Chinese Journal of Animal Nutrition >

2026 , Vol. 38 >Issue 4: 3047 - 3057

DOI: https://doi.org/10.12418/CJAN2026.244

RESEARCH PAPER

Molecular Mechanism of Zearalenone-Induced Hepatotoxicity Explored via Network Toxicology and Molecular Docking Techniques

  • ZHAO Meihe , 1 ,
  • DU Liyin 1, 2, 3 ,
  • DENG Qinghua 1, 2, 3 ,
  • QIU Jun 1 ,
  • MAO Jingdong , 1, * ,
  • ZHANG Yuming , 1, 2, 3, *
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  • 1 College of Animal Science and Technology, Inner Mongolia Minzu University, Tongliao 028000, China
  • 2 Inner Mongolia Autonomous Region Engineering Technology Research Center of Beef and Mutton Industry (Beef and Mutton Disease Prevention and Control Research Center), Tongliao 028000, China
  • 3 Inner Mongolia Beef and Mutton Industry College, Tongliao 028000, China
*MAO Jingdong, associate professor, E-mail: ;
ZHANG Yuming, lecturer, E-mail:

Received date: 2025-09-16

  Online published: 2026-04-14

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Abstract

This study aimed to investigate the molecular mechanism of zearalenone (ZEA)-induced hepatotoxicity using network toxicology and molecular docking techniques. Based on the network toxicology approach, toxicity targets of ZEA and hepatotoxicity-related targets were first collected from multiple databases, and potential targets for ZEA-induced hepatotoxicity (intersection targets) were screened. Subsequently, the CytoHubba plugin in Cytoscape software was used to identify core targets. Furthermore, the STRING database was employed to construct a protein-protein interaction (PPI) network of the intersection targets, and enrichment analysis of GO functions and KEGG pathways were performed using the DAVID database. For molecular docking, ZEA was used as the ligand and the top eight core targets ranked by degree value were selected as receptors, the molecular docking and binding free energy calculations were performed using AutoDock Vina, and then the docking results were visualized using PyMOL software. The results showed that a total of 21 potential targets for ZEA-induced hepatotoxicity were screened from the databases. GO function enrichment analysis of the core targets indicated that ZEA-induced hepatotoxicity may be related to mitochondrion, cellular components, and metabolic functions. KEGG pathway enrichment analysis revealed that ZEA-induced hepatotoxicity may be closely associated with pathways such as epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance, acute myeloid leukemia and prolactin signaling pathway. Molecular docking results demonstrated that ZEA can stably bind to the top 8 core targets ranked by degree: signal transducer and activator of transcription 3 (STAT3), heat shock protein 90 alpha family class a member 1 (HSP90AA1), matrix metallopeptidase 9 (MMP9), estrogen receptor 1 (ESR1), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 3 (MAPK3), matrix metallopeptidase 2 (MMP2) and mechanistic target of rapamycin (MTOR). These targets may be key targets in ZEA-induced hepatotoxicity. This study systematically reveals potential targets and related signaling pathways involved in ZEA-induced hepatotoxicity, providing a new theoretical basis for elucidating the mechanism of ZEA liver toxicity and assessing its risks to animal health.

Key words： zearalenone; hepatotoxicity; molecular docking; core targets

Cite this article

ZHAO Meihe , DU Liyin , DENG Qinghua , QIU Jun , MAO Jingdong , ZHANG Yuming . Molecular Mechanism of Zearalenone-Induced Hepatotoxicity Explored via Network Toxicology and Molecular Docking Techniques[J]. Chinese Journal of Animal Nutrition, 2026 , 38(4) : 3047 -3057 . DOI: 10.12418/CJAN2026.244

