Phylogeny predicts sensitivity in aquatic animals for only a minority of chemicals.

There are substantial gaps in our empirical knowledge of the effects of chemical exposure on aquatic life that are unlikely to be filled by traditional laboratory toxicity testing alone. One possible alternative of generating new toxicity data is cross-species extrapolation (CSE), a statistical approach in which existing data are used to predict the effect of a chemical on untested species. Some CSE models use relatedness as a predictor of chemical sensitivity, but relatively little is known about how strongly shared evolutionary history influences sensitivity across all chemicals. To address this question, we conducted a survey of phylogenetic signal in the toxicity data from aquatic animal species for a large set of chemicals using a phylogeny inferred from taxonomy. Strong phylogenetic signal was present in just nine of thirty-six toxicity datasets, and there were no clear shared properties among those datasets with strong signal. Strong signal was rare even among chemicals specifically developed to target insects, meaning that these chemicals may be equally lethal to non-target taxa, including chordates. When signal was strong, distinct patterns of sensitivity were evident in the data, which may be informative when assembling toxicity datasets for regulatory use. Although strong signal does not appear to manifest in aquatic toxicity data for most chemicals, we encourage additional phylogenetic evaluations of toxicity data in order to guide the selection of CSE tools and as a means to explore the patterns of chemical sensitivity across the broad diversity of life.

Micafungin Population PK Analysis in Healthy and Septic Pigs: Can the Septic Porcine Model Predict the Micafungin PK in Septic Patients?

OBJECTIVES: To describe micafungin pharmacokinetic (PK) alterations of sepsis induced in piglets and to determine whether the porcine septic model is able to predict the PK of micafungin in septic patients at the plasma and peritoneal sites. METHODS: From healthy (n = 8) and septic piglet group (n = 16), total micafungin concentrations were subject to a population PK analysis using Monolix®. Data from 16 septic humans patients from others studies was used to compare micafungin PK between septic piglets and septic patients. RESULTS: Sepsis induced in piglets slightly alters the total clearance and the volume of distribution, while inter-compartment clearance is increased (from 3.88 to 5.74 L/h) as well as the penetration into peritoneal cavity (from 61 to 90%). In septic human patients, PK parameters are similar except for the Vd, which is corrected by an allometric factor based on the body weight of each species. Micafungin penetration into peritoneal cavity of humans is lower than in septic piglets (40 versus 90%). CONCLUSIONS: The sepsis induced in the porcine model alters the PK of micafungin comparable to that in humans. In addition, micafungin PK is similar between these two species at the plasma level taking into account the allometric relationship of the body weight of these species on the central volume of distribution. The porcine septic plasma model would be able to predict the micafungin PK in the septic patients. However, further studies on peritoneal penetration are necessary to characterize this inter-species difference.

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.

Using TKTD Models in Combination with In Vivo Enzyme Inhibition Assays to Investigate the Mechanisms behind Synergistic Interactions across Two Species.

The aim of this study is to compare the azole synergy across an insect, Chironomus riparius, and a crustacean species, Daphnia magna. We use a combination of in vivo measurements of cytochrome P450 monooxygenase (CYP) biotransformation potential and toxicokinetic (TK) and toxicodynamic (TD) modeling to understand the mechanism behind the synergy of two azole fungicides: the imidazole prochloraz and the triazole propiconazole on the pyrethroid insecticide α-cypermethrin. For both species, the synergistic effect of prochloraz was well-described by its effect on in vivo CYP activity, which corresponded to the biotransformation rate of the TK model parameterized on the survival data of the mixture experiment. For propiconazole, however, there were 100-fold and 50-fold differences between the 50% effect concentration of in vivo CYP activity and the modeled biotransformation rate for C. riparius and D. magna, respectively. Propiconazole, therefore, seems to induce synergy through a mechanism that cannot be quantified solely by the CYP activity assay used in this study in either of the two species. We discuss the differences between prochloraz and propiconazole as synergists across the two species in the light of the type and time dynamics of affected biotransformation processes.

A workflow to build PBTK models for novel species.

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

ERGO: Breaking Down the Wall between Human Health and Environmental Testing of Endocrine Disrupters.

ERGO (EndocRine Guideline Optimization) is the acronym of a European Union-funded research and innovation action, that aims to break down the wall between mammalian and non-mammalian vertebrate regulatory testing of endocrine disruptors (EDs), by identifying, developing and aligning thyroid-related biomarkers and endpoints (B/E) for the linkage of effects between vertebrate classes. To achieve this, an adverse outcome pathway (AOP) network covering various modes of thyroid hormone disruption (THD) in multiple vertebrate classes will be developed. The AOP development will be based on existing and new data from in vitro and in vivo experiments with fish, amphibians and mammals, using a battery of different THDs. This will provide the scientifically plausible and evidence-based foundation for the selection of B/E and assays in lower vertebrates, predictive of human health outcomes. These assays will be prioritized for validation at OECD (Organization for Economic Cooperation and Development) level. ERGO will re-think ED testing strategies from in silico methods to in vivo testing and develop, optimize and validate existing in vivo and early life-stage OECD guidelines, as well as new in vitro protocols for THD. This strategy will reduce requirements for animal testing by preventing duplication of testing in mammals and non-mammalian vertebrates and increase the screening capacity to enable more chemicals to be tested for ED properties.

