Chemicals in the environment occur in mixtures rather than as individual entities. Environmental quality monitoring thus faces the challenge to comprehensively assess a multitude of contaminants and ...potential adverse effects. Effect-based methods have been suggested as complements to chemical analytical characterisation of complex pollution patterns. The regularly observed discrepancy between chemical and biological assessments of adverse effects due to contaminants in the field may be either due to unidentified contaminants or result from interactions of compounds in mixtures. Here, we present an interlaboratory study where individual compounds and their mixtures were investigated by extensive concentration-effect analysis using 19 different bioassays. The assay panel consisted of 5 whole organism assays measuring apical effects and 14 cell- and organism-based bioassays with more specific effect observations. Twelve organic water pollutants of diverse structure and unique known modes of action were studied individually and as mixtures mirroring exposure scenarios in freshwaters. We compared the observed mixture effects against component-based mixture effect predictions derived from additivity expectations (assumption of non-interaction). Most of the assays detected the mixture response of the active components as predicted even against a background of other inactive contaminants. When none of the mixture components showed any activity by themselves then the mixture also was without effects. The mixture effects observed using apical endpoints fell in the middle of a prediction window defined by the additivity predictions for concentration addition and independent action, reflecting well the diversity of the anticipated modes of action. In one case, an unexpectedly reduced solubility of one of the mixture components led to mixture responses that fell short of the predictions of both additivity mixture models. The majority of the specific cell- and organism-based endpoints produced mixture responses in agreement with the additivity expectation of concentration addition. Exceptionally, expected (additive) mixture response did not occur due to masking effects such as general toxicity from other compounds. Generally, deviations from an additivity expectation could be explained due to experimental factors, specific limitations of the effect endpoint or masking side effects such as cytotoxicity in in vitro assays. The majority of bioassays were able to quantitatively detect the predicted non-interactive, additive combined effect of the specifically bioactive compounds against a background of complex mixture of other chemicals in the sample. This supports the use of a combination of chemical and bioanalytical monitoring tools for the identification of chemicals that drive a specific mixture effect. Furthermore, we demonstrated that a panel of bioassays can provide a diverse profile of effect responses to a complex contaminated sample. This could be extended towards representing mixture adverse outcome pathways. Our findings support the ongoing development of bioanalytical tools for (i) compiling comprehensive effect-based batteries for water quality assessment, (ii) designing tailored surveillance methods to safeguard specific water uses, and (iii) devising strategies for effect-based diagnosis of complex contamination.
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•Multiple mixtures of water pollutants demonstrated combined effects across bioassays.•Bioassays detected joint responses from active components against a background.•Mixture effects were in agreement with an additivity assumption.•Jointly, apical and receptor-based assays retrieved mixture components bioactivities.
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•Screening of 610 chemicals in 445 stream water samples enables mixture assessment.•Chemical footprints: 504 detected compounds impact aquatic life in European streams.•74 % of the ...sites exceed risk thresholds for adverse effects to aquatic organisms.•Invertebrates most affected; over 70 chemicals surpass chronic risk thresholds.•Urban discharge doesn't correlate with footprints due to effluent-specific quality.
There is increasing awareness that chemical pollution of freshwater systems with complex mixtures of chemicals from domestic sources, agriculture and industry may cause a substantial chemical footprint on water organisms, pushing aquatic ecosystems outside the safe operating space. The present study defines chemical footprints as the risk that chemicals or chemical mixtures will have adverse effects on a specific group of organisms. The aim is to characterise these chemical footprints in European streams based on a unique and uniform screening of more than 600 chemicals in 445 surface water samples, and to derive site- and compound-specific information for management prioritisation purposes. In total, 504 pesticides, biocides, pharmaceuticals and other compounds have been detected, including frequently occurring and site-specific compounds with concentrations up to 74 µg/L. Key finding is that three-quarter of the investigated sites in 22 European river basins exceed established thresholds for chemical footprints in freshwater, leading to expected acute or chronic impacts on aquatic organisms. The largest footprints were recorded on invertebrates, followed by algae and fish. More than 70 chemicals exceed thresholds of chronic impacts on invertebrates. For all organism groups, pesticides and biocides were the main drivers of chemical footprints, while mixture impacts were particularly relevant for invertebrates. No clear significant correlation was found between chemical footprints and the urban discharge fractions, suggesting that effluent-specific quality rather than the total load of treated wastewater in the aquatic environment and the contribution of diffuse sources, e.g. from agriculture, determine chemical footprints.
