Complex Chemical Mixtures Research Articles

Enabling Automatic Detection of Anomalies in Wastewater: A Highly Simplified Approach to Defining “Normal” in Complex Chemical Mixtures

Wastewater treatment demands management of influent conditions to stabilize biological processes. Generally wastewater collection systems lack advance warning of approaching water parcels with anomalous characteristics, which could then be diverted for testing or pre-treatment. A major challenge in achieving this goal is identifying anomalies against the complex chemical background of wastewaters. This work evaluates unsupervised clustering methods to characterize “normal” wastewater characteristics, using >17 months of 10-min resolution absorbance spectrometry data collected at an operating wastewater treatment facility. Comparison of results using K-means, GMM, Hierarchical, and DBSCAN clustering shows minimal intra-cluster variability achieved using K-means. The four K-means clusters include three representing 99% of samples, with the remaining cluster (<0.3% of samples) representing atypical measurements, demonstrating utility in identifying both underlying modalities of wastewater characteristics and outliers. K-means clustering provides a better separation than grouping based on factors such as month, precipitation, or flow (with 25% overlap at 1-σ level, compared to 93, 93, and 83%, respectively) and enables identification of patterns that are not visible in factor-driven grouping, e.g., shows that summer and November months have a characteristic type of behavior. When evaluated with respect to wastewater influent changes occurring during the SARS-CoV-2 pandemic, the K-means approach shows a distinct change in strength of diurnal patterns when compared to non-pandemic periods during the same season. This method may therefore be useful both as a tool for fast anomaly detection in wastewaters, contributing to improved infrastructure resilience, as well for providing overall analysis of temporal patterns in wastewater characteristics.

Chemical contaminant exposures assessed using silicone wristbands among occupants in office buildings in the USA, UK, China, and India.

Little is known about chemical contaminant exposures of office workers in buildings globally. Complex mixtures of harmful chemicals accumulate indoors from building materials, building maintenance, personal products, and outdoor pollution. We evaluated exposures to 99 chemicals in urban office buildings in the USA, UK, China, and India using silicone wristbands worn by 251 participants while they were at work. Here, we report concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and other brominated flame retardants (BFRs), organophosphate esters (OPEs), phthalates and phthalate alternatives, pesticides, and polycyclic aromatic hydrocarbons (PAHs). First, we found major differences in office worker chemical exposures by country, some of which can be explained by regulations and use patterns. For example, exposures to several pesticides were substantially higher in India where there were fewer restrictions and unique malaria challenges, and exposures to flame retardants tended to be higher in the USA and UK where there were historic, stringent furniture flammability standards. Higher exposures to PAHs in China and India could be due to high levels of outdoor air pollution that penetrates indoors. Second, some office workers were still exposed to legacy PCBs, PBDEs, and pesticides, even decades after bans or phase-outs. Third, we identified exposure to a contemporary PCB that is not covered under legacy PCB bans due to its presence as an unintentional byproduct in materials. Fourth, exposures to novel BFRs, OPEs, and other chemicals commonly used as substitutes to previously phased-out chemicals were ubiquitous. Fifth, some exposures were influenced by individual factors, not just countries and buildings. Phthalate exposures, for example, were related to personal care product use, country restrictions, and building materials. Overall, we found substantial country differences in chemical exposures and continued exposures to legacy phased-out chemicals and their substitutes in buildings. These findings warrant further research on the role of chemicals in office buildings on worker health.

Groundwater remediation using Magnesium–Aluminum alloys and in situ layered doubled hydroxides

In situ remediation of groundwater by zerovalent iron (ZVI)-based technology faces the problems of rapid passivation, fast agglomeration, limited range of pollutants and secondary contamination. Here a new concept of Magnesium-Aluminum (Mg-Al) alloys and in situ layered double hydroxides on is proposed for the degradation and removal of a wide variety of inorganic and organic pollutants from groundwater. The Mg-Al alloy provides the electrons for the chemical reduction and/or the degradation of pollutants while released Mg2+, Al3+ and OH- ions react to generate in situ LDH precipitates, incorporating other divalent and trivalent metals and oxyanions pollutants and further adsorbing the micropollutants. The Mg-Al alloy outperforms ZVI for treating acidic, synthetic groundwater samples contaminated by complex chemical mixtures of heavy metals (Cd2+, Cr6+, Cu2+, Ni2+ and Zn2+), nitrate, AsO33-, methyl blue, trichloroacetic acid and glyphosate. Specifically, the Mg-Al alloy achieves removal efficiency ≥99.7% for these multiple pollutants at concentrations ranging between 10 and 50mgL-1 without producing any secondary contaminants. In contrast, ZVI removal efficiency did not exceed 90% and secondary contamination up to 220mgL-1 Fe was observed. Overall, this study provides a new alternative approach to develop efficient, cost-effective and green remediation for water and groundwater.

