Giltrap Michelle C, Leaver Michael J, White Kelly, Wilson James G, Rahman Atiqur, Maguire Adrian, Meade Aidan D, Baršiene Janina, Robinson Craig D
School of Food Science and Environmental Health, Technological University Dublin, City Campus, Grangegorman, D07 ADY7 Dublin, Ireland.
Radiation and Environmental Science Centre, Physical to Life Sciences Hub, Technological University Dublin, D08 CKP1 Dublin, Ireland.
Toxics. 2025 Mar 12;13(3):203. doi: 10.3390/toxics13030203.
For many years, there has been increasing concern about the effects of the presence of hazardous substances in the environment. The chemical and biological effect (BE) monitoring of these pollutants has proven difficult due to low environmental concentrations, variable bioavailability, and the generalised nature of ecological responses to these substances. The over- or under-expression of key genes has proven to be useful in understanding the molecular mechanisms of the toxicity of contaminants. This study uses a quantitative PCR array to detect the changes in gene expression in flounder livers after exposure to both laboratory- and field-based contaminants. The model contaminants included 17β-estradiol (E2), 3-methylcholanthrene (3-MC), a commercial mixture of polychlorinated biphenyls (PCB, Arochlor), perfluoroctanoic acid (PFOA), and lindane. Multivariate analysis was used to investigate relationships between higher-organisational-level biomarkers, supporting parameters, and genes. A scoring system enabled the visualisation of biological effect responses and contaminants in field samples. Although gene expression was useful for inferring the pathways of toxicity in this organism, we recommend that this array be used in combination with existing and recommended higher-level biomarkers and should not be used as a replacement for traditional biomarkers currently used in monitoring.
多年来,人们越来越关注环境中有害物质的影响。由于环境浓度低、生物可利用性可变以及生态系统对这些物质反应的普遍性,对这些污染物进行化学和生物效应(BE)监测已被证明具有难度。关键基因的过度表达或表达不足已被证明有助于理解污染物毒性的分子机制。本研究使用定量PCR阵列检测比目鱼肝脏在暴露于实验室和现场污染物后的基因表达变化。模型污染物包括17β-雌二醇(E2)、3-甲基胆蒽(3-MC)、多氯联苯商业混合物(PCB,Arochlor)、全氟辛酸(PFOA)和林丹。多变量分析用于研究高级组织水平生物标志物、支持参数和基因之间的关系。一个评分系统能够直观显示现场样本中的生物效应反应和污染物。虽然基因表达有助于推断该生物体的毒性途径,但我们建议将此阵列与现有的和推荐的高级生物标志物结合使用,而不应将其用作目前监测中使用的传统生物标志物的替代品。