the mixture, which was vortexed again to ensure thorough mixing. The mixture was then centrifuged at 20,000 × g for 15 minutes at 20 °C. The upper organic phase (100 µL) was carefully extracted and dried under a gentle stream of nitrogen.After complete drying, 200 µL of 2 M oxalyl chloride (dissolved in dichloromethane) was added to the dried residue. The mixture was incubated at 65 °C for 5 minutes to allow the derivatization reaction to proceed. Following incubation, the mixture was dried under nitrogen. Subsequently, 150 µL of 3-pyridylmethylamine solution (3-pyridylmethylamine: acetonitrile, 1:99, v/v) was added to the dried sample to form the 3-pyridylmethylamine derivative. The mixture was incubated at room temperature for 5 minutes and then dried under nitrogen.For mass spectrometry analysis, the dried derivative was reconstituted in 1 mL of methanol. The solution was vortexed for 10 minutes at room temperature to ensure complete dissolution. The reconstituted sample was then centrifuged at 15,000 × g for 15 minutes at 20 °C to remove any particulate matter. A 10 µL aliquot of the supernatant was transferred to a fresh vial containing 90 µL of methanol and vortexed to mix thoroughly. Finally, 36 µL of the resulting solution was transferred to an injection vial for mass spectrometry analysis.Rattus norvegicushttps://www.ebi.ac.uk/metabolights/MTBLS14873Xuejiao Li. The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology. white_snow1987@163.com.Chuanxin Liu. The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology. 9906194@haust.edu.cn.The discriminating metabolites were obtained using a statistically significant threshold of fold change (FC) and two-tailed Student’s t test (p value) on the normalized raw data. The p value was calculated by one-way analysis of variance (ANOVA) for multiple groups analysis. Metabolites with FC greater than 1.5 and p value less than 0.05 were considered to be statistically significant metabolites. And the identified differential metabolites were used to perform cluster analyses with R package.TreatmentDosewhite_snow1987@163.comsamples of colonic feces were taken and storge in -80 ℃.MetabolomicsMetabolomicstargeted analysisQTRAP 6500+Rattus norvegicusShimadzu LC-30A Nexera UHPLC systemexperimental blankFecestargeted metabolite profilingShort Chain Fatty AcidMetabolomicstargeted analysisQTRAP 6500+Rattus norvegicusShimadzu LC-30A Nexera UHPLC systemexperimental blanktargeted metabolite profilingFecesShort Chain Fatty AcidThe MS conditions were set as follows: Perform mass spectrometry analysis using QTRAP 6500+mass spectrometer (AB SCIEX) in positive ion mode. The ESI source parameters are as follows:Positive ion mode: Source Temperature 550 ℃, Ion Source Gas1(GAS1):40psi, Ion Source Gas2(GAS2): 50psi, Curtain Gas(CUR): 35psi, Ion Spray Voltage Floating (ISVF) 5500V. Use MRM mode to detect the ion pairs of the test substance.Valeric acidIsobutyric acidCaproic acidIsovaleric acidPropionic acidAcetic acidButyric acidfalsetargeted metabolomics detemination of SCFAPodophyllotoxin (PPT) exhibits limited clinical utility due to its nephrotoxicity, and its underlying mechanisms remain poorly understood. This study employs the toxicological evidence chain (TEC) framework and integrated multi-omics analyses to investigate the potential involvement of the microbiota-gut-kidney (MGK) axis in PPT- induced nephrotoxicity in SD rats. Toxicity was systematically evaluated through longitudinal monitoring of body weight, general behavior, biochemical markers, intestinal barrier function, and histopathological alterations. In parallel, multi-omics analyses, encompassing microbiome, metabolomics, and transcriptomics, were conducted to delineate the mechanistic underpinnings. The results showed that PPT exposure induced pronounced renal and intestinal damage, manifesting as significant weight loss, diarrhea, elevated renal injury biomarkers, increased lipopolysaccharide (LPS) levels, and diamine oxidase (DAO), along with histopathological lesions and enhanced apoptosis in renal and colonic tissues. PPT exposure perturbed gut microbiota homeostasis, characterized by depletion of beneficial taxa (e.g., Lactobacillus) and enrichment of potentially pathogenic genera (e.g., Bacteroides and Aggregatibacter), concomitant with diminished short-chain fatty acid (SCFA) production and altered metabolite profiles in fecal, serum, and renal samples. Integrated multi- omics analysis further revealed activation of the JAK1/2-STAT3 signaling pathway, upregulation of pro-inflammatory mediators (TNF-α, IL-6, IL-1β, LPS, and TMAO), and suppression of anti-inflammatory cytokines (IL-10 and IL-4). These in vivo molecular and inflammatory patterns were partially reproduced in HK-2 cells co-cultured with fecal microbiota supernatant from PPT-treated rats. In addition, the JAK1/2 inhibitor ruxolitinib attenuated PPT-induced JAK1/2-STAT3 phosphorylation and inflammatory cytokine secretion in HK-2 cells. Correlation network analysis further identified associations between gut dysbiosis, systemic inflammation, and metabolic perturbations. Collectively, these findings support a mechanistic hypothesis that MGK- axis disruption and JAK1/2-STAT3 signaling may contribute to PPT-associated nephrotoxicity. However, in vivo interventional studies are required to establish definitive causality2026-06-282026-06-28MTBLS14873MTBLC15366MTBLC30768MTBLC16135MTBLC30772MTBLC28484MTBLC17418MTBLC30776CHEBI:15366CHEBI:30768CHEBI:16135CHEBI:30772CHEBI:28484CHEBI:17418CHEBI:30776