玉米赤霉烯酮(ZEA),又称F-2毒素,是全球饲料和农产品中最常见的真菌毒素之一,其污染在全球饲料体系中具有高度流行性。据既往监测,约45%的饲料样品可检出ZEA,阳性样品的中位浓度为55 μg/kg[1]。我国面临的ZEA污染形势更为严峻。2021—2024年多省份饲料系统监测显示,ZEA常与黄曲霉毒素B1(AFB1)和呕吐毒素(DON)共同存在,呈现显著的多毒素共污染特征[2]。2024年华南地区家禽配合饲料监测进一步发现,ZEA检出率达到100%,且常与柄曲霉素(STC)和赭曲霉毒素A(OTA)同时出现,检出率分别为70.3%和22.0%[3]。由于ZEA具有较强的雌激素样活性,其在玉米油、玉米胚芽油等油脂类原料中的污染尤为引人关注。一项针对陕西省2013—2016年市售食品的调查表明,玉米油中ZEA检出率高达79.37%,平均含量为149 μg/kg,显著高于其他食品类别[4],提示其在食品加工链中存在较高的暴露风险。随着农产品深加工比例的提升,ZEA污染已从饲料体系延伸至食品链,成为当前需要重点监管的真菌毒素。
ZEA主要由镰刀菌属真菌产生,是一种典型的具有雌激素样活性的内分泌干扰物[5]。大量研究证实,ZEA能够干扰性腺轴功能,导致生长发育异常,临床可表现为女孩性早熟与男孩青春期延迟等[5-6]。2020年奥地利儿童生物监测项目显示,受试者尿液中ZEA的检出率高达100%,提示人群暴露已相当普遍[7]。除生殖与发育毒性外,ZEA还具有多靶器官毒性,可对免疫系统、肾脏及肝脏等造成损害,其毒性效应因靶器官不同而存在差异,其中肝毒性尤为显著。作为ZEA代谢与转化的主要场所,肝脏是其毒性作用的关键靶点。研究表明,ZEA可诱导肝细胞内活性氧(ROS)过量生成,降低抗氧化酶活性,进而激活细胞凋亡及炎症反应通路,最终导致明显的肝脏损伤[8-10]。此外,Wu等[11]报道,槲皮万寿菊素(quercetagetin)可通过激活Kelch样环氧氯丙烷相关蛋白1(Keap1)/核因子E2相关因子2(Nrf2)/抗氧化反应元件(ARE)信号通路缓解ZEA诱导的兔肝脏损伤,提示Nrf2介导的抗氧化防御系统在ZEA肝毒性干预中具有重要作用。Zhou等[12]的研究进一步证实,ZEA暴露可显著升高血清丙氨酸氨基转移酶(ALT)、碱性磷酸酶(ALP)等肝功能指标的活性,增强半胱天冬酶-3(Caspase-3)mRNA的表达,并诱导肝细胞凋亡。然而,尽管已有充分证据表明ZEA具有明确的肝毒性,但其导致肝脏损伤的关键分子靶点、核心调控网络及具体作用机制尚未得到系统阐明。鉴于ZEA在饲料中普遍存在,并能通过肉、蛋、奶等动物源性食品进入人类食物链,其肝毒性不仅直接危害畜禽健康与生产性能,还可能构成潜在的食品安全风险。因此,从分子层面系统解析ZEA的肝毒性机制,对于完善其风险评估和制定有效防控策略具有重要意义。
尽管已有研究揭示了ZEA通过氧化应激、炎症和凋亡等途径引发肝脏损伤,但其多靶点、多通路的系统性毒性机制尚待深入阐明。网络毒理学能够整合多数据库资源,系统构建“污染物-靶点-通路”关联网络,为复杂毒性机制的整体解析提供有力工具;分子对接技术则可在蛋白质-小分子相互作用层面验证核心靶点的结合潜力,从而提升靶点筛选与机制推断的可信度。本研究整合网络毒理学与分子对接技术,系统筛选并验证与ZEA相关的肝毒性核心靶点,构建其潜在信号通路网络,从分子层面解析ZEA诱导肝脏损伤的作用机制,以期为ZEA的肝毒性风险评估与饲料安全防控提供理论依据。

1 材料与方法

1.1 ZEA毒性预测

通过PubChem数据库搜索英文名为“Zearalenone”的化合物,以确定该化合物的结构、标准结构式和SMILES名称。应用ProTox 3.0(https://tox.charite.de/protox3/index.php?site=home)和ADMETlab 2.0数据库(https://admetmesh.scbdd.com)预测化合物的毒性和药代动力学特性。

1.2 ZEA毒性靶点的获取

分别在SwissTargetPrediction(http://www.swisstargetprediction.ch)、STITCH(http://stitch.embl.de)和SEA数据库(https://sea.bkslab.org)中检索ZEA毒性靶点,将每个活性成分在3个数据库中的检索结果进行合并、去重、汇总,并通过UniProt数据库(https://www.uniprot.org)对蛋白靶点进行校正,得到ZEA毒性靶点。

1.3 肝毒性相关靶点的获取

分别在GeneCards(https://www.genecards.org)、OMIM(https://omim.org)和CTD数据库(https://ctdbase.org)中以“Liver Injury”“Drug Induce Liver Injury”“Hepatic Injury”等与肝毒性相关的疾病作为关键词进行检索,获取肝毒性相关靶点。

1.4 ZEA致肝毒性潜在靶点的获取

借助在线工具Venny 2.1.0(https://bioinfogp.cnb.csic.es/tools/venny),将ZEA作用靶点与肝毒性相关基因靶点进行映射,即两者取交集,绘制韦恩图,得到ZEA致肝毒性的潜在作用靶点。

1.5 ZEA-肝毒性蛋白质-蛋白质相互作用(PPI)网络的构建和核心靶点筛选

为进一步分析ZEA毒性靶点与肝毒性相关靶点间的相互作用,将获取的交集靶点导入STRING数据库(https://string-db.org),构建PPI网络。将得到的PPI网络导入CytoScape软件,基于CytoHubba插件,通过分子复合物检测算法对PPI网络中的核心模块进行聚类分析。应用CytoScape软件构建ZEA-肝毒性靶点-通路网络模型,并对该网络进行网络拓扑分析,基于度值(degree)、介度(betweenness)、紧密度(closeness)等网络拓扑学参数预测分析ZEA产生肝毒性的核心靶点及关键成分。