Assessing integrated biomarkers of triplefin fish Forsterygion capito inhabiting contaminated marine water - A multivariate approach

The presence of multiple chemicals in aquatic ecosystems makes evaluation of their real impact on the biota difficult. Integrated biomarkers are therefore needed to evaluate how these chemicals contribute to environmental degradation. The aims of the present study were to evaluate responses to and effects of marine pollution using a series of biomarkers through multivariate analyses. Transcriptional responses of cyp1a (cytochrome P450), mt (metallothionein), vtg (vitellogenin) and cyp19b (cytochrome P450 aromatase); branchial and hepatic histological alterations; and Fulton condition factors (CF) were evaluated, as well as the metals and polycyclic aromatic hydrocarbons present in Forsterygion capito in Auckland, New Zealand. Sites were selected along a contamination gradient: four highly contaminated sites and four less contaminated. Molecular responses with a higher relative expression of the mt and cyp1a genes were detected at a highly contaminated site (Panmure). Several histological lesion types were found in the livers of fish inhabiting both types of sites, but gill lesions were present primarily at highly contaminated sites. In terms of general health status, the lowest CF values were overwhelmingly found in fish from the same site (Panmure). The multivariate approach revealed that telangiectasia and hyperplasia were associated with the presence of chemicals, and these showed negative associations with the CF values, with fish from three highly contaminated sites being most affected. In conclusion, the multivariate approach helped to integrate these biological markers in this blennioid fish, thus providing a more holistic view of the complex chemical mixtures involved. Future studies should implement these analyses.

Online Coupling of Liquid Chromatography with Fourier Transform Ion Cyclotron Resonance Mass Spectrometry at 21 T Provides Fast and Unique Insight into Crude Oil Composition.

High magnetic field Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry provides the highest mass resolving power and mass measurement accuracy for detailed characterization of complex chemical mixtures. Here, we report the coupling of online liquid chromatography of complex mixtures with a 21 tesla FT-ICR mass spectrometer. The high magnetic field enables large ion populations to be analyzed for each spectrum for a high dynamic range, with 3.2 million mass resolving power at m/z 400 (6.2 s transient duration) or 1.6 million (3.1 s transient duration) while maintaining high mass accuracy for molecular formula assignment (root-mean-square assignment error < 0.150 ppm). Thousands of unique elemental compositions are assigned per mass spectrum, which can be grouped by the heteroatom class, double bond equivalents (the number of rings and double bonds to carbon), and carbon number. Figures of merit are discussed, as well as characterization of an Arabian heavy vacuum gas oil in terms of the ring number, compound class, double bond equivalents, and ion type. Consideration of elemental composition and retention order provides additional structural information.

Sub-lethal effects of soil multiple contamination on the avoidance behaviour of Eisenia fetida

Natural ecosystems are frequently exposed to complex mixtures of different chemicals. However, the environmental risk assessment is mainly based on data from individual substances. In this study, the individual and combined effects on the terrestrial earthworm E. fetida exposed to the anionic surfactant sodium lauryl ether sulphate (SLES) and the pesticides chlorpyrifos (CPF) and imidacloprid (IMI) were investigated, by using the avoidance behaviour as endpoint. Earthworms were exposed to a soil artificially contaminated with five sub-lethal concentrations of each contaminant, both as single substances and in combination of binary and ternary mixtures. Overall results showed that IMI provoked the highest avoidance effect on earthworms, with a concentration value that induced an avoidance rate of 50% of treated organisms (AC50) of 1.30 mg/kg, followed by CPF (AC50 75.26 mg/kg) and SLES (AC50 139.67 mg/kg). The application of the Combination Index (CI) method, indicated that a deviation from the additive response occurred for most of the tested chemical mixtures, leading to synergistic or antagonistic avoidance responses. Synergistic effects were produced by the exposure to the two lowest concentrations of the CPF+IMI mixture, and by the highest concentrations of SLES+CPF and SLES+CPF+IMI mixtures. On the contrary, antagonistic effects were observed at the lowest concentrations of the binary mixtures containing the SLES and at almost all the tested concentrations of the SLES+CPF+IMI mixture (with the exception of the highest tested concentration). These results show that the avoidance test is suitable to assess the detrimental effects exerted on earthworms by chemical mixtures in soil ecosystems and the use of behavioural endpoints can increase the ecological significance of environmental risk assessment procedures.

