QSAR analysis and specific endpoints for classifying the physiological modes of action of biocides in synchronous green algae

Effect of wastewater from the in-water cleaning of ship hulls on attached and unattached microalgae

Environmental spills of in-water hull cleaning wastewater (HCW) containing heavy metals and biocides is inevitable, and the effects of HCW on microalgae are unknown. To investigate this, we conducted microcosm experiments by adding HCW to natural seawater. HCW samples were obtained from two different cleaning methods (soft: sponge, hard: brush), and 5 % or 10 % were added to natural seawater as treatments. Dissolved Cu concentrations were 5 to 10 times higher in the treatments than those in the control. There were significant differences in growth of unattached microalgae depending on HCW dose (chlorophyll a: 34.1 ± 0.8 μg L-1 in control vs. 12.6 ± 4.3 μg L-1 in treatments). Conversely, the biomass of attached microalgae increased with HCW dose, which was associated with most of the nutrient reduction later in the experiment, rather than unattached microalgae. Our findings suggest that HCW can significantly impact microalgal community, especially depending on spill volume.

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artificial intelligence (AI) and machine learning (MI) can be used to analyze and interpret large amounts of data in the field of toxicology, such as data from toxicological databases and high-content image-based screening data. Physiologically based pharmacokinetic (PBPK) models and nano-quantitative structure-activity relationship (QSAR) models can be used to predict the behavior and toxic effects of nanomaterials, respectively. PBPK and Nano-QSAR are prominent ML tool for harmful event analysis that is used to understand the mechanisms by which chemical compounds can cause toxic effects, while toxicogenomics is the study of the genetic basis of toxic responses in living organisms. Despite the potential of these methods, there are still many challenges and uncertainties that need to be addressed in the field. In this review, we provide an overview of artificial intelligence (AI) and machine learning (ML) techniques in nanomedicine and nanotoxicology to better understand the potential toxic effects of these materials at the nanoscale.

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.

Recommendations for Improving Methods and Models for Aquatic Hazard Assessment of Ionizable Organic Chemicals

Ionizable organic chemicals (IOCs) such as organic acids and bases are an important substance class requiring aquatic hazard evaluation. Although the aquatic toxicity of IOCs is highly dependent on the water pH, many toxicity studies in the literature cannot be interpreted because pH was not reported or not kept constant during the experiment, calling for an adaptation and improvement of testing guidelines. The modulating influence of pH on toxicity is mainly caused by pH-dependent uptake and bioaccumulation of IOCs, which can be described by ion-trapping and toxicokinetic models. The internal effect concentrations of IOCs were found to be independent of the external pH because of organisms' and cells' ability to maintain a stable internal pH milieu. If the external pH is close to the internal pH, existing quantitative structure-activity relationships (QSARs) for neutral organics can be adapted by substituting the octanol-water partition coefficient by the ionization-corrected liposome-water distribution ratio as the hydrophobicity descriptor, demonstrated by modification of the target lipid model. Charged, zwitterionic and neutral species of an IOC can all contribute to observed toxicity, either through concentration-additive mixture effects or by interaction of different species, as is the case for uncoupling of mitochondrial respiration. For specifically acting IOCs, we recommend a 2-step screening procedure with ion-trapping/QSAR models used to predict the baseline toxicity, followed by adjustment using the toxic ratio derived from in vitro systems. Receptor- or plasma-binding models also show promise for elucidating IOC toxicity. The present review is intended to help demystify the ecotoxicity of IOCs and provide recommendations for their hazard and risk assessment. Environ Toxicol Chem 2020;39:269-286. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Multiple toxicity endpoint-structure relationships for substituted phenols and anilines

Quantitative structure-toxicity relationship (QSTR) models with the same mathematical structure were proposed for predicting the multiple toxicity endpoints of substituted phenols and anilines towards Chlorella vulgaris (C. vulgaris) based on the norm indexes. Four aquatic toxicity endpoints including growth inhibition concentrations of IC₅₀, IC₂₀, LOEC and NOEC towards C. vulgaris were involved in the modeling work. The results indicated that the developed models could produce satisfactory predictive results for the four different toxicity endpoints with high squared correlation coefficients (R²). Leave-one-out cross validation, Y-randomized validation and application domain analysis demonstrated the accuracy, robustness and reliability of these models. Accordingly, the results obtained in this work suggested that it might be possible to develop QSTR models with the same mathematical structure for predicting multiple toxicity endpoints successfully via norm index descriptors.

