IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression.

Aryl hydrocarbon receptor (AHR) activation by tryptophan (Trp) catabolites enhances tumor malignancy and suppresses anti-tumor immunity. The context specificity of AHR target genes has so far impeded systematic investigation of AHR activity and its upstream enzymes across human cancers. A pan-tissue AHR signature, derived by natural language processing, revealed that across 32 tumor entities, interleukin-4-induced-1 (IL4I1) associates more frequently with AHR activity than IDO1 or TDO2, hitherto recognized as the main Trp-catabolic enzymes. IL4I1 activates the AHR through the generation of indole metabolites and kynurenic acid. It associates with reduced survival in glioma patients, promotes cancer cell motility, and suppresses adaptive immunity, thereby enhancing the progression of chronic lymphocytic leukemia (CLL) in mice. Immune checkpoint blockade (ICB) induces IDO1 and IL4I1. As IDO1 inhibitors do not block IL4I1, IL4I1 may explain the failure of clinical studies combining ICB with IDO1 inhibition. Taken together, IL4I1 blockade opens new avenues for cancer therapy.

In Vitro Metabolism and p53 Activation of Genotoxic Chemicals: Abiotic CYP Enzyme vs Liver Microsomes.

Chemicals often require metabolic activation to become genotoxic. Established test guidelines recommend the use of the rat liver S9 fraction or microsomes to introduce metabolic competence to in vitro cell-based bioassays, but the use of animal-derived components in cell culture raises ethical concerns and may lead to quality issues and reproducibility problems. The aim of the present study was to compare the metabolic activation of cyclophosphamide (CPA) and benzo[a]pyrene (BaP) by induced rat liver microsomes and an abiotic cytochrome P450 (CYP) enzyme based on a biomimetic porphyrine catalyst. For the detection of genotoxic effects, the chemicals were tested in a reporter gene assay targeting the activation of the cellular tumor protein p53. Both chemicals were metabolized by the abiotic CYP enzyme and the microsomes. CPA showed no activation of p53 and low cytotoxicity without metabolic activation, but strong activation of p53 and increased cytotoxicity upon incubation with liver microsomes or abiotic CYP enzyme. The effect concentration causing a 1.5-fold induction of p53 activation was very similar with both metabolization systems (within a factor of 1.5), indicating that genotoxic metabolites were formed at comparable concentrations. BaP also showed low cytotoxicity and no p53 activation without metabolic activation. The activation of p53 was detected for BaP upon incubation with active and inactive microsomes at similar concentrations, indicating experimental artifacts caused by the microsomes or NADPH. The activation of BaP with the abiotic CYP enzyme increased the cytotoxicity of BaP by a factor of 8, but no activation of p53 was detected. The results indicate that abiotic CYP enzymes may present an alternative to rat liver S9 fraction or microsomes for the metabolic activation of test chemicals, which are completely free of animal-derived components. However, an amendment of existing test guidelines would require testing of more chemicals and genotoxicity end points.

Effects of Chemicals in Reporter Gene Bioassays with Different Metabolic Activities Compared to Baseline Toxicity.

High-throughput cell-based bioassays are used for chemical screening and risk assessment. Chemical transformation processes caused by abiotic degradation or metabolization can reduce the chemical concentration or, in some cases, lead to the formation of more toxic transformation products. Unaccounted loss processes may falsify the bioassay results. Capturing the formation and effects of transformation products is important for relating the in vitro effects to in vivo. Reporter gene cell lines are believed to have low metabolic activity, but inducibility of cytochrome P450 (CYP) enzymes has been reported. Baseline toxicity is the minimal toxicity a chemical can have and is caused by the incorporation of the chemical into cell membranes. In the present study, we improved an existing baseline toxicity model based on a newly defined critical membrane burden derived from freely dissolved effect concentrations, which are directly related to the membrane concentration. Experimental effect concentrations of 94 chemicals in three bioassays (AREc32, ARE-bla and GR-bla) were compared with baseline toxicity by calculating the toxic ratio (TR). CYP activities of all cell lines were determined by using fluorescence-based assays. Only ARE-bla showed a low basal CYP activity and inducibility and AREc32 showed a low inducibility. Overall cytotoxicity was similar in all three assays despite the different metabolic activities indicating that chemical metabolism is not relevant for the cytotoxicity of the tested chemicals in these assays. Up to 28 chemicals showed specific cytotoxicity with TR > 10 in the bioassays, but baseline toxicity could explain the effects of the majority of the remaining chemicals. Seven chemicals showed TR < 0.1 indicating inaccurate physicochemical properties or experimental artifacts like chemical precipitation, volatilization, degradation, or other loss processes during the in vitro bioassay. The new baseline model can be used not only to identify specific cytotoxicity mechanisms but also to identify potential problems in the experimental performance or evaluation of the bioassay and thus improve the quality of the bioassay data.

