Effect-directed analysis and mechanism-specific bioassays to assess the toxicity of sediments of the Yangtze River (China)
Bibliographic record
Abstract
The Yangtze River has been a source of life and prosperity for the Chinese people for centuries. The river basin plays an important role for the economics of China and is habitat for a remarkable variety of aquatic species. Since 2009, the Three Gorges Dam (TGD) – located in the upper Yangtze Reaches, is operating at full capacity, with the benefits of flood control, electrical energy production, and improvement of river navigation. However, as a consequence of TGD impoundment, large amounts of pollutants entered the newly established ecosytem – Three Gorges Reservior (TGR). Thus, numerous questions in ecotoxicological research are raised.With respect to the ecotoxciological challenges in the TGR, the Yangtze-Hydro project was cooperated among six Germany institutes, to study on sustainable water management of the Yangtze River. The subproject “MICROTOX” was conducted at the Institute for Environmental Research of RWTH Aachen University, in order to investigate the TGR ecosystem on ecology, ecotoxicology and environmental behavior of organic pollutants, and to assess the risk for human and the ecosystem. The thesis has been carried out as part of MICROTOX, aiming to (i) determinate the hazards potential of the Yangtze River Basin, (ii) provide a detailed insight into the ecological risks of TGR, and (iii) develop a monitoring strategy for future implementation for the Yangtze River. To achieve that, the thesis (1) investigated the ecotoxicological status in the Yangtze River through a literature study, (2) evaluated the hazard potential of the TGR by applying the “triad approach”, and further (3) identified the causitive contaminants using effect directed anylsis (EDA) that were responsible for the environmental relevant endpoints at the regional “hot-spots” sites. Additionally, (4) an ecotoxicological study of the presence of the widely applied herbicides in TGR – propanil, and its metabolite 3,4-dichloroaniline (3,4-DCA), as well as 3,4,3’,4’-tetrachloroazobenzene (TCAB) was conducted with respect to support the regulatory decisions. Lastly, (5) an optimized work-flow for identification of dioxin like compounds was developed with regard to rapid assessment of the AhR-agonists in the areas. The literature study gave an comprehensive overview on the environmental pollution status from upstream of Chongqing until the Yangtze River mouth at the East China Sea. Persistent organic pollutants (POPs) levels such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs) showed comparable levels to other major Chinese and European river, while large share of measured pollutant levels in water and sediments reported in the literature met the current official criteria and related standards in China. However, by considering the pollutant levels, mechanism-specific effect assessment, and adverse effects in aquatic organisms, the sections of Wuhan, Nanjing, and Shanghai Estuary presented a higher pollution level than other sections of the river, indicating a potential ecotoxicological impact on the surrounding areas. Triad approach, integrates chemical analysis, bioassays, and in situ biomarkers, is a holistic assessment method to determine the potential risks associated with environmental samples. Based on the methodology of the triad approach, the ecotoxicological potential in TGR was evaluated. Among the chemical pollutants, PAHs appeared to be the dominant pollutants for the TGR, ranging from 165 – 1,653 ng/g in 2011 and 127 – 590 ng/g in 2013. Adverse effects such as in vitro AhR-mediated activity, mutagenicity and in vivo embryotoxity/teratogenity were detected in the sediments. By applying in vivo bioassays with Danio rerio eggs, it was shown that sediments induced embryotoxic/teratogenic effects, particularly on the cardiovascular system to fish embryos. However, the bioavailability of particle bound pollutants was rather low. Significant genotoxic impacts could be observed on erythrocytes of Pelteobagrus vachellii sampled from Chongqing, as well as from Hanfeng Lake. By accounting of chemical analysis, toxic effects in vitro and in vivo, and in situ biomarkers, it was concluded that adverse effects might be induced to the fish at long term at current environmental relevant concentrations, which will have influence on the overall fitness of fish and other aquatic organisms; Chongqing and Kaixian were taken as regional “hot-spots” with respect to mutagenicity, genotoxicity, and AhR-mediated activity.EDA, featuring a combination of fractionation, chemical analysis and bioassays, is a useful tool to identify causative toxicants in complex environmental samples. Hence, EDA was implemented follow by the triad approach at Chongqing and Kaixian. High molecular weight PAHs accounted for 28 43% of the significant bioactive fractions in Chongqing section, thus presented to be significant AhR-active compounds at these sampling sites. The possible pollution source might come from urban traffic emissions and runoff, coal combustion, as well as intensified shipping activities. In Kaixian area, PAHs, methylated derivatives and heterocyclic polycyclic aromatic compounds (PACs) such as dinaphthofurans were identified as major contributor to the observed AhR-mediated activity, which might come from incomplete combustion and industrial processes or fossil fuels. Biomass burning should be considered since the Kaixian area constitutes a rather rural area. Besides, benzothiazole and its derivatives were identified as suspected toxicants by non-target analysis, which most likely originated from an identified rubber factory nearby the sampling site. The identified compounds were recommended to be included in long-term monitoring strategies in TGR. Moreover, the toxicity of propanil, 3,4-DCA, with a focus on TCAB in mechanism specific cell assays and early vertebrate development was investigated. As TCAB was considered as AhR agonist, an in silico tool has been applied to simulate the binding affinity of the three compounds to the AhR, as well as other cell-based receptors. The toxic equivalency factor (TEF) values of TCAB in AhR-mediated activity were founded ranging four to five orders of magnitude less potent than TCDD based on fish liver cell line (RTL-W1) and rat hepatoma cell line (H4IIE). Thereafter, the experimented TEF is comparable to those well-known dioxin-like chemicals like some mono-ortho coplanar PCBs and large PAHs. Besides, the three compounds were shown to be weak estrogenic compounds. The value of estradiol equivalence factor (EEF) and dihydrotestosterone equivalency factor (DEF) of TCAB were nine to ten orders of magnitude less potent than the corresponding standard compound. In FET, the exposure of Danio rerio indicated significant embryotoxicity and teratogenicity of TCAB. Together with recorded sub-lethal effects, under exposure of TCAB, it might result in adverse outcomes in aquatic systems on the long term. Importantly, it demonstrated that TCAB has a higher toxicity than its parent compounds – propanil and DCA. Hence, risk assessment of pesticides are recommended to include the assessment of the toxicity and fate of their metabolites before they are deliberately brought to the environment.Finally, to enlarge the application of EDA in environmental risk assessment and biological effects monitoring programs, a high-throughput EDA (ht-EDA) workflow – using reversed phase high-performance liquid chromatography (RP-HPLC) fractionation of samples into 96-well microplates, followed by toxicity assessment in the H4IIE Micro-EROD bioassay, and chemical analysis of biologically active fractions was developed. The approach was applied in the extracts of sediment samples collected at TGR the Yangtze River, China as well as the rivers Rhine and Elbe, Germany successfully. Furthermore, by seeding previously adapted suspension-cultured H4IIE cells directly into the microplate used for fractionation, the ht-EDA work-flow was further simplified, and could become the method of choice for the prioritization of environmental contaminants and support for regulatory decisions for TGR.In conclusion, the present study might contribute to long-term monitoring strategies of the Yangtze River Basin, and support the prioritization of contaminants and regulatory decisions in TGR. The recommended monitoring strategies can be applied globaly to other similar river systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".