A Novel Multispecies Toxicokinetic Modeling Approach in Support of Chemical Risk Assessment.

Standardized laboratory tests with a limited number of model species are a key component of chemical risk assessments. These surrogate species cannot represent the entire diversity of native species, but there are practical and ethical objections against testing chemicals in a large variety of species. In previous research, we have developed a multispecies toxicokinetic model to extrapolate chemical bioconcentration across species by combining single-species physiologically based toxicokinetic (PBTK) models. This "top-down" approach was limited, however, by the availability of fully parameterized single-species models. Here, we present a "bottom-up" multispecies PBTK model based on available data from 69 freshwater fishes found in Canada. Monte Carlo-like simulations were performed using statistical distributions of model parameters derived from these data to predict steady-state bioconcentration factors (BCFs) for a set of well-studied chemicals. The distributions of predicted BCFs for 1,4-dichlorobenzene and dichlorodiphenyltrichloroethane largely overlapped those of empirical data, although a tendency existed toward overestimation of measured values. When expressed as means, predicted BCFs for 26 of 34 chemicals (82%) deviated by less than 10-fold from measured data, indicating an accuracy similar to that of previously published single-species models. This new model potentially enables more environmentally relevant predictions of bioconcentration in support of chemical risk assessments.

Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors.

The intrinsic metabolic clearance rate (Clint) and the fraction of the chemical unbound in plasma (fup) serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER < 1 indicates that exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6484 chemicals), we found that the proportion of chemicals with BER <1 was similar using either in silico (1133/6484; 17.5%) or in vitro (148/848; 17.5%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER <1 or >1 using either in silico or in vitro parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.

Correction to Designing QSARs for Parameters of High Throughput Toxicokinetic Models Using Open-Source Descriptors.

The intrinsic metabolic clearance rate (Clint) and fraction of chemical unbound in plasma (fup) serve as important parameters for high throughput toxicokinetic models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on Bioactivity: Exposure Ratios (BER), in which a BER < 1 indicates exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6631 chemicals) we found that the proportion of chemicals with BER < 1 was similar using either in silico (1337/6631; 20.16%) or in vitro (151/850; 17.76%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER < 1 or >1 using either in silico or in vitro parameters (776/850, 91.30%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.

Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.

The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data are scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0.11-0.14), and acids (MAE 0.14-0.17). A consensus model had the highest accuracy across both pharmaceuticals (MAE 0.151-0.155) and environmentally relevant chemicals (MAE 0.110-0.131). The inclusion of the majority of the ToxCast test sets within the AD of the consensus model, coupled with high prediction accuracy for these chemicals, indicates the model provides a QSAR for Fub that is broadly applicable to both pharmaceuticals and environmentally relevant chemicals.

Which Molecular Features Affect the Intrinsic Hepatic Clearance Rate of Ionizable Organic Chemicals in Fish?

Greater knowledge of biotransformation rates for ionizable organic compounds (IOCs) in fish is required to properly assess the bioaccumulation potential of many environmentally relevant contaminants. In this study, we measured in vitro hepatic clearance rates for 50 IOCs using a pooled batch of liver S9 fractions isolated from rainbow trout (Oncorhynchus mykiss). The IOCs included four types of strongly ionized acids (carboxylates, phenolates, sulfonates, and sulfates), three types of strongly ionized bases (primary, secondary, tertiary amines), and a pair of quaternary ammonium compounds (QACs). Included in this test set were several surfactants and a series of beta-blockers. For linear alkyl chain IOC analogues, biotransformation enzymes appeared to act directly on the charged terminal group, with the highest clearance rates for tertiary amines and sulfates and no clearance of QACs. Clearance rates for C12-IOCs were higher than those for C8-IOC analogues. Several analogue series with multiple alkyl chains, branched alkyl chains, aromatic rings, and nonaromatic rings were evaluated. The likelihood of multiple reaction pathways made it difficult to relate all differences in clearance to specific molecular features the tested IOCs. Future analysis of primary metabolites in the S9 assay is recommended to further elucidate biotransformation pathways for IOCs in fish.

