Biotransformation model of neutral and weakly polar organic compounds in fish incorporating internal partitioning

Modeling the Partitioning of Anionic Carboxylic and Perfluoroalkyl Carboxylic and Sulfonic Acids to Octanol and Membrane Lipid

Perfluoroalkyl carboxylic and sulfonic acids (PFCAs and PFSAs, respectively) have low acid dissociation constant values and are, therefore, deprotonated under most experimental and environmental conditions. Hence, the anionic species dominate their partitioning between water and organic phases, including octanol and phospholipid bilayers which are often used as model systems for environmental and biological matrices. However, data for solvent-water (SW) and membrane-water partition coefficients of the anion species are only available for a few per- and polyfluoroalkyl substances (PFAS). In the present study, an equation is derived using a Born-Haber cycle that relates the partition coefficients of the anions to those of the corresponding neutral species. It is shown via a thermodynamic analysis that for carboxylic acids (CAs), PFCAs, and PFSAs, the log of the solvent-water partition coefficient of the anion, log KSW (A- ), is linearly related to the log of the solvent-water partition coefficient of the neutral acid, log KSW (HA), with a unity slope and a solvent-dependent but solute-independent intercept within a PFAS (or CA) family. This finding provides a method for estimating the partition coefficients of PFCAs and PFSAs anions using the partition coefficients of the neutral species, which can be reliably predicted using quantum chemical methods. In addition, we have found that the neutral octanol-water partition coefficient, log KOW , is linearly correlated to the neutral membrane-water partition coefficient, log KMW ; therefore, log KOW , being a much easier property to estimate and/or measure, can be used to predict the neutral log KMW . Application of this approach to KOW and KMW for PFCAs and PFSAs demonstrates the utility of this methodology for evaluating reported experimental data and extending anion property data for chain lengths that are unavailable. Environ Toxicol Chem 2023;42:2317-2328. © 2023 SETAC.

Predicting Primary Biodegradation of Petroleum Hydrocarbons in Aquatic Systems: Integrating System and Molecular Structure Parameters using a Novel Machine-Learning Framework

Quantitative structure-property relationship (QSPR) models for predicting primary biodegradation of petroleum hydrocarbons have been previously developed. These models use experimental data generated under widely varied conditions, the effects of which are not captured adequately within model formalisms. As a result, they exhibit variable predictive performance and are unable to incorporate the role of study design and test conditions on the assessment of environmental persistence. To address these limitations, a novel machine-learning System-Integrated Model (HC-BioSIM) is presented, which integrates chemical structure and test system variability, leading to improved prediction of primary disappearance time (DT50) values for petroleum hydrocarbons in fresh and marine water. An expanded, highly curated database of 728 experimental DT50 values (181 unique hydrocarbon structures compiled from 13 primary sources) was used to develop and validate a supervised model tree machine-learning model. Using relatively few parameters (6 system and 25 structural parameters), the model demonstrated significant improvement in predictive performance (root mean square error = 0.26, R²  = 0.67) over existing QSPR models. The model also demonstrated improved accuracy of persistence (P) categorization (i.e., "Not P/P/vP"), with an accuracy of 96.8%, and false-positive and -negative categorization rates of 0.4% and 2.7%, respectively. This significant improvement in DT50 prediction, and subsequent persistence categorization, validates the need for models that integrate experimental design and environmental system parameters into biodegradation and persistence assessment. Environ Toxicol Chem 2022;41:1359-1369. © 2022 ExxonMobil Biomedical Sciences, Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Determination of In Vivo Biotransformation Kinetics Using Early-Time Biota Concentrations

Technical challenges have hampered the characterization of biotransformation kinetics-a critical link in understanding and predicting the toxicokinetics and ecotoxicology of organic compounds. A shortcut approach to characterize the in vivo biotransformation rate constant (k_M ) with incomplete pathway or metabolite details was proposed. The value of k_M can be derived as 2tln1fPC(t)) , with f_PC (t) being the molar equivalent fraction of the parent compound (PC) at an early time t in both constant exposure and decay source chemical uptake scenarios. The approximation-based k_M values agreed well with k_M values derived from rigorous fitting or toxicokinetic modeling (n = 42, root mean square error = 0.30) with accuracy exceeding those of typical toxicokinetic or partitioning models. The method is accurate when sampling time is adequately resolved (i.e., t < ln(2)/k_M ) but will likely produce biased k_M values with improper time-averaging. The approximate equation yields consistent theoretical expectations for fast and slow biotransformation reactions and is fully compatible with standard bioaccumulation and toxicity testing protocols. The simplification strategy circumvents statistical complications and numerical issues inherent in regressing or modeling the toxicokinetics of multimetabolite systems and may be adapted to similar problems at other physiological scales or ecotoxicological contexts. The method can help advance interspecies comparison of chemical metabolism and support the development of in vitro-in vivo extrapolations and in silico models needed for building next-generation ecological and health risk-assessment practices. Environ Toxicol Chem 2022;41:148-158. © 2021 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 (CL_int). In the present study, cryopreserved hepatocytes from humans, rats, and rainbow trout were used to measure CL_int 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") CL_int 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 K_OW 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 CL_int determination.

