Effect of Lipid Partitioning on Predictions of Acute Toxicity of Oil Sands Process Affected Water to Embryos of Fathead Minnow (Pimephales promelas)

详细信息    查看全文

• 作者：Garrett D. Morandi ; Kun Zhang ; Steve B. Wiseman ; Alberto dos Santos Pereira ; Jonathan W. Martin ; John P. Giesy
• 刊名：Environmental Science & Technology
• 出版年：2016
• 出版时间：August 16, 2016
• 年：2016
• 卷：50
• 期：16
• 页码：8858-8866
• 全文大小：375K
• 年卷期：0
• ISSN：1520-5851

文摘

Dissolved organic compounds in oil sands process affected water (OSPW) are known to be responsible for most of its toxicity to aquatic organisms, but the complexity of this mixture prevents use of traditional bottom-up approaches for predicting toxicities of mixtures. Therefore, a top-down approach to predict toxicity of the dissolved organic fraction of OSPW was developed and tested. Accurate masses (i.e., m/z) determined by ultrahigh resolution mass spectrometry in negative and positive ionization modes were used to assign empirical chemical formulas to each chemical species in the mixture. For each chemical species, a predictive measure of lipid accumulation was estimated by stir-bar sorptive extraction (SBSE) to poly(dimethyl)siloxane, or by partitioning to solid-supported lipid membranes (SSLM). A narcosis mode of action was assumed and the target-lipid model was used to estimate potencies of mixtures by assuming strict additivity. A model developed using a combination of the SBSE and SSLM lipid partitioning estimates, whereby the accumulation of chemicals to neutral and polar lipids was explicitly considered, was best for predicting empirical values of LC50 in 96-h acute toxicity tests with embryos of fathead minnow (Pimephales promelas). Model predictions were within 4-fold of observed toxicity for 75% of OSPW samples, and within 8.5-fold for all samples tested, which is comparable to the range of interlaboratory variability for in vivo toxicity testing.