Optimization of a UDP-glucuronosyltransferase assay for trout liver S9 fractions: activity enhancement by alamethicin, a pore-forming peptide.

1. An existing assay for UDP-glucuronosyltransferase (UGT) activity in trout liver microsomes was optimized using trout liver S9 fractions. Individual experiments were conducted to determine the time dependence of UGT activity as well as optimal levels of S9 protein, uridine 5'-diphosphoglucuronic acid (UDPGA), substrate (p-nitrophenol) and alamethicin, a pore-forming agent added to eliminate latency. 2. Addition of Mg2+ (to 1 mM) or bovine serum albumin (BSA; to 2% w/v) had variable effects on activity, but these effects were minor. Eliminating alamethicin from the system resulted in very low levels of activity. A portion of this activity could be recovered by adding Triton X-100 or Brij 58; however, the optimal concentration range for either detergent was very narrow. 3. When expressed on a pmol/min/g liver basis, UGT activities determined using this updated assay were substantially higher than those reported previously for uninduced trout. 4. These results clearly demonstrate the advantages of using alamethicin for the removal of latency in UGT activity studies with trout and may have broad implications for the study of UGTs in other fish species.

Predicting the bioconcentration of fragrance ingredients by rainbow trout using measured rates of in vitro intrinsic clearance.

Bioaccumulation in aquatic species is a critical end point in the regulatory assessment of chemicals. Few measured fish bioconcentration factors (BCFs) are available for fragrance ingredients. Thus, predictive models are often used to estimate their BCFs. Because biotransformation can reduce chemical accumulation in fish, models using QSAR-estimated biotransformation rates have been developed. Alternatively, biotransformation can be measured by in vitro methods. In this study, biotransformation rates for nine fragrance ingredients were measured using trout liver S9 fractions and used as inputs to a recently refined in vitro-in vivo extrapolation (IVIVE) model. BCFs predicted by the model were then compared to (i) in vivo BCFs, (ii) BCFs predicted using QSAR-derived biotransformation rates, (iii) BCFs predicted without biotransformation, and (iv) BCFs predicted by a well-known regression model. For fragrance ingredients with relatively low (<4.7) log K(OW) values, all models predicted BCFs below a bioaccumulation threshold of 1000. For chemicals with higher (4.7-5.8) log K(OW) values, the model incorporating measured in vitro biotransformation rates and assuming no correction for potential binding effects on hepatic clearance provided the most accurate predictions of measured BCFs. This study demonstrates the value of integrating measured biotransformation rates for prediction of chemical bioaccumulation in fish.

Intra- and interlaboratory reliability of a cryopreserved trout hepatocyte assay for the prediction of chemical bioaccumulation potential.

Measured rates of intrinsic clearance determined using cryopreserved trout hepatocytes can be extrapolated to the whole animal as a means of improving modeled bioaccumulation predictions for fish. To date, however, the intra- and interlaboratory reliability of this procedure has not been determined. In the present study, three laboratories determined in vitro intrinsic clearance of six reference compounds (benzo[a]pyrene, 4-nonylphenol, di-tert-butyl phenol, fenthion, methoxychlor and o-terphenyl) by conducting substrate depletion experiments with cryopreserved trout hepatocytes from a single source. O-terphenyl was excluded from the final analysis due to nonfirst-order depletion kinetics and significant loss from denatured controls. For the other five compounds, intralaboratory variability (% CV) in measured in vitro intrinsic clearance values ranged from 4.1 to 30%, while interlaboratory variability ranged from 27 to 61%. Predicted bioconcentration factors based on in vitro clearance values exhibited a reduced level of interlaboratory variability (5.3-38% CV). The results of this study demonstrate that cryopreserved trout hepatocytes can be used to reliably obtain in vitro intrinsic clearance of xenobiotics, which provides support for the application of this in vitro method in a weight-of-evidence approach to chemical bioaccumulation assessment.