Water Quality Monitoring with the Multiplexed Assay MitoOxTox for Mitochondrial Toxicity, Oxidative Stress Response, and Cytotoxicity in AREc32 Cells.

Mitochondria play a key role in the energy production of cells, but their function can be disturbed by environmental toxicants. We developed a cell-based mitochondrial toxicity assay for environmental chemicals and their mixtures extracted from water samples. The reporter gene cell line AREc32, which is frequently used to quantify the cytotoxicity and oxidative stress response of water samples, was multiplexed with an endpoint of mitochondrial toxicity. The disruption of the mitochondrial membrane potential (MMP) was quantified by high-content imaging and compared to measured cytotoxicity, predicted baseline toxicity, and activation of the oxidative stress response. Mitochondrial complex I inhibitors showed highly specific effects on the MMP, with minor effects on cell viability. Uncouplers showed a wide distribution of specificity on the MMP, often accompanied by specific cytotoxicity (enhanced over baseline toxicity). Mitochondrial toxicity and the oxidative stress response were not directly associated. The multiplexed assay was applied to water samples ranging from wastewater treatment plant (WWTP) influent and effluent and surface water to drinking and bottled water from various European countries. Specific effects on MMP were observed for the WWTP influent and effluent. This new MitoOxTox assay is an important complement for existing in vitro test batteries for water quality testing and has potential for applications in human biomonitoring.

Species Difference? Bovine, Trout, and Human Plasma Protein Binding of Per- and Polyfluoroalkyl Substances.

Per- and polyfluoroalkyl substances (PFAS) strongly bind to proteins and lipids in blood, which govern their accumulation and distribution in organisms. Understanding the plasma binding mechanism and species differences will facilitate the quantitative in vitro-to-in vivo extrapolation and improve risk assessment of PFAS. We studied the binding mechanism of 16 PFAS to bovine serum albumin (BSA), trout, and human plasma using solid-phase microextraction. Binding of anionic PFAS to BSA and human plasma was found to be highly concentration-dependent, while trout plasma binding was linear for the majority of the tested PFAS. At a molar ratio of PFAS to protein ν < 0.1 molPFAS/molprotein, the specific protein binding of anionic PFAS dominated their human plasma binding. This would be the scenario for physiological conditions (ν < 0.01), whereas in in vitro assays, PFAS are often dosed in excess (ν > 1) and nonspecific binding becomes dominant. BSA was shown to serve as a good surrogate for human plasma. As trout plasma contains more lipids, the nonspecific binding to lipids affected the affinities of PFAS for trout plasma. Mass balance models that are parameterized with the protein-water and lipid-water partitioning constants (chemical characteristics), as well as the protein and lipid contents of the plasma (species characteristics), were successfully used to predict the binding to human and trout plasma.

Baseline Toxicity Model to Identify the Specific and Nonspecific Effects of Per- and Polyfluoroalkyl Substances in Cell-Based Bioassays.

