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Article

Moringa oleifera Leaf Extract Alleviates AFB1-Induced Hepatotoxicity and Oxidative Stress Through the PPARγ/Nrf2 Signaling Pathway

by
Yujie Chen
1,2,†,
Peijin Li
1,2,†,
Minglu Xue
1,
Zongmin Shu
1,2,
Qingyi Zhou
1,2,
Xia Fan
1,2,
Yongyun Zhang
2,
Junlong Bi
1,
Weizhen Li
1,2,* and
Ming Li
1,2,*
1
The Yunnan Key Laboratory of Veterinary Etiological Biology, College of Veterinary Medicine, Yunnan Agricultural University, Kunming 650201, China
2
Teaching Demonstration Center of the Basic Experiments of Agricultural Majors, Yunnan Agricultural University, Kunming 650201, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Foods 2026, 15(4), 616; https://doi.org/10.3390/foods15040616
Submission received: 29 December 2025 / Revised: 19 January 2026 / Accepted: 27 January 2026 / Published: 9 February 2026
(This article belongs to the Section Food Toxicology)
Browse Figures
Versions Notes

Abstract

Aflatoxin B1 (AFB1), a potent carcinogen, is widely present in various crops, with limited prevention and treatment methods, continuously threatening food safety and public health. Moringa oleifera leaf extract (MOLE) is rich in bioactive compounds such as flavonoids, polysaccharides, triterpenes, and volatile oils, exhibiting antioxidant and anti-inflammatory potential. However, its specific effects and underlying mechanisms against AFB1-induced hepatotoxicity remain unclear. This study aimed to elucidate the alleviative effect of MOLE on AFB1 hepatotoxicity and its molecular mechanisms. In AFB1-induced mouse-liver tissue and hepatocyte models, MOLE significantly reduced the activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Data indicated that MOLE treatment markedly suppressed AFB1-induced accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA), while enhancing antioxidant indicators such as total antioxidant capacity (T-AOC) and glutathione (GSH). Network pharmacology identified 50 bioactive components in MOLE and revealed 78 common targets with AFB1-induced hepatotoxicity. Protein–protein interaction analysis identified 10 core targets. Key active compounds included naringenin, quercetin, and luteolin. GO and KEGG enrichment results were closely associated with ROS-related pathways. Molecular docking demonstrated strong binding affinity between MOLE components and core targets, particularly with PPARG. Mechanistically, MOLE significantly increased PPARγ protein levels and upregulated Nrf2 protein expression. It also enhanced the mRNA expression of HO-1, SOD, NQO1, CAT, and GPX1 and improved cellular total antioxidant capacity. Crucially, inhibiting PPARγ abolished the protective effects of MOLE and reversed its promotion of Nrf2. In conclusion, MOLE alleviates liver injury by binding to PPARγ to activate the Nrf2 pathway, thereby inhibiting AFB1-induced ROS accumulation.

1. Introduction

Aflatoxin B1 (AFB1) is a polyketide secondary metabolite produced by fungi such as Aspergillus flavusand and Aspergillus parasiticus. This toxic compound is characterized by a bifuran ring and a coumarin–cyclopentenone fused system [1] and is prevalent in various crops, including grains, oilseeds, tree nuts, and spices. AFB1’s high contamination frequency, extreme toxicity, and environmental persistence make it a major concern for food safety and animal health. Incomplete estimates suggest that over 4.5 billion people worldwide are chronically exposed to AFB1 through contaminated food [2]. Extensive toxicological studies have established AFB1 as a potent carcinogen and immunosuppressant agent. Clinical and pathological manifestations are dose- and time-dependent; chronic low-dose exposure can cause hepatic steatosis and immunosuppression, whereas acute high-dose exposure leads to centrilobular necrosis and biliary hyperplasia [3].
As a lipophilic compound, AFB1 is absorbed mainly via passive diffusion in the small intestine (particularly the duodenum) post-ingestion and is subsequently metabolized in the liver [4]. Its pathogenicity is largely driven by AFB1-exo-8,9-epoxide (AFBO), a metabolite formed during epoxidation catalyzed by cytochrome P450 enzymes [5]. This electrophilic metabolite is capable of forming DNA adducts, which can initiate mutations and carcinogenesis [3,6,7]. Additionally, AFBO induces excessive generation of reactive oxygen species (ROS) [8]. ROS attack cellular components—lipids, proteins, and RNA—causing oxidative stress, membrane damage, protein dysfunction, and metabolic disruption [9], which synergize to trigger apoptosis. Elmorsy et al. [10] demonstrated that fucoxanthin reduces oxidative stress in HepG2 cells, alleviating AFB1-induced hepatotoxicity, while Qiao et al. [11] also confirmed that curcumin alleviates AFB1-induced duck-liver injury by inhibiting oxidative stress and lysosomal damage. The Nrf2 pathway is central to antioxidant defense; its activation upregulates the expression of a series of ARE-dependent cytoprotective genes, enhancing oxidative damage resistance. Studies confirm Nrf2’s protective role against AFB1-induced hepatocyte oxidative stress [12].
Moringa oleifera, a perennial tropical deciduous tree of the Moringaceae family (Magnoliopsida, Brassicales) [13,14], is native to South Asia (e.g., Afghanistan, India) [15]. It was introduced to Taiwan, China, and has since been widely cultivated in tropical and subtropical provinces across southern and southeastern China. It is now mainly distributed in Yunnan, Guangdong, Hainan, and Taiwan. Moringa oleifera leaves exhibit antioxidant, anti-inflammatory, antibacterial, and antitumor activities, offering potential in livestock, nutraceuticals, and pharmaceuticals [16]. The leaves exhibit significant antioxidant activity by scavenging free radicals and reducing lipid peroxidation. This is achieved through a marked decrease in Malondialdehyde (MDA) levels and a concurrent boost in the activities of key antioxidant enzymes, including Superoxide Dismutase (SOD), Catalase (CAT), and Glutathione Peroxidase (GPX) [17,18,19]. These effects are attributed to their high content of phenolics (e.g., quercetin, kaempferol) and carotenoids (e.g., β-carotene, lutein) [20]. Jami et al. [18] confirmed that Moringa oleifera leaves exhibit significant antioxidant capacity in both in vivo and in vitro experiments [21]. In a high-fat diet rat model, supplementation with Moringa oleifera leaf powder significantly increased serum total antioxidant capacity (T-AOC) and enhanced SOD and GPX activities. Fakurazi et al. [22] found phenolic compounds in Moringa leaf alleviate acetaminophen-induced liver injury, restoring Glutathione (GSH) levels. Moringa oleifera leaf extract (MOLE) also shows antitumor activity by inhibiting proliferation [23], mitigating cancer-related damage [24], and promoting apoptosis [25]. Specifically, it is currently unknown whether MOLE activates the Nrf2 signaling pathway and, if so, whether this activation constitutes the principal mechanism underlying its protection against AFB1-induced oxidative stress and hepatotoxicity. Consequently, systematic investigation of this proposed mechanism is necessary to provide a scientific basis for the practical utilization of MOLE.
In conclusion, based on MOLE’s antioxidant properties, we hypothesize that MOLE attenuates AFB1-induced oxidative damage and hepatotoxicity through the Nrf2 pathway. This study employs in vivo/in vitro models, network pharmacology, and molecular docking to provide important theoretical support and practical guidance for the application of MOLE in the prevention and treatment of AFB1 poisoning, while also holding significant practical importance for ensuring the sustainable development of animal husbandry and food safety.

