Identifying bioaccessible suspect toxicants in sediment using adverse outcome pathway directed analysis

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

Since a large number of contaminants are detected in source waters (SWs) and tap waters (TWs), it is important to perform a comprehensive effect evaluation and key contributor identification. A reduced human transcriptome (RHT)-based effect-directed analysis, which consisted of a concentration-dependent RHT to reveal the comprehensive effects and noteworthy pathways and systematic identification of key contributors based on the interactions between compounds and pathway effects, was developed and applied to typical SWs and TWs along the Yangtze River. By RHT, 42% more differentially expressed genes and 33% more pathways were identified in the middle and lower reaches, indicating heavier pollution. Hormone and immune pathways were prioritized based on the detection frequency, sensitivity, and removal efficiency, among which the estrogen receptor pathway was the most noteworthy. Consistent with RHT, estrogenic effects were widespread along the Yangtze River based on in vitro evaluations. Furthermore, 38 of 100 targets, 39 pathway-related suspects, and 16 estrogenic nontargets were systematically identified. Among them, diethylstilbestrol was the dominant contributor, with the estradiol equivalent (EEQ) significantly correlated with EEQ_water. In addition, zearalenone and niclosamide explained up to 54% of the EEQ_water. The RHT-based EDA method could support the effect evaluation, contributor identification, and risk management of micropolluted waters.

Point or non-point source: Toxicity evaluation using m-POCIS and zebrafish embryos in municipal sewage treatment plants and urban waterways

Municipal sewage treatment plants (STPs) have been regarded as an important source of organic contaminants in aquatic environment. To assess the impact of STPs on occurrence and toxicity of STP-associated contaminants in receiving waterways, a novel passive sampler modified from polar organic chemical integrative sampler (m-POCIS) was deployed at the inlet and outlet of a STP and several upstream and downstream sites along a river receiving STP effluent in Guangzhou, China. Eighty-seven contaminants were analyzed in m-POCIS extracts, along with toxicity evaluation using zebrafish embryos. Polycyclic musks were the predominant contaminants in both STP and urban waterways, and antibiotics and current-use pesticides (e.g., neonicotinoids, fiproles) were also ubiquitous. The m-POCIS extracts from downstream sites caused significant deformity in embryos, yet the toxicity could not be explained by the measured contaminants, implying the presence of nontarget stressors. Sewage treatment process substantially reduced embryo deformity, chemical oxygen demand, and contamination levels of some contaminants; however, concentrations of neonicotinoids and fiproles increased after STP treatment, possibly due to the release of chemicals from perturbed sludge. Source identification showed that most of the contaminants found in urban waterways were originated from nonpoint runoff, while cosmetics factories and hospitals were likely point sources for musks and antibiotics, respectively. Although the observed embryo toxicity could not be well explained by target contaminants, the present study showed a promising future of using passive samplers to evaluate chemical occurrence and aquatic toxicity concurrently. Zebrafish embryo toxicity significantly decreased after sewage treatment, but higher toxicity was observed for downstream samples, demonstrating that urban runoff may produce detrimental effects to aquatic life, particularly in rainy season. These results highlight the relevance of monitoring nonpoint source pollution along with boosting municipal sewage treatment infrastructure.

Signposts for Aquatic Toxicity Evaluation in China: Text Mining using Event-Driven Taxonomy within and among Regions

Selection of toxicity endpoints affects outcomes of risk assessment. Scientific decisions based on more holistic evidence is preferable for designing bioassay batteries rather than subjective selections, particularly when systems are poorly understood. Here, we propose a novel event-driven taxonomy (EDT)-based text mining tool to prioritize stressors likely to elicit water quality deterioration. The tool integrated automated literature collection, natural language processing using adverse outcome pathway-based toxicological terminologies and machine learning to classify event drivers (EDs). From aquatic toxicity assessments within China over the past decade, we gathered over 14 000 sources of information. With a dictionary that included 1039 toxicological terms, 15 bioassay-related modes of actions were mapped, yet less than half of the bioassays could be elucidated by available adverse outcome pathways. To fill these mechanistic knowledge gaps, we developed a Naïve Bayesian ED-classifier to annotate apical responses. The classifier's 4-fold cross-validation reached 74% accuracy and labeled 85% bioassays as 26 EDs. Narcosis, estrogen receptor-, and aryl hydrogen receptor-mediators were the major EDs in aquatic systems across China, whereas individual regions had distinct ED fingerprints. The EDT-based tool provides a promising diagnostic strategy to inform region-specific bioassay design and selection for water quality assessments in a big data era.

Multiple Bioassays and Targeted and Nontargeted Analyses to Characterize Potential Toxicological Effects Associated with Sediments of Masan Bay: Focusing on AhR-Mediated Potency

An enhanced, multiple lines of evidence approach was applied to assess potential toxicological effects associated with polluted sediments. Two in vitro bioassays (H4IIE-luc and Vibrio fischeri) and three in vivo bioassays (microalgae: Isochrysis galbana and Phaeodactylum tricornutum; zebrafish embryo: Danio rerio) were applied. To identify causative chemicals in samples, targeted analyses (polycyclic aromatic hydrocarbons (PAHs), styrene oligomers (SOs), and alkylphenols) and nontargeted full-scan screening analyses (FSA; GC- and LC-QTOFMS) were performed. First, great AhR-mediated potencies were observed in midpolar and polar fractions of sediment extracts, but known and previously characterized AhR agonists, including PAHs and SOs could not fully explain the total potencies of samples. Enoxolone was identified as a novel AhR agonist in a highly potent sediment fraction by use of FSA. Enoxolone has a relative potency of 0.13 compared to benzo[a]pyrene (1.0) in the H4IIE-luc bioassay. Nonylphenols associated with membrane damage that influenced the viability of the microalgae were also observed. Finally, inhibitions of bioluminescence of V. fischeri and lethality of D. rerio embryos were strongly related to nonpolar compounds. Overall, the present work addressed assay- and end point-specific variations and sensitivities for potential toxicities of mixture samples, warranting a significant utility of the "multiple lines of evidence" approach in ecological risk assessment.