Optimizing the use of rainbow trout hepatocytes for bioaccumulation assessments with fish.

Biotransformation rates measured using cryopreserved trout hepatocytes can be extrapolated to the whole animal to predict metabolism impacts on chemical bioaccumulation. Future use of these methods within a regulatory context requires, however, that they be optimized and standardized. Specifically, questions exist concerning gender differences in metabolism, cryopreservability of cells, and the accuracy of in vitro-in vivo scaling factors. 2. In this study, we evaluated hepatocytes from juvenile male and female trout. No gender differences in cell size, protein abundance, cytochrome P450 content, ethoxyresorufin-O-deethylase activity, uridine diphosphate glucuronosyltransferase activity or intrinsic clearance of pyrene were observed for freshly isolated hepatocytes. There was a small difference in measured glutathione-S-transferase activity (<25%; males > females). 3. Cells were cryopreserved by two methods: direct placement into liquid N2 vapor and controlled, slow-rate freezing. Comparable live recovery and enzymatic activity were observed regardless of freezing method or gender. Cells cryopreserved in liquid N2 vapor exhibited activity levels similar to those of freshly isolated cells, although there were small but significant differences in pyrene clearance and glutathione-S-transferase activity (frozen < fresh). Hepatocellularity values did not differ by sex. 4. These results suggest that hepatocytes from male and female juvenile trout may be used interchangeably for in vitro-in vivo metabolism extrapolations.

Enantiomer-specific in vitro biotransformation of select pharmaceuticals in rainbow trout (Oncorhynchus mykiss).

The occurrence of pharmaceuticals in the environment represents a challenge of emerging concern. Many pharmaceuticals are chiral compounds; however, few studies have examined the relative toxicity of pharmaceutical enantiomers to wildlife. Further, our understanding of stereospecific pharmacokinetics remains largely informed by research on humans and a few well-studied laboratory test animals, and not by studies conducted with environmentally relevant species, including fish. The objective of this study was to investigate whether rainbow trout display stereospecific in vitro metabolism of three common chiral pharmaceuticals. Metabolism by trout liver S9 fractions was evaluated using a substrate depletion approach, which provides an estimate of intrinsic hepatic clearance (CL(IN VITRO,INT)). No biotransformation was observed for rac-, R-, or S-fluoxetine. Ibuprofen, including both enantiomers and the racemic mixture, appeared to undergo slow metabolism, but the resulting substrate depletion curves did not differ significantly from those of inactive controls. Contrary to relative clearance rates in humans, S(-)-propranolol was more rapidly cleared than the R(+)-enantiomer. This work demonstrates that relative clearance rates and the effects of racemic mixtures in trout could not have been predicted based on human data. Additional research describing species differences and exploring tools for species extrapolation in biomedical and environmental studies is needed.

Models Used to Predict Chemical Bioaccumulation in Fish from in Vitro Biotransformation Rates Require Accurate Estimates of Blood-Water Partitioning and Chemical Volume of Distribution.

Methods for extrapolating measured in vitro intrinsic clearance to a whole-body biotransformation rate constant (kB ) have been developed to support modeled bioaccumulation assessments for fish. The inclusion of extrapolated kB values into existing bioaccumulation models improves the prediction of chemical bioconcentration factors (BCFs), but there remains a tendency for these methods to overestimate BCFs relative to measured values. Therefore, a need exists to evaluate the extrapolation procedure to assess potential sources of error in predicted kB values. We examined how three different approaches (empirically based, composition based, and polyparameter linear free energy relationships [ppLFERs]) used to predict chemical partitioning in vitro (liver S9 system; KS9W ), in blood (KBW ), and in whole fish tissues (KFW ) impact the prediction of a chemical's hepatic clearance binding term (fU ) and apparent volume of distribution (VD ), both of which factor into the calculation of kB and the BCF. Each approach yielded different KS9W , KBW , and KFW values, but resulted in fU values that were of similar magnitude and remained relatively constant at log octanol-water partition ratios (KOW ) greater than 4. This is because KBW and KS9W values predicted by any given approach exhibit a similar dependence on log KOW (i.e., regression slope), which results in a cancelation of "errors" when fU is calculated. In contrast, differences in KBW values predicted by the three approaches translate to differences in VD , and by extension kB and the BCF, which become most apparent at log KOW greater than 6. There is a need to collect KBW and VD data for hydrophobic chemicals in fish that can be used to evaluate and improve existing partitioning prediction approaches in extrapolation models for fish. Environ Toxicol Chem 2023;42:33-45. © 2022 SETAC.