Food and nutrition-related disease

Plants and fungi used by humans for food represent complex mixtures of chemicals, some of which have dose-dependent neurotoxic potential that may trigger acute, delayed or long-latency neurological disease. Whether or how botanical chemicals trigger nervous system disorders, including their participation in sporadic neurodegenerative diseases, is a growing area of research interest in environmental neurology. Acute-onset disorders include hypoglycemic encephalopathy induced in hungry children who ingest immature fruit of the Soapberry family (Sapindaceae), notably lychee (Litchi sinenesis) in Asia or ackee (B.

Modelling the attenuation of flowback chemicals for a soil-groundwater pathway from a hypothetical spill accident

Flowback water from shale gas operations contains formation-derived compounds, including trace metals, radionuclides, and organics. While accidental releases from storage tanks with flowback water are low-probability events if multiple containment barriers are put in place, they cannot be entirely excluded. Here the natural attenuation potential of deep unsaturated zones and groundwater was explored using predictive modelling involving a hypothetical leak from a storage tank. Actual chemical concentrations from flowback water at two shale gas wells with contrasting salinity (12,300 and 105,000 ppm TDS) in the Beetaloo Sub-basin (Northern Territory, Australia) served as input to the one-dimensional HYDRUS model for simulating chemical transport through the unsaturated zone, with groundwater at 50 and 100 m depth, respectively. Subsequent chemical transport in groundwater involved the use of a three-dimensional analytical transport model. For a total of 63 chemicals the long-term attenuation from dilution and dispersion in unsaturated sediments and groundwater was calculated. Predicted environmental concentrations for aquatic receptors were compared with no-effect levels of individual chemicals to derive risk quotients (RQ) and identify chemicals of no concern to ecosystem health (i.e. RQ <1). Except for salinity and radium-228 in one of the two wells, RQ < 1 for all other chemicals. The initial approach considered testing of toxicity to individual chemicals only. When direct toxicity assessments (DTAs) were used to account for effects of chemical mixtures, the required DTA-derived safe dilution factor for 95% species protection was 1.8 to 2.5 times higher than the dilution factor accounting for dispersion and dilution only. Accounting for biodegradation, sorption and radioactive decay decreased chemical concentrations in unsaturated sediments to safe levels using the DTA for all chemicals. The study highlighted the importance of incorporating DTA in chemical risk assessments involving complex chemical mixtures. Improved understanding of fate and transport of flowback chemicals will help effectively manage water-quality risks associated with shale gas extraction.

Quantitative but not qualitative flavor recognition impairments in COVID-19 patients

BackgroundSmell and taste dysfunctions (STDs) are symptoms associated with COVID-19 syndrome, even if their incidence is still uncertain and variable.AimsIn this study, the effects of SARS-CoV-2 infection on chemosensory function have been investigated using both a self-reporting questionnaire on smell and flavor perception, and a simplified flavor test.MethodsA total of 111 subjects (19 hospitalized [HOS] and 37 home-isolated [HI] COVID-19 patients, and 55 healthy controls [CTRL]) were enrolled in the study. They received a self-evaluation questionnaire and a self-administered flavor test kit. The flavor test used consists in the self-administration of four solutions with a pure olfactory stimulus (coffee), a mixed olfactory-trigeminal stimulus (peppermint), and a complex chemical mixture (banana).ResultsAfter SARS-CoV-2 infection, HOS and HI patients reported similar prevalence of STDs, with a significant reduction of both smell and flavor self-estimated perception. The aromas of the flavor test were recognized by HI and HOS COVID-19 patients similarly to CTRL; however, the intensity of the perceived aromas was significantly lower in patients compared to controls.ConclusionData reported here suggests that a chemosensory impairment is present after SARS-CoV-2 infection, and the modified “flavor test” could be a novel self-administering objective screening test to assess STDs in COVID-19 patients.Clinical trial registration no. NCT04840966; April 12, 2021, retrospectively registered

Identification of Specific Substances in the FAIMS Spectra of Complex Mixtures Using Deep Learning.