1.6 GO功能与KEGG通路富集分析

将ZEA诱导肝毒性的潜在靶点导入DAVID数据库(https://david.ncifcrf.gov)进行GO功能和KEGG通路富集分析。GO功能注释涵盖生物过程(BP)、细胞组分(CC)和分子功能(MF)三大类别,用于揭示靶点的主要生物学功能。KEGG通路富集分析则用于识别与肝毒性相关的显著通路,并以P<0.05作为筛选标准。

1.7 ZEA与肝毒性靶点蛋白的分子对接

首先,通过PubChem数据库(https://pubchem.ncbi.nlm.nih.gov)获取ZEA的分子结构,并保存为PDB格式;然后,从PDB数据库(https://www.rcsb.org)下载肝毒性相关靶点的蛋白质三维结构文件,利用PyMol软件对蛋白质结构进行预处理,包括去除水分子和配体;随后,使用AutoDock Tools对蛋白靶点进行加氢处理;接着利用AutoDock Vina进行分子对接,计算配体与靶点的结合自由能;最后,使用PyMol软件对对接结果进行可视化分析。

2 结果与分析

2.1 ZEA毒性预测

通过ADMETlab 2.0和ProTox 3.0预测结果可知,ZEA具有较强的肝毒性(表1),并主要通过激活细胞色素P450 3A4(CYP3A4)发挥作用(表2)。
表1 ZEA毒性预测

Table 1 Prediction of toxicity of ZEA

属性
Proerties		 数据库
Database		 预测概率
Predicted
probability
肝毒性Hepatotoxicity ProTox 3.0 ++
肝毒性Hepatotoxicity ADMETlab 2.0 +++

图中预测概率以符号表示:“-”表示[0.3,0.5),“+”表示[0.5,0.7),“++”表示[0.7,0.9),“+++”表示[0.9,1.0]。这些概率值可作为评估潜在毒性风险的参考指标,概率越高,毒性风险越大。

In the figure, predicted probabilities are denoted by symbols: “-” represents [0.3, 0.5), “+” represents [0.5, 0.7), “++” represents [0.7, 0.9), and “+++” represents [0.9,1.0]. These probability values can serve as reference indicators for assessing potential toxicity risks, with higher probabilities suggesting a greater risk of toxicity.

表2 ZEA代谢靶点预测

Table 2 Prediction of metabolism targets of ZEA

代谢酶靶点
Metabolic Enzyme targets		 预测结果
Prediction result		 相互作用类型
Interaction type		 可能性
Probability
细胞色素P450 1A2 CYP1A2 不代谢 代谢 0.83
细胞色素P450 2C19 CYP2C19 不代谢 代谢 0.81
细胞色素P450 2C9 CYP2C9 不代谢 代谢 0.58
细胞色素P450 2D6 CYP2D6 不代谢 代谢 0.81
细胞色素P450 3A4 CYP3A4 代谢 代谢 0.89
细胞色素P45 03A4 CYP3A4 不代谢 代谢 0.99

2.2 ZEA毒性靶点的获取

以“Zearalenone”为关键词,在SEA和SwissTargetPrediction数据库中检索靶点信息,物种限定为“Homo sapiens”。将所得靶点进行合并与去重处理后,共获得657个ZEA毒性靶点。

2.3 肝毒性相关靶点的获取

将从GeneCards、OMIM和CTD数据库检索到的所得靶点进行合并与去重汇总后,最终得到120个肝毒性相关靶点。

2.4 ZEA致肝毒性潜在靶点的获取

利用Venny 2.1.0在线工具对获取的657个ZEA毒性靶点与120个肝毒性相关靶点进行交集分析,映射后得到21个交集靶点,作为ZEA诱导肝毒性的潜在作用靶点(图1)。
图1 肝毒性相关靶点与ZEA毒性靶点的韦恩图

Fig.1 Venn diagram of hepatotoxicity-related targets and ZEA toxicity targets

2.5 ZEA-肝毒性PPI网络的构建

利用Cytoscape 3.9.1构建化合物-靶点-疾病网络(图2-A)。将21个ZEA诱导肝毒性的潜在作用靶点导入STRING 11.5数据库,物种限定为“Homo sapiens”,最小互作阈值设为“High confidence (0.400)”,结果获得1个包含21个节点和109条边的PPI网络,平均节点度值为10.4(图2-B)。为进一步探讨ZEA诱导肝毒性的潜在机制,将该PPI网络导入Cytoscape 3.9.1,并通过CytoHubba插件进行拓扑分析。根据度值筛选出排名前8的核心靶点,并对其进行可视化(图2-C),同时选取其作为后续分子对接的候选靶点(表3)。
图2 化合物-靶点-疾病网络图(A)、PPI网络图(B)与核心靶点筛选网络图(C)