In Vitro-In Vivo Extrapolation of Hepatic Biotransformation Data for Fish. III. An In-depth Case Study with Pyrene.

Computational models that predict chemical bioaccumulation in fish generally account for biotransformation using an apparent first-order whole-body rate constant (kB ; d-1 ). The use of such models requires, therefore, that methods exist for estimating kB , ideally without the need to expose live animals. One promising approach for estimating kB involves the extrapolation of measured in vitro intrinsic clearance (CLIN VITRO,INT ) to the whole animal (in vitro-in vivo extrapolation, [IVIVE]). To date, however, the accuracy of such predictions has been difficult to assess due to uncertainties associated with one or more extrapolation factors and/or a mismatch between fish used to generate in vitro data and those used to conduct in vivo exposures. In the present study we employed a combined in vitro and in vivo experimental approach to evaluate the IVIVE procedure using pyrene (PYR) as a model chemical. To the extent possible, measured rates of CLIN VITRO,INT were extrapolated to estimates of kB using extrapolation factors based on measured values. In vitro material (liver S9 fraction) was obtained from fish exposed to PYR in a controlled bioconcentration study protocol. Fish from the same study were then used to estimate in vivo kB values from an analysis of chemical depuration data. Averaged across four study groups, kB values estimated by IVIVE underestimated those determined from in vivo data by 2.6-fold. This difference corresponds to a 4.1-fold underestimation of true in vivo intrinsic clearance, assuming the liver is the only site of biotransformation. These findings are consistent with previous work performed using mammals and have important implications for use of measured CLIN VITRO,INT values in bioaccumulation assessments with fish. Environ Toxicol Chem 2023;42:1501-1515. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

An amended in vitro-in vivo extrapolation model that accounts for first pass clearance effects on chemical bioaccumulation in fish.

Measured rates of in vitro intrinsic clearance for fish may be extrapolated to the whole animal as a means of estimating a whole-body biotransformation rate constant (kB; d-1). This estimate of kB can then be used as an input to existing bioaccumulation prediction models. Most in vitro-in vivo extrapolation/bioaccumulation (IVIVE/B) modeling efforts to date have focused on predicting the chemical bioconcentration in fish (aqueous only exposure), with less attention paid to dietary exposures. Following dietary uptake, biotransformation in the gut lumen, intestinal epithelia, and liver can reduce chemical accumulation; however, current IVIVE/B models do not consider these first pass clearance effects on dietary uptake. Here we present an amended IVIVE/B model that accounts for first pass clearance. The model is then used to examine how biotransformation in the liver and intestinal epithelia (alone or combined) may impact chemical accumulation that occurs during dietary exposure. First pass clearance by the liver can greatly reduce dietary uptake of contaminants, but these effects are only apparent at rapid rates of in vitro biotransformation (first order depletion rate constant kDEP ≥ 10 h-1). The impact of first pass clearance becomes more pronounced when biotransformation in the intestinal epithelia is included in the model. Modelled results suggest that biotransformation in the liver and intestinal epithelia cannot entirely explain reduced dietary uptake reported in several in vivo bioaccumulation tests. This unexplained reduction in dietary uptake is attributed to chemical degradation in the gut lumen. These findings underscore the need for research to directly investigate luminal biotransformation in fish.

