环境中可致肝脏损伤化学成分体外筛选模型的建立

高美琪, 林鹤, 于娜, 刘兆泉, 任利翔. 环境中可致肝脏损伤化学成分体外筛选模型的建立[J]. 生态毒理学报, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
引用本文: 高美琪, 林鹤, 于娜, 刘兆泉, 任利翔. 环境中可致肝脏损伤化学成分体外筛选模型的建立[J]. 生态毒理学报, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
Gao Meiqi, Lin He, Yu Na, Liu Zhaoquan, Ren Lixiang. Establishment of an in vitro Screening Model for Environmental Chemicals that Can Induce Liver Damage[J]. Asian Journal of Ecotoxicology, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
Citation: Gao Meiqi, Lin He, Yu Na, Liu Zhaoquan, Ren Lixiang. Establishment of an in vitro Screening Model for Environmental Chemicals that Can Induce Liver Damage[J]. Asian Journal of Ecotoxicology, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001

环境中可致肝脏损伤化学成分体外筛选模型的建立

    作者简介: 高美琪(1994-),女,硕士,研究方向为肿瘤药理学、替代毒理学,E-mail:1014773401@qq.com
  • 中图分类号: X171.5

Establishment of an in vitro Screening Model for Environmental Chemicals that Can Induce Liver Damage

  • 摘要: 环境污染日益严重,环境中的有害化学成分对人类的身体健康具有潜在的危害,而肝脏作为代谢的主要器官,无疑最易受到损伤。本研究旨在建立一种高效的、多参数的肝脏毒性体外筛选方法。采用了5种肝毒性阳性化合物和3种阴性化合物,3种试验方法对2种肝细胞进行了比较。采用四甲基偶氮唑盐微量酶反应比色法(MTT法)考察了化合物对2种细胞体外的生长抑制作用,采用高内涵检测法考察了化合物对肝损伤相关指标的影响,采用实时定量聚合酶链式反应(PCR法)比较了2种细胞的肝药酶含量。5种明确能够导致肝损伤的阳性化学物质对HepG2和L-02细胞均有不同程度的体外生长抑制作用,而3种明确不能诱导肝损伤的化合物对2种细胞均无明显生长抑制作用,且L-02细胞对肝毒性阳性化学物相对敏感。高内涵检测结果表明,不同毒性机制的阳性化合物作用于2种细胞时,与肝损伤机制相关的参数呈现出不同程度的变化,且L-02细胞预测肝损伤的精确度、灵敏度和特异度更高,表明其预测肝损伤的能力更强。此外,L-02细胞药物代谢酶的mRNA表达含量显著高于HepG2细胞,表明其与体内肝脏代谢水平更加接近。综上所述,L-02细胞结合高内涵检测为合适的肝脏毒性体外筛选模型。
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  • Visentin M, Lenggenhager D, Gai Z, et al. Drug-induced bile duct injury[J]. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 2018, 1864:1498-1506
    Woodhead J L, Brock W J, Roth S E, et al. Application of a mechanistic model to evaluate putative mechanisms of tolvaptan drug-induced liver injury and identify patient susceptibility factors[J]. Toxicological Sciences, 2017, 155(1):61-74
    Hamilton L A, Collins Y A, Collins R E. Drug-induced liver injury[J]. Advanced Critical Care Nursing, 2016, 27(4):430-440
    Zhang J, Doshi U, Suzuki A, et al. Evaluation of multiple mechanism-based toxicity endpoints in primary cultured human hepatocytes for the identification of drugs with clinical hepatotoxicity:Results from 152 marketed drugs with known liver injury profiles[J]. Chemico-Biological Interactions, 2016, 255:3-11
    Ye H, Nelson L J, Gómez D M M, et al. Dissecting the molecular pathophysiology of drug-induced liver injury[J]. World Journal of Gastroenterology, 2018, 24:1373-1385
    Donato M T, Gómez-Lechón M J, Tolosa L. Using high-content screening technology for studying drug-induced hepatotoxicity in preclinical studies[J]. Expert Opinion on Drug Discovery, 2017, 12(2):201-211
    Mandavilli B S, Aggeler R J, Chambers K M. Tools to measure cell health and cytotoxicity using high content imaging and analysis[J]. Methods in Molecular Biology, 2018, 1683:33-46
    Tolosa L, Gómez-L M J, Donato M T. High-content screening technology for studying drug-induced hepatotoxicity in cell models[J]. Archives of Toxicology, 2015, 89(7):1007-1022
    Zhang J, Wang S, Xu L, et al. Multiple perspectives of qingkailing injection-fraction-single compound in revealing the hepatotoxicity of baicalin and hyodeoxycholic acid[J]. Journal of Ethnopharmacology, 2017, 215:147-155
    Wu Y, Geng X C, Wang J F, et al. The HepaRG cell line, a superior in vitro model to L-02, HepG2 and hiHeps cell lines for assessing drug-induced liver injury[J]. Cell Biology and Toxicology, 2016, 32(1):37-59
    Thakkar S, Tong W, Chen M, et al. The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury[J]. Expert Review of Gastroenterology & Hepatology, 2017, 12(1):31-38
    Yu K, Zhang J, Chen M, et al. Mining hidden knowledge for drug safety assessment:Topic modeling of LiverTox as a case study[J]. BMC Bioinformatics, 2014, 15(Suppl 17):S6
    Li X, Li X Y, Huang N, et al. A comprehensive review and perspectives on pharmacology and toxicology of saikosaponins[J]. Phytomedicine, 2018, 50:73-87
    Moo L B, Cheul L W, Young J J, et al. Clinical features of drug-induced liver injury according to etiology[J]. Journal of Korean Medical Science, 2015, 30(12):1815-1820
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  • 收稿日期:  2019-10-24
高美琪, 林鹤, 于娜, 刘兆泉, 任利翔. 环境中可致肝脏损伤化学成分体外筛选模型的建立[J]. 生态毒理学报, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
引用本文: 高美琪, 林鹤, 于娜, 刘兆泉, 任利翔. 环境中可致肝脏损伤化学成分体外筛选模型的建立[J]. 生态毒理学报, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
Gao Meiqi, Lin He, Yu Na, Liu Zhaoquan, Ren Lixiang. Establishment of an in vitro Screening Model for Environmental Chemicals that Can Induce Liver Damage[J]. Asian Journal of Ecotoxicology, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001
Citation: Gao Meiqi, Lin He, Yu Na, Liu Zhaoquan, Ren Lixiang. Establishment of an in vitro Screening Model for Environmental Chemicals that Can Induce Liver Damage[J]. Asian Journal of Ecotoxicology, 2020, 15(3): 56-63. doi: 10.7524/AJE.1673-5897.20191024001