Tributyltin: Advancing the Science on Assessing Endocrine Disruption with an Unconventional Endocrine-Disrupting Compound

Tributyltin (TBT) has been recognized as an endocrine disrupting chemical (EDC) for several decades. However, only in the last decade, was its primary endocrine mechanism of action (MeOA) elucidated-interactions with the nuclear retinoid-X receptor (RXR), peroxisome proliferator-activated receptor γ (PPARγ), and their heterodimers. This molecular initiating event (MIE) alters a range of reproductive, developmental, and metabolic pathways at the organism level. It is noteworthy that a variety of MeOAs have been proposed over the years for the observed endocrine-type effects of TBT; however, convincing data for the MIE was provided only recently and now several researchers have confirmed and refined the information on this MeOA. One of the most important lessons learned from years of research on TBT concerns apparent species sensitivity. Several aspects such as the rates of uptake and elimination, chemical potency, and metabolic capacity are all important for identifying the most sensitive species for a given chemical, including EDCs. For TBT, much of this was discovered by trial and error, hence important relationships and important sensitive taxa were not identified until several decades after its introduction to the environment. As recognized for many years, TBT-induced responses are known to occur at very low concentrations for molluscs, a fact that has more recently also been observed in fish species. This review explores the MeOA and effects of TBT in different species (aquatic molluscs and other invertebrates, fish, amphibians, birds, and mammals) according to the OECD Conceptual Framework for Endocrine Disruptor Testing and Assessment (CFEDTA). The information gathered on biological effects that are relevant for populations of aquatic animals was used to construct Species Sensitivity Distributions (SSDs) based on No Observed Effect Concentrations (NOECs) and Lowest Observed Effect Concentrations (LOECs). Fish appear at the lower end of these distributions, showing that they are as sensitive as molluscs, and for some species, even more sensitive. Concentrations in the range of 1 ng/L for water exposure (10 ng/g for whole-body burden) have been shown to elicit endocrine-type responses, whereas mortality occurs at water concentrations ten times higher. Current screening and assessment methodologies as compiled in the OECD CFEDTA are able to identify TBT as a potent endocrine disruptor with a high environmental risk for the original use pattern. If those approaches had been available when TBT was introduced to the market, it is likely that its use would have been regulated sooner, thus avoiding the detrimental effects on marine gastropod populations and communities as documented over several decades.

Development of a bioanalytical test battery for water quality monitoring: Fingerprinting identified micropollutants and their contribution to effects in surface water

Surface waters can contain a diverse range of organic pollutants, including pesticides, pharmaceuticals and industrial compounds. While bioassays have been used for water quality monitoring, there is limited knowledge regarding the effects of individual micropollutants and their relationship to the overall mixture effect in water samples. In this study, a battery of in vitro bioassays based on human and fish cell lines and whole organism assays using bacteria, algae, daphnids and fish embryos was assembled for use in water quality monitoring. The selection of bioassays was guided by the principles of adverse outcome pathways in order to cover relevant steps in toxicity pathways known to be triggered by environmental water samples. The effects of 34 water pollutants, which were selected based on hazard quotients, available environmental quality standards and mode of action information, were fingerprinted in the bioassay test battery. There was a relatively good agreement between the experimental results and available literature effect data. The majority of the chemicals were active in the assays indicative of apical effects, while fewer chemicals had a response in the specific reporter gene assays, but these effects were typically triggered at lower concentrations. The single chemical effect data were used to improve published mixture toxicity modeling of water samples from the Danube River. While there was a slight increase in the fraction of the bioanalytical equivalents explained for the Danube River samples, for some endpoints less than 1% of the observed effect could be explained by the studied chemicals. The new mixture models essentially confirmed previous findings from many studies monitoring water quality using both chemical analysis and bioanalytical tools. In short, our results indicate that many more chemicals contribute to the biological effect than those that are typically quantified by chemical monitoring programs or those regulated by environmental quality standards. This study not only demonstrates the utility of fingerprinting single chemicals for an improved understanding of the biological effect of pollutants, but also highlights the need to apply bioassays for water quality monitoring in order to prevent underestimation of the overall biological effect.

