摘要:
污染物在环境中普遍以混合物的形式存在,其累积毒性与毒性相互作用具有潜在的环境风险。因此,本研究以水环境中普遍存在的氨基糖苷类抗生素(硫酸链霉素、硫酸安普霉素和双氢链霉素)和重金属锌(Zn)为目标污染物,以蛋白核小球藻(Chlorella pyrenoidosa, C. pyrenoidosa)为指示生物,应用直接均分射线法设计3种抗生素与Zn的3个二元混合物体系,应用时间毒性微板分析法系统测定3种抗生素和重金属Zn及其二元混合物射线的时间-浓度-毒性数据,以浓度加和(concentration addition, CA)与独立作用(independent action, IA)为标准加和参考模型,分析混合物毒性相互作用及其随时间变化规律。结果表明,随着暴露时间延长,3种抗生素和重金属Zn对C. pyrenoidosa的毒性逐渐增强;2种模型对3个二元混合物体系的毒性相互作用评估基本一致,即在低浓度区域始终呈现加和作用,而在高浓度区域随暴露时间延长由协同作用逐渐转变为加和作用;而对于同一混合物体系,CA和IA模型预测毒性之间的差距随着浓度增加而增加,且IA预测曲线始终位于CA预测曲线上方,显示了IA模型在评估具有相异组分混合物的毒性时较CA模型接近实际观测值。
Abstract:
Contaminants commonly present in the form of mixtures in the environment, and their cumulative toxicity and toxicity interaction have potential environmental risks. Therefore, aminoglycoside antibiotics (apramycin sulfate, dihydrostreptomycin, streptomycin sulfate) and heavy metal (Zn) commonly existing in aquatic environment were selected as target contaminants, Chlorella pyrenoidosa (C. pyrenoiosa) was taken as a test organism, and a direct equipartition ray method was used to design three binary mixture systems of three antibiotics and Zn in this study. The time-concentration-toxicity data of the three antibiotics, heavy metal Zn and their mixture systems toward C. pyrenoiosa in different exposure time was determined using the time-dependent microplate toxicity analysis method. Concentration addition (CA) and independent action (IA) were used as the standard additive reference models to analyze toxicity interaction within mixture systems and their changings with time. The results showed that toxicity of the three antibiotics and Zn toward C. pyrenoiosa gradually increased with the lengthening of exposure time. The two models, CA and IA, were basically consistent in the assessment of the toxicity interaction within three binary mixtures, i.e., the additive effect was always present in the low-concentration region, while the synergistic effect gradually changed to the additive effect in the high-concentration region with the extension of exposure time. For the same mixtrue system, deviations between the predicted toxicity by CA and IA models increased with the increasing of concentration. The predicted curves by IA were always above those predicted by CA, which indicated the toxicity predicted by IA was more accurate than that predicted by CA when assessing mixtures with different modes of action.