基于GADD153-LUC的重组人肺上皮细胞快速检测痕量PM2.5致DNA损伤效应
Rapid detection of DNA damage caused by trace PM2.5 using recombinant human lung epithelial cells based on GADD153-LUC
姚炜 1詹劲基 1姚云英 1汪东篱 1李燕 1杜海荣1
作者信息
- 1. 深圳市光明区疾病预防控制中心,广东 深圳 518106
- 折叠
摘要
目的:利用重组人体肺上皮细胞(BEAS-2B)快速检测细颗粒物(PM2.5)导致的DNA损伤效应.方法:制备不同浓度的PM2.5并作用于重组肺上皮细胞,观察不同浓度条件下MTS(内盐法,3-(4,5-二甲基噻唑-2)-5-(3-羧甲基苯基)-2-(4-磺苯基)-2氢-四唑内盐法)检测重组人肺上皮细胞细胞生存率、彗星实验检测DNA损伤、RT-PCR检测GADD153-luc基因表达变化、荧光素酶发光检测DNA损伤情况.结果:相比于阴性对照,25、125 μ g/mLPM2.5可诱导重组细胞活性显著下降和DNA损伤显著增加,相比于阴性对照,5、25、125 μ g/mL PM2.5可诱导重组细胞内源性GADD153mRNA基因表达、荧光素酶活性显著增加,且GADD153mRNA基因表达、荧光素酶活性具有良好的相关性(r2=0.992,P＜0.01).结论:相比传统细胞DNA损伤的方法,基于GADD153-LUC的重组人肺上皮细胞可快速检测更痕量PM2.5所致DNA损伤效应.
Abstract
Objective:Rapid detection of DNA damage caused by trace fine particulate matter(PM2.5)using recombinant human lung epithelial cells(BEAS-2B).Methods:Different concentrations of PM2.5 were prepared and applied to recombinant lung epithelial cells.The survival rate of recombinant human lung epithelial cells was detected by MTS(Internal salt method,3-(4,5-dimethylthiazole-2)-5-(3-carboxymethylphenyl)-2-(4-sulfophenyl)-2H-tetrazole internal salt method),DNA damage was detected by comet assay,GADD153 mRNA gene expression was detected by RT-PCR,and DNA damage was detected by luciferase activity under different concentrations.Results:Compared with negative control,25,125 μg/mL PM2.5 significantly decreased the activity of recombinant cells and significantly increased the DNA damage(comet assay).Compared with negative control,5,25,125 μg/mL PM2.5 significantly increased the endogenous GADD153 mRNA gene expression and luciferase activity of recombinant cells.GADD153 mRNA gene expression and luciferase activity had a good correlation(r2=0.992,P＜0.01).Conclusion:Compared with the traditional methods for DNA damage in cells,recombinant human lung epithelial cells based on GADD153-LUC can rapidly detect DNA damage caused by lower dose PM2.5.
关键词
细颗粒物/人肺上皮细胞/DNA损伤/Gadd153-lucKey words
Fine particulate matter/Lung epithelial cells/DNA damage/Gadd1 53-luc gene引用本文复制引用
出版年
2024
NETL
NSTL
万方数据