High-throughput screening is a strategy to identify potential adverse outcome pathways (AOP) for thousands of per- and polyfluoroalkyl substances (PFAS) if the specific effects can be distinguished from nonspecific effects. We hypothesize that baseline toxicity may serve as a reference to determine the specificity of the cell responses. Baseline toxicity is the minimum (cyto)toxicity caused by the accumulation of chemicals in cell membranes, which disturbs their structure and function. A mass balance model linking the critical membrane concentration for baseline toxicity to nominal (i.e., dosed) concentrations of PFAS in cell-based bioassays yielded separate baseline toxicity prediction models for anionic and neutral PFAS, which were based on liposome-water distribution ratios as the sole model descriptors. The specificity of cell responses to 30 PFAS on six target effects (activation of peroxisome proliferator-activated receptor (PPAR) gamma, aryl hydrocarbon receptor, oxidative stress response, and neurotoxicity in own experiments, and literature data for activation of several PPARs and the estrogen receptor) were assessed by comparing effective concentrations to predicted baseline toxic concentrations. HFPO-DA, HFPO-DA-AS, and PFMOAA showed high specificity on PPARs, which provides information on key events in AOPs relevant to PFAS. However, PFAS were of low specificity in the other experimentally evaluated assays and others from the literature. Even if PFAS are not highly specific for certain defined targets but disturb many toxicity pathways with low potency, such effects are toxicologically relevant, especially for hydrophobic PFAS and because PFAS are highly persistent and cause chronic effects. This implicates a heightened need for the risk assessment of PFAS mixtures because nonspecific effects behave concentration-additive in mixtures.

Impact of Biotransformation on Internal Concentrations and Specificity Classification of Organic Chemicals in the Zebrafish Embryo (Danio rerio).

Internal concentrations (ICs) are crucial for linking exposure to effects in the development of New Approach Methodologies. ICs of chemicals in aquatic organisms are primarily driven by hydrophobicity and modulated by biotransformation and efflux. Comparing the predicted baseline to observed toxicity enables the estimation of effect specificity, but biological processes can lead to overestimating ICs and bias the specificity assessment. To evaluate the prediction of a mass balance model (MBM) and the impact of biotransformation on ICs, experimental ICs of 63 chemicals in zebrafish embryos were compared to predictions with physicochemical properties as input parameters. Experimental ICs of 79% (50 of 63) of the chemicals deviated less than 10-fold from predictions, and the remaining 13 deviated up to a factor of 90. Using experimental ICs changed the classification for 19 chemicals, with ICs 5 to 90 times lower than predicted, showing the bias of specificity classification. Uptake kinetics of pirinixic acid, genistein, dexamethasone, ethoprophos, atorvastatin, and niflumic acid were studied over a 96 h exposure period, and transformation products (TPs) were elucidated using suspect- and nontarget screening with UPLC-HRMS. 35 TPs (5 to 8 TPs per compound) were tentatively identified and semiquantified based on peak areas, suggesting that biotransformation may partly account for the overpredictions of ICs.

Neurotoxic Effects of Mixtures of Perfluoroalkyl Substances (PFAS) at Environmental and Human Blood Concentrations.

Per- and polyfluoroalkyl substances (PFAS) may cause various deleterious health effects. Epidemiological studies have demonstrated associations between PFAS exposure and adverse neurodevelopmental outcomes. The cytotoxicity, neurotoxicity, and mitochondrial toxicity of up to 12 PFAS including perfluoroalkyl carboxylates, perfluoroalkyl sulfonates, 6:2 fluorotelomer sulfonic acid (6:2 FTSA), and hexafluoropropylene oxide-dimer acid (HPFO-DA) were tested at concentrations typically observed in the environment (e.g., wastewater, biosolids) and in human blood using high-throughput in vitro assays. The cytotoxicity of all individual PFAS was classified as baseline toxicity, for which prediction models based on partition constants of PFAS between biomembrane lipids and water exist. No inhibition of the mitochondrial membrane potential and activation of oxidative stress response were observed below the cytotoxic concentrations of any PFAS tested. All mixture components and the designed mixtures inhibited the neurite outgrowth in differentiated neuronal cells derived from the SH-SY5Y cell line at concentrations around or below cytotoxicity. All designed mixtures acted according to concentration addition at low effect and concentration levels for cytotoxicity and neurotoxicity. The mixture effects were predictable from the experimental single compounds' concentration-response curves. These findings have important implications for the mixture risk assessment of PFAS.