2. Materials and Methods

2.1. Animals

All animal procedures were approved by the Animal Ethics Committee of Yunnan Agricultural University. The animal experimental protocol was designed based on well-established models previously reported by Demirkapi et al. [26] and Zhu et al. [27], with appropriate modifications to suit the specific objectives of this study. Eighteen five-week-old male C57BL/6 mice were randomly assigned to three groups (n = 6 per group): Control, AFB1 and AFB1 + MOLE. The Control group received a daily oral gavage of 0.5% carboxymethyl cellulose (CMC) solution. The AFB1 group was administered 0.5% CMC for the first 5 days, followed by AFB1 (0.75 mg/kg, dissolved in dimethyl sulfoxide and diluted in 0.5% CMC) to induce toxicity. The AFB1 + MOLE group received prophylactic MOLE treatment (400 mg/kg, dissolved in double-distilled water) for 5 days, after which they were challenged with AFB1 under identical conditions as the AFB1 group, with concurrent MOLE administration. Mice were housed under a 12 h light/dark cycle with ad libitum access to food and water; body weight was recorded daily. On day 35, blood was collected via the orbital venous plexus and mice were euthanized for liver collection. Liver samples were analyzed for liver-to-body weight ratio, histopathology, injury markers, and antioxidant capacity.

2.2. Liver-to-Body Weight Ratio and Histopathological Analysis

Liver tissues were weighed and the liver-to-body weight ratio was calculated as (liver weight/ body weight) × 100%. Small liver fragments were then fixed in 4% paraformaldehyde. After fixation, tissues were processed for paraffin embedding, sectioned at 4 μm thickness, and stained with hematoxylin and eosin (H&E). Stained sections were examined under an inverted microscope. Pathological alterations in the liver tissue, such as steatosis, hydropic degeneration, and hepatocyte necrosis, were systematically evaluated based on the criteria established by Ge et al. [28].

2.3. Measurement of Serum Liver Injury Markers and Hepatic Antioxidant Activity

Orbital vein blood (0.5 mL) was collected into coagulation tubes, clotted at room temperature for 30 min, and centrifuged at 1000× g and 4 °C for 10 min to obtain serum. Serum ALT and AST activities were measured using an automated biochemical analyzer to evaluate liver damage. For antioxidant assessment, liver tissues were homogenized in saline (1:20 w/v) to prepare 5% homogenates. After centrifugation at 4 °C, the supernatant was assayed for MDA, GSH and T-AOC levels using commercial kits (MDA: BC0020; GSH: BC1170; T-AOC: BC1310; Solarbio, Beijing, China).

2.4. RNA Extraction, Reverse Transcription, and Quantitative PCR

Total RNA was isolated with Trizol reagent, and quality was verified by A260/A280 ratios measured on a NanoDrop Lite Plus (Thermo Fisher Scientific, Waltham, MA, USA). RNA was reverse-transcribed into cDNA following the manufacturer’s instructions. Quantitative PCR was performed using 2SYBR Green master mix on a MyiQ™ Real-Time PCR System (BioRad, Hercules, CA, USA). Amplification efficiency and primer specificity were assessed via amplification and melting curves. Relative mRNA expression was calculated by the 2−ΔΔCT method, normalized to β-actin. All primers are listed in Table 1.