High-field asymmetric ion mobility spectrometry (FAIMS) spectra of single chemicals are easy to interpret but identifying specific chemicals within complex mixtures is difficult. This paper demonstrates that the FAIMS system can detect specific chemicals in complex mixtures. A homemade FAIMS system is used to analyze pure ethanol, ethyl acetate, acetone, 4-methyl-2-pentanone, butanone, and their mixtures in order to create datasets. An EfficientNetV2 discriminant model was constructed, and a blind test set was used to verify whether the deep-learning model is capable of the required task. The results show that the pre-trained EfficientNetV2 model completed convergence at a learning rate of 0.1 as well as 200 iterations. Specific substances in complex mixtures can be effectively identified using the trained model and the homemade FAIMS system. Accuracies of 100%, 96.7%, and 86.7% are obtained for ethanol, ethyl acetate, and acetone in the blind test set, which are much higher than conventional methods. The deep learning network provides higher accuracy than traditional FAIMS spectral analysis methods. This simplifies the FAIMS spectral analysis process and contributes to further development of FAIMS systems.

Demonstration of an aggregated biomarker response approach to assess the impact of point and diffuse contaminant sources in feral fish in a small river case study

The assessment of the exposure of aquatic wildlife to complex environmental mixtures of chemicals originating from both point and diffuse sources and evaluating the potential impact thereof constitutes a significant step towards mitigating toxic pressure and the improvement of ecological status. In the current proof-of-concept study, we demonstrate the potential of a novel Aggregated Biomarker Response (ABR) approach involving a comprehensive set of biomarkers to identify complex exposure and impacts on wild brown trout (Salmo trutta fario). Our scenario used a small lowland river in Germany (Holtemme river in the Elbe river catchment) impacted by two wastewater treatment plants (WWTP) and diffuse agricultural runoff as a case study. The trout were collected along a pollution gradient (characterised in a parallel study) in the river. Compared to fish from the reference site upstream of the first WWTP, the trout collected downstream of the WWTPs showed a significant increase in micronucleus formation, phase I and II enzyme activities, and oxidative stress parameters in agreement with increasing exposure to various chemicals. By integrating single biomarker responses into an aggregated biomarker response, the two WWTPs' contribution to the observed toxicity could be clearly differentiated. The ABR results were supported by chemical analyses and whole transcriptome data, which revealed alterations of steroid biosynthesis and associated pathways, including an anti-androgenic effect, as some of the key drivers of the observed toxicity. Overall, this combined approach of in situ biomarker responses complemented with molecular pathway analysis allowed for a comprehensive ecotoxicological assessment of fish along the river. This study provides evidence for specific hazard potentials caused by mixtures of agricultural and WWTP derived chemicals at sublethal concentrations. Using aggregated biomarker responses combined with chemical analyses enabled an evidence-based ranking of sites with different degrees of pollution according to toxic stress and observed effects.

Unravelling cocktail effects of complex chemical mixtures using integrated -omics: a case study with agricultural fungicides

Unravelling cocktail effects of complex chemical mixtures using integrated -omics: a case study with agricultural fungicides

Plastic Products Leach Chemicals That Induce In Vitro Toxicity under Realistic Use Conditions.

Plastic products contain complex mixtures of extractable chemicals that can be toxic. However, humans and wildlife will only be exposed to plastic chemicals that are released under realistic conditions. Thus, we investigated the toxicological and chemical profiles leaching into water from 24 everyday plastic products covering eight polymer types. We performed migration experiments over 10 days at 40 °C and analyzed the migrates using four in vitro bioassays and nontarget high-resolution mass spectrometry (UPLC-QTOF-MSE). All migrates induced baseline toxicity, 22 an oxidative stress response, 13 antiandrogenicity, and one estrogenicity. Overall, between 17 and 8681 relevant chemical features were present in the migrates. In other words, between 1 and 88% of the plastic chemicals associated with one product were migrating. Further, we tentatively identified ∼8% of all detected features implying that most plastic chemicals remain unknown. While low-density polyethylene, polyvinyl chloride, and polyurethane induced most toxicological endpoints, a generalization for other materials is not possible. Our results demonstrate that plastic products readily leach many more chemicals than previously known, some of which are toxic in vitro. This highlights that humans are exposed to many more plastic chemicals than currently considered in public health science and policies.

A Deep Dive into the Complex Chemical Mixture and Toxicity of Tire Wear Particle Leachate in Fathead Minnow.