限于篇幅,仅对度值排名前8的靶点的英文简写进行注释 due to space limitations, only the abbreviations of the top 8 targets by degree value are annotated。STAT3:信号转导与转录激活因子3 signal transducer and activator of transcription 3;HSP90AA1:热休克蛋白90αA1 heat shock protein 90 alpha family class a member 1;MMP9:基质金属蛋白酶9 matrix metallopeptidase 9;ESR1:雌激素受体1 estrogen receptor 1;MAPK1:丝裂原活化蛋白激酶1 mitogen-activated protein kinase 1;MAPK3:丝裂原活化蛋白激酶3 mitogen-activated protein kinase 3;MMP2:基质金属蛋白酶2 matrix metallopeptidase 2;MTOR:哺乳动物雷帕霉素靶蛋白 mechanistic target of rapamycin。图5和图6同 the same as Fig.5 and Fig.6。

Fig.2 Compound-target-disease network diagram (A), PPI network diagram (B) and core target screening network diagram (C)

表3 度值排前8位的核心靶点的信息

Table 3 Information on top 8 core targets by degrees

靶点名称Target names 介度Betweenness 紧密度Closeness 度值Degree
信号转导与转录激活因子3 STAT3 30.890 476 190 476 190 0.950 000 000 000 000 0 18
热休克蛋白90αA1 HSP90AA1 23.990 476 190 476 187 0.904 761 904 761 904 8 17
基质金属蛋白酶9 MMP9 27.923 809 523 809 524 0.904 761 904 761 904 8 17
雌激素受体1 ESR1 13.523 809 523 809 526 0.826 086 956 521 739 1 15
丝裂原活化蛋白激酶1 MAPK1 14.404 761 904 761 903 0.826 086 956 521 739 1 15
丝裂原活化蛋白激酶3 MAPK3 12.018 253 968 253 969 0.791 666 666 666 666 6 14
基质金属蛋白酶2 MMP2 12.278 571 428 571 427 0.791 666 666 666 666 6 14
哺乳动物雷帕霉素靶蛋白MTOR 5.799 999 999 999 999 0.791 666 666 666 666 6 14

2.6 GO功能和KEGG通路富集分析

对21个ZEA诱导肝毒性的潜在作用靶点进行GO功能和KEGG通路富集分析。
GO功能注释共获得249项条目,其中属于BP的有148项,属于CC的有24项,属于MF的有77项。在这三大类别中分别选取前10项进行可视化(图3)。在BP中显著富集的功能包括细胞成分组织的调节(regulation of cellular component organization)、磷酸化(phosphorylation)、细胞对活性氧的反应(cellular response to reactive oxygen species)、肽基丝氨酸磷酸化(peptidyl-serine phosphorylation)、细胞迁移(cell migration)以及胰岛素受体信号通路(insulin receptor signaling pathway)等;在CC中主要涉及伪足(pseudopodium)、富含ficolin-1的颗粒腔(ficolin-1-rich granule lumen)、有丝分裂纺锤体(mitotic spindle)和线粒体(mitochondrion);在MF主要集中于金属肽酶活性(metallopeptidase activity)、肽结合(peptide binding)、蛋白丝氨酸激酶活性(protein serine kinase activity)及ATP结合(ATP binding)。
图3 GO功能富集分析结果

BP:生物过程 biological process;CC:细胞组分 cellular component;MF:分子功能molecular function;Regulation of cellular component organization:细胞组分组织的调控;Phosphorylation:磷酸化;Cellular Response to reactive oxygen species:细胞对活性氧物种的反应;Peptidyl-serine phosphorylation:肽基-丝氨酸磷酸化;Insulin receptor signaling pathway:胰岛素受体信号通路;Response to xenobiotic stimulus:对外源性刺激的反应;Cell migration:细胞迁移;Negative regulation of gene expression:基因表达的负向调控;Negative regulation of apoptotic process:细胞凋亡过程的负向调控;Chromatin remodeling:染色质重构;Pseudopodium:伪足;ficolin-1-rich granule lumen:富集ficolin-1的颗粒腔;Mitotic spindle:有丝分裂纺锤体;Membrane raft:膜筏;Mitochondrion:线粒体;Nucleoplasm:核质;Plasma membrane:质膜;Cytoplasm:细胞质;Cytosol:细胞溶质;Nucleus:细胞核;Metallopeptidase activity:金属肽酶活性;Peptide binding:肽结合;Protein serine kinase activity:蛋白质丝氨酸激酶活性;Protein serine/threonine kinase activity:蛋白质丝氨酸/苏氨酸激酶活性;Kinase activity:激酶活性;Protein kinase activity:蛋白激酶活性;Histone H3S28 kinase activity:组蛋白H3S28激酶活性;Histone H2BS36 kinase activity:组蛋白H2BS36激酶活性;Identical protein binding:同源蛋白结合;ATP binding:ATP结合。

Fig.3 Results of GO function enrichment analysis

KEGG通路富集分析结果(图4)显示,在P<0.05的阈值下,显著通路包括表皮生长因子受体(EGFR)酪氨酸激酶抑制剂耐药性(EGFR tyrosine kinase inhibitor resistance)、急性髓系白血病(acute myeloid leukemia)、催乳素信号通路(prolactin signaling pathway)和磷酸肌醇3-激酶(PI3K)-蛋白激酶(Akt)信号通路(PI3K-Akt signaling pathway)等。
图4 KEGG通路富集分析结果

