Partitioning of polar and non-polar neutral organic chemicals into human and cow milk

Polyparameter Linear Free Energy Relationships for Partitioning of Neutral Organic Compounds to Storage Lipids

Storage lipids are an important compartment in the bioaccumulation of neutral organic compounds. Reliable models for predicting storage lipid-water and storage lipid-air partition coefficients (Kislip/w and Kislip/a), as well as their temperature dependence, are considered useful. Polyparameter linear free energy relationships (PP-LFERs) are accurate, general, and mechanistically clear models for predicting partitioning-related physicochemical quantities. About a decade ago, PP-LFERs were calibrated for Kislip/w at the physiological temperature of 37 °C. However, to date, a comprehensive collection and sufficiently reliable PP-LFERs for Kislip/w and Kislip/a at the most common standard temperature of 25 °C are still lacking. In this study, experimentally based Kislip/w and/or Kislip/a values at 25 °C for 278 compounds were extensively collected or converted from the literature. Subsequently, PP-LFERs were calibrated for Kislip/w and Kislip/a at 25 °C, performing well over 10 orders of magnitude with root-mean-square errors of 0.17-0.21 log units for compounds with reliable descriptors. Furthermore, standard internal energy changes of transfer from water or air to storage lipids for 158 compounds were derived and used to calibrate PP-LFERs for estimating the temperature dependence of Kislip/w or Kislip/a. Additionally, using PP-LFERs, low-density polyethylene was confirmed to be a better storage lipid analogue than silicone and polyoxymethylene in the equilibrium passive sampling of nonpolar and H-bond acceptor polar compounds.

Species Difference? Bovine, Trout, and Human Plasma Protein Binding of Per- and Polyfluoroalkyl Substances

Per- and polyfluoroalkyl substances (PFAS) strongly bind to proteins and lipids in blood, which govern their accumulation and distribution in organisms. Understanding the plasma binding mechanism and species differences will facilitate the quantitative in vitro-to-in vivo extrapolation and improve risk assessment of PFAS. We studied the binding mechanism of 16 PFAS to bovine serum albumin (BSA), trout, and human plasma using solid-phase microextraction. Binding of anionic PFAS to BSA and human plasma was found to be highly concentration-dependent, while trout plasma binding was linear for the majority of the tested PFAS. At a molar ratio of PFAS to protein ν < 0.1 molPFAS/molprotein, the specific protein binding of anionic PFAS dominated their human plasma binding. This would be the scenario for physiological conditions (ν < 0.01), whereas in in vitro assays, PFAS are often dosed in excess (ν > 1) and nonspecific binding becomes dominant. BSA was shown to serve as a good surrogate for human plasma. As trout plasma contains more lipids, the nonspecific binding to lipids affected the affinities of PFAS for trout plasma. Mass balance models that are parameterized with the protein-water and lipid-water partitioning constants (chemical characteristics), as well as the protein and lipid contents of the plasma (species characteristics), were successfully used to predict the binding to human and trout plasma.

Predicting partitioning from low density polyethylene to blood and adipose tissue by linear solvation energy relationship models

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (D_MLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive D_MLW. We use IAM-HPLC based D_MLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMB_narc) of 140 mmol kg^-1 lipid, with a lower limit of 14 mmol kg^-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMB_narc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Acritical review and weight of evidence approach for assessing the bioaccumulation of phenanthrene in aquatic environments