2.5. Network Pharmacology and Molecular Docking

To ensure the robustness of the network pharmacology analysis, the criteria for compound screening and target identification were established based on the well-accepted protocols described by Guo et al. [29]. Specifically, the potential therapeutic targets of MOLE were obtained by retrieving compounds from Moringa oleifera leaves using the keyword “Moringa oleifera” in the IMPPAT database (https://cb.imsc.res.in/imppat/, accessed on 3 May 2025), supplemented by a literature review. The chemical structures and Simplified Molecular Input Line Entry System (SMILES) notations of the obtained compounds were searched in the PubChem database (https://pubchem.ncbi.nlm.nih.gov, accessed on 3 May 2025). To identify the main active components in MOLE, the SMILES notations were imported into the SwissADME database (https://www.swissadme.ch/, accessed on 3 May 2025) for screening. Components with “GI absorption” parameter as “High” satisfying at least two of the five common drug-likeness rules (Lipinski, Ghose, Veber, Egan, Muegge) and with bioavailability > 30% were selected as active ingredients. The SMILES notations of all screened active components were input into SwissTargetPrediction to predict potential targets and targets with a probability ≥ 0.1 were considered as potential targets of MOLE active components.
Using the keyword “AFB1 hepatotoxicity”, potential targets were retrieved from the GeneCards database (https://www.genecards.org, accessed on 3 May 2025), OMIM database (https://omim.org, accessed on 3 May 2025), and MalaCards database (https://www.malacards.org, accessed on 3 May 2025). The gene targets obtained from these three databases were merged, duplicates were removed, and the resulting set was defined as potential targets for AFB1 hepatotoxicity. The intersection between these targets and the potential targets of MOLE active components was taken as the potential targets for MOLE alleviation of AFB1 hepatotoxicity.
The intersection genes were imported into the STRING database (https://string-db.org, accessed on 3 May 2025) with the species set to “Homo sapiens” and other parameters kept default, to obtain a protein–protein interaction network. The data were downloaded and imported into Cytoscape 3.7.0 software. Using the CytoNCA plugin combined with the MCC and MNC algorithms in the CytoHubba plugin, core targets were selected.
The “active component-intersection target” network files and type files were constructed using Excel and imported into Cytoscape 3.7.0 software for adjustment and optimization. The CytoNCA plugin was used to screen the top ten core active components based on betweenness (BC), closeness (CC), and degree (DC).
The DAVID database (https://davidbioinformatics.nih.gov/, accessed on 3 May 2025) was used to perform GO function and KEGG pathway enrichment analysis on the intersection targets of drugs and diseases, to explore the signaling pathways of potential target genes for MOLE alleviation of AFB1 hepatotoxicity. GO enrichment analysis included biological process (BP), cellular component (CC) and molecular function (MF). Bubble diagrams for top GO functions and enrichment maps for KEGG pathways were plotted.
The molecular structures of MOLE active components were downloaded from the PubChem database and converted to PDB format using Open Babel 3.1.1 software. The 3D structures of core targets were obtained from the PDB database (https://www.rcsb.org/, accessed on 3 May 2025) and preprocessed by dehydration and hydrogenation. These files were imported into AutoDock 1.5.7 for molecular docking and the best docking conformation was exported as a complex structure file. The docking results were converted to PDB format compatible with PyMOL 2.4 using Open Babel 3.1.1 and receptor-ligand colors, transparency, hydrogen bonds, and residues were adjusted to display key interactions.

2.6. Cell Culture

AML-12 hepatocytes were maintained in RPMI 1640 with 10% FBS and 1% penicillin-streptomycin at 37 °C/5% CO2. Cells were pretreated with MOLE (80 µg/mL, 1 h) before AFB1 (20 µM) exposure for a specified duration before sample collection.

2.7. Cell Viability Assay

Viability was assessed by CCK-8. AML-12 were seeded in 96-well plates and cultured in an incubator. When the cells reached 70–80% confluence, they were treated with varying concentrations of MOLE (10, 20, 40, 80, 160, and 320 µg/mL). After 12 h of treatment, 10 μL of CCK-8 solution was added to each test well, and the cells were incubated at 37 °C until the supernatant color turned orange. The absorbance at 450 nm was measured using a multi-function microplate reader, and cell viability was calculated accordingly.

2.8. Liver Injury Markers in Cell Supernatant

AML-12 supernatant was collected after centrifugation (1000× g, 4 °C, 10 min). ALT and AST activities were measured using an automated analyzer.

2.9. Intracellular ROS Detection

Intracellular ROS levels induced by AFB1 were measured using a ROS detection kit. Hepatocytes were seeded in 24-well plates, pretreated with MOLE, and then stimulated with or without AFB1 for 1 h. After 12 h, the culture medium was discarded and cells were washed twice with PBS. Then, 500 µL of serum-free medium containing 10 µM DCFH-DA was added to each well, and cells were incubated in the dark at 37 °C for 30 min. After incubation, cells were washed three times with serum-free medium. ROS levels were observed under a fluorescence inverted microscope.

2.10. Cellular Antioxidant Capacity

Cell suspensions were placed in 6-well plates, with 2 mL per well. After treatment, the supernatant was discarded and cells were washed twice with PBS. Then, 200 µL of PBS was added to collect cells into 1.5 mL centrifuge tubes. Cells were sonicated (power 200 W, 3 s on/9 s off, total 3 min) and centrifuged at 10,000 rpm at 4 °C for 10 min. The supernatant was collected and placed on ice for assay. MDA, GSH, and T-AOC levels were measured using commercial kits (MDA: BC0020; GSH: BC1170; T-AOC: BC1310; Solarbio, Beijing, China).

2.11. Western Blotting

Cells were lysed with lysis buffer (200 µL RIPA lysis buffer, 1 µL protease inhibitor mixture, 1 µL broad-spectrum phosphatase inhibitor mixture (100×)). Lysates (20 µg) were loaded onto SDS-PAGE and transferred to nitrocellulose membranes. Membranes were blocked with rapid blocking buffer (PS108P, Epizyme, Shanghai China) at room temperature for 0.5 h and incubated overnight with polyclonal antibodies against PPARγ, Nrf2, and β-actin. Membranes were washed with 1× TBS-T, incubated with HRP-conjugated secondary antibodies at room temperature for 1 h, and detected using an ECL detection system (Servicebio, Wuhan, China). Band intensities were quantified by densitometry using ImageJ 1.47 software.

