FME alleviates DON-induced intestinalliver injury in mice

Description

Research Hypothesis: This study was designed to test the hypothesis that Fructus Mume extract (FME) alleviates deoxynivalenol (DON)-induced intestinal and liver injury in mice by attenuating oxidative stress, suppressing inflammation and apoptosis, repairing the intestinal barrier, modulating gut microbiota, and restoring liver metabolism. Data Content and Collection Methods: Male C57BL/6 mice (n = 5 per group) were randomly assigned to five groups: control, DON (3 mg/kg body weight), and DON plus low-, medium-, or high-dose FME (25, 50, 100 mg/kg body weight, respectively). All treatments were administered daily for 4 weeks. Data were collected from multiple biological levels: Growth and pathological data: Body weight, hepatic vacuolation, and intestinal villus damage. Oxidative stress markers: Hepatic CAT, SOD, GSH, T-AOC (measured by biochemical assays) and MDA levels. Inflammatory markers: Serum IL-6, IL-1β, TNF-α, IFN-γ, IL-10, and IgG (measured by ELISA and qRT-PCR). Intestinal barrier function: Protein levels of ZO-1, Occludin, Claudin-1 (via immunohistochemistry). Apoptosis-related genes: Tradd, *Caspase-3/7/8*, Bax, and *Bcl-2* (via qRT-PCR) along with TUNEL staining. Gut microbiota: Metagenomic sequencing of fecal samples. Liver metabolites: Untargeted metabolomics (LC-MS/MS). Key Findings: FME dose-dependently alleviated DON-induced growth inhibition, hepatic vacuolation, and intestinal villus damage. It enhanced hepatic antioxidant capacity (CAT, SOD, GSH, T-AOC) and reduced MDA levels. FME suppressed NF-κB signaling, downregulated pro-inflammatory cytokines (IL-6, IL-1β, TNF-α, IFN-γ), upregulated IL-10, and restored serum IgG levels. Intestinal tight junction proteins (ZO-1, Occludin, Claudin-1) were upregulated, while apoptosis-related genes (Tradd, *Caspase-3/7/8*, Bax) were inhibited and *Bcl-2* promoted, thereby reducing intestinal epithelial apoptosis. Metagenomics revealed restored microbial diversity, increased beneficial genera (Clostridium, Oscillibacter, Alistipes), and decreased harmful bacteria. Liver metabolomics indicated that FME reversed DON-induced metabolic disruptions in lipid, amino acid, and antioxidant pathways. Data Interpretation and Usage: Statistical analyses were performed using one-way ANOVA followed by multiple comparison tests. For metagenomic data, diversity indices and relative abundances were calculated using standard bioinformatics pipelines. Metabolomic data were processed using principal component analysis (PCA) and pathway enrichment analysis. Correlation analysis was used to evaluate relationships between gut microbiota and liver metabolites. These data can be reused for meta-analyses, mechanism validation, or comparative studies on natural products against mycotoxin-induced toxicity. All raw sequencing data have been deposited in NCBI SRA (see Data Availability section), and supporting data are available in the Mendeley Data repository.

Steps to reproduce

2. Materials and Methods 2.1 Chemicals: FME (Desifu, Nanjing) and DON (≥90%; Yujing, Shanghai). 2.2 Animals & Design: Male C57BL/6 mice (3-4 weeks, ~18 g; Slack, Shanghai; license SCXK(Hu)2022-00B4; ethics PZCASFAFU26064) were housed at 20-24°C, 45% humidity, 12 h light/dark cycle. After 1 week of acclimation, mice were randomized into 5 groups (n=12): Control (normal saline), DON (3 mg/kg), L-FME (25 mg/kg FME + DON), M-FME (50 mg/kg FME + DON), H-FME (100 mg/kg FME + DON). Treatments were given daily by oral gavage (FME 8 h before DON) for 4 weeks. Blood, liver, duodenum, and jejunum were collected. 2.3 Body weight was recorded daily. 2.4 Histopathology: H&E staining of liver and jejunum. 2.5 ELISA: Serum IL-6, IL-10, and IgG (Jianglai, Shanghai). 2.6 Network pharmacology: Active FME components from TCMSP (OB≥30%, DL≥0.18). Targets predicted via SwissTargetPrediction, SEA, PharmMapper, TargetNet. Disease targets from DrugBank, GeneCards, OMIM, PharmGKB. Overlap identified with Venny 2.1.0. PPI network via STRING, Cytoscape (v3.9.1). GO/KEGG enrichment by DAVID. 2.7 Oxidative stress: Hepatic MDA, GSH, T-AOC, CAT, SOD (Grace, Suzhou); protein by BCA. 2.8 qRT-PCR: RNA (AG RNAex Pro), cDNA (Evo M-MLV). Protocol: 42°C 5 min, 95°C 10 min, 40 cycles (95°C 10 s, 60°C 35 s). 2⁻ΔΔCt method with β-actin as internal control. Primers in Table 1. 2.9 TUNEL: Jejunum sections were stained and imaged under a fluorescence microscope. 2.10 IHC: Jejunum sections (4 μm) incubated with anti-Claudin-1 (1:1000), anti-Occludin (1:6000), anti-ZO-1 (1:1300) at 4°C overnight, then MaxVision HRP IHC kit, DAB, hematoxylin. 2.11 Metagenomic sequencing: Fecal DNA (QIAGEN kit), library (Rapid Barcoding Kit V14), Illumina NovaSeq PE150. Reads filtered with fastp, host DNA removed by Bowtie2. Taxonomy via Kraken2/Bracken. Alpha (Shannon, Chao1) and beta (PCoA) diversity in R. 2.12 Liver metabolomics: Liver (30 mg) extracted in methanol-acetonitrile-water (2:2:1, v/v/v) with L-2-chlorophenylalanine (1 μg/mL). Lyophilized, reconstituted in methanol-water (1:1). UHPLC-MS/MS (ACQUITY UPLC HSS T3, 100×2.1 mm, 1.8 μm; 0.1% formic acid gradient; ESI± MRM). Data processed with Progenesis QI. PCA, OPLS-DA (SIMCA 14.1, R). Differential metabolites: VIP>1, P < 0.05; annotated via HMDB/Metlin. 2.13 Statistical analysis: Data are mean ± SEM. One-way ANOVA with Tukey's test (GraphPad Prism 8.0/Origin 2022). P < 0.05 was significant.

Institutions

• Fujian Agriculture and Forestry University

  Fujian, Fuzhou

Categories

Funders

• the Fujian Provincial Department of Finance, Fujian, China

  Grant ID: KLY24109XA
• the Key Project of Fujian Provincial Education and Scientific Research Program for Young and Middle-aged Teachers (Science and Technology Category)

  Grant ID: JZ230013

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