A comparison of fish pesticide metabolic pathways with those of the rat and goat.

Ecological risk assessments are often limited in their ability to consider metabolic transformations for fish species due to a lack of data. When these types of evaluations are attempted they are often based on parent chemical only, or by assuming similarity to available mammalian metabolic pathways. The metabolism maps for five pesticides (fluazinam, halauxifen-methyl, kresoxim-methyl, mandestrobin, and tolclofos-methyl) were compared across three species. A rapid and transparent process, utilizing a database of systematically collected information for rat, goat, and fish (bluegill or rainbow trout), and using data evaluation tools in the previously described metabolism pathway software system MetaPath, is presented. The approach demonstrates how comparisons of metabolic maps across species are aided by considering the sample matrix in which metabolites were quantified for each species, differences in analytical methods used to identify metabolites in each study, and the relative amounts of metabolites quantified. By incorporating these considerations, more extensive rat and goat metabolism maps were found to be useful predictors of the more limited metabolism of the five pesticides in fish.

Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA).

Chemical regulation is challenged by the large number of chemicals requiring assessment for potential human health and environmental impacts. Current approaches are too resource intensive in terms of time, money and animal use to evaluate all chemicals under development or already on the market. The need for timely and robust decision making demands that regulatory toxicity testing becomes more cost-effective and efficient. One way to realize this goal is by being more strategic in directing testing resources; focusing on chemicals of highest concern, limiting testing to the most probable hazards, or targeting the most vulnerable species. Hypothesis driven Integrated Approaches to Testing and Assessment (IATA) have been proposed as practical solutions to such strategic testing. In parallel, the development of the Adverse Outcome Pathway (AOP) framework, which provides information on the causal links between a molecular initiating event (MIE), intermediate key events (KEs) and an adverse outcome (AO) of regulatory concern, offers the biological context to facilitate development of IATA for regulatory decision making. This manuscript summarizes discussions at the Workshop entitled "Advancing AOPs for Integrated Toxicology and Regulatory Applications" with particular focus on the role AOPs play in informing the development of IATA for different regulatory purposes.

Cross-Species Extrapolation of Biological Data to Guide the Environmental Safety Assessment of Pharmaceuticals-The State of the Art and Future Priorities.

The extrapolation of biological data across species is a key aspect of biomedical research and drug development. In this context, comparative biology considerations are applied with the goal of understanding human disease and guiding the development of effective and safe medicines. However, the widespread occurrence of pharmaceuticals in the environment and the need to assess the risk posed to wildlife have prompted a renewed interest in the extrapolation of pharmacological and toxicological data across the entire tree of life. To address this challenge, a biological "read-across" approach, based on the use of mammalian data to inform toxicity predictions in wildlife species, has been proposed as an effective way to streamline the environmental safety assessment of pharmaceuticals. Yet, how effective has this approach been, and are we any closer to being able to accurately predict environmental risk based on known human risk? We discuss the main theoretical and experimental advancements achieved in the last 10 years of research in this field. We propose that a better understanding of the functional conservation of drug targets across species and of the quantitative relationship between target modulation and adverse effects should be considered as future research priorities. This pharmacodynamic focus should be complemented with the application of higher-throughput experimental and computational approaches to accelerate the prediction of internal exposure dynamics. The translation of comparative (eco)toxicology research into real-world applications, however, relies on the (limited) availability of experts with the skill set needed to navigate the complexity of the problem; hence, we also call for synergistic multistakeholder efforts to support and strengthen comparative toxicology research and education at a global level. Environ Toxicol Chem 2024;43:513-525. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Quantitative cross-species comparison of serum albumin binding of per- and polyfluoroalkyl substances from five structural classes.