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•Four types of tubes used for human samples show specific contamination patterns.•A medical-grade tube shows a lower contamination level than three other types.•A cleaning procedure ...reduces contamination, but releases specific contaminants.•Several polymer additives and surfactants were identified in the sample tubes.•The obtained dataset is available as a reference of potential background contamination.
Controlling and minimising background contamination is crucial for maintaining a high quality of samples in human biomonitoring targeting organic chemicals. We assessed the contamination of three previous types and one newly introduced medical-grade type of sample tubes used for storing human body fluids at the German Environmental Specimen Bank. Aqueous extracts from these tubes were analysed by non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) before and after a dedicated cleaning procedure. After peak detection using MZmine, Bayesian hypothesis testing was used to group peaks into those originating either from instrumental and laboratory background contamination, or actual tube contaminants, based on if their peak height was reduced, increased or not affected by the cleaning procedure. For all four tube types 80–90% of the 2475 peaks (1549 in positive and 926 in negative mode) were assigned to laboratory/instrumental background, which we have to consider as potential sample tube contaminants. Among the tube contaminants, results suggest a considerable difference in the contaminant peak inventory and the absolute level of contamination among the different sample tube types. The cleaning procedure did not affect the largest fraction of peaks (50–70%). For the medical grade tubes, the removal of contaminants by the cleaning procedure was strongest compared to the previous tubes, but in all cases a small fraction increased in intensity after cleaning, probably due to a release of oligomers or additives. The identified laboratory background contaminants were mainly semi-volatile polymer additives such as phthalates and phosphate esters. A few compounds could be assigned solely as tube-specific contaminants, such as N,N-dibutylformamide and several constituents of the oligomeric light stabiliser Tinuvin-622. A cleaning procedure before use is an effective way to standardise the used sample tubes and minimises the background contamination, and therefore increases sample quality and therewith analytical results.
Non-target screening (NTS) including suspect screening with high resolution mass spectrometry has already shown its feasibility in detecting and identifying emerging contaminants, which subsequently ...triggered exposure mitigating measures. NTS has a large potential for tasks such as effective evaluation of regulations for safe marketing of substances and products, prioritization of substances for monitoring programmes and assessment of environmental quality. To achieve this, a further development of NTS methodology is required, including: (i) harmonized protocols and quality requirements, (ii) infrastructures for efficient data management, data evaluation and data sharing and (iii) sufficient resources and appropriately trained personnel in the research and regulatory communities in Europe. Recommendations for achieving these three requirements are outlined in the following discussion paper. In particular, in order to facilitate compound identification it is recommended that the relevant information for interpretation of mass spectra, as well as about the compounds usage and production tonnages, should be made accessible to the scientific community (via open-access databases). For many purposes, NTS should be implemented in combination with effect-based methods to focus on toxic chemicals.
Suspended particulate matter (SPM) plays an important role in the fate of organic micropollutants in rivers during rain events, when sediments are remobilized and turbid runoff components enter the ...rivers. Under baseflow conditions, the SPM concentration is low and the contribution of SPM-bound contaminants to the overall risk of organic contaminants in rivers is assumed to be negligible. To challenge this assumption, we explored if SPM may act as a source or sink for all or specific groups of organic chemicals in a small river. The concentrations of over 600 contaminants and the mixture effects stemming from all chemicals in in vitro bioassays were measured for river water, SPM, and the surface sediment after solid-phase extraction or exhaustive solvent extraction. The bioavailable fractions of chemicals and mixture effects were estimated after passive equilibrium sampling of enriched SPM slurries and sediments in the lab. Dissolved compounds dominated the total chemical burden in the water column (water plus SPM) of the river, whereas SPM-bound chemicals contributed up to 46% of the effect burden even if the SPM concentration in rivers was merely 1 mg/L. The equilibrium between water and SPM was still not reached under low-flow conditions with SPM as a source of water contamination. The ratios of SPM-associated to sediment-associated neutral and hydrophobic chemicals as well as the ratios of the mixture effects expressed as bioanalytical equivalent concentrations were close to 1, suggesting that the surface sediment can be used as a proxy for SPM under baseflow conditions when the sampling of a large amount of water to obtain sufficient SPM cannot be realized.
