Methylation and Demethylation of Emerging Contaminants Changed Bioaccumulation and Acute Toxicity in Daphnia magna

Abstract

Contaminants of emerging concern (CECs) in the environment undergo various transformations, leading to the formation of transformation products (TPs) with a modified ecological risk potential. Although the environmental significance of TPs is increasingly recognized, there has been relatively little research to understand the influences of such transformations on subsequent ecotoxicological safety. In this study, we used four pairs of CECs and their methylated or demethylated derivatives as examples to characterize changes in bioaccumulation and acute toxicity in Daphnia magna , as a result of methylation or demethylation. The experimental results were further compared to quantitative structure–activity relationship (QSAR) predictions. The methylated counterpart in each pair generally showed greater acute toxicity in D. magna , which was attributed to their increased hydrophobicity. For example, the LC50 values of methylparaben (34.4 ± 4.3 mg L–1) and its demethylated product (225.6 ± 17.3 mg L–1) differed about eightfold in D. magna . The methylated derivative generally exhibited greater bioaccumulation than the demethylated counterpart. For instance, the bioaccumulation of methylated acetaminophen was about 33-fold greater than that of acetaminophen. In silico predictions via QSARs aligned well with the experimental results and suggested an increased persistence of the methylated forms. The study findings underline the consequences of simple changes in chemical structures induced by transformations such as methylation and demethylation and highlight the need to consider TPs to achieve a more holistic understanding of the environmental fate and risks of CECs.

Emerging contaminants: A One Health perspective

“…Quantitative structure-activity relationships (QSARs), one class of numerically analytical models that are developed highlighting the intrinsic correlations with or dependency on a pool of topologically, spectrally, and physicochemically interpretable structural information, can be used as an alternative approach to unravel the toxicologically relevant or environmental influencing mechanism and the structural requirements for transfer, migration, and toxicity of ECs. Furthermore, QSARs developed using advanced statistical methods, such as machine-learning techniques, along with comprehensive datasets encompassing not only structural descriptors but also environmental factors, can effectively predict the environmental fate of ECs, including volatilization, photodegradation, and bioaccumulation.. 492 , 493 Although QSARs were classically applied to the virtue screening of novel effective drugs for human health, the application of QSARs in environmental research arouses new vitality and greatly facilitates understanding the cause for the variance of toxicology and behavior of pollutants and even provides basic data guiding risk management and remediation administration. Nevertheless, the development of QSAR models is typically hindered by several limitations.…”