A biologically based computational model for the hypothalamic-pituitary-thyroid (HPT) axis in Xenopus laevis larvae.

A biologically based computational model was developed to describe the hypothalamic-pituitary-thyroid (HPT) axis in developing Xenopus laevis larvae. The goal of this effort was to develop a tool that can be used to better understand mechanisms of thyroid hormone-mediated metamorphosis in X. laevis and predict organismal outcomes when those mechanisms are perturbed by chemical toxicants. In this report, we describe efforts to simulate the normal biology of control organisms. The structure of the model borrows from established models of HPT axis function in mammals. Additional features specific to X. laevis account for the effects of organism growth, growth of the thyroid gland, and developmental changes in regulation of thyroid stimulating hormone (TSH) by circulating thyroid hormones (THs). Calibration was achieved by simulating observed changes in stored and circulating levels of THs during a critical developmental window (Nieuwkoop and Faber stages 54-57) that encompasses widely used in vivo chemical testing protocols. The resulting model predicts that multiple homeostatic processes, operating in concert, can act to preserve circulating levels of THs despite profound impairments in TH synthesis. Represented in the model are several biochemical processes for which there are high-throughput in vitro chemical screening assays. By linking the HPT axis model to a toxicokinetic model of chemical uptake and distribution, it may be possible to use this in vitro effects information to predict chemical effects in X. laevis larvae resulting from defined chemical exposures.

Predicting the Accumulation of Ionizable Pharmaceuticals and Personal Care Products in Aquatic and Terrestrial Organisms.

The extent to which chemicals bioaccumulate in aquatic and terrestrial organisms represents a fundamental consideration for chemicals management efforts intended to protect public health and the environment from pollution and waste. Many chemicals, including most pharmaceuticals and personal care products (PPCPs), are ionizable across environmentally relevant pH gradients, which can affect their fate in aquatic and terrestrial systems. Existing mathematical models describe the accumulation of neutral organic chemicals and weak acids and bases in both fish and plants. Further model development is hampered, however, by a lack of mechanistic insights for PPCPs that are predominantly or permanently ionized. Targeted experiments across environmentally realistic conditions are needed to address the following questions: (1) What are the partitioning and sorption behaviors of strongly ionizing chemicals among species? (2) How does membrane permeability of ions influence bioaccumulation of PPCPs? (3) To what extent are salts and associated complexes with PPCPs influencing bioaccumulation? (4) How do biotransformation and other elimination processes vary within and among species? (5) Are bioaccumulation modeling efforts currently focused on chemicals and species with key data gaps and risk profiles? Answering these questions promises to address key sources of uncertainty for bioaccumulation modeling of ionizable PPCPs and related contaminants. Environ Toxicol Chem 2022;00:1-11. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals.

Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Evaluation and comparison of in vitro intrinsic clearance rates measured using cryopreserved hepatocytes from humans, rats, and rainbow trout.

In vitro and in silico methods that can reduce the need for animal testing are being used with increasing frequency to assess chemical risks to human health and the environment. The rate of hepatic biotransformation is an important species-specific parameter for determining bioaccumulation potential and extrapolating in vitro bioactivity to in vivo effects. One approach to estimating hepatic biotransformation is to employ in vitro systems derived from liver tissue to measure chemical (substrate) depletion over time which can then be translated to a rate of intrinsic clearance (CLint). In the present study, cryopreserved hepatocytes from humans, rats, and rainbow trout were used to measure CLint values for 54 industrial and pesticidal chemicals at starting test concentrations of 0.1 and 1 µM. A data evaluation framework that emphasizes the behavior of Heat-Treated Controls (HTC) was developed to identify datasets suitable for rate reporting. Measured or estimated ("greater than" or "less than") CLint values were determined for 124 of 226 (55 %) species-chemical-substrate concentration datasets with acceptable analytical chemistry. A large percentage of tested chemicals exhibited low HTC recovery values, indicating a substantial abiotic loss of test chemical over time. An evaluation of KOW values for individual chemicals suggested that in vitro test performance declined with increasing chemical hydrophobicity, although differences in testing devices for mammals and fish also likely played a role. The current findings emphasize the value of negative controls as part of a rigorous approach to data quality assessment for in vitro substrate depletion studies. Changes in current testing protocols can be expected to result in the collection of higher quality data. However, poorly soluble chemicals are likely to remain a challenge for CLint determination.