The ecological impact of tire wear particles in aquatic ecosystems is a growing environmental concern. We combined toxicity testing, using fathead minnow (Pimephales promelas) embryos, with nontarget high‐resolution liquid chromatography Orbitrap mass spectrometry to characterize the toxicity and chemical mixture of organic chemicals associated with tire particle leachates. We assessed: 1) exposure to tire particle leachates after leaching for 1‐, 3‐, and 10‐d; and 2) the effect of the presence and absence of small tire particulates in the leachates. We observed a decrease in embryonic heart rates, hatching success, and lengths, as well as an increase in the number of embryos with severe deformities and diminished eye and body pigmentation, after exposure to the leachates. Overall, there was a pattern whereby we observed more toxicity in the 10‐d leachates, and greater toxicity in unfiltered leachates. Redundancy analysis showed that several benzothiazoles and aryl‐amines were correlated with the toxic effects observed in the embryos. These included benzothiazole, 2‐aminobenzothiazole, 2‐mercaptobenzothiazole, N,N′‐diphenylguanidine, and N,N′‐diphenylurea. However, many other chemicals characterized as unknowns are likely to also play a key role in the adverse effects observed. Our study provides insight into the types of chemicals likely to be important toxicological drivers in tire leachates, and improves our understanding of the ecotoxicological impacts of tire wear particles. Environ Toxicol Chem 2022;41:1144–1153. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Anaerobic digestion of sewage sludge has no effect on glucocorticoid and anti-progestagenic activity but increases estrogenicity three-fold

Although the recovery and beneficial reuse of organic matter and nutrients from sludge represents an important move towards environmental sustainability, the accumulation of chemicals in biosolid-amended soils could pose serious environmental and human health risks. However, (eco)toxicological profiling of complex chemical mixtures in biosolids is currently limited. In particular, the effect of anaerobic digestion (AD), the most common stabilization process for sewage sludge, on the (eco)toxicity of those complex mixtures is poorly studied. In this work, we fill this research gap by applying an effect-based monitoring approach to screen sludge samples (n = 4) from a full-scale sewage treatment plant before and after conventional mesophilic (37 °C) AD using a battery of cell-based in vitro bioassays for four types of hormonal activity: estrogenic, androgenic, progestagenic and glucocorticoid activity, both in agonist and antagonist modes. We detected estrogenic, glucocorticoid and anti-progestagenic activity in all sludge samples. The glucocorticoid and anti-progestagenic activity remained mostly unchanged after AD treatment, but estrogenicity increased three-fold, likely as a result of bioactivation processes in the digestor. This study presents the first report on the concentration and fate of glucocorticoid and anti-progestagenic activity in AD. Future research should apply bioanalytical tools to a wider range of sludge samples to get a better understanding of the typical hormonal activity in sludge and develop effect-based trigger (EBT) values for biosolids to help interpret the risk posed by the hormonal activity detected in sludge.

Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery.

Background:Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.Objectives:We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.Discussion:The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome—the totality of the biologically active exposures relevant to disease development—through coupling biochemical receptor-binding assays with affinity purification–mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.Conclusions:Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327

A targeted transcriptomics approach for the determination of mixture effects of pesticides

While real-life exposure occurs to complex chemical mixtures, toxicological risk assessment mostly focuses on individual compounds. There is an increasing demand for in vitro tools and strategies for mixture toxicity analysis. Based on a previously established set of hepatotoxicity marker genes, we analyzed mixture effects of non-cytotoxic concentrations of different pesticides in exposure-relevant binary mixtures in human HepaRG hepatocarcinoma cells using targeted transcriptomics. An approach for mixture analysis at the level of a complex endpoint such as a transcript pattern is presented, including mixture design based on relative transcriptomic potencies and similarities. From a mechanistic point of view, goal of the study was to evaluate combinations of chemicals with varying degrees of similarity in order to determine whether differences in mechanisms of action lead to different mixtures effects. Using a model deviation ratio-based approach for assessing mixture effects, it was revealed that most data points are consistent with the assumption of dose addition. A tendency for synergistic effects was only observed at high concentrations of some combinations of the test compounds azoxystrobin, cyproconazole, difenoconazole, propiconazole and thiacloprid, which may not be representative of human real-life exposure. In summary, the findings of our study suggest that, for the pesticide mixtures investigated, risk assessment based on the general assumption of dose addition can be considered sufficiently protective for consumers. The way of data analysis presented in this paper can pave the way for a more comprehensive use of multi-gene expression data in experimental studies related to mixture toxicity.