EGFR tyrosine kinase inhibitor resistance:EGFR酪氨酸激酶抑制剂耐药性;Acute myeloid leukemia:急性髓系白血病;Prolactin signaling pathway:催乳素信号通路;Prostate cancer:前列腺癌;Endocrine resistance:内分泌耐药;Proteoglycans in cancer:癌症中的蛋白聚糖;Chemical carcinogenesis-receptor activation:化学致癌作用-受体激活;Human cytomegalovirus infection:人巨细胞病毒感染;PI3K-Akt signaling pathway:PI3K-Akt信号通路;Pathways in cancer:癌症通路。

Fig.4 Results of KEGG pathway enrichment analysis

进一步对核心基因进行富集分析,结果揭示其在多种疾病及生物学过程中具有潜在作用(图5)。具体而言,丝裂原活化蛋白激酶3(MAPK3)显著富集于急性髓系白血病及脂质与动脉粥样硬化通路,提示其在血液恶性疾病和代谢异常中的双重作用;哺乳动物雷帕霉素靶蛋白(MTOR)与膀胱癌密切相关;基质金属蛋白酶9(MMP9)则主要参与Th17细胞分化,提示其在免疫应答中的关键作用;雌激素受体α(ESR1)显著富集于前列腺癌及化学致癌作用-受体激活通路;丝裂原活化蛋白激酶1(MAPK1)与雌激素信号通路增强相关,表明其与激素依赖性疾病紧密联系;信号转导与转录激活因子3(STAT3)在内分泌抵抗中具有较强富集性;基质金属蛋白酶2(MMP2)主要涉及癌症通路;值得注意的是,热休克蛋白90αA1(HSP90AA1)在癌症通路中的富集最为显著,提示其可能在肿瘤发生发展中发挥核心作用。综上可知,HSP90AA1的高度显著性提示其为潜在关键因子,而MAPK3与MMP9的多通路关联则反映了其在不同疾病背景下的多功能性。这些结果不仅揭示了核心基因的多重生物学作用,也为进一步阐明其在ZEA诱导肝毒性中的潜在机制提供了理论依据。
图5 核心靶点的通路富集分析

Acute myeloid leukemia:急性髓系白血病;Lipid and atherosclerosis:脂质与动脉粥样硬化;Bladder cancer:膀胱癌;Th17 cell differentiation:Th17细胞分化;Prostate cancer:前列腺癌;Chemical carcinogenesis-receptor activation:化学致癌作用-受体激活;Estrogen signaling pathway:雌激素信号通路;Endocrine resistance:内分泌耐药;Pathways in cancer:癌症通路。

Fig.5 Pathway enrichment analysis of core targets

2.7 ZEA致肝毒性核心靶点的分子对接

利用AutoDock Vina,选择ZEA作为配体,8个核心靶点作为受体进行分子对接,其可视化结果见图6-A至图6-H。通常认为,结合自由能<0,表明两者能自发结合;结合自由能小于-5 kcal/mol(1 kcal/mol≈4.184 kJ/mol),则表明两者能很好地结合。图6-I显示,ZEA与MAPK1的结合自由能最低,与其余7个核心靶点的结合自由能也均小于-5 kcal/mol,表明ZEA可调控这些靶点损伤肝脏,致肝毒性。
图6 分子对接可视化分析

A:ZEA与ESR1的对接 docking of ZEA with ESR1;B:ZEA与HSP90的对接 docking of ZEA and HSP90;C:ZEA与MAPK1的对接 docking of ZEA and MAPK1;D:ZEA与MAPK3的对接 docking of ZEA and MAPK3;E:ZEA与MMP2的对接 docking of ZEA与MMP2;F:ZEA与MMP9的对接 docking of ZEA and MMP9;G:ZEA与MTOR的对接 docking of ZEA and MTOR;H:ZEA与STAT3的对接 docking of ZEA and STAT3;I:分子对接结合能示意图 schematic diagram of molecular docking binding free energy。