Per- and polyfluoroalkyl substances (PFAS) are a class of over 8000 chemicals, many of which are persistent, bioaccumulative, and toxic to humans, livestock, and wildlife. Serum protein binding affinity is instrumental in understanding PFAS toxicity, yet experimental binding data is limited to only a few PFAS congeners. Previously, we demonstrated the usefulness of a high-throughput, in vitro differential scanning fluorimetry assay for determination of relative binding affinities of human serum albumin for 24 PFAS congeners from 6 chemical classes. In the current study, we used this assay to comparatively examine differences in human, bovine, porcine, and rat serum albumin binding of 8 structurally informative PFAS congeners from 5 chemical classes. With the exception of the fluorotelomer alcohol 1H, 1H, 2H, 2H-perfluorooctanol (6:2 FTOH), each PFAS congener bound by human serum albumin was also bound by bovine, porcine, and rat serum albumin. The critical role of the charged functional headgroup in albumin binding was supported by the inability of albumin of each species tested to bind 6:2 FTOH. Significant interspecies differences in serum albumin binding affinities were identified for each of the bound PFAS congeners. Relative to human albumin, perfluoroalkyl carboxylic and sulfonic acids were bound with greater affinity by porcine and rat serum albumin, and the perfluoroalkyl ether acid congener bound with lower affinity to porcine and bovine serum albumin. These comparative affinity data for PFAS binding by serum albumin from human, experimental model, and livestock species reduce critical interspecies uncertainty and improve accuracy of predictive bioaccumulation and toxicity assessments for PFAS.

Bridging the Gap Between Human Toxicology and Ecotoxicology Under One Health Perspective by a Cross-Species Adverse Outcome Pathway Network for Reproductive Toxicity.

Although ecotoxicological and toxicological risk assessments are performed separately from each other, recent efforts have been made in both disciplines to reduce animal testing and develop predictive approaches instead, for example, via conserved molecular markers, and in vitro and in silico approaches. Among them, adverse outcome pathways (AOPs) have been proposed to facilitate the prediction of molecular toxic effects at larger biological scales. Thus, more toxicological data are used to inform on ecotoxicological risks and vice versa. An AOP has been previously developed to predict reproductive toxicity of silver nanoparticles via oxidative stress on the nematode Caenorhabditis elegans (AOPwiki ID 207). Following this previous study, our present study aims to extend the biologically plausible taxonomic domain of applicability (tDOA) of AOP 207. Various types of data, including in vitro human cells, in vivo, and molecular to individual, from previous studies have been collected and structured into a cross-species AOP network that can inform both human toxicology and ecotoxicology risk assessments. The first step was the collection and analysis of literature data to fit the AOP criteria and build a first AOP network. Then, key event relationships were assessed using a Bayesian network modeling approach, which gave more confidence in our overall AOP network. Finally, the biologically plausible tDOA was extended using in silico approaches (Genes-to-Pathways Species Conservation Analysis and Sequence Alignment to Predict Across Species Susceptibility), which led to the extrapolation of our AOP network across over 100 taxonomic groups. Our approach shows that various types of data can be integrated into an AOP framework, and thus facilitates access to knowledge and prediction of toxic mechanisms without the need for further animal testing. Environ Toxicol Chem 2024;00:1-14. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Projection of Interspecific Competition (PIC) Matrices: A Conceptual Framework for Inclusion in Population Risk Assessments.

Accounting for intraspecific and interspecific competition when assessing the effects of chemical and nonchemical stressors is an important uncertainty in ecological risk assessments. We developed novel projection of interspecific competition (PIC) matrices that allow for analysis of population dynamics of two or more species exposed to a given stressor(s) that compete for shared resources within a landscape. We demonstrate the application of PIC matrices to investigate the population dynamics of two hypothetical fish species that compete with one another and have differences in net reproductive rate and intrinsic rate of population increase. Population status predictions were made under scenarios that included exposure to a chemical stressor that reduced fecundity for one or both species. The results of our simulations demonstrated that measures obtained from the life table and Leslie matrix of an organism, including net reproductive rate and intrinsic rate of increase, can result in erroneous conclusions of population status and viability in the absence of a consideration of resource limitation and interspecific competition. This modeling approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects due to stressors to possible outcomes within an ecosystem. In addition, PIC matrices could be combined with adverse outcome pathways to allow for ecosystem projection based on taxonomic conservation of molecular targets of chemicals to predict the likelihood of relative cross-species susceptibility. Overall, the present study shows how PIC matrices can integrate effects across the life cycles of multiple species, provide a linkage between endpoints observed in individual and population-level responses, and project outcomes at the community level for multiple generations for multiple species that compete for limited resources. Environ Toxicol Chem 2024;43:1406-1422. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

Comparing Transcriptomic Responses to Chemicals Across Six Species Using the EcoToxChip RNASeq Database.

The EcoToxChip project includes RNA-sequencing data from experiments involving model (Japanese quail, fathead minnow, African clawed frog) and ecological (double-crested cormorant, rainbow trout, northern leopard frog) species at multiple life stages (whole embryo and adult) exposed to eight chemicals of environmental concern known to perturb a wide range of biological systems (ethinyl estradiol, hexabromocyclododecane, lead, selenomethionine, 17ß trenbolone, chlorpyrifos, fluoxetine, and benzo[a]pyrene). The objectives of this short communication were to (1