Image Cytometric Analysis of Algal Spores for Evaluation of Antifouling Activities of Biocidal Agents

Chemical biocides have been widely used as marine antifouling agents, but their environmental toxicity impose regulatory restriction on their use. Although various surrogate antifouling biocides have been introduced, their comparative effectiveness has not been well investigated partly due to the difficulty of quantitative evaluation of their antifouling activity. Here we report an image cytometric method to quantitatively analyze the antifouling activities of seven commercial biocides using Ulva prolifera as a target organism, which is known to be a dominant marine species causing soft fouling. The number of spores settled on a substrate is determined through image analysis using the intrinsic fluorescence of chlorophylls in the spores. Pre-determined sets of size and shape of spores allow for the precise determination of the number of settled spores. The effects of biocide concentration and combination of different biocides on the spore settlement are examined. No significant morphological changes of Ulva spores are observed, but the amount of adhesive pad materials is appreciably decreased in the presence of biocides. It is revealed that the growth rate of Ulva is not directly correlated with the antifouling activities against the settlement of Ulva spores. This work suggests that image cytometric analysis is a very convenient, fast-processable method to directly analyze the antifouling effects of biocides and coating materials.

Spatial analysis of 4,5-dichloro-2-n-octyl-4-isothiazolin-3-one (Sea-Nine 211) concentrations and probabilistic risk to marine organisms in Hiroshima Bay, Japan

We analyzed the spatial distribution of an antifouling biocide, 4,5-dichloro-2-n-octyl-4-isothiazolin-3-one (Sea-Nine 211) in the surface water and sediments of Hiroshima Bay, Japan to determine the extent of contamination by this biocide. A quantitative estimate of the environmental concentration distribution (ECD) and species sensitivity distributions (SSDs) for marine organisms were derived by using a Bayesian statistical model to carry out a probabilistic ecological risk analysis, such as calculation of the expected potentially affected fraction (EPAF). The spatial distribution analysis supported the notion that Sea-Nine 211 is used mainly for treatment of ship hulls in Japan. The calculated EPAF suggests that approximately up to a maximum of 0.45% of marine species are influenced by the toxicity of Sea-Nine 211 in Hiroshima Bay. In addition, estimation of the ecological risk with a conventional risk quotient method indicated that the risk was a cause for concern in Hiroshima Bay.