Fig.6 Molecular docking visualization analysis

3 讨论

ZEA是镰刀菌产生的典型真菌毒素,广泛存在于谷物、饲料及动物源性食品中,是畜禽生产中最常见的危害因子之一[13-14]。动物通过摄入受污染饲料暴露于ZEA,其在体内主要经肠肝循环代谢并随胆汁排泄[15-16]。ZEA的急性毒性较低,但在持续或高剂量暴露条件下可引发活性氧(ROS)积累、线粒体功能障碍和细胞凋亡,并诱发显著的类雌激素效应,导致肝脏功能异常与生殖损伤[14,16-17]。本研究整合网络毒理学预测和分子对接分析,从多层级系统性阐释了ZEA诱导肝毒性的潜在分子机制。
基于ProTox 3.0与ADMETlab 2.0的预测结果,ZEA对CYP1A2、CYP2C9、CYP2C19、CYP2D6和CYP2E1显著抑制,而对CYP3A4具有激活效应。由于细胞色素P450(CYP450)是肝脏最核心的解毒与代谢系统,提示ZEA可干扰多种内源性与外源性物质的代谢平衡。CYP3A4是肝脏中最主要的药物代谢酶之一,参与多种临床药物的氧化代谢过程,其变异或异常表达会导致毒性增强或解毒不足[18-20]。因此,在ZEA暴露条件下,CYP3A4的激活或许是一种“代偿性保护机制”,也提示其可能是调控ZEA毒性的重要干预靶点。GO功能富集分析显示,ZEA主要影响线粒体、细胞膜及胞质器官等关键结构,诱导氧化应激、糖与脂代谢紊乱及凋亡通路异常。有研究表明,ZEA能通过诱发氧化应激与细胞内钙离子稳态失衡,诱导猪肾脏上皮细胞发生凋亡和坏死性凋亡[21]。此外,ZEA暴露的AML12细胞呈现铁离子积累、铁蛋白降解及核受体共激活因子4(NCOA4)参与的铁死亡激活,进一步加剧细胞损伤[22]。
中药在缓解ZEA毒性方面具有潜力,例如,紫堇灵可通过调控Nrf2/谷胱甘肽过氧化物酶4(GPX4)抑制铁死亡,改善ZEA诱导的肝脏损伤[23]。这些结果表明,ZEA通过氧化应激-凋亡-铁死亡的交互放大机制造成肝脏损伤。上述研究在小鼠的研究中得到了验证。有研究显示,ZEA暴露可导致小鼠肝脏和肾脏组织中ROS与丙二醛(MDA)含量显著升高,并抑制超氧化物歧化酶(SOD)、过氧化氢酶(CAT)等关键抗氧化酶的活性[24],这为开发针对ZEA肝毒性的有效干预策略提供了明确的靶点和方向。KEGG通路富集分析结果表明,ZEA的肝毒性涉及EGFR酪氨酸激酶抑制剂耐药性、急性髓系白血病等多个通路,其中PI3K-Akt信号通路最为关键,该通路在维持肝脏代谢稳态中起着核心作用。已有研究证明,PI3K-Akt信号通路的激活对调控肝脏代谢稳态、细胞增殖与存活发挥着重要作用[25-26],提示ZEA可能通过异常激活该通路促进糖酵解增强、脂质代谢重编程和细胞生长失衡。这一推测在动物试验中得到佐证,在猪肠道上皮细胞中的研究发现,ZEA暴露会引发广泛的代谢紊乱[27]。这与本研究预测的PI3K-Akt信号通路介导的代谢失调机制相吻合。磷脂酰肌醇-4,5-二磷酸3-激酶催化亚基α(PIK3CA)和磷脂酰肌醇-4,5-二磷酸3-激酶催化亚基β(PIK3CB)基因的上调或突变已被证实与肝细胞早期病变高度相关[28-29],这进一步支持了PI3K-Akt信号通路在ZEA肝毒性中的核心地位。更为重要的是,ZEA能够通过ROS介导的PI3K-Akt信号通路,抑制乳腺上皮细胞增殖并诱导其凋亡,最终导致泌乳功能下降[30]。这项发现证明了本研究的预测结果,从动物模型层面揭示了ZEA危害畜牧业生产性能的一条关键分子通路,凸显了本研究筛选出的核心靶点具有重要的生产实践意义。分子对接结果显示,ZEA与多个核心靶点稳定结合。ZEA与MAPK1、MAPK3、MMP2有较低的结合自由能,MAPK1与MAPK3是细胞外信号调节激酶,主导调控细胞增殖、分化与应激反应,其异常激活与炎症及肿瘤发生密切相关;MMP2则通过降解细胞外基质参与肝纤维化、肝硬化及肿瘤侵袭转移过程[31-32]。ZEA与ESR1的高亲和力,证明了其类雌激素毒性是引发生殖内分泌紊乱的分子基础。MTOR与ZEA的稳定结合同样值得关注。MTOR是调控细胞生长与代谢的核心蛋白,可形成哺乳动物雷帕霉素靶蛋白复合体1(mTORC1)与哺乳动物雷帕霉素靶蛋白复合体2(mTORC2)复合物,并且其通路在肝纤维化与肝癌中持续激活[33-34]。ZEA可能通过直接高亲和力地干扰丝裂原活化蛋白激酶(MAPK)信号传导及MMP2的基质重塑功能,并协同影响MTOR等核心通路,从而在肝细胞代谢损伤、纤维化乃至肿瘤进程中发挥多重毒性作用。
综上可知,ZEA的肝毒性是一个由代谢紊乱、氧化损伤、细胞死亡通路激活及关键信号转导异常共同构成的复杂网络过程。本研究从分子层面系统揭示了ZEA诱导肝毒性的潜在机制,虽然具体的分子互作机制尚需进一步的功能试验验证,但相关发现仍为开发ZEA毒性防控的饲料添加剂及制定动物健康保护策略提供了重要理论依据。

4 结论

本研究结合网络毒理学与分子对接技术,系统揭示了饲料中常见污染物ZEA诱导肝毒性的分子机制,结果表明,ZEA的毒性效应具有多靶点、多通路的协同特征,其可通过干扰肝脏代谢关键酶CYP450系统、诱导线粒体氧化应激与铁死亡过程,并调控PI3K-Akt和STAT3等关键信号通路,最终引起肝细胞功能紊乱与结构损伤。

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
LIU J D, APPLEGATE T. Zearalenone (ZEN) in livestock and poultry:dose,toxicokinetics,toxicity and estrogenicity[J]. Toxins, 2020, 12(6):377.