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments.

Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typically rely on an apical and/or single endpoint, providing limited diagnostic potential to guide chemical prioritization. We proposed an event-driven taxonomy framework for mixture risk assessment that relied on high-throughput screening bioassays and toxicant identification integrated by deep learning. In this work, the framework was evaluated using chemical mixtures in sediments eliciting aryl-hydrocarbon receptor activation and oxidative stress response. Mixture prediction using target analysis explained <10% of observed sediment bioactivity. To identify additional contaminants, two deep learning models were developed to predict fingerprints of a pool of bioactive substances (event driver fingerprint, EDFP) and convert these candidates to MS-readable information (event driver ion, EDION) for nontarget analysis. Two libraries with 121 and 118 fingerprints were established, and 247 bioactive compounds were identified at confidence level 2 or 3 in sediment extract using GC-qToF-MS. Among them, 12 toxicants were analytically confirmed using reference standards. Collectively, we present a "bioactivity-signature-toxicant" strategy to deconvolute mixtures and to connect patchy data sets and guide nontarget analysis for diverse chemicals that elicit the same bioactivity.

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data.

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.

Three perspectives on the prediction of chemical effects in ecosystems.

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Reactivity of Acrylamides Causes Cytotoxicity and Activates Oxidative Stress Response.

Acrylamides are widely used industrial chemicals that cause adverse effects in humans or animals, such as carcinogenicity or neurotoxicity. The excess toxicity of these reactive electrophilic chemicals is especially interesting, as it is mostly triggered by covalent reactions with biological nucleophiles, such as DNA bases, proteins, or peptides. The cytotoxicity and activation of oxidative stress response of 10 (meth)acrylamides measured in three reporter gene cell lines occurred at similar concentrations. Most acrylamides exhibited high excess toxicity, while methacrylamides acted as baseline toxicants. The (meth)acrylamides showed no reactivity toward the hard biological nucleophile 2-deoxyguanosine (2DG) within 24 h, and only acrylamides reacted with the soft nucleophile glutathione (GSH). Second-order degradation rate constants (kGSH) were measured for all acrylamides with N,N'-methylenebis(acrylamide) (NMBA) showing the highest kGSH (134.800 M-1 h-1) and N,N-diethylacrylamide (NDA) the lowest kGSH (2.574 M-1 h-1). Liquid chromatography coupled to high-resolution mass spectrometry was used to confirm the GSH conjugates of the acrylamides with a double conjugate formed for NMBA. The differences in reactivity between acrylamides and methacrylamides could be explained by the charge density of the carbon atoms because the electron-donating inductive effect of the methyl group of the methacrylamides lowered their electrophilicity and thus their reactivity. The differences in reactivity within the group of acrylamides could be explained by the energy of the lowest unoccupied molecular orbital and steric hindrance. Cytotoxicity and activation of oxidative stress response were linearly correlated with the second-order reaction rate constants of the acrylamides with GSH. The reaction of the acrylamides with GSH is hence not only a detoxification mechanism but also leads to disturbances of the redox balance, making the cells more vulnerable to reactive oxygen species. The reactivity of acrylamides explained the oxidative stress response and cytotoxicity in the cells, and the lack of reactivity of the methacrylamides led to baseline toxicity.

Recovery of 400 Chemicals with Three Extraction Methods for Low Volumes of Human Plasma Quantified by Instrumental Analysis and In Vitro Bioassays.

