林鹤1,
于娜1,
刘兆泉1,
任利翔1
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
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
Gao Meiqi1,2,Lin He1,
Yu Na1,
Liu Zhaoquan1,
Ren Lixiang1
1. Shenyang Research Institute of Chemical Industry, Safety Evaluation Center, Shenyang 110021, China;
2. Faculty of Life Sciences and Biological Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, China
CLC number: X171.5
-->
摘要
HTML全文
图
参考文献
相关文章
施引文献
资源附件
访问统计
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。
关键词: 肝细胞/
肝脏毒性/
毒性筛选/
高内涵检测
Abstract:The environmental pollution pose a threat to human health when exposed to harmful chemicals. Liver, mainly for metabolism, is undoubtedly the most sensitive organ to those harmful chemicals. In the present study, we established an effective in vitro screening model with multiple parameters for evaluation of hepatotoxicity. Five hepatotoxic chemicals and a plurality of three non-hepatotoxic chemicals were selected as positive controls and negative controls, respectively. Meanwhile, three kinds of assay were also applied in two hepatocytes for comparison. The growth inhibitions in these cell types induced by these chemicals were examined using MTT assay. Close relevant indicators of liver injury were then checked using high-content detection method. Hepatic enzyme contents were finally tested by real-time quantitative PCR. Five hepatotoxic chemicals showed significant inhibition on the growth of HepG2 and L-02 cells in different patterns. Furthermore, when those hepatotoxic chemicals were administrated in these cells, the liver injury-related parameters exhibited distinct degrees of changes. Our finding indicates that L-02 cells showed obvious higher sensitivity and specificity than HepG2 cells in hepatotoxic evaluation. The mRNA levels of metabolizing enzymes were also remarkably higher in L-02 cells than in HepG2 cells, indicating that L-02 cell is suitable for in vitro model closely simulating liver metabolism levels in vivo for hepatotoxic screening.
Key words:hepatocytes/
hepatotoxic/
toxicity screening/
high-content detection.
| 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 |
