The Combined Algae Test for the Evaluation of Mixture Toxicity in Environmental Samples

Using a Novel Multiplexed Algal Cytological Imaging (MACI) Assay and Machine Learning as a Way to Characterize Complex Phenotypes in Plant-Type Organisms

High-throughput phenotypic profiling assays, popular for their ability to characterize alternations in single-cell morphological feature data, have been useful in recent years for predicting cellular targets and mechanisms of action (MoAs) for different chemicals and novel drugs. However, this approach has not been extensively used in environmental toxicology due to the lack of studies and established methods for performing this kind of assay in environmentally relevant species. Here, we developed a multiplexed algal cytological imaging (MACI) assay, based on the subcellular structures of the unicellular microalgae, Raphidocelis subcapitata, a toxicology and ecological model species. Several different herbicides and antibiotics with unique MoAs were exposed to R. subcapitata cells, and MACI was used to characterize cellular impacts by measuring subtle changes in their morphological features, including metrics of area, shape, quantity, fluorescence intensity, and granularity of individual subcellular components. This study demonstrates that MACI offers a quick and effective framework for characterizing complex phenotypic responses to environmental chemicals that can be used for determining their MoAs and identifying their cellular targets in plant-type organisms.

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.

Wastewater toxicity removal: Integrated chemical and effect-based monitoring of full-scale conventional activated sludge and membrane bioreactor plants

The literature is currently lacking effect-based monitoring studies targeted at evaluating the performance of full-scale membrane bioreactor plants. In this research, a monitoring campaign was performed at a full-scale wastewater treatment facility with two parallel lines (traditional activated sludge and membrane bioreactor). Beside the standard parameters (COD, nitrogen, phosphorus, and metals), 6 polynuclear aromatic hydrocarbons, 29 insecticides, 2 herbicides, and 3 endocrine disrupting compounds were measured. A multi-tiered battery of bioassays complemented the investigation, targeting different toxic modes of action and employing various biological systems (uni/multicellular, prokaryotes/eukaryotes, trophic level occupation). A traffic light scoring approach was proposed to quickly visualize the impact of treatment on overall toxicity that occurred after the exposure to raw and concentrated wastewater. Analysis of the effluents of the CAS and MBR lines show very good performance of the two systems for removal of organic micropollutants and metals. The most noticeable differences between CAS and MBR occurred in the concentration of suspended solids; chemical analyses did not show major differences. On the other hand, bioassays demonstrated better performance for the MBR. Both treatment lines complied with the Italian law's "ecotoxicity standard for effluent discharge in surface water". Yet, residual biological activity was still detected, demonstrating the adequacy and sensitivity of the toxicological tools, which, by their inherent nature, allow the overall effects of complex mixtures to be taken into account.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

Combining Polar Organic Chemical Integrative Samplers (POCIS) with Toxicity Testing on Microalgae to Evaluate the Impact of Herbicide Mixtures in Surface Waters

Pesticide risk assessment within the European Union Water Framework Directive is largely deficient in the assessment of the actual exposure and chemical mixture effects. Pesticide contamination, in particular herbicidal loading, has been shown to exert pressure on surface waters. Such pollution can have direct impact on autotrophic species, as well as indirect impacts on freshwater communities through primary production degradation. The present study proposes a screening method combining polar organic chemical integrative samplers (POCIS) with mode of action-specific toxicity testing on microalgae exposed to POCIS extracts as a standard approach to effectively address the problem of herbicide mixture effects detection. This methodology has been tested using Luxembourgish rivers as a case study and has proven to be a fast and reliable information source that is complementary to chemical analysis, allowing assessment of missing target analytes. Pesticide pressure in the 24 analyzed streams was mainly exerted by flufenacet, terbuthylazine, nicosulfuron, and foramsulfuron, with occasional impacts by the nonagricultural biocide diuron. Algae tests were more sensitive to endpoints affecting photosystem II and reproduction than to growth and could be best predicted with the concentration addition model. In addition, analysis revealed that herbicide mixture toxicity is correlated with macrophyte disappearance in the field, relating mainly to emissions from maize cultures. Combining passive sampler extracts with standard toxicity tests offers promising perspectives for ecological risk assessment. The full implementation of the proposed approach, however, requires adaptation of the legislation to scientific progress. Environ Toxicol Chem 2022;41:2667-2678. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model