Evaluation of toxicity data to green algae and relationship with hydrophobicity

The quality of the biological activity data is of great importance for the development of algal quantitative structure-activity relationship (QSAR) models. However, a number of algal QSAR models in the literature were developed based on toxicity data without considering the response endpoints, exposure periods and species sensitivity. In this paper, 2323 algal toxicity data (log 1/EC50) in different toxicity response endpoints for 1081 compounds to 26 algal species within different exposure periods (14 and 15 min; 24, 48, 72, 96, 168 and 192 h) were used to evaluate the quality of the toxicity data to green algae. Analysis of 72 h toxicity to algae showed that the closed test had the same sensitivity as the open test for most of the test compounds, but a significant difference was observed for a few compounds. The overall average difference for all compounds ranges from 0.15 to 0.43 log units between toxicity endpoints (yield–growth rate). The relationships between exposure periods of 24, 48, 72 and 96 h indicated that 48 h exposure period is the most sensitive for algal growth inhibition test, and its sensitivity is 0.25 log units greater than 72 and 96 h exposure periods, respectively. Interspecies relationships showed that some algal species have very close sensitivity (e.g. Pseudokirchneriella subcapitata and Chlorella pyrenoidosa or Chlorella vulgaris and Scenedesmus obliquus, respectively), whereas some species have significantly different sensitivity (e.g. P. subcapitata and S. obliquus). Relationships between toxicity and hydrophobicity demonstrated that no difference was observed for non-polar narcotics within different exposure periods (24, 48, 72, and 96 h) or response variables (yield and growth rate). For polar narcotics, in contrast, algal toxicity is dependent on algal species and is related to the response variables and exposure period. We cannot expect significant QSAR models between algal toxicity and descriptors without considering species sensitivity, exposure periods and response endpoints.

Predictive modeling studies for the ecotoxicity of ionic liquids towards the green algae Scenedesmus vacuolatus

Hazardous potential of ionic liquids is becoming an issue of high concern with increasing application of these compounds in various industrial processes. Predictive toxicological modeling on ionic liquids provides a rational assessment strategy and aids in developing suitable guidance for designing novel analogues. The present study attempts to explore the chemical features of ionic liquids responsible for their ecotoxicity towards the green algae Scenedesmus vacuolatus by developing mathematical models using extended topochemical atom (ETA) indices along with other categories of chemical descriptors. The entire study has been conducted with reference to the OECD guidelines for QSAR model development using predictive classification and regression modeling strategies. The best models from both the analyses showed that ecotoxicity of ionic liquids can be decreased by reducing chain length of cationic substituents and increasing hydrogen bond donor feature in cations, and replacing bulky unsaturated anions with simple saturated moiety having less lipophilic heteroatoms.

Toxicity characterization of urban stormwater with bioanalytical tools

Stormwater harvesting has become an attractive alternative strategy to address the rising demand for urban water supply due to limited water sources and population growth. Nevertheless, urban stormwater is also a major source of surface water pollution. Runoff from different urban catchments with source contributions from anthropogenic activities and various land uses causes variable contaminant profiles, thus posing a challenging task for environmental monitoring and risk assessment. A thorough understanding of raw stormwater quality is essential to develop appropriate treatment facilities for potential indirect potable reuse of stormwater. While some of the key chemical components have previously been characterized, only scarce data are available on stormwater toxicity. We benchmarked stormwater samples from urban, residential and industrial sites across various Australian capital cities against samples from the entire water cycle, from sewage to drinking water. Six biological endpoints, targeting groups of chemicals with modes of toxic action of particular relevance for human and environmental health, were investigated: non-specific toxicity (Microtox and combined algae test), the specific modes of action of phytotoxicity (combined algae test), dioxin-like activity (AhR-CAFLUX), and estrogenicity (E-SCREEN), as well as reactive toxicity encompassing genotoxicity (umuC) and oxidative stress (AREc32). Non-specific toxicity was highly variable across sites. The baseline toxicity equivalent concentrations of the most polluted samples were similar to secondary treated effluent from wastewater treatment plants. Phytotoxicity results correlated well with the measured herbicide concentrations at all sites. High estrogenicity was found in two sampling events and could be related to sewage overflow. Genotoxicity, dioxin-like activity, and oxidative stress response were evident in only three of the samples where the stormwater drain was beside a heavy traffic road, confirming that road runoff is the potential source of contaminants, while the bioanalytical equivalent concentrations (BEQ) of these samples were similar to those of raw sewage. This study demonstrates the benefit of bioanalytical tools for screening-level stormwater quality assessment, forming the basis for the evaluation of future stormwater treatment and reuse schemes.