A Reduced Model for Bioconcentration and Biotransformation of Neutral Organic Compounds in Midge

A bioconcentration factor (BCF) database and a toxicokinetic model considering only biota-water partitioning and biotransformation were constructed for neutral organic chemicals in midge. The database contained quality-reviewed BCF and toxicokinetic data with variability constrained to within 0.5 to 1 log unit. Diverse conditions in exposure duration, flow set-up, substrate presence, temperature, and taxonomic classification did not translate into substantial variability in BCF, uptake rate constant (k₁ ), or depuration rate constant (k_T ), and no systematic bias was observed in BCFs derived in unlabeled versus radiolabeled studies. Substance-specific biotransformation rate constants k_M were derived by difference between the calculated biota-water partitioning coefficient (K_BW ) and experimental BCF for developing a midge biotransformation model. Experimental midge BCF was modeled as BCF = K_BW /(1 + k_M/ k₂ ) with log k_M (k_M in h^-1 ) = -0.37 log K_OW - 0.06T (in K) + 18.87 (root mean square error [RMSE] = 0.60), log k₁ (k₁ in L kg_wet.wt^-1  h^-1 ) = -0.0747 W (body weight in mg_wet.wt ) + 2.35 (RMSE = 0.48). The K_BW value was estimated using midge biochemical composition and established polyparameter linear free energy relationships, and the diffusive elimination rate constant (k₂ ) was computed as k₂  = k₁ /K_BW. The BCF model predicted >85% of BCFs that associated with neutral organic compounds (log K_OW  = 1.46 - 7.75) to within 1 log-unit error margin and had comparable accuracy similar to amphipod or fish models. A number of outliers and critical limitations of the k_M model were identified and examined, and they largely reflected the inherent limitation of difference-derived k_M , the lack of chemical diversity, and inadequate temperature variation in existing data. Future modeling efforts can benefit from more BCF and toxicokinetic observations of BCF on structurally diverse chemicals for model training, validation, and diagnosis. Environ Toxicol Chem 2021;40:57-71. © 2020 SETAC.

Concentration dependence of in vitro biotransformation rates of hydrophobic organic sunscreen agents in rainbow trout S9 fractions: Implications for bioaccumulation assessment

In vitro biotransformation studies were performed to support the bioaccumulation assessment of 3 hydrophobic organic ultraviolet filters (UVFs), 4-methylbenzylidene camphor (4-MBC), 2-ethylhexyl-4-methoxycinnamate (EHMC), and octocrylene. In vitro depletion rate constants (kdep ) were determined for each UVF using rainbow trout liver S9 fractions. Incubations performed with and without added cofactors showed complete (4-MBC) or partial (EHMC and octocrylene) dependence of kdep on addition of the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH), suggesting that hydrolysis of EHMC and octocrylene by NADPH-independent enzymes (e.g., carboxylesterases) is an important metabolic route. The concentration dependence of kdep was then evaluated to estimate Michaelis-Menten parameters (KM and Vmax ) for each UVF. Measured kdep values were then extrapolated to apparent whole-body biotransformation rate constants using an in vitro-in vivo extrapolation (IVIVE) model. Bioconcentration factors (BCFs) calculated from kdep values measured at concentrations well below KM were closer to empirical BCFs than those calculated from kdep measured at higher test concentrations. Modeled BCFs were sensitive to in vitro binding assumptions employed in the IVIVE model, highlighting the need for further characterization of chemical binding effects on hepatic clearance. The results suggest that the tested UVFs are unlikely to accumulate to levels exceeding the European Union Registration, Evaluation, Authorisation, and Restriction regulation criterion for bioaccumulative substances (BCF > 2000 L kg-1 ). However, consideration of appropriate in vitro test concentrations and binding correction factors are important when IVIVE methods are used to refine modeled BCFs. Environ Toxicol Chem 2019;38:548-560. © 2018 SETAC.