Human biomonitoring studies are important for understanding adverse health outcomes caused by exposure to chemicals. Complex mixtures of chemicals detected in blood - the blood exposome - may serve as proxies for systemic exposure. Ideally, several analytical methods are combined with in vitro bioassays to capture chemical mixtures as diverse as possible. How many and which (bio)analyses can be performed is limited by the sample volume and compatibility of extraction and (bio)analytical methods. We compared the extraction efficacy of three extraction methods using pooled human plasma spiked with >400 organic chemicals. Passive equilibrium sampling (PES) with polydimethylsiloxane (PDMS) followed by solid phase extraction (PES + SPE), SPE alone (SPE), and solvent precipitation (SolvPrec) were compared for chemical recovery in LC-HRMS and GC-HRMS as well as effect recovery in four mammalian cell lines (AhR-CALUX, SH-SY5Y, AREc32, PPARγ-BLA). The mean chemical recoveries were 38% for PES + SPE, 27% for SPE, and 61% for SolvPrec. PES + SPE enhanced the mean chemical recovery compared to SPE, especially for neutral hydrophobic chemicals. PES + SPE and SolvPrec had effect recoveries of 100-200% in all four cell lines, outperforming SPE, which had 30-100% effect recovery. Although SolvPrec has the best chemical recoveries, it does not remove matrix like inorganics or lipids, which might pose problems for some (bio)analytical methods. PES + SPE is the most promising method for sample preparation in human biomonitoring as it combines good recoveries with cleanup, enrichment, and potential for high throughput.

Antimicrobial Transformation Products in the Aquatic Environment: Global Occurrence, Ecotoxicological Risks, and Potential of Antibiotic Resistance.

The global spread of antimicrobial resistance (AMR) is concerning for the health of humans, animals, and the environment in a One Health perspective. Assessments of AMR and associated environmental hazards mostly focus on antimicrobial parent compounds, while largely overlooking their transformation products (TPs). This review lists antimicrobial TPs identified in surface water environments and examines their potential for AMR promotion, ecological risk, as well as human health and environmental hazards using in silico models. Our review also summarizes the key transformation compartments of TPs, related pathways for TPs reaching surface waters and methodologies for studying the fate of TPs. The 56 antimicrobial TPs covered by the review were prioritized via scoring and ranking of various risk and hazard parameters. Most data on occurrences to date have been reported in Europe, while little is known about antibiotic TPs in Africa, Central and South America, Asia, and Oceania. Occurrence data on antiviral TPs and other antibacterial TPs are even scarcer. We propose evaluation of structural similarity between parent compounds and TPs for TP risk assessment. We predicted a risk of AMR for 13 TPs, especially TPs of tetracyclines and macrolides. We estimated the ecotoxicological effect concentrations of TPs from the experimental effect data of the parent chemical for bacteria, algae and water fleas, scaled by potency differences predicted by quantitative structure-activity relationships (QSARs) for baseline toxicity and a scaling factor for structural similarity. Inclusion of TPs in mixtures with their parent increased the ecological risk quotient over the threshold of one for 7 of the 24 antimicrobials included in this analysis, while only one parent had a risk quotient above one. Thirteen TPs, from which 6 were macrolide TPs, posed a risk to at least one of the three tested species. There were 12/21 TPs identified that are likely to exhibit a similar or higher level of mutagenicity/carcinogenicity, respectively, than their parent compound, with tetracycline TPs often showing increased mutagenicity. Most TPs with increased carcinogenicity belonged to sulfonamides. Most of the TPs were predicted to be mobile but not bioaccumulative, and 14 were predicted to be persistent. The six highest-priority TPs originated from the tetracycline antibiotic family and antivirals. This review, and in particular our ranking of antimicrobial TPs of concern, can support authorities in planning related intervention strategies and source mitigation of antimicrobials toward a sustainable future.

Application of Effect-Based Methods to Water Quality Monitoring: Answering Frequently Asked Questions by Water Quality Managers, Regulators, and Policy Makers.