Effect propagation in a toxicokinetic/toxicodynamic model explains delayed effects on the growth of unicellular green algae Scenedesmus vacuolatus

Ecotoxicological standard tests assess toxic effects by exposing an organism to high concentrations over defined periods of time. To evaluate toxicity under field conditions such as fluctuating and pulsed exposures, process-based toxicokinetic/toxicodynamic (TK/TD) models may be used for extrapolation from the existing evidence. A TK/TD model was developed that simulates the effect on growth of the green algae Scenedesmus vacuolatus continuously exposed to the model chemicals norflurazon, triclosan, and N-phenyl-2-naphthylamine. A pharmacological time-response model describing the effects of anticancer treatments on cancer cell growth was adapted and modified to model the affected growth of synchronized algae cells. The TK/TD model simulates the temporal effect course by linking the ambient concentration of a chemical to the observable adverse effect via an internal concentration and a sequence of biological events in the organism. The parameters of the toxicodynamic model are related to the growth characteristics of algae cells, a no effect concentration, the chemical efficacy as well as the ability of recovery and repair, and the delay during damage propagation. The TK/TD model fits well to the observed algae growth. The effect propagation through cumulative cell damage explained the observed delayed responses better than just the toxicokinetics. The TK/TD model could facilitate the link between several effect levels within damage propagation, which prospectively may be helpful to model adverse outcome pathways and time-dependent mixture effects.

Multiple-endpoint assay provides a detailed mechanistic view of responses to herbicide exposure in Chlamydomonas reinhardtii

The release of herbicides into the aquatic environment raises concerns about potential detrimental effects on ecologically important non-target species, such as unicellular algae, necessitating ecotoxicological risk assessment. Algal toxicity tests based on growth, a commonly assessed endpoint, are integrative, and hence do not provide information about underlying toxic mechanisms and effects. This limitation may be overcome by measuring more specific biochemical and physiological endpoints. In the present work, we developed and applied a novel multiple-endpoint assay, and analyzed the effects of the herbicides paraquat, diuron and norflurazon, each representing a specific mechanism of toxic action, on the single celled green alga Chlamydomonas reinhardtii. The endpoints added to assessment of growth were pigment content, maximum and effective photosystem II quantum yield, ATP content, esterase and oxidative activity. All parameters were measured at 2, 6 and 24h of exposure, except for growth and pigment content, which were determined after 6 and 24h only. Effective concentrations causing 50% of response (EC50s) and lowest observable effect concentrations (LOECs) were determined for all endpoints and exposure durations where possible. The assay provided a detailed picture of the concentration- and time-dependent development of effects elicited by the analyzed herbicides, thus improving the understanding of the underlying toxic mechanisms. Furthermore, the response patterns were unique to the respective herbicide and reflected the different mechanisms of toxicity. The comparison of the endpoint responses and sensitivities revealed that several physiological and biochemical parameters reacted earlier or stronger to disturbances than growth. Overall, the presented multiple-endpoint assay constitutes a promising basis for investigating stressor and toxicant effects in green algae.

Crucial role of mechanisms and modes of toxic action for understanding tissue residue toxicity and internal effect concentrations of organic chemicals