2.12. Statistical Analysis

Data are mean ± SD. Group differences were analyzed by one-way ANOVA (GraphPad Prism 9.5); p-value less than 0.05 (p < 0.05) was considered to be statistically significant.

3. Results

3.1. MOLE Alleviates AFB1-Induced Weight Loss and Hepatic Damage in Mice

To evaluate the protective role of MOLE against AFB1 toxicity, mice were intoxicated with AFB1 (0.75 mg/kg) and co-treated with MOLE (400 mg/kg) via gavage (Figure 1A). Daily body-weight increases were observed in all groups (Control, AFB1, and AFB1 + MOLE) (Figure 1B). The AFB1 group showed a markedly slower weight-gain rate compared to the Controls, while the AFB1 + MOLE group displayed a restored weight-gain trend, converging with the Control group after day 15. The liver-to-body weight ratio was significantly elevated in the AFB1 group versus the Controls (p < 0.05) but was reduced by MOLE intervention in the AFB1 + MOLE group (p < 0.05) (Figure 1C). Liver tissue samples were collected, stained with hematoxylin and eosin (H&E), and observed under a microscope (Figure 1D). Compared to the Control group, the AFB1 group displayed disordered hepatocyte arrangement, apparent vacuolar degeneration, a reticular appearance of cells, nuclei suspended centrally or displaced to one side, significant cell swelling, cleared cytoplasm, and nuclear enlargement. However, following MOLE intervention, vacuolar degeneration in hepatocytes was reduced and staining became more uniform.
To further elucidate the protective effect of MOLE on AFB1-induced liver injury in mice, the activities of ALT and AST in serum were measured (Figure 1E,F). AFB1 increased the activities of ALT and AST in mouse serum (p < 0.05). In contrast, compared to the AFB1 group, the AFB1 + MOLE group significantly reduced the activities of ALT and AST in serum (p < 0.05). These results support our hypothesis that MOLE can alleviate AFB1-induced liver injury.

3.2. MOLE Enhances Hepatic Antioxidant Capacity in AFB1-Exposed Mice

To evaluate the effect of MOLE on the hepatic antioxidant capacity (Figure 2A–C), we measured MDA, GSH, and T-AOC levels. Compared with the Control group, AFB1-induced liver injury resulted in a significant increase in MDA content in liver homogenate, no significant change but a decreasing trend in GSH (p < 0.05), and a significant decrease in T-AOC (p < 0.05), indicating that AFB1 induced hepatic oxidative stress, leading to decreased total antioxidant capacity and increased lipid peroxidation. After MOLE administration, the contents of GSH and T-AOC in liver homogenate were significantly increased and MDA content was significantly reduced (p < 0.05), demonstrating that MOLE can enhance hepatic antioxidant capacity, alleviate AFB1-induced oxidative stress, and reduce lipid peroxidation, thereby mitigating liver injury.
Analysis of antioxidant gene expression (Figure 2D–H) revealed that AFB1 significantly downregulated HO-1, SOD, NQO1, and GPX1 mRNA levels (p < 0.05) relative to the Controls, with no significant change in CAT expression. MOLE intervention significantly upregulated HO-1, SOD, NQO1, CAT, and GPX1 mRNA levels (p < 0.05). These findings indicate that MOLE enhances the antioxidant defense in AFB1-intoxicated mice by modulating the expression of key antioxidant genes.

3.3. Network Pharmacology and Molecular Docking of MOLE’s Mitigation of AFB1 Hepatotoxicity

3.3.1. Identification of Potential Targets for MOLE-Mediated Alleviation of AFB1 Hepatotoxicity

A total of 163 active components of MOLE were retrieved through the IMPPAT database and literature search. After screening with PubChem and SwissADME, 50 active components were selected. Target prediction via SwissTargetPrediction yielded 529 potential drug targets after deduplication. Meanwhile, 1140 targets associated with AFB1 hepatotoxicity were retrieved from GeneCards, OMIM and MalaCards (Figure 3). A Venn diagram generated using Venny revealed 78 intersection targets (Figure 3A), defined as potential targets for MOLE’s alleviation of AFB1 hepatotoxicity.

3.3.2. PPI Network Analysis and Core Target Screening

To comprehensively elucidate the potential mechanism of MOLE alleviation of AFB1 hepatotoxicity, the 78 intersection targets were analyzed in STRING to construct a protein–protein interaction network. After filtering out isolated genes, the network was imported into Cytoscape 3.7.0 for analysis. Node size and color intensity correlate with degree values, with larger, lighter nodes indicating higher degrees (Figure 3B) The top 10 targets by degree were IL6, GAPDH, EGFR, STAT3, PPARG, SRC, MTOR, MMP2, KDR, and JAK2. Using CytoNCA and cytoHubba plugins, 10 core targets were identified: IL-6, GAPDH, EGFR, STAT3, PPARG, SRC, MTOR, MMP2, KDR, and JAK2 (Figure 3C).

3.3.3. Active Component-Target Network Analysis

Since MOLE contains multiple components, an “active component-intersection target” network was visualized in Cytoscape 3.7.0 to identify key MOLE components (Figure 3D). CytoNCA was used to compute BC, CC, and DC. The top 10 active compounds based on these scores were naringenin, rhamnetin, isorhamnetin, luteolin, α-linolenic acid, quercetin, apigenin, o-coumaric acid, kaempferol, and hesperetin (Table 2).