Bioaccumulation (B) assessment is challenging because there are various B-metrics from laboratory and field studies, multiple criteria and thresholds for classifying bioaccumulative (B), very bioaccumulative (vB), and not bioaccumulative (nB) chemicals, as well as inherent variability and uncertainty in the data. These challenges can be met using a weight of evidence (WoE) approach. The Bioaccumulation Assessment Tool (BAT) provides a transparent WoE assessment framework that follows Organisation for Economic Co-operation and Development (OECD) principles for performing a WoE analysis. The BAT guides an evaluator through the process of data collection, generation, evaluation, and integration of various lines of evidence (LoE) (i.e., B-metrics) to inform decision-making. Phenanthrene (PHE) is a naturally occurring chemical for which extensive B and toxicokinetics data are available. A B assessment for PHE using the BAT is described that includes a critical evaluation of 74 measured in vivo LoE for fish and invertebrate species from laboratory and field studies. The number of LoE are reasonably well balanced across taxa (i.e., fish and invertebrates) and the different B-metrics. Additionally, in silico and in vitro biotransformation rate estimates and corresponding model-predicted B-metrics are included as corroborating evidence. Application of the BAT provides a consistent, coherent, and scientifically defensible WoE evaluation to conclude that PHE is not bioaccumulative (nB) because the overwhelming majority of the bioconcentration, bioaccumulation, and biomagnification metrics for both fish and invertebrates are below regulatory thresholds. An analysis of the relevant data using fugacity ratios is also provided, showing that PHE does not biomagnify in aquatic food webs. The critical review identifies recommendations to increase the consistency of B assessments, such as improved standardization of B testing guidelines, data reporting requirements for invertebrate studies, and consideration of temperature and salinity effects on certain B-metrics. Integr Environ Assess Manag 2021;17:911-925. © 2021 Concawe. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Estimating the Equilibrium Distribution of Perfluoroalkyl Acids and 4 of Their Alternatives in Mammals

Perfluoroalkyl acids (PFAAs) mostly exist as ionic compounds that are of major concern because of their accumulative behavior. The discussion about their risk is ongoing considering the increasing production of structurally similar alternatives. We conducted model calculations based on equilibrium distribution coefficients that allow studying the distribution of PFAAs and their alternatives in various mammalian organs through comparison to empirical measurements in humans and rats. The calculations rely on experimentally determined distribution coefficients of a series of PFAAs and 4 of their alternatives to physiological matrices such as structural proteins, storage lipids, membrane lipids, albumin, and fatty acid binding protein (FABP). The relative sorption capacities in each organ were calculated from the combination of distribution coefficients and physiological data. The calculated distribution of PFAAs and alternatives within the organs showed that albumin and membrane lipids and, to a lesser extent, structural proteins have the highest relative sorption capacities for the compounds. Sorption to FABP is only relevant in the distribution of short-chain PFAAs. Storage lipids play a minor role in the distribution of all studied compounds. Our calculated distribution of PFAAs was evaluated by comparison to reported PFAA concentrations in various organs. Environ Toxicol Chem 2021;40:910-920. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

In vitro methods for predicting the bioconcentration of xenobiotics in aquatic organisms

The accumulation of anthropogenic chemical substances in aquatic organisms is an immensely important issue from the point of view of environmental protection. In the context of the increasing number and variety of compounds that may potentially enter the environment, there is a need for efficient and reliable solutions to assess the risks. However, the classic approach of testing with fish or other animals is not sufficient. Due to very high costs, significant time and labour intensity, as well as ethical concerns, in vivo methods need to be replaced by new laboratory-based tools. So far, many models have been developed to estimate the bioconcentration potential of chemicals. However, most of them are not sufficiently reliable and their predictions are based on limited input data, often obtained with doubtful quality. The octanol-water partition coefficient is still often used as the main laboratory tool for estimating bioconcentration. However, according to current knowledge, this method can lead to very unreliable results, both for neutral species and, above all, for ionic compounds. It is therefore essential to start using new, more advanced and credible solutions on a large scale. Over the last years, many in vitro methods have been newly developed or improved, allowing for a much more adequate estimation of the bioconcentration potential. Therefore, the aim of this work was to review the most recent laboratory methods for assessing the bioconcentration potential and to evaluate their applicability in further research.

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.

Predicting storage-lipid water partitioning of organic solutes from molecular structure

Partitioning to storage fat is the major process for bioaccumulation of many neutral organic chemicals. In this work, we evaluated the performance of four predictive models, ABSOLV, COSMOtherm, KOWWIN, and SPARC to calculate storage lipid-water partition coefficients. In a first step of the validation, we used over 300 literature data for chemicals with relatively simple molecular structures. For these compounds the overall performance was similar for all models with a root-mean-square error (rmse) between 0.45 and 0.61 log units. Clear differences became visible in the second validation step where a subset with only H-bond-donor compounds was used. Here, COSMOtherm and SPARC performed clearly better with an rmse of 0.35 and 0.42 log units, respectively, compared to ABSOLV and KOWWIN with an rmse of 0.91 and 0.85 log units, respectively. The last step in our validation was a comparison with experimental values for 22 complex, multifunctional chemicals (including pesticides, hormones, mycotoxins) that we measured specifically for this validation purpose. For these chemicals, predictions by all models were less accurate than those for simpler chemicals. COSMOtherm performed the best (rmse 0.71 log units) while the other methods showed considerably poorer results (rmse 1.29 (ABSOLV), 1.25 (SPARC), and 1.62 (KOWWIN) log units).