This article reviews the mechanistic basis of the tissue residue approach for toxicity assessment (TRA). The tissue residue approach implies that whole-body or organ concentrations (residues) are a better dose metric for describing toxicity to aquatic organisms than is the aqueous concentration typically used in the external medium. Although the benefit of internal concentrations as dose metrics in ecotoxicology has long been recognized, the application of the tissue residue approach remains limited. The main factor responsible for this is the difficulty of measuring internal concentrations. We propose that environmental toxicology can advance if mechanistic considerations are implemented and toxicokinetics and toxicodynamics are explicitly addressed. The variability in ecotoxicological outcomes and species sensitivity is due in part to differences in toxicokinetics, which consist of several processes, including absorption, distribution, metabolism, and excretion (ADME), that influence internal concentrations. Using internal concentrations or tissue residues as the dose metric substantially reduces the variability in toxicity metrics among species and individuals exposed under varying conditions. Total internal concentrations are useful as dose metrics only if they represent a surrogate of the biologically effective dose, the concentration or dose at the target site. If there is no direct proportionality, we advise the implementation of comprehensive toxicokinetic models that include deriving the target dose. Depending on the mechanism of toxicity, the concentration at the target site may or may not be a sufficient descriptor of toxicity. The steady-state concentration of a baseline toxicant associated with the biological membrane is a good descriptor of the toxicodynamics of baseline toxicity. When assessing specific-acting and reactive mechanisms, additional parameters (e.g., reaction rate with the target site and regeneration of the target site) are needed for characterization. For specifically acting compounds, intrinsic potency depends on 1) affinity for, and 2) type of interaction with, a receptor or a target enzyme. These 2 parameters determine the selectivity for the toxic mechanism and the sensitivity, respectively. Implementation of mechanistic information in toxicokinetic-toxicodynamic (TK-TD) models may help explain time-delayed effects, toxicity after pulsed or fluctuating exposure, carryover toxicity after sequential pulses, and mixture toxicity. We believe that this mechanistic understanding of tissue residue toxicity will lead to improved environmental risk assessment.

Application of nd-SPME to determine freely dissolved concentrations in the presence of green algae and algae-water partition coefficients

Biological tests are essential for toxicity assessment of chemicals to aquatic organisms. Since awareness is increasing that freely dissolved concentrations in test media may change during exposure and deviate significantly from nominal concentrations there is a need for concentration monitoring in biotests. Biotests are increasingly miniaturized with effect amounts of toxicants that are close to or below quantification limits of conventional analytical methods. Thus, the suitability of pre-equilibrium non-depletive (nd) solid phase microextraction (SPME) as an analytical method for small test volumes in the presence of green algae Scenedesmus vacuolatus was investigated. The method was validated for several compounds with different physical-chemical properties and effect concentrations. Limits of quantification were at least about 10 times smaller than the EC(50) of the compounds determined in earlier studies in a cell multiplication inhibition tests with Scenedesmus vacuolatus. Fouling of the fibres due to attached algae cells could be excluded and the method was found to be well suited to measure free concentrations in the algae test. The nd-SPME-method was applied to determine partitioning coefficients between algae and the surrounding aqueous phase and can be used to determine real exposure concentrations in a cell multiplication inhibition test with green algae.

Physiological modes of action of fluoxetine and its human metabolites in algae

Fluoxetine, the active ingredient of many antidepressants, was identified as specifically toxic toward algae in a quantitative structure-activity relationship (QSAR) analysis with literature data for algae, daphnia, and fish. The goal of this study was to elucidate the mode of action in algae and to evaluate the toxicity of the major human metabolites of fluoxetine using two different algae tests. The time dependence and sensitivity of thedifferenteffectendpointsyield information on the physiological mode of action. Baseline toxicity was predicted with QSARs based on measured liposome-water partition coefficients. The ratio of predicted baseline toxicity to experimental toxicity (toxic ratio TR) gives information on the intrinsic potency (extent of specificity of effect). The metabolite p-trifluoromethylphenol was classified to act as baseline toxicant Fluoxetine (TR 60-150) and its pharmacologically active metabolite norfluoxetine (TR 10-80) exhibited specific toxicity. By comparison with reference compounds we conclude that fluoxetine and norfluoxetine have an effect on the energy budget of algal cells since the time pattern of these two compounds is most similar to that observed for norflurazon, but they act less specifically as indicated by lower TR values and the similarity of the effect pattern to baseline toxicants. The mixture toxicity of fluoxetine and its human metabolites norfluoxetine and p-TFMP can be predicted using the model of concentration addition for practical purposes of risk assessment despite small deviations from this model for the specific endpoints like PSII inhibition because the integrative endpoints like growth rate and reproduction in all cases gave agreement with the predictions for concentration addition.