Toxicokinetic and toxicodynamic model for diazinon toxicity--mechanistic explanation of differences in the sensitivity of Daphnia magna and Gammarus pulex

Occurrence, removal and risk assessment of chemicals of emerging concern in selected rivers and wastewater treatment plants in western Kenya

Water resources play a crucial role in sustaining life on earth yet chemicals of emerging concern (CECs) arising from extensive human applications are an increasing threat towards their existence. In this study, we examined the occurrence, removal and potential risk of CECs found in rivers and wastewater treatment plants (WWTPs) in western Kenya. Samples were prepared by solid-phase extraction and analysed using high performance liquid chromatography-mass spectrometry with a target list of 785 compounds. Out of these, 333 and 352 (influent 322, effluent 265) compounds were quantified in rivers and wastewater respectively, with pharmaceuticals, industrial compounds, and pesticides being frequently detected in both rivers and WWTPs. Compounds with highest concentrations included saccharin (9.9 μg/L), metformin (7.5 μg/L), and oxypurinol (6.5 μg/L) in rivers whereas caffeine (280 μg/L), deoxycholic acid (179 μg/L), 2-oxindole (10.9 μg/L) and ibuprofen (8.1 μg/L) were found at high concentrations in WWTPs. Based on the types of crops grown, samples from maize growing regions recorded the highest number of pesticides (75) which coincided with the spraying season. The WWTP showed the capacity to eliminate some compounds although the removal efficiencies varied greatly with 204 compounds exhibiting an average removal efficiency exceeding 50 %. Based on the risk assessment, crustaceans had the highest potential risk for toxicity with toxic unit (TU) values up to 5.4 driven primarily by diazinon and dichlorvos followed by algae (TU up to 0.07) and fish (TU up to 0.01) in rivers. A similar trend was observed in WWTP with diazinon (TU up to 5.5), diuron (TU up to 0.07) and carbendazim (TU up to 0.006) driving the risk for crustaceans, algae and fish respectively. These findings highlight the significance of surface water and WWTPs as sources and sinks of CECs in the environment translating to potential risks on aquatic organisms and humans.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

High Tolerance and Delayed Responses of Daphnia magna to Neonicotinoid Insecticide Imidacloprid: Toxicokinetic and Toxicodynamic Modeling

Species sensitivity to neonicotinoids has been shown to be highly variable among aquatic invertebrates. Toxicokinetic and toxicodynamic (TKTD) models were constructed to mechanistically elucidate the susceptibility of Daphnia magna to imidacloprid. D. magna was highly tolerant to single short-term exposure to imidacloprid (96-h LC50 of 8.47 μg/mL), but delayed and carry-over toxicity occurred under repeated pulse exposures. Kinetic distribution of imidacloprid between exoskeleton and soft tissues of D. magna was evaluated using a newly developed method. Approximately 84% imidacloprid was distributed to soft tissues but was rapidly depurated from the tissue (t_1/2 of 1.2 h), resulting in low bioaccumulation and high tolerance. TKTD modeling also successfully simulated the survival of D. magna after pulsed exposures. The calculated recovery time was 45 d, indicating significant delayed and carry-over toxicity of the insecticide. While complete elimination of imidacloprid only took about 5 h (TK), slow damage recovery (45 d) caused slow organism recovery (TD). Consequently, although D. magna was tolerant to imidacloprid due to fast depuration from soft tissue, long damage recovery time significantly enhanced the toxicity under repeated pulse exposures. Our study highlights the necessity of integrating delayed and carry-over toxicity quantification in assessing the risk of neonicotinoids to aquatic invertebrates.

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.

Mechanistic Effect Modeling Approach for the Extrapolation of Species Sensitivity

In the higher-tier environmental risk assessment of chemicals, species sensitivity distributions (SSDs) are used to statistically describe differences in sensitivity between species and derive community level endpoints. SSDs are usually based on the results from short-term laboratory experiments performed under constant environmental conditions. However, different species may be kept at different "optimal" temperatures, which influence their apparent sensitivity and thus the derivation of endpoints. Also, the extrapolation capacity of SSDs is largely limited to the tested species and conditions. Time-variable exposures and effects at higher levels of biological organization, including biological interactions, are not considered. The quantitative effect prediction at higher tiers would ultimately require the extrapolation of toxicokinetics and toxicodynamics to untested species and the involvement of population and community modeling. In this regard, we tested a toxicokinetic-toxicodynamic modeling approach to mechanistically consider and correct endpoints for ambient temperature and demonstrate the significance for SSDs. We explored correlations in toxicokinetic-toxicodynamic model parameters which would allow for the extrapolation of sensitivities to untested species. Finally, we illustrate the applicability of the approach for higher level effect predictions using an individual-based model. Our results suggest that mechanistic effect modeling approaches can reduce the uncertainties in higher tier effect assessments related to knowledge gaps.

Comparison of Diazinon Toxicity to Temperate and Tropical Freshwater Daphnia Species

The presence of pesticides in water bodies presents unique challenges to the ecosystem and all the life forms. Biological methods have been widely used to examine the toxic effects of various toxicants including pesticides. The present study aims at determining the adverse effects of diazinon, a nonsystemic organophosphate insecticide, on two cladoceran species including the temperate Daphnia magna (D. magna) and the tropical Daphnia lumholtzi (D. lumholtzi). The 48 h LC50 values demonstrated higher toxicity of diazinon for D. lumholtzi at a concentration of 3.41 µg·L−1 compared to D. magna at a concentration of 4.63 µg·L−1. After 14 days of exposure to diazinon, the survival capacity as well as the reproduction potential of the two cladoceran species clearly reduced and their rate of population increase (RPI) decreased at concentrations >0.1 µg·L−1. The present study indicated that the tropical cladoceran (D. lumholtzi) was more sensitive than the temperate D. magna. Therefore, it could be used as an indicator for toxicity assessment in tropical environments. The presence of diazinon in water bodies can be associated with significant risk to aquatic organisms.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913. © 2016 SETAC.