Applications of polyparameter linear free energy relationships in environmental chemistry

Partitioning behavior of organic chemicals has tremendous influences on their environmental distribution, reaction rates, bioaccumulation, and toxic effects. Polyparameter linear free energy relationships (PP-LFERs) have been proven to be useful to characterize the equilibrium partitioning of organic chemicals in various environmental and technical partitioning systems and predict the respective partition coefficients. Over the past decade, PP-LFER solute descriptors for numerous environmentally relevant organic chemicals and system parameters for environmentally important partitioning systems have been determined, extending substantially the applicability of the PP-LFER approaches. However, the information needed for the use of PP-LFERs including descriptors and parameters is scattered over a large number of publications. In this work, we review the state of the art of the PP-LFER approaches in environmental chemical applications. The solute descriptors and system parameters reported in the literature and the availability of their database are summarized, and their calibration and prediction methods are overviewed. We also describe tips and pitfalls associated with the use of the PP-LFER approaches and identify research needs to improve further the usefulness of PP-LFERs for environmental chemistry.

General model for estimating partition coefficients to organisms and their tissues using the biological compositions and polyparameter linear free energy relationships

Equilibrium partition coefficients of organic chemicals from water to an organism or its tissues are typically estimated by using the total lipid content in combination with the octanol-water partition coefficient (K(ow)). This estimation method can cause systematic errors if (1) different lipid types have different sorptive capacities, (2) nonlipid components such as proteins have a significant contribution, and/or (3) K(ow) is not a suitable descriptor. As an alternative, this study proposes a more general model that uses detailed organism and tissue compositions (i.e., contents of storage lipid, membrane lipid, albumin, other proteins, and water) and polyparameter linear free energy relationships (PP-LFERs). The values calculated by the established PP-LFER-composition-based model agree well with experimental in vitro partition coefficients and in vivo steady-state concentration ratios from the literature with a root mean squared error of 0.32-0.53 log units, without any additional fitting. This model estimates a high contribution of the protein fraction to the overall tissue sorptive capacity in lean tissues (e.g., muscle), in particular for H-bond donor polar compounds. Direct model comparison revealed that the simple lipid-octanol model still calculates many tissue-water partition coefficients within 1 log unit of those calculated by the PP-LFER-composition-based model. Thus, the lipid-octanol model can be used as an order-of-magnitude approximation, for example, for multimedia fate modeling, but may not be suitable for more accurate predictions. Storage lipid-rich phases (e.g., adipose, milk) are prone to particularly large systematic errors. The new model provides useful implications for validity of lipid-normalization of concentrations in organisms, interpretation of biomonitoring results, and assessment of toxicity.

Partitioning of organic chemicals to storage lipids: elucidating the dependence on fatty acid composition and temperature

Lipids serve as important compartments in partitioning of neutral organic chemicals into organisms. Storage lipids, made up of triglycerides with various fatty acids, are among the major classes of lipids. Here, we present experimental equilibrium partition data for diverse chemicals in fish oil, linseed oil, and goose fat at 37 °C. These data, in combination with data from the literature for olive oil and milk fat, show that the fatty acid composition of triglycerides has no significant influence on the partition coefficient. This result allows the derivation of a general predictive model for partitioning into storage lipids. We have collected storage lipid/water partition coefficients for 247 compounds to calibrate polyparameter linear free energy relationships (pp-LFERs) for 37 °C, which achieved a model fit with a root mean squared error of 0.20 log units. To extend the applicability of this model toward the aquatic food chain, we also measured fish oil partition data at 7 °C. The resulting enthalpies were used to calibrate an additional pp-LFER for the temperature dependence of storage lipid/water partitioning. This model allows us to estimate partition coefficients at desired temperatures that occur under typical ambient conditions.