Biotransformation Potential of Cationic Surfactants in Fish Assessed with Rainbow Trout Liver S9 Fractions.

Biotransformation may substantially reduce the extent to which organic environmental contaminants accumulate in fish. Presently, however, relatively little is known regarding the biotransformation of ionized chemicals, including cationic surfactants, in aquatic organisms. To address this deficiency, a rainbow trout liver S9 substrate depletion assay (RT-S9) was used to measure in vitro intrinsic clearance rates (CLint ; ml min-1 g liver-1 ) for 22 cationic surfactants that differ with respect to alkyl chain length and degree of methylation on the charged nitrogen atom. None of the quaternary N,N,N-trimethylalkylammonium compounds exhibited significant clearance. Rapid clearance was observed for N,N-dimethylalkylamines, and slower rates of clearance were measured for N-methylalkylamine analogs. Clearance rates for primary alkylamines were generally close to or below detectable levels. For the N-methylalkylamines and N,N-dimethylalkylamines, the highest CLint values were measured for C10 -C12 homologs; substantially lower clearance rates were observed for homologs containing shorter or longer carbon chains. Based on its cofactor dependency, biotransformation of C12 -N,N-dimethylamine appears to involve one or more cytochrome P450-dependent reaction pathways, and sulfonation. On a molar basis, N-demethylation metabolites accounted for up to 25% of the N,N-dimethylalkylamines removed during the 2-h assay, and up to 55% of the removed N-methylalkylamines. These N-demethylation products possess greater metabolic stability in the RT-S9 assay than the parent structures from which they derive and may contribute to the overall risk of ionizable alkylamines. The results of these studies provide a set of consistently determined CLint values that may be extrapolated to whole trout to inform in silico bioaccumulation assessments. Environ Toxicol Chem 2021;40:3123-3136. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Addition of Phenylmethylsulfonyl Fluoride Increases the Working Lifetime of the Trout Liver S9 Substrate Depletion Assay, Resulting in Improved Detection of Low Intrinsic Clearance Rates.

The activity of a trout liver S9 substrate depletion assay has been shown to decline over time, presumably due to proteolytic degradation of biotransformation enzymes. To address this problem, assay performance was evaluated following the addition of phenylmethylsulfonyl fluoride (PMSF) or a general-purpose protease inhibitor cocktail to liver homogenization buffers and/or S9 reaction mixtures. Addition of PMSF to liver homogenization buffers and/or S9 reaction mixtures had little or no effect on clearance of phenanthrene, a model cytochrome P450 substrate, in short-term (25 or 30 min) depletion experiments but resulted in significant improvements in retention of this initial activity over time. The protease inhibitor cocktail strongly inhibited initial activity when added to homogenization buffers or reaction mixtures. Taking into consideration potential effects on liver carboxylesterases, the treatment approach determined to be optimal was addition of 10 µM PMSF to the S9 reaction mixture. Addition of 10 µM PMSF to the mixture resulted in significantly higher rates of phenanthrene clearance in 2-h incubations relative to those obtained in the absence of PMSF and a 6-fold increase in the working lifetime of the preparation. The results of a statistical power analysis suggest that by increasing the working lifetime of the assay, addition of PMSF to the reaction mixture could result in substantially improved detection of low in vitro clearance rates when compared to current practice. These findings demonstrate the value of adding PMSF to the trout S9 preparation and may have broad implications for use of this assay to support chemical bioaccumulation assessments for fish. Environ Toxicol Chem 2021;40:148-161. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.