•CECscreen is an annotation database for CECs in human biological samples.•CECscreen includes 70,397 structures, 306,071 simulated metabolites, and metadata.•CECscreen is openly accessible and is ...incorporated into Metfrag.•CECscreen facilitates large-scale detection of chemicals in exposome research.
Chemicals of Emerging Concern (CECs) include a very wide group of chemicals that are suspected to be responsible for adverse effects on health, but for which very limited information is available. Chromatographic techniques coupled with high-resolution mass spectrometry (HRMS) can be used for non-targeted screening and detection of CECs, by using comprehensive annotation databases. Establishing a database focused on the annotation of CECs in human samples will provide new insight into the distribution and extent of exposures to a wide range of CECs in humans.
This study describes an approach for the aggregation and curation of an annotation database (CECscreen) for the identification of CECs in human biological samples.
The approach consists of three main parts. First, CECs compound lists from various sources were aggregated and duplications and inorganic compounds were removed. Subsequently, the list was curated by standardization of structures to create “MS-ready” and “QSAR-ready” SMILES, as well as calculation of exact masses (monoisotopic and adducts) and molecular formulas. The second step included the simulation of Phase I metabolites. The third and final step included the calculation of QSAR predictions related to physicochemical properties, environmental fate, toxicity and Absorption, Distribution, Metabolism, Excretion (ADME) processes and the retrieval of information from the US EPA CompTox Chemicals Dashboard.
All CECscreen database and property files are publicly available (DOI: https://doi.org/10.5281/zenodo.3956586). In total, 145,284 entries were aggregated from various CECs data sources. After elimination of duplicates and curation, the pipeline produced 70,397 unique “MS-ready” structures and 66,071 unique QSAR-ready structures, corresponding with 69,526 CAS numbers. Simulation of Phase I metabolites resulted in 306,279 unique metabolites. QSAR predictions could be performed for 64,684 of the QSAR-ready structures, whereas information was retrieved from the CompTox Chemicals Dashboard for 59,739 CAS numbers out of 69,526 inquiries. CECscreen is incorporated in the in silico fragmentation approach MetFrag.
The CECscreen database can be used to prioritize annotation of CECs measured in non-targeted HRMS, facilitating the large-scale detection of CECs in human samples for exposome research. Large-scale detection of CECs can be further improved by integrating the present database with resources that contain CECs (metabolites) and meta-data measurements, further expansion towards in silico and experimental (e.g., MassBank) generation of MS/MS spectra, and development of bioinformatics approaches capable of using correlation patterns in the measured chemical features.
The presence of nitrosamines in wastewater might pose a risk to water resources even in countries where chlorination or chloramination are hardly used for water disinfection. We studied the variation ...of concentrations and removal efficiencies of eight
N-nitrosamines among 21 full-scale sewage treatment plants (STPs) in Switzerland and temporal variations at one of these plants.
N-nitrosodimethylamine (NDMA) was the predominant compound in STP primary effluents with median concentrations in the range of 5–20
ng/L, but peak concentrations up to 1
μg/L.
N-nitrosomorpholine (NMOR) was abundant in all plants at concentrations of 5–30
ng/L, other nitrosamines occurred at a lower number of plants at similar levels. From concentrations in urine samples and domestic wastewater we estimated that human excretion accounted for levels of <5
ng/L of NDMA and <1
ng/L of the other nitrosamines in municipal wastewater, additional domestic sources for <5
ng/L of NMOR. Levels above this domestic background are probably caused by industrial or commercial discharges, which results in highly variable concentrations in sewage. Aqueous removal efficiencies in activated sludge treatment were in general above 40% for NMOR and above 60% for the other nitrosamines, but could be lower if concentrations were below 8–15
ng/L in primary effluent. We hypothesize that substrate competition in the cometabolic degradation explains the occurrence of such threshold concentrations. An additional sand filtration step resulted in a further removal of nitrosamines from secondary effluents even at low concentrations. Concentrations released to surface waters were largely below 10
ng/L, suggesting a low impact on Swiss water resources and drinking water generation considering the generally high environmental dilution and possible degradation. However, local impacts in case a larger fraction of wastewater is present cannot be ruled out.