Acceptable-by-design QSARs to predict the dietary biomagnification of organic chemicals in fish

This work presents the first-time QSAR approach to predict the laboratory-based fish biomagnification factor (BMF) of organic chemicals, to be used as a supporting tool for assessing bioaccumulation at the regulatory level. The developed strategy is based on 2 levels of prediction, with a varying trade-off between interpretability and performance according to the user's needs. We designed our models to be intrinsically acceptable at the regulatory level (in what we defined as "acceptable-by-design" strategy), by (i) complying with OECD principles directly in the approach development phase, (ii) choosing easy-to-apply modeling techniques, (iii) preferring simple descriptors when possible, and (iv) striving to provide data-driven mechanistic insights. Our novel tool has an error comparable to the observed experimental inter- and intraspecies variability and is stable on borderline compounds (root mean square error [RMSE] ranging from RMSE = 0.45 to RMSE = 0.45 log units on test data). Additionally, the models' molecular descriptors are carefully described and interpreted, allowing us to gather additional mechanistic insights into the structural features controlling the dietary bioaccumulation of chemicals in fish. To improve the transparency and promote the application of the model, the data set and the stand alone prediction tool are provided free of charge at https://github.com/grisoniFr/bmf_qsar Integr Environ Assess Manag 2019;15:51-63. © 2018 SETAC.

Multi-compartmental toxicokinetic modeling of fipronil in tilapia: Accumulation, biotransformation and elimination

Bioaccumulation and biotransformation are critical processes modifying toxicity of easily metabolizable chemicals to aquatic organisms. In this study, tissue-specific accumulation, biotransformation and elimination of a current-use pesticide fipronil in tilapia (Oreochromis niloticus) were quantified by combining in vivo measurements and a newly developed multi-compartmental toxicokinetic model. Waterborne fipronil was taken up via gills and metabolized rapidly and solely to fipronil sulfone. Significant decrease of fipronil residues in liver and intestine during exposure period strongly suggested the induction of metabolism in these two organs. Significant transport of fipronil and fipronil sulfone in the liver-bile-intestine system implied that hepatobiliary excretion and enterohepatic re-absorption played important roles in fipronil metabolism and system circulation of the parent compound and the metabolite. The multi-compartmental model quantitatively described the highly dynamic inter-compartmental transport and rapid branchial clearance of fipronil in fish. Modeling results also suggested that uptake and biotransformation were the stronger driving forces for the inter-compartmental transport of fipronil in fish than the inherent partitioning capacity. Overall, our findings highlight the importance of biotransformation on internal disposition of fipronil in fish, which helps to improve aquatic toxicity assessment of this pesticide.

Bioconcentration model for non-ionic, polar, and ionizable organic compounds in amphipod

The present study presents a bioconcentration model for non-ionic, polar, and ionizable organic compounds in amphipod based on first-order kinetics. Uptake rate constant k₁ is modeled as logk1=10.81logKOW + 0.15 (root mean square error [RMSE] = 0.52). Biotransformation rate constant k_M is estimated using an existing polyparameter linear free energy relationship model. Respiratory elimination k₂ is calculated as modeled k₁ over theoretical biota-water partition coefficient K_biow considering the contributions of lipid, protein, carbohydrate, and water. With negligible contributions of growth and egestion over a typical amphipod bioconcentration experiment, the bioconcentration factor (BCF) is modeled as k₁ /(k_M + k₂ ) (RMSE = 0.68). The proposed model performs well for non-ionic organic compounds (log K_OW range = 3.3-7.62) within 1 log-unit error margin. Approximately 12% of the BCFs are underpredicted for polar and ionizable compounds. However, >50% of the estimated k₂ values are found to exceed the total depuration rate constants. Analyses suggest that these excessive k₂ values and underpredicted BCFs reflect underestimation in K_biow , which may be improved by incorporating exoskeleton as a relevant partitioning component and refining the membrane-water partitioning model. The immediate needs to build up high-quality experimental k_M values, explore the sorptive role of exoskeleton, and investigate the prevalence of k₂ overestimation in other bioconcentration models are also identified. The resulting BCF model can support, within its limitations, the ecotoxicological and risk assessment of emerging polar and ionizable organic contaminants in aquatic environments and advance the science of invertebrate bioaccumulation. Environ Toxicol Chem 2018;37:1378-1386. © 2018 SETAC.