环境中可致肝脏损伤化学成分体外筛选模型的建立

    作者简介: 高美琪(1994-),女,硕士,研究方向为肿瘤药理学、替代毒理学,E-mail:1014773401@qq.com
  • 1. 沈阳化工研究院有限公司安全评价中心, 沈阳 110021;
  • 2. 沈阳药科大学生命科学与生物制药学院, 沈阳 110016

摘要: 环境污染日益严重,环境中的有害化学成分对人类的身体健康具有潜在的危害,而肝脏作为代谢的主要器官,无疑最易受到损伤。本研究旨在建立一种高效的、多参数的肝脏毒性体外筛选方法。采用了5种肝毒性阳性化合物和3种阴性化合物,3种试验方法对2种肝细胞进行了比较。采用四甲基偶氮唑盐微量酶反应比色法(MTT法)考察了化合物对2种细胞体外的生长抑制作用,采用高内涵检测法考察了化合物对肝损伤相关指标的影响,采用实时定量聚合酶链式反应(PCR法)比较了2种细胞的肝药酶含量。5种明确能够导致肝损伤的阳性化学物质对HepG2和L-02细胞均有不同程度的体外生长抑制作用,而3种明确不能诱导肝损伤的化合物对2种细胞均无明显生长抑制作用,且L-02细胞对肝毒性阳性化学物相对敏感。高内涵检测结果表明,不同毒性机制的阳性化合物作用于2种细胞时,与肝损伤机制相关的参数呈现出不同程度的变化,且L-02细胞预测肝损伤的精确度、灵敏度和特异度更高,表明其预测肝损伤的能力更强。此外,L-02细胞药物代谢酶的mRNA表达含量显著高于HepG2细胞,表明其与体内肝脏代谢水平更加接近。综上所述,L-02细胞结合高内涵检测为合适的肝脏毒性体外筛选模型。

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