Ionic Liquid-Based Quartz Crystal Microbalance Sensors for Organic Vapors: A Tutorial Review

Organic vapor sensors are used in diverse applications ranging from environmental monitoring to biomedical diagnostics. Among a number of these sensors, quartz crystal microbalance (QCM) sensors prepared by coating ionic liquids (ILs) or their composites are promising devices for the analysis of volatile organic compounds (VOCs) in complex chemical mixtures. Ionic liquids are remarkable materials, which exhibit tunable physico-chemical properties, chemical and thermal stability, multiple interactions with diverse group of molecules, and enormous structural variability. Moreover, ILs exhibit viscoelastic properties, and hence these materials are ideal for creation of QCM virtual sensor arrays. While the scientific literature on IL-coated QCM sensors is rapidly growing, there is still much to learn. This manuscript provides a comprehensive review on the development of IL-coated QCM sensors and multi-sensor arrays as well as their applications for the analysis of VOCs in complex mixtures. Furthermore, IL-coated QCM virtual sensor arrays and their applications are presented. A short overview of some of the QCM designs, future research areas, and recommendations are also discussed. This short review is a necessary first step towards standardization and further development of QCM for the analysis of VOCs.

Time-dependent biological responses of juvenile yellow perch (Perca flavescens) exposed in situ to a major urban effluent

Municipal wastewater treatment plant (WWTP) effluents are significant sources of organic and inorganic pollutants to aquatic ecosystems. Several studies have shown that the health of aquatic organisms can be adversely impacted following exposure to these complex chemical mixtures. The objective of this study was to examine the effects of in situ exposure in the St. Lawrence River (QC, Canada) of juvenile yellow perch (Perca flavescens) to a major WWTP effluent. Perch were caged at a reference site in the St. Lawrence River and downstream of a WWTP effluent-influenced site for one, three, and six weeks. Fish kept in controlled laboratory setting were also examined at the beginning of the experiment to evaluate the potential effect of caging on fish. Liver metabolites and gill oxidative stress biomarkers as well as body condition of perch were investigated at four time points (zero, one, three, and six weeks). Nitrogen (δ15N) and carbon (δ13C) stable isotopes as well as tissue concentrations of halogenated flame retardants and trace metals were also analyzed. Results indicated that body condition of perch caged in the effluent increased after three and six weeks of exposure compared to that of reference fish. Perch caged at the WWTP effluent-influenced site also had higher muscle δ13C and slightly depleted muscle δ15N after three and six weeks of exposure, suggesting differences in sewage-derived nutrient assimilation between sites. Concentrations of Σ34 polybrominated diphenyl ether (PBDE) were 2-fold greater in perch exposed downstream of the WWTP compared to those caged at the reference site. Metal concentrations in kidney of perch after three weeks of exposure were significantly lower at the effluent-influenced site. Kidney concentrations of Cd, Cu, Se, As, Zn and Fe were, however, higher after six weeks of exposure, supporting that metal accumulation is time- and element-specific. The metabolomes of perch from the effluent-influenced and reference sites were similar, but were distinct from the laboratory control fish, suggesting a caging effect on fish. Seven liver metabolites (glucose, malate, fumarate, glutamate, creatinine, histamine, and oxypurinol) were significantly more abundant in perch from cages than in the laboratory control perch. The combination of metabolomics and physiological variables provides a powerful tool to improve our understanding of the mechanisms of action of complex environmental pollutant mixtures in wild fish.

An eight-compound mixture but not corresponding concentrations of individual chemicals induces triglyceride accumulation in human liver cells

In real life, organisms are exposed to complex mixtures of chemicals at low concentration levels, whereas research on toxicological effects is mostly focused on single compounds at comparably high doses. Mixture effects deviating from the assumption of additivity, especially synergistic effects, are of concern. In an adverse outcome pathway (AOP)-guided manner, we analyzed the accumulation of triglycerides in human HepaRG liver cells by a mixture of eight steatotic chemicals (amiodarone, benzoic acid, cyproconazole, flusilazole, imazalil, prochloraz, propiconazole and tebuconazole), each present below its individual effect concentration at 1–3 μM. Pronounced and significantly enhanced triglyceride accumulation was observed with the mixture, and similar effects were seen at the level of pregnane-X-receptor activation, a molecular initiating event leading to hepatic steatosis. Transcript pattern analysis indicated subtle pro-steatotic changes at low compound concentrations, which did not exert measurable effects on cellular triglycerides. Mathematical modeling of mixture effects indicated potentially more than additive behavior using a model for compounds with similar modes of action. The present data underline the usefulness of AOP-guided in vitro testing for the identification of mixture effects and highlight the need for further research on chemical mixtures and harmonization of data interpretation of mixture effects.