3.3.4. Results of GO and KEGG Enrichment Analysis

To investigate the mechanism of MOLE alleviation of AFB1 hepatotoxicity, the 78 intersecting target genes were imported into the DAVID online database. GO analysis yielded 346 significant terms (p < 0.05), including 249 BP terms, 31 CC terms, and 66 MF terms. The top five GO terms with the lowest p-values were selected and visualized (Figure 3E). BP terms were primarily associated with phosphorylation, protein phosphorylation, positive regulation of cell migration, positive regulation of gene expression, and positive regulation of MAPK cascade. CC terms mainly involved receptor complex, nucleus, cytosol, nucleoplasm, and cytoplasm. MF terms were mainly related to nuclear receptor activity, ATP binding, protein tyrosine kinase activity, protein serine kinase activity, and protein kinase activity. KEGG enrichment analysis identified 129 significant pathways (p < 0.05) and the top 10 pathways with the lowest p-values were visualized (Figure 3F), including EGFR tyrosine kinase inhibitor resistance, pathways in cancer, PI3K-Akt signaling pathway, Rap1 signaling pathway, Proteoglycans in cancer, and Chemical carcinogenesis–reactive oxygen species. All GO and KEGG enrichment results were closely associated with AFB1-induced liver injury.

3.3.5. Molecular Docking and Visualization

In this study, molecular docking was performed to evaluate the interactions between the 10 obtained active components and 10 core target proteins. A total of 100 docking results were obtained (Figure 4A), showing that all 10 active components could spontaneously bind with the 10 core target proteins. Lower docking scores indicate stronger binding affinity. The binding energies of naringenin with PPARG, quercetin with PPARG, naringenin with JAK2, luteolin with EGFR, and luteolin with PPARG were all less than −7 kcal/mol, indicating a strong binding affinity. Notably, naringenin exhibited the lowest binding energy with PPARG (−7.85 kcal/mol). The 10 results with the lowest docking energies were selected (Table 3) and subjected to visual analysis (Figure 4B–K).

3.4. MOLE’s Effects on Cell Viability and AFB1-Induced Damage

To determine if MOLE mitigates AFB1-induced oxidative stress and damage, we first examined its impact on AML-12 cell viability (Figure 5). Cells were treated with MOLE (10–320 µg/mL) for 4 h, and viability was assessed via CCK-8 assay, a standard method for evaluating cell health and compound toxicity. MOLE at 20, 40, and 80 µg/mL did not significantly affect viability, whereas concentrations of 160 and 320 µg/mL suppressed it (Figure 5A). Based on these results, 80 µg/mL MOLE was selected for further experiments.
We next explored MOLE’s protective role against AFB1-induced damage. Cells were pretreated with MOLE for 1 h before exposure to 20 µM AFB1 for 12 h. MOLE at 80 µg/mL significantly reduced ALT activity in the supernatant (p < 0.05) (Figure 5B) and both 40 and 80 µg/mL lowered AST activity (p < 0.05) (Figure 5C). The protective effect strengthened with increasing MOLE concentrations, indicating a dose-dependent response.

3.5. MOLE Alleviates AFB1-Induced Oxidative Stress in Hepatocytes

To determine whether MOLE reduces oxidative stress in hepatocytes, we measured ROS levels in AFB1-stimulated AML-12 cells using DCFH-DA. After entering cells, DCFH-DA is hydrolyzed by intracellular esterases and then oxidized by ROS to fluorescent DCF. The results showed that AFB1 induction significantly altered ROS levels in AML-12 cells, with obvious green fluorescence observed under microscopy. Interestingly, after MOLE pretreatment, the green fluorescence was significantly reduced (Figure 5D). We then measured MDA, GSH, and T-AOC levels, which are closely related to oxidative stress. Compared with the control group, AFB1 induction significantly increased MDA content and decreased GSH and T-AOC levels (p < 0.05). MOLE pretreatment reversed these effects (Figure 5E–G). These results indicate that MOLE has antioxidant effects against AFB1-induced oxidative stress.

3.6. MOLE Alleviates Oxidative Stress Through the PPARγ-Mediated Nrf2 Signaling Pathway

Based on network pharmacology and molecular docking analyses, it was predicted that multiple active constituents in MOLE possess low binding energy to PPARγ. PPARγ functions as an upstream regulator of Nrf2, the central regulatory protein in antioxidant defense mechanisms [30]. To corroborate these findings from network pharmacology and molecular docking, we employed Western blotting to evaluate the protein expression levels of PPARγ and Nrf2. Compared with the control group, AFB1 induction decreased PPARγ protein expression in AML-12 cells (p < 0.05), while MOLE pretreatment significantly upregulated PPARγ expression (Figure 6A). Compared with the AFB1 group, MOLE pretreatment significantly increased Nrf2 protein levels, but treatment with GW9662 significantly reduced Nrf2 expression in AML-12 cells (p < 0.05) (Figure 6B). We also used qPCR to detect the expression of antioxidant genes downstream of the Nrf2 pathway. We found that compared with the AFB1 group, MOLE pretreatment upregulated the mRNA expression of HO-1, NQO1, SOD, and CAT. Interestingly, when the selective inhibitor GW9662 was added, this effect was reversed (Figure 6C–F). Together, these results demonstrate that GW9662 pretreatment inhibited PPARγ activity, thereby reducing Nrf2 expression, confirming that MOLE reduces AFB1-induced oxidative stress by activating PPARγ and subsequently increasing Nrf2 expression. This suggests that MOLE may enhance cellular antioxidant capacity and alleviate AFB1 hepatotoxicity by activating the PPARγ/Nrf2 pathway.