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In the present study on endocrine disrupting chemicals (EDCs) in treated wastewater, we used chemical and effect-based tools to analyse 56 wastewater treatment plant (WWTP) effluents ...from 15 European countries. The main objectives were (i) to compare three different receptor-based estrogenicity assays (ERα-GeneBLAzer, p-YES, ERα-CALUX®), and (ii) to investigate a combined approach of chemical target analysis and receptor-based testing for estrogenicity, glucocorticogenic activity, androgenicity and progestagenic activity (ERα-, GR-, AR- and PR-GeneBLAzer assays, respectively) in treated wastewater. A total of 56 steroids and phenols were detected at concentrations ranging from 25 pg/L (estriol, E3) up to 2.4 μg/L (cortisone). WWTP effluents, which passed an advanced treatment via ozonation or via activated carbon, were found to be less contaminated, in terms of lower or no detection of steroids and phenols, as well as hormone receptor-mediated effects. This result was confirmed by the effect screening, including the three ERα-bioassays. In the GeneBLAzer assays, ERα-activity was detected in 82 %, and GR-activity in 73 % of the samples, while AR- and PR-activity were only measured in 14 % and 21 % of the samples, respectively. 17β-estradiol was confirmed as the estrogen dominating the observed estrogenic mixture effect and triamcinolone acetonide was the dominant driver of glucocorticogenic activity. The comparison of bioanalytical equivalent concentrations (BEQ) predicted from the detected concentrations and the relative effect potency (BEQchem) with measured BEQ (BEQbio) demonstrated good correlations of chemical target analysis and receptor-based testing results with deviations mostly within a factor of 10. Bioassay-specific effect-based trigger values (EBTs) from the literature, but also newly calculated EBTs based on previously proposed derivation options, were applied and allowed a preliminary assessment of the water quality of the tested WWTP effluent samples. Overall, this study demonstrates the high potential of linking chemical with effect-based analysis in water quality assessment with regard to EDC contamination.
Background
The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest (
www.casmi-contest.org
) was held in 2016, with two new categories for automated methods. This ...article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification.
Results
The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in “Category 2: Best Automatic Structural Identification—
In Silico
Fragmentation Only”, won by Team Brouard with 41% challenge wins. The winner of “Category 3: Best Automatic Structural Identification—Full Information” was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways.
Conclusions
The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for “known unknowns”. As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for “real life” annotations. The true “unknown unknowns” remain to be evaluated in future CASMI contests.
Graphical abstract
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There is an increasing demand for analytical tools to measure the internal concentrations of xenobiotic pollutants in small organisms. Such tools are required to determine exposure in ...ecotoxicological studies yet avoid sophisticated clean-up and enrichment techniques or large-scale experimental design. Thus, this paper presents a modified QuEChERS method coupled to gas chromatography tandem mass spectrometry (GC–MS/MS) for small volume organic samples. Ten zebrafish (
Danio rerio
) embryos were exposed to a 46-compound mixture at 10 ng/mL. After 72 h of exposure, they were extracted in 200 μL glass inserts using 70 μL of both acetonitrile and water. Volumes of 50 μL of extract were injected into a GC–MS/MS with a multi-mode inlet. Internal concentrations of zebrafish embryos could be reproducibly quantified in the lower nanogram per millilitre range at detection limits of 1–25 ng/mL and with recoveries of 63–133%. Internal concentrations varied over the tested range of compounds between 5.88 ± 0.616 ng/mL for dicofol and 232 ± 18.6 ng/mL for diflufenican. Detectability and recovery were best for compounds with a log D greater than four. As internal concentrations did not seem to exclusively depend on log D, biochemical transport processes could play an important role in the uptake kinetics of early zebrafish life stages.
Graphical Abstract
This paper presents an extraction and quantification method for 46 volatile organic compounds in zebrafish embryos. After exposure, pools of ten embryos were extracted with 70 μL acetonitrile applying a micro-QuEChERS approach. Internal embryo concentrations were analytically determined and quantified by large volumen injection gas chromatography tandem mass spectrometry (GC-MS/MS).
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