DOI

[2]
LIU M, XIA Z Y, ZHANG Y, et al. Contamination of aflatoxin B1,deoxynivalenol and zearalenone in feeds in China from 2021 to 2024[J]. Journal of Animal Science and Biotechnology, 2025, 16(1):66.

DOI

[3]
曾睿, 陈佩榕, 王琼珊, 等. 我国华南地区家禽配合饲料中3种真菌毒素污染现状分析[J]. 动物营养学报, 2024, 36(1):672-680.

DOI

ZENG R, CHEN P R, WANG Q S, et al. Pollution situation analysis of 3 mycotoxins in poultry compound feeds from south China[J]. Chinese Journal of Animal Nutrition, 2024, 36(1):672-680. (in Chinese)

DOI

[4]
胡佳薇, 王彩霞, 田丽, 等. 2013—2016年陕西省市售食品中玉米赤霉烯酮的污染状况及暴露评估[J]. 卫生研究, 2017, 46(4):585-588,627.

HU J W, WANG C X, TIAN L, et al. Analysis on contamination of zearalenone and dietary exposure assessment in food samples of Shaanxi province in 2013—2016[J]. Journal of Hygiene Research, 2017, 46(4):585-588. (in Chinese)

[5]
LI F H, ZHAO X Q, JIAO Y N, et al. Exposure assessment of aflatoxins and zearalenone in edible vegetable oils in Shandong,China:health risks posed by mycotoxin immunotoxicity and reproductive toxicity in children[J]. Environmental Science and Pollution Research, 2023, 30(2):3743-3758.

DOI

[6]
ZHENG W L, FENG N N, WANG Y, et al. Effects of zearalenone and its derivatives on the synthesis and secretion of mammalian sex steroid hormones:a review[J]. Food and Chemical Toxicology, 2019, 126:262-276.

DOI

[7]
AYENI K I, JAMNIK T, FAREED Y, et al. The Austrian children’s biomonitoring survey 2020 Part B:mycotoxins,phytotoxins,phytoestrogens and food processing contaminants[J]. Food and Chemical Toxicology,2023,182:114173.

[8]
ZHANG Y, LI X, WANG Z, et al. Zearalenone induces oxidative stress and apoptosis in hepatocytes via mitochondrial pathway[J]. Food and Chemical Toxicology, 2021, 156:112502.

DOI

[9]
LONG M, YANG S H, HAN J X, et al. Theprotective effect of grape-seed proanthocyanidin extract on oxidative damage induced by zearalenone in Kunming mice liver[J]. International Journal of Molecular Sciences, 2016, 17(6):808.

DOI

[10]
WU J, LI J Y, WU Y, et al. Betulinic acid mitigates zearalenone-induced liver injury by ERS/MAPK/Nrf2 signaling pathways in mice[J]. Food and Chemical Toxicology, 2023, 177:113811.

DOI

[11]
WU F Y, WANG F X, TANG Z H, et al. Quercetagetin alleviates zearalenone-induced liver injury in rabbits through Keap1/Nrf2/ARE signaling pathway[J]. Frontiers in Pharmacology, 2023, 14:1271384.

DOI

[12]
ZHOU C, ZHANG Y, YIN S, et al. Biochemical changes and oxidative stress induced by zearalenone in the liver of pregnant rats[J]. Human & Experimental Toxicology, 2015, 34(1):65-73.

[13]
BENNETT J W, KLICH M. Mycotoxins[J]. Clinical Microbiology Reviews, 2003, 16(3):497-516.

DOI PMID

[14]
RAI A, DAS M, TRIPATHI A, et al. Occurrence and toxicity of a fusarium mycotoxin,zearalenone[J]. Critical reviews in food science and nutrition, 2020, 60(16):2710-2729.

DOI

[15]
YANG S P, LI Y S, DE BOEVRE M, et al. Toxicokinetics of α-zearalenol and its masked form in rats and the comparative biotransformation in liver microsomes from different livestock and humans[J]. Journal of Hazardous Materials, 2020, 393:121403.

DOI

[16]
ROPEJKO K, TWARUZEK M. Zearalenone and its metabolites-general overview,occurrence,and toxicity[J]. Toxins, 2021, 13(1):35.

DOI

[17]
RONG X, WANG Y L, OUYANG F X, et al. Combined effects of zearalenone and deoxynivalenol on oxidative stress,hepatotoxicity,apoptosis,and inflammation in zebrafish embryos[J]. Science of The Total Environment, 2023, 859(Pt 2):160233.