A weight-of-evidence approach for the bioaccumulation assessment of triclosan in aquatic species

The bioaccumulation assessment of chemicals is challenging because of various metrics and criteria, multiple lines of evidence and underlying uncertainty in the data. Measured in vivo laboratory and field bioaccumulation data are generally considered preferable; however, quantitative structure-activity relationships (QSARs), mass balance models and in vitro data can also be considered. This case study critically evaluates in vivo, in vitro and in silico data and provides new data for the bioaccumulation assessment of triclosan (TCS). The review focusses on measured fish bioconcentration factors (BCFs) because this is the most commonly used regulatory metric. Reported measured fish BCFs range from about 20 to 8700L/kg-ww spanning a range of possible bioaccumulation assessment outcomes, i.e. from "not bioaccumulative" to "very bioaccumulative". Estimated biotransformation rate constants for fish obtained from in vivo, in vitro and in silico methods show general consensus fostering confidence in the selection of plausible values to confront uncertainty in the measured fish BCF tests. Other measurements (lines of evidence) from various species are also collected and reviewed. The estimated biotransformation rate constants and selected chemical property data are used to parameterize bioaccumulation models for aquatic species. Collectively the available lines of evidence are presented using a weight of evidence approach for assessing the bioaccumulation of TCS in aquatic species. Acceptable quality measured data and model predictions for TCS BCFs and bioaccumulation factors are lower than 2000L/kg. Biomagnification factors are <1 (kg/kg). The general consistency in the acceptable quality data is largely explained by the relatively efficient rates of TCS biotransformation in a range of species including measurements of significant in vitro activity of phase II conjugation reactions. The review demonstrates the value of combining models and measurements and, when necessary, applying multiple lines of evidence for chemical assessment.

Can poly-parameter linear-free energy relationships (pp-LFERs) improve modelling bioaccumulation in fish?

A wide range of studies have characterized different types of biosorbent, with regard to their interactions with chemicals. This has resulted in the development of poly-parameter linear free energy relationships (pp-LFERs) for the estimation of partitioning of neutral organic compounds to biological phases (e.g., storage lipids, phospholipids and serum albumins). The aims of this study were to explore and evaluate the influence of implementing pp-LFERs both into a one-compartment fish model and a multi-compartment physiologically based toxicokinetic (PBTK) fish model and the associated implications for chemical risk assessment. For this purpose, fish was used as reference biota, due to their important role in aquatic food chains and dietary exposure to humans. The bioconcentration factor (BCF) was utilized as the evaluation metric. Overall, our results indicated that models incorporating pp-LFERs (R² = 0.75) slightly outperformed the single parameter (sp) LFERs approach in the one-compartmental fish model (R² = 0.72). A pronounced enhancement was achieved for compounds with log K_OW between 4 and 5 with increased R² from 0.52 to 0.71. The minimal improvement was caused by the overestimation of lipid contribution and underestimation of protein contribution by the sp-approach, which cancelled each other out. Meanwhile, a greater improvement was observed for multi-compartmental PBTK models with consideration of metabolism, making all predictions fall within a factor of 10 compared with measured data. For screening purposes, the K_OW-based (sp-LFERs) approach should be sufficient to quantify the main partitioning characteristics. Further developments are required for the consideration of ionization and more accurate quantification of biotransformation in biota.

Estimating Grass-Soil Bioconcentration of Munitions Compounds from Molecular Structure

A partitioning-based model is presented to estimate the bioconcentration of five munitions compounds and two munition-like compounds in grasses. The model uses polyparameter linear free energy relationships (pp-LFERs) to estimate the partition coefficients between soil organic carbon and interstitial water and between interstitial water and the plant cuticle, a lipid-like plant component. Inputs for the pp-LFERs are a set of numerical descriptors computed from molecular structure only that characterize the molecular properties that determine the interaction with soil organic carbon, interstitial water, and plant cuticle. The model is validated by predicting concentrations measured in the whole plant during independent uptake experiments with a root-mean-square error (log predicted plant concentration-log observed plant concentration) of 0.429. This highlights the dominant role of partitioning between the exposure medium and the plant cuticle in the bioconcentration of these compounds. The pp-LFERs can be used to assess the environmental risk of munitions compounds and munition-like compounds using only their molecular structure as input.

Development of human biotransformation QSARs and application for PBT assessment refinement

Toxicokinetics heavily influence chemical toxicity as the result of Absorption, Distribution, Metabolism (Biotransformation) and Elimination (ADME) processes. Biotransformation (metabolism) reactions can lead to detoxification or, in some cases, bioactivation of parent compounds to more toxic chemicals. Moreover, biotransformation has been recognized as a key process determining chemical half-life in an organism and is thus a key determinant for bioaccumulation assessment for many chemicals. This study addresses the development of QSAR models for the prediction of in vivo whole body human biotransformation (metabolism) half-lives measured or empirically-derived for over 1000 chemicals, mainly represented by pharmaceuticals. Models presented in this study meet regulatory standards for fitting, validation and applicability domain. These QSARs were used, in combination with literature models for the prediction of biotransformation half-lives in fish, to refine the screening of the potential PBT behaviour of over 1300 Pharmaceuticals and Personal Care Products (PPCPs). The refinement of the PBT screening allowed, among others, for the identification of PPCPs, which were predicted as PBTs on the basis of their chemical structure, but may be easily biotransformed. These compounds are of lower concern in comparison to potential PBTs characterized by large predicted biotransformation half-lives.