4. Discussion

AFB1, a mycotoxin produced by Aspergillus fungi, is a potent hepatotoxic and carcinogenic compound. It commonly contaminates agricultural products such as corn and peanuts and is frequently detected in animal feed, posing significant risks to animal husbandry and human health via the food chain. Currently, research on its detection methods, toxic mechanisms, and prevention strategies has become a major focus in the scientific community, with the aim of providing new solutions for food safety and toxicological interventions. MOLE is rich in flavonoids, polyphenols, and alkaloids, and is widely used in traditional medicine. Recent studies have focused on its antioxidant, anti-inflammatory, and detoxifying properties, showing promising potential in combating mycotoxin contamination. AFB1 poisoning can cause hepatic hemorrhagic necrosis, fibrosis, connective tissue hyperplasia, elevated AST and ALT levels, and increased liver-to-body weight ratio, potentially leading to brain edema and death. Chronic exposure results in hepatic fat deposition, hypertrophy, and pathological changes including granular degeneration, steatosis, and vacuolar degeneration, ultimately promoting hepatocellular carcinoma [31]. ALT and AST activities are established biomarkers for liver injury, primarily reflecting disruption of hepatocyte membrane integrity or enzyme release following necrosis [32]. In this study, MOLE intervention significantly reduced serum ALT and AST activities in mice and upregulated antioxidant genes compared to the AFB1 group. These results align with Kim et al. [33], indicating that MOLE mitigates oxidative stress by enhancing antioxidant gene expression.
Oxidative stress is a critical synergistic factor in AFB1 pathogenesis, arising from an imbalance between oxidative capacity and antioxidant defense. AFB1 metabolism by hepatic CYP450 generates highly reactive AFBO, accompanied by substantial ROS production and suppressed antioxidant mechanisms, leading to oxidative stress and lipid peroxidation products like MDA [34]. Persistent oxidative stress activates pathways involved in cell proliferation, survival, inflammation, and tumorigenesis (e.g., NF-κB, MAPK, Nrf2). For instance, NF-κB pathway activation promotes the production of inflammatory factors, creating a microenvironment conducive to tumorigenesis [35]. The primary detoxification pathway for AFB1 involves the conjugation of AFBO with GSH catalyzed by Glutathione S-transferases (GST), forming AFB1-GSH conjugates that are excreted. The rate of this conjugation reaction is much higher than that of AFBO with DNA, thereby preferentially neutralizing AFBO toxicity through competitive protection [36]. Thus, enhancing the body’s antioxidant capacity may be an effective strategy to mitigate AFB1 hepatotoxicity. The polyphenols and flavonoids in Moringa oleifera leaves exhibit significant antioxidant capacity [37]. Experiments confirmed that MOLE intervention significantly upregulated the mRNA expression of antioxidant genes in the liver, reducing AFB1-induced accumulation of ROS and MDA. In vitro experiments further supported these results. Additionally, MOLE intervention restored body-weight gain and liver-to-body weight ratio to normal levels in mice. These findings indicate that MOLE enhances hepatic antioxidant capacity, alleviates oxidative stress, and thereby reduces AFB1-induced liver injury.
Network pharmacology analysis in this study predicted the potential molecular mechanisms by which MOLE active components alleviate AFB1 hepatotoxicity. This in silico approach identified that potential targets were significantly enriched in pathways such as pathways in cancer, EGFR tyrosine kinase inhibitor resistance, and the PI3K-Akt signaling pathway. Research shows that AFB1 treatment increases caveolin-1 (CAV-1) expression in hepatocytes and activates the PI3K/AKT/mTOR pathway via EGFR, promoting autophagy and inhibiting apoptosis induced by oxidative stress [38]. Moreover, studies indicate that PI3K/Akt plays a crucial role in regulating Nrf2 pathway-dependent protection during acute stress, and activating the Nrf2/ARE pathway is a primary method to eliminate ROS by inducing antioxidant and detoxification responses [39]. Molecular docking results showed that multiple active components in MOLE had low binding energy with PPARγ, indicating stable binding energies, hinting at a potential for modulating its downstream pathways. PPARγ, a ligand-activated transcription factor of the nuclear hormone receptor superfamily, is a key metabolic regulator in hepatic lipid metabolism and inflammation. Fang et al. [40] found that PPARγ inhibits microglia-mediated neuroinflammation and oxidative stress, and Chen et al. [41] reported that targeting PPARγ alleviates oxidative and endoplasmic reticulum stress in non-alcoholic fatty liver disease. Studies have shown that PPARγ agonists upregulate Nrf2 expression [42], while PPARγ knockout reduces it [43,44]. In conclusion, these computational analyses predict that the role of PPARγ and its crosstalk with the Nrf2 pathway constitutes a key mechanistic insight into MOLE-mediated protection against AFB1-induced hepatotoxicity.
Substantial evidence indicates that AFB1-induced severe oxidative stress leads to a downregulation of the Nrf2 signaling pathway, which serves as the central axis of the endogenous antioxidant defense system [45,46,47]. Nrf2, as a key transcription factor, directly regulates the expression of various antioxidant and cytoprotective genes (HO-1, NQO1, GPX1) via the Nrf2/ARE pathway [48], thereby enhancing cellular antioxidant capacity, countering AFB1-induced oxidative damage, and restoring cellular homeostasis [49,50,51]. PPARγ, a nuclear transcription factor, can form a heterodimer with the retinoid X receptor (RXR) upon ligand activation, and this complex binds to specific PPAR response elements (PPREs) within the promoter regions of PPAR-regulated genes. Kvandova et al. [52] postulated that putative PPREs exist within the promoter region of the Nrf2 gene. Furthermore, Lai et al. [53] demonstrated that knockdown of RXRα in HTR-8/SVneo cells leads to reduced expression of Nrf2. Collectively, this evidence implies that PPARγ may directly bind to the Nrf2 promoter, resulting in the positive regulation of the Nrf2 signaling pathway. In this study, inhibition of PPARγ reverses the regulatory effect of MOLE on Nrf2. This reveals that MOLE enhances antioxidant capacity and alleviates oxidative stress by activating PPARγ and subsequently increasing Nrf2 expression, consistent with the findings of Kuret et al. [30]. Furthermore, molecular docking simulations predicted stable binding between the principal bioactive constituents of MOLE and PPARγ, indicating a plausible mechanism whereby these components activate PPARγ to enhance Nrf2-mediated antioxidant responses.
Nevertheless, this study has certain limitations: the absence of in vivo pharmacokinetic data for the active components of MOLE makes it challenging to comprehensively evaluate their bioavailability and duration of action. Additionally, the predictions from methods such as network pharmacology and molecular docking lack more detailed validation. Future research should be conducted in conjunction with clinical studies to delve deeper into the underlying mechanisms, thereby advancing the translation of the findings into practical applications.