DOI

[18]
MULDER T A M, VAN EERDEN R A G, DE WITH M, et al. CYP3A4*22 genotyping in clinical practice:ready for implementation?[J]. Frontiers in Genetics, 2021, 12:711943.

DOI

[19]
XU X Y, CHEN J, CHEN Z X, et al. CYP3A4 activity variations can lead to stratified metabolism of abemaciclib[J]. International Journal of Biological Macromolecules, 2025, 304(Pt 1):140836.

DOI

[20]
DESTA Z, GELLER A, et al. Clinical significance of CYP3A enzymes in drug metabolism and drug interactions[J]. Drug Metabolism Reviews, 2020, 52(2):1-25.

DOI

[21]
CHEN S S, XU T, XU A Q, et al. Quercetin alleviates zearalenone-induced apoptosis and necroptosis of porcine renal epithelial cells by inhibiting CaSR/CaMKII signaling pathway[J]. Food and Chemical Toxicology, 2023, 182:114184.

DOI

[22]
BAO L G, HUANG Y Z, GU F H, et al. Zearalenone induces liver injury in mice through ferroptosis pathway[J]. Science of the Total Environment, 2024, 952:175875.

DOI

[23]
孙立群. 紫堇灵调控Nrf2/GPX4抑制铁死亡改善玉米赤霉烯酮诱导肝损伤的机制研究[D]. 博士学位论文. 长春: 吉林大学, 2023.

SUN L Q. Corynoline attenuates zearalenone-induced liver injury by inhibiting ferroptosis through regulating Nrf2/GPX4 signaling pathway[D]. Ph.D.Thesis. Changchun: Jilin University, 2023. (in Chinese)

[24]
韩建鑫, 何剑斌, 高锋, 等. 原花青素对玉米赤霉烯酮致小鼠肝脏、肾脏氧化损伤的保护作用[J]. 中国畜牧兽医, 2016, 43(2):402-406.

DOI

HAN J X, HE J B, GAO F, et al. Protective effects of proanthocyanidins on the liver and kidney oxidative damage induced by zearalenone in mice[J]. China Animal Husbandry & Veterinary Medicine, 2016, 43(2):402-406. (in Chinese)

[25]
SHAMSAN E, ALMEZGAGI M, GAMAH M, et al. The role of PI3K/AKT signaling pathway in attenuating liver fibrosis:a comprehensive review[J]. Frontiers in Medicine, 2024, 11:1389329.

DOI

[26]
LI C, LI Y, HE L N, et al. PI3K/AKT signaling regulates bioenergetics in immortalized hepatocytes[J]. Free Radical Biology & Medicine, 2013, 60:29-40.

DOI

[27]
WANG H F, XIAO Y Y, XU C, et al. Integrated metabolomics and transcriptomics analyses reveal metabolic mechanisms in porcine intestinal epithelial cells under zearalenone stress[J]. Journal of Agricultural and Food Chemistry, 2022, 70(21):6561-6572.

DOI

[28]
SCHEITER A, EVERT K, REIBENSPIES L, et al. RASSF1A independence and early galectin-1 upregulation in PIK3CA-induced hepatocarcinogenesis:new therapeutic venues[J]. Molecular Oncology, 2022, 16(5):1091-1118.

DOI

[29]
NARCI K, KAHRAMAN D C, KOYAS A, et al. Context dependent isoform specific PI3K inhibition confers drug resistance in hepatocellular carcinoma cells[J]. BMC Cancer, 2022, 22(1):320.

DOI PMID

[30]
CHEN H, QIU D, MIAO X, et al. Zearalenone depresses lactation capacity through the ROS-mediated PI3K/AKT pathway[J]. Animals, 2025, 15(7):1050.

DOI

[31]
巩婷婷, 司凯, 刘会平, 等. MAPK级联调控细胞生长及其在免疫、炎症及癌症中作用的研究进展[J]. 中南大学学报(医学版), 2022, 47(12):1721.

GONG T T, SI K, LIU H P, et al. Advances in research of MAPK cascades regulating cell growth and their roles in immunity,inflammation and cancer[J]. Journal of Central South University (Medical Sciences), 2022, 47(12):1721-1731. (in Chinese)

[32]
SHAN L, WANG F, ZHAI D, et al. Matrix metalloproteinases induce extracellular matrix degradation through various pathways to alleviate hepatic fibrosis[J]. Biomedicine & Pharmacotherapy, 2023, 161:114472.

DOI

[33]
ZHANG H, XIA T, XIA Z J, et al. KIF18A inactivates hepatic stellate cells and alleviates liver fibrosis through the TTC3/Akt/mTOR pathway[J]. Cellular and Molecular Life Sciences, 2024, 81(1):96.

DOI PMID

[34]
PORTA C, PAGLINO C, MOSCA A. Targeting PI3K/Akt/mTOR signaling in cancer[J]. Frontiers in Oncology, 2014, 4:64.

DOI PMID

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