Linear free energy relationships for the adsorption of volatile organic compounds onto multiwalled carbon nanotubes at different relative humidities: comparison with organoclays and activated carbon

Accurate prediction of the sorption coefficients of volatile organic compounds (VOCs) on carbon nanotubes (CNTs) is of major importance for developing an effective VOC removal process and risk assessment of released nanomaterial-carrying contaminants. The linear free energy relationship (LFER) approach was applied to investigate the adsorption mechanisms of VOCs on multiwalled CNTs (MWCNTs). The gas-solid partition coefficients (log K_d) of 17 VOCs were determined at 0%, 55%, and 90% relative humidity (RH). The cavity/dispersion interaction is generally the most influential adsorption mechanism for all RH cases. The hydrogen-accepting interactions declined but with constant hydrogen-donating interactions during the increase of RH, suggesting that the acidity of VOC was important in forming sorptive interaction with the MWCNT surface. Moreover, the comparison of log K_d of VOCs on MWCNTs and other sorbents revealed that the sorption performance of MWCNTs is much more stable over a wider range of RHs due to better site availability and site quality. Furthermore, for all 6 adsorbents in all RHs, the positive contribution of hydrogen bonding ability was found as compared to the negative one found for sorbents completely in water, indicating that the hydrogen-bond donor and acceptor on the sorbent surface contribute to the sorption in the gas phase. In conclusion, the LFER-derived coefficients can be useful in predicting the performance of VOC adsorption on adsorbents and in facilitating the design of efficient VOC removal systems.

Deriving in vivo biotransformation rate constants and metabolite parent concentration factor/stable metabolite factor from bioaccumulation and bioconcentration experiments: An illustration with worm accumulation data

Growing concern for the biological fate of organic contaminants and their metabolites and the urge to connect in vitro and in vivo toxicokinetics have prompted researchers to characterize the biotransformation behavior of organic contaminants in biota. The whole body biotransformation rate constant (k_M ) is currently determined by the difference approach, which has significant methodological limitations. A new approach for determining k_M from the kinetic observations of the parent contaminant and its intermediate metabolites is proposed. In this method, k_M can be determined by fitting kinetic data of the parent contaminant and the metabolites to analytical equations that depict the bioaccumulation kinetics. The application of the proposed method is illustrated using worm bioaccumulation-biotransformation data collected from the literature. Furthermore, a metabolite parent concentration factor (MPCF) is also proposed to characterize the persistence of the metabolite in biota. Because both the proposed k_M method and MPCF build on the existing theoretical framework for bioaccumulation, they can be readily incorporated into standard experimental bioaccumulation protocols or risk assessment procedures or frameworks. Possible limitations, implications, and future directions are elaborated. Environ Toxicol Chem 2016;35:2903-2909. © 2016 SETAC.

Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish

Dietary bioaccumulation tests for fish have been conducted for about 40 years. Standardized test guidance has recently been developed. Test metrics of primary scientific and regulatory interest are the whole body depuration rate constant (kT), whole body growth corrected depuration rate constant (kTg), and corresponding chemical half-lives (t1/2 and t1/2g), dietary chemical absorption efficiency (AE), and biomagnification factor (BMF). A database of 3032 measurement end points for 477 discrete organic chemicals including 964 half-lives, 1199 AEs and 869 BMFs from 19 species (primarily trout and carp) was developed from the literature. Biological properties (e.g., organism weight, lipid content) and exposure conditions (e.g., temperature, feeding rate, dietary lipid content, exposure duration) are documented. Test chemicals range in molar mass from 120 to 1423 g·mol(-1) with log octanol-water partition coefficients (KOW) ranging from 0.8 to 14.3; 50% of the database entries are for polychlorinated biphenyls. The measured end points are derived from various protocols and sources of variability are described. The data are evaluated and categorized using proposed data quality (confidence) criteria derived from the standardized test protocol providing initial guidance for data users. Half-lives range from 0.13 to 2600 days; however, approximately 54% have an identifiable source of uncertainty. The data suggest that chemicals absorbed from the gastrointestinal tract with a log KOW ≥ ∼5 and at least as high as ∼9 have biomagnification potential in fish. A mechanistic bioaccumulation model is compared to the measured data and used to illustrate the influence of growth and biotransformation rates on the BMF.