Effect-based methods (EBM) have great potential for water quality monitoring as they can detect the mixture effects of all active known and unknown chemicals in a sample, which cannot be addressed by chemical analysis alone. To date, EBM have primarily been applied in a research context, with a lower level of uptake by the water sector and regulators. This is partly due to concerns regarding the reliability and interpretation of EBM. Using evidence from the peer-reviewed literature, this work aims to answer frequently asked questions about EBM. The questions were identified through consultation with the water industry and regulators and cover topics related to the basis for using EBM, practical considerations regarding reliability, sampling for EBM and quality control, and what to do with the information provided by EBM. The information provided in this work aims to give confidence to regulators and the water sector to stimulate the application of EBM for water quality monitoring.

Modernizing persistence-bioaccumulation-toxicity (PBT) assessment with high throughput animal-free methods.

The assessment of persistence (P), bioaccumulation (B), and toxicity (T) of a chemical is a crucial first step at ensuring chemical safety and is a cornerstone of the European Union's chemicals regulation REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals). Existing methods for PBT assessment are overly complex and cumbersome, have produced incorrect conclusions, and rely heavily on animal-intensive testing. We explore how new-approach methodologies (NAMs) can overcome the limitations of current PBT assessment. We propose two innovative hazard indicators, termed cumulative toxicity equivalents (CTE) and persistent toxicity equivalents (PTE). Together they are intended to replace existing PBT indicators and can also accommodate the emerging concept of PMT (where M stands for mobility). The proposed "toxicity equivalents" can be measured with high throughput in vitro bioassays. CTE refers to the toxic effects measured directly in any given sample, including single chemicals, substitution products, or mixtures. PTE is the equivalent measure of cumulative toxicity equivalents measured after simulated environmental degradation of the sample. With an appropriate panel of animal-free or alternative in vitro bioassays, CTE and PTE comprise key environmental and human health hazard indicators. CTE and PTE do not require analytical identification of transformation products and mixture components but instead prompt two key questions: is the chemical or mixture toxic, and is this toxicity persistent or can it be attenuated by environmental degradation? Taken together, the proposed hazard indicators CTE and PTE have the potential to integrate P, B/M and T assessment into one high-throughput experimental workflow that sidesteps the need for analytical measurements and will support the Chemicals Strategy for Sustainability of the European Union.

High-Throughput Assessment of the Abiotic Stability of Test Chemicals in In Vitro Bioassays.

Abiotic stability of chemicals is not routinely tested prior to performing in vitro bioassays, although abiotic degradation can reduce the concentration of test chemicals leading to the formation of active or inactive transformation products, which may lead to misinterpretation of bioassay results. A high-throughput workflow was developed to measure the abiotic stability of 22 test chemicals in protein-rich aqueous media under typical bioassay conditions at 37 °C for 48 h. These test chemicals were degradable in the environment according to a literature review. The chemicals were extracted from the exposure media at different time points using a novel 96-pin solid-phase microextraction. The conditions were varied to differentiate between various reaction mechanisms. For most hydrolyzable chemicals, pH-dependent degradation in phosphate-buffered saline indicated that acid-catalyzed hydrolysis was less important than reactions with hydroxide ions. Reactions with proteins were mainly responsible for the depletion of the test chemicals in the media, which was simulated by bovine serum albumin (BSA) and glutathione (GSH). 1,2-Benzisothiazol-3(2H)-one, 2-methyl-4-isothiazolinone, and l-sulforaphane reacted almost instantaneously with GSH but not with BSA, indicating that GSH is a good proxy for reactivity with electrophilic amino acids but may overestimate the actual reaction with three-dimensional proteins. Chemicals such as hydroquinones or polyunsaturated chemicals are prone to autoxidation, but this reaction is difficult to differentiate from hydrolysis and could not be simulated by the oxidant N-bromosuccinimide. Photodegradation played a minor role because cells are exposed in incubators in the dark and simulations with high light intensities did not yield realistic degradation. Stability predictions from various in silico prediction models for environmental conditions can give initial indications of the stability but were not always consistent with the experimental stability in bioassays. As the presented workflow can be performed in high throughput under realistic bioassay conditions, it can be used to provide an experimental database for developing bioassay-specific stability prediction models.

The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs).

Substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs) are over 70 000 "complex" chemical mixtures produced and used at significant levels worldwide. Due to their unknown or variable composition, applying chemical assessments originally developed for individual compounds to UVCBs is challenging, which impedes sound management of these substances. Across the analytical sciences, toxicology, cheminformatics, and regulatory practice, new approaches addressing specific aspects of UVCB assessment are being developed, albeit in a fragmented manner. This review attempts to convey the "big picture" of the state of the art in dealing with UVCBs by holistically examining UVCB characterization and chemical identity representation, as well as hazard, exposure, and risk assessment. Overall, information gaps on chemical identities underpin the fundamental challenges concerning UVCBs, and better reporting and substance characterization efforts are needed to support subsequent chemical assessments. To this end, an information level scheme for improved UVCB data collection and management within databases is proposed. The development of UVCB testing shows early progress, in line with three main methods: whole substance, known constituents, and fraction profiling. For toxicity assessment, one option is a whole-mixture testing approach. If the identities of (many) constituents are known, grouping, read across, and mixture toxicity modeling represent complementary approaches to overcome data gaps in toxicity assessment. This review highlights continued needs for concerted efforts from all stakeholders to ensure proper assessment and sound management of UVCBs.

Modeling the Dynamics of Mixture Toxicity and Effects of Organic Micropollutants in a Small River under Unsteady Flow Conditions.

The presence of anthropogenic organic micropollutants in rivers poses a long-term threat to surface water quality. To describe and quantify the in-stream fate of single micropollutants, the advection-dispersion-reaction (ADR) equation has been used previously. Understanding the dynamics of the mixture effects and cytotoxicity that are cumulatively caused by micropollutant mixtures along their flow path in rivers requires a new concept. Thus, we extended the ADR equation from single micropollutants to defined mixtures and then to the measured mixture effects of micropollutants extracted from the same river water samples. Effects (single and mixture) are expressed as effect units and toxic units, the inverse of effect concentrations and inhibitory concentrations, respectively, quantified using a panel of in vitro bioassays. We performed a Lagrangian sampling campaign under unsteady flow, collecting river water that was impacted by a wastewater treatment plant (WWTP) effluent. To reduce the computational time, the solution of the ADR equation was expressed by a convolution-based reactive transport approach, which was used to simulate the dynamics of the effects. The dissipation dynamics of the individual micropollutants were reproduced by the deterministic model following first-order kinetics. The dynamics of experimental mixture effects without known compositions were captured by the model ensemble obtained through Bayesian calibration. The highly fluctuating WWTP effluent discharge dominated the temporal patterns of the effect fluxes in the river. Minor inputs likely from surface runoff and pesticide diffusion might contribute to the general effect and cytotoxicity pattern but could not be confirmed by the model-based analysis of the available effect and chemical data.

Sorption and Mobility of Charged Organic Compounds: How to Confront and Overcome Limitations in Their Assessment.

Permanently charged and ionizable organic compounds (IOC) are a large and diverse group of compounds belonging to many contaminant classes, including pharmaceuticals, pesticides, industrial chemicals, and natural toxins. Sorption and mobility of IOCs are distinctively different from those of neutral compounds. Due to electrostatic interactions with natural sorbents, existing concepts for describing neutral organic contaminant sorption, and by extension mobility, are inadequate for IOC. Predictive models developed for neutral compounds are based on octanol-water partitioning of compounds (Kow) and organic-carbon content of soil/sediment, which is used to normalize sorption measurements (KOC). We revisit those concepts and their translation to IOC (Dow and DOC) and discuss compound and soil properties determining sorption of IOC under water saturated conditions. Highlighting possible complementary and/or alternative approaches to better assess IOC mobility, we discuss implications on their regulation and risk assessment. The development of better models for IOC mobility needs consistent and reliable sorption measurements at well-defined chemical conditions in natural porewater, better IOC-, as well as sorbent characterization. Such models should be complemented by monitoring data from the natural environment. The state of knowledge presented here may guide urgently needed future investigations in this field for researchers, engineers, and regulators.