Although humans are continuously exposed to complex chemical mixtures in the environment, it has been extremely challenging to investigate the resulting cumulative risks and impacts. Recent studies proposed the use of “new approach methods,” in particular in vitro assays, for hazard and dose−response evaluation of mixtures. We previously found, using five human cell-based assays, that concentration addition (CA), the usual default approach to calculate cumulative risk, is mostly accurate to within an order of magnitude. Here, we extend these findings to further investigate how cell-based data can be used to quantify inter-individual variability in CA. Utilizing data from testing 42 Superfund priority chemicals separately and in 8 defined mixtures in a human cell-based population-wide in vitro model, we applied CA to predict effective concentrations for cytotoxicity for each individual, for “typical” (median) and “sensitive” (first percentile) members of the population, and for the median-to-sensitive individual ratio (defined as the toxicodynamic variability factor, TDVF). We quantified the accuracy of CA with the Loewe Additivity Index (LAI). We found that LAI varies more between different mixtures than between different individuals, and that predictions of the population median are generally more accurate than predictions for the “sensitive” individual or the TDVF. Moreover, LAI values were generally <1, indicating that the mixtures were more potent than predicted by CA. Together with our previous studies, we posit that new approach methods data from human cell-based in vitro assays, including multiple phenotypes in diverse cell types and studies in a population-wide model, can fill critical data gaps in cumulative risk assessment, but more sophisticated models of in vitro mixture additivity and bioavailability may be needed. In the meantime, because simple CA models may underestimate potency by an order of magnitude or more, either whole-mixture testing in vitro or, alternatively, more stringent benchmarks of cumulative risk indices (e.g., lower hazard index) may be needed to ensure public health protection.

Lab-scale photobioreactor systems: principles, applications, and scalability

Phototrophic microorganisms that convert carbon dioxide are being explored for their capacity to solve different environmental issues and produce bioactive compounds for human therapeutics and as food additives. Full-scale phototrophic cultivation of microalgae and cyanobacteria can be done in open ponds or closed photobioreactor systems, which have a broad range of volumes. This review focuses on laboratory-scale photobioreactors and their different designs. Illuminated microtiter plates and microfluidic devices offer an option for automated high-throughput studies with microalgae. Illuminated shake flasks are used for simple uncontrolled batch studies. The application of illuminated bubble column reactors strongly emphasizes homogenous gas distribution, while illuminated flat plate bioreactors offer high and uniform light input. Illuminated stirred-tank bioreactors facilitate the application of very well-defined reaction conditions. Closed tubular photobioreactors as well as open photobioreactors like small-scale raceway ponds and thin-layer cascades are applied as scale-down models of the respective large-scale bioreactors. A few other less common designs such as illuminated plastic bags or aquarium tanks are also used mainly because of their relatively low cost, but up-scaling of these designs is challenging with additional light-driven issues. Finally, this review covers recommendations on the criteria for photobioreactor selection and operation while up-scaling of phototrophic bioprocesses with microalgae or cyanobacteria.

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.

Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex

BACKGROUND

Yeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of increasingly large datasets, and several software packages have been developed to analyze such data. We previously established the currently most efficient Y1H system, meiosis-directed Y1H; however, the available software tools were not designed for processing the additional parameters suggested by meiosis-directed Y1H to avoid false positives and required programming skills for operation.

RESULTS

We developed a new tool named GateMultiplex with high computing performance using C++. GateMultiplex incorporated a graphical user interface (GUI), which allows the operation without any programming skills. Flexible parameter options were designed for multiple experimental purposes to enable the application of GateMultiplex even beyond Y1H platforms. We further demonstrated the data analysis from other three fields using GateMultiplex, the identification of lead compounds in preclinical cancer drug discovery, the crop line selection in precision agriculture, and the ocean pollution detection from deep-sea fishery.

CONCLUSIONS

The user-friendly GUI, fast C++ computing speed, flexible parameter setting, and applicability of GateMultiplex facilitate the feasibility of large-scale data analysis in life science fields.