Adverse Outcome Pathway (AOP) Informed Modeling of Aquatic Toxicology: QSARs, Read-Across, and Interspecies Verification of Modes of Action

Alternative approaches have been promoted to reduce the number of vertebrate and invertebrate animals required for the assessment of the potential of compounds to cause harm to the aquatic environment. A key philosophy in the development of alternatives is a greater understanding of the relevant adverse outcome pathway (AOP). One alternative method is the fish embryo toxicity (FET) assay. Although the trends in potency have been shown to be equivalent in embryo and adult assays, a detailed mechanistic analysis of the toxicity data has yet to be performed; such analysis is vital for a full understanding of the AOP. The research presented herein used an updated implementation of the Verhaar scheme to categorize compounds into AOP-informed categories. These were then used in mechanistic (quantitative) structure-activity relationship ((Q)SAR) analysis to show that the descriptors governing the distinct mechanisms of acute fish toxicity are capable of modeling data from the FET assay. The results show that compounds do appear to exhibit the same mechanisms of toxicity across life stages. Thus, this mechanistic analysis supports the argument that the FET assay is a suitable alternative testing strategy for the specified mechanisms and that understanding the AOPs is useful for toxicity prediction across test systems.

Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum

This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

A simulation study on effects of exposure to a combination of pesticides used in an orchard and tuber crop on the recovery time of a vulnerable aquatic invertebrate

The aim of the present study was to assess whether population effects and recovery times increase when a population of a vulnerable aquatic invertebrate is exposed to concentrations of 1 or multiple pesticides. The 2 sets of pesticide combinations tested are typical for orchard and tuber crops in The Netherlands. Exposure concentrations were predicted using the FOCUS step 3 modeling framework and the Dutch drainage ditch scenario. Recovery times were assessed using the MASTEP population model. We simulated the population dynamics and pesticide effects in a Monte Carlo style by using median effective concentration values drawn from an arthropod species sensitivity distribution. In the tuber scenario, exposure to λ-cyhalothrin resulted in long-term effects, whereas exposure to the co-occurring compound fluazinam hardly resulted in (additional) effects. In the orchard scenario, 3 pesticides resulted in large effects just after exposure, but pulse exposures to these compounds did not coincide. The probabilities of effects for the single compounds added up for the combination; in contrast, the recovery times were not higher for the combination compared to those associated with exposure to the individual compounds. The conclusion from the present study's simulations is that exposure to the evaluated pesticide packages may lead to increased mortality probabilities and effect sizes of the combination, but does not lead to longer recovery times for populations with synchronized reproduction than when exposed to the individual compounds.

Characterization of acetylcholinesterase inhibition and energy allocation in Daphnia magna exposed to carbaryl

The inhibition of acetylcholinesterase (AChE) activity and energy allocation in the freshwater organism Daphnia magna exposed to carbaryl and potential recovery from the effects was examined. The binding of carbaryl-AChE was characterized through in vitro assays. To evaluate the recovery from inhibition and the alteration in energy budget, in vivo exposure and recovery regime tests were conducted. In comparison to diazoxon, the active metabolite of the insecticide diazinon, the stability of enzyme-carbaryl complex was fifteen times lower and the reactivity toward the active site was two times lower, resulting in approximately 30 times lower overall inhibition rate than for diazoxon. The in vitro reactivation rate constant of the inhibited enzyme and the in vivo recovery rate constant of AChE activity were 1.9 h⁻¹ and 0.12 h⁻¹ for carbaryl, respectively, which are much higher than the corresponding rate constants for diazoxon. The lower AChE inhibition and greater reactivation/recovery rates are in accordance with the lower toxicity of carbaryl compared to diazinon. Carbaryl exposure also altered the profile of the energy reserve: the decrease in lipid and glycogen and the increase in protein content resulted in the reduction of the total energy budget by about 45 mJ/g(ww). This corresponds to 26 percent of the available energy, which might allocate for external stressors. The mechanistic model of AChE inhibition is helpful to get an insight into (eco-)toxicological effects of AChE inhibitors on freshwater crustaceans under environmentally realistic conditions.

Comparative toxicokinetics of organic micropollutants in freshwater crustaceans

Exposure and depuration experiments for Gammarus pulex and Daphnia magna were conducted to quantitatively analyze biotransformation products (BTPs) of organic micropollutants (tramadol, irgarol, and terbutryn). Quantification for BTPs without available standards was performed using an estimation method based on physicochemical properties. Time-series of internal concentrations of micropollutants and BTPs were used to estimate the toxicokinetic rates describing uptake, elimination, and biotransformation processes. Bioaccumulation factors (BAF) for the parents and retention potential factors (RPF), representing the ratio of the internal amount of BTPs to the parent at steady state, were calculated. Nonlinear correlation of excretion rates with hydrophobicity indicates that BTPs with lower hydrophobicity are not always excreted faster than the parent compound. For irgarol, G.pulex showed comparable elimination, but greater uptake and BAF/RPF values than D.magna. Further, G. pulex had a whole set of secondary transformations that D. magna lacked. Tramadol was transformed more and faster than irgarol and there were large differences in toxicokinetic rates for the structurally similar compounds irgarol and terbutryn. Thus, predictability of toxicokinetics across species and compounds needs to consider biotransformation and may be more challenging than previously thought because we found large differences in closely related species and similar chemical structures.

Developing predictive systems models to address complexity and relevance for ecological risk assessment

Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have.