5. Conclusions

MOLE can enhance the antioxidant capacity of hepatocytes through the PPARγ/Nrf2 signaling pathway, thereby alleviating AFB1-induced hepatic oxidative stress and injury. The key bioactive constituents of MOLE, such as naringenin, quercetin, luteolin, and apigenin, may function synergistically to achieve this effect. These findings provide new insights into the mechanisms underlying the beneficial effects of MOLE in preventing and treating AFB1 poisoning.

Author Contributions

Y.C.: Writing—original draft, Supervision, Project administration. P.L.: Writing—original draft, Supervision, Project administration, Methodology. M.X.: Visualization, Conceptualization. Z.S.: Formal analysis, Data curation. Q.Z.: Visualization, Data curation. X.F.: Conceptualization, Methodology, Data curation, Visualization. Y.Z.: Investigation, Formal analysis, Data curation. J.B.: Formal analysis, Data curation, Funding acquisition. W.L.: Writing—review and editing, Validation. M.L.: Writing—review and editing, Validation, Funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This project was supported by grants from Yunnan Province Special Project for Building a Science and Technology Innovation Center for South and Southeast Asia—Yunnan Province International Joint Research and Development Center for Veterinary Pharmaceuticals (No. 202403AP140012) and Yunnan Key Laboratory of Veterinary Etiological Biology (No. 202449CE340019).