Estrogenicity of chemical mixtures revealed by a panel of bioassays

Estrogenic compounds are widely released to surface waters and may cause adverse effects to sensitive aquatic species. Three hormones, estrone, 17β-estradiol and 17α-ethinylestradiol, are of particular concern as they are bioactive at very low concentrations. Current analytical methods are not all sensitive enough for monitoring these substances in water and do not cover mixture effects. Bioassays could complement chemical analysis since they detect the overall effect of complex mixtures. Here, four chemical mixtures and two hormone mixtures were prepared and tested as reference materials together with two environmental water samples by eight laboratories employing nine in vitro and in vivo bioassays covering different steps involved in the estrogenic response. The reference materials included priority substances under the European Water Framework Directive, hormones and other emerging pollutants. Each substance in the mixture was present at its proposed safety limit concentration (EQS) in the European legislation. The in vitro bioassays detected the estrogenic effect of chemical mixtures even when 17β-estradiol was not present but differences in responsiveness were observed. LiBERA was the most responsive, followed by LYES. The additive effect of the hormones was captured by ERα-CALUX, MELN, LYES and LiBERA. Particularly, all in vitro bioassays detected the estrogenic effects in environmental water samples (EEQ values in the range of 0.75-304 × EQS), although the concentrations of hormones were below the limit of quantification in analytical measurements. The present study confirms the applicability of reference materials for estrogenic effects' detection through bioassays and indicates possible methodological drawbacks of some of them that may lead to false negative/positive outcomes. The observed difference in responsiveness among bioassays - based on mixture composition - is probably due to biological differences between them, suggesting that panels of bioassays with different characteristics should be applied according to specific environmental pollution conditions.

Suspended Particulate Matter-A Source or Sink for Chemical Mixtures of Organic Micropollutants in a Small River under Baseflow Conditions?

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.

Wastewater treatment efficacy evaluated with in vitro bioassays

Bioassays show promise as a complementary approach to chemical analysis to assess the efficacy of wastewater treatment processes as they can detect the mixture effects of all bioactive chemicals in a sample. We investigated the treatment efficacy of ten Australian wastewater treatment plants (WWTPs) covering 42% of the national population over seven consecutive days. Solid-phase extracts of influent and effluent were subjected to an in vitro test battery with six bioassays covering nine endpoints that captured the major modes of action detected in receiving surface waters. WWTP influents and effluents were compared on the basis of population- and flow-normalised effect loads, which provided insights into the biological effects exhibited by the mixture of chemicals before and after treatment. Effect removal efficacy varied between effect endpoints and depended on the treatment process. An ozonation treatment step had the best treatment efficacy, while WWTPs with only primary treatment resulted in poor removal of effects. Effect removal was generally better for estrogenic effects and the peroxisome proliferator-activated receptor than for inhibition of photosynthesis, which is consistent with the persistence of herbicides causing this effect. Cytotoxicity and oxidative stress response provided a sum parameter of all bioactive chemicals including transformation products and removal was poorer than for specific endpoints except for photosynthesis inhibition. Although more than 500 chemicals were analysed, the detected chemicals explained typically less than 10% of the measured biological effect, apart from algal toxicity, where the majority of the effect could be explained by one dominant herbicide, diuron. Overall, the current study demonstrated the utility of applying bioassays alongside chemical analysis to evaluate loads of chemical pollution reaching WWTPs and treatment efficacy.

Resilience of Micropollutant and Biological Effect Removal in an Aerated Horizontal Flow Treatment Wetland

The performance of an aerated horizontal subsurface flow treatment wetland was investigated before, during and after a simulated aeration failure. Conventional wastewater parameters (e.g., carbonaceous biological oxygen demand, total nitrogen, and Escherichia coli) as well as selected micropollutants (caffeine, ibuprofen, naproxen, benzotriazole, diclofenac, acesulfame, and carbamazepine) were investigated. Furthermore, the removal of biological effects was investigated using in vitro bioassays. The six bioassays selected covered environmentally relevant endpoints (indicative of activation of aryl hydrocarbon receptor, AhR; binding to the peroxisome proliferator-activated receptor gamma, PPARγ; activation of estrogen receptor alpha, ERα; activation of glucocorticoid receptor, GR; oxidative stress response, AREc32; combined algae test, CAT). During the aeration interruption phase, the water quality deteriorated to a degree comparable to that of a conventional (non-aerated) horizontal subsurface flow wetland. After the end of the aeration interruption, the analytical and biological parameters investigated recovered at different time periods until their initial treatment performance. Treatment efficacy for conventional parameters was recovered within a few days, but no complete recovery of treatment efficacy could be observed for bioassays AhR, AREc32 and CAT in the 21 days following re-start of the aeration system. Furthermore, the removal efficacy along the flow path for most of the chemicals and bioassays recovered as it was observed in the baseline phase. Only for the activation of AhR and AREc32 there was a shift of the internal treatment profile from 12.5% to 25% (AhR) and 50% (AREc32) of the fractional length.