Institutional Review Board Statement

All animal procedures were approved by the Animal Ethics Committee of Yunnan Agricultural University (Approve code: 202303008, Approve date: 8 March 2023).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Body weight and liver injury analysis. (A) Gavage procedure diagram. (B) Changes in body weight of mice. (C) Liver-specific gravity. (D) Liver pathological sections and liver histopathological scoring. Serum AST (E) and ALT (F) activities. Statistical significance differences between groups are indicated by asterisks: * p < 0.05, n = 6.
Figure 1. Body weight and liver injury analysis. (A) Gavage procedure diagram. (B) Changes in body weight of mice. (C) Liver-specific gravity. (D) Liver pathological sections and liver histopathological scoring. Serum AST (E) and ALT (F) activities. Statistical significance differences between groups are indicated by asterisks: * p < 0.05, n = 6.
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Figure 2. Hepatic antioxidant capacity analysis. Hepatic MDA (A), GSH (B), and T-AOC (C) concentrations; Relative mRNA expression levels of antioxidant-related genes HO-1 (D), SOD (E), NQO1 (F), CAT (G), and GPX1 (H). Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns” (not significant), n = 6.
Figure 2. Hepatic antioxidant capacity analysis. Hepatic MDA (A), GSH (B), and T-AOC (C) concentrations; Relative mRNA expression levels of antioxidant-related genes HO-1 (D), SOD (E), NQO1 (F), CAT (G), and GPX1 (H). Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns” (not significant), n = 6.
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Figure 3. Network pharmacology analysis. (A) Venn diagram of the intersection targets of Moringa leaf extract active components and AFB1 hepatotoxicity. (B) PPI network of potential therapeutic targets. (C) Screening of core target networks. (D) Network of ‘Active Components-Intersection Targets’. Diamonds represent the active pharmaceutical ingredients and rectangles represent the intersecting target points. (E) Bubble plot of GO enrichment analysis (BP, CC, MF). (F) Bubble plot of the KEGG pathway.
Figure 3. Network pharmacology analysis. (A) Venn diagram of the intersection targets of Moringa leaf extract active components and AFB1 hepatotoxicity. (B) PPI network of potential therapeutic targets. (C) Screening of core target networks. (D) Network of ‘Active Components-Intersection Targets’. Diamonds represent the active pharmaceutical ingredients and rectangles represent the intersecting target points. (E) Bubble plot of GO enrichment analysis (BP, CC, MF). (F) Bubble plot of the KEGG pathway.
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Figure 4. Molecular docking analysis. (A) Heatmap of binding energies between core targets and active components. The binding energies are presented in units of kcal/mol. Deeper colors indicate lower binding energies, which correspond to stronger binding affinities. (B–K) Docking patterns of the 10 lowest energy binding results between core targets and core components, including naringenin with PPARG (B), quercetin with PPARG (C), naringenin with JAK2 (D), luteolin with EGFR (E), luteolin with PPARG (F), naringenin with MMP2 (G), apigenin with PPARG (H), apigenin with EGFR (I), hesperetin with EGFR (J), and naringenin with SRC (K). (B–K): Target protein (blue), ligand (orange), amino acid residues (green).
Figure 4. Molecular docking analysis. (A) Heatmap of binding energies between core targets and active components. The binding energies are presented in units of kcal/mol. Deeper colors indicate lower binding energies, which correspond to stronger binding affinities. (B–K) Docking patterns of the 10 lowest energy binding results between core targets and core components, including naringenin with PPARG (B), quercetin with PPARG (C), naringenin with JAK2 (D), luteolin with EGFR (E), luteolin with PPARG (F), naringenin with MMP2 (G), apigenin with PPARG (H), apigenin with EGFR (I), hesperetin with EGFR (J), and naringenin with SRC (K). (B–K): Target protein (blue), ligand (orange), amino acid residues (green).
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Figure 5. Analysis of cell viability and injury markers. (A) Effects of different concentrations of MOLE on cell viability. Effects of varying concentrations of MOLE on ALT (B) and AST (C) activities in AFB1-treated AML-12 cells. (D) Intracellular ROS levels measured by DCFH-DA assay. Concentrations of MDA (E), GSH (F), and T-AOC (G) in AML-12 cells. Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns”, n = 3.
Figure 5. Analysis of cell viability and injury markers. (A) Effects of different concentrations of MOLE on cell viability. Effects of varying concentrations of MOLE on ALT (B) and AST (C) activities in AFB1-treated AML-12 cells. (D) Intracellular ROS levels measured by DCFH-DA assay. Concentrations of MDA (E), GSH (F), and T-AOC (G) in AML-12 cells. Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns”, n = 3.
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Figure 6. Analysis of PPARγ-mediated Nrf2 signaling pathway. The effect of MOLE on PPARγ expression in AML-12 cells. (A) The effect of GW9662 on Nrf2 expression in MOLE-treated AML-12 cells. (B) Relative mRNA expression levels of antioxidant-related genes in AML-12 cells HO-1 (C), NQO1 (D), SOD (E), CAT (F). Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns”, n = 3.
Figure 6. Analysis of PPARγ-mediated Nrf2 signaling pathway. The effect of MOLE on PPARγ expression in AML-12 cells. (A) The effect of GW9662 on Nrf2 expression in MOLE-treated AML-12 cells. (B) Relative mRNA expression levels of antioxidant-related genes in AML-12 cells HO-1 (C), NQO1 (D), SOD (E), CAT (F). Statistical significance differences between groups are indicated by asterisks: * p < 0.05. The absence of statistically significant differences between groups by “ns”, n = 3.
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Table 1. Primer information.
Table 1. Primer information.
Primer NamePrimer Sequence (5′-3′)Primer Size/bpProduct Size/bp
HO-1F:CACTCTGGAGATGACACCTGAG22115
R:GTGTTCCTCTGTCAGCATCACC22
NQO1F:GCCGAACACAAGAAGCTGGAAG22120
R:GGCAAATCCTGCTACGAGCACT22
SODF:CCAGTGCAGGACCTCATTTT20281
R:AATCCCAATCACTCCACAGG20
CATF:CACTGACGAGATGGCACACT20175
R:TGTGGAGAATCGAACGGCAA20
GPX1F:TGCGGAATGCCTTGCCAACAC21261
R:AGCCAGTAATCACCAAGCCAATGC24
β-acitnF:TCTGGCACCACACCTTCTA21180
R:AGGCATACAGGGACAGCAC19
Table 2. 10 core active substances.
Table 2. 10 core active substances.
Serial NumberCodeName
1MOLE20Naringenin
2MOLE17Rhamnetin
3MOLE16Isorhamnetin
4MOLE2Luteolin
5MOLE299,12,15-octadecatrienoic acid,(Z,Z,Z)
6MOLE19Quercetin
7MOLE3Apigenin
8MOLE49O-coumaric acid
9MOLE18Kaempferol
10MOLE5Hesperetin
Table 3. Binding information between protein receptors and small molecule ligands (Unit: kcal/mol).
Table 3. Binding information between protein receptors and small molecule ligands (Unit: kcal/mol).
Core TargetPDB IDCompoundBinding Energy/(kcal/mol)
PPARG9f7wNaringenin−7.85
PPAGR9f7wQuercetin−7.46
JAK27rekNaringenin−7.15
EGFR4hzrLuteolin−7.13
PPARG9f7wLuteolin−7.07
MMP23ayuNaringenin−6.97
PPARG9f7wApigenin−6.93
EGFR4hzrApigenin−6.83
EGFR4hzrHesperetin−6.77
SRC8a4nNaringenin−6.76
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Chen, Y.; Li, P.; Xue, M.; Shu, Z.; Zhou, Q.; Fan, X.; Zhang, Y.; Bi, J.; Li, W.; Li, M. Moringa oleifera Leaf Extract Alleviates AFB1-Induced Hepatotoxicity and Oxidative Stress Through the PPARγ/Nrf2 Signaling Pathway. Foods 2026, 15, 616. https://doi.org/10.3390/foods15040616

AMA Style

Chen Y, Li P, Xue M, Shu Z, Zhou Q, Fan X, Zhang Y, Bi J, Li W, Li M. Moringa oleifera Leaf Extract Alleviates AFB1-Induced Hepatotoxicity and Oxidative Stress Through the PPARγ/Nrf2 Signaling Pathway. Foods. 2026; 15(4):616. https://doi.org/10.3390/foods15040616

Chicago/Turabian Style

Chen, Yujie, Peijin Li, Minglu Xue, Zongmin Shu, Qingyi Zhou, Xia Fan, Yongyun Zhang, Junlong Bi, Weizhen Li, and Ming Li. 2026. "Moringa oleifera Leaf Extract Alleviates AFB1-Induced Hepatotoxicity and Oxidative Stress Through the PPARγ/Nrf2 Signaling Pathway" Foods 15, no. 4: 616. https://doi.org/10.3390/foods15040616

APA Style

Chen, Y., Li, P., Xue, M., Shu, Z., Zhou, Q., Fan, X., Zhang, Y., Bi, J., Li, W., & Li, M. (2026). Moringa oleifera Leaf Extract Alleviates AFB1-Induced Hepatotoxicity and Oxidative Stress Through the PPARγ/Nrf2 Signaling Pathway. Foods, 15(4), 616. https://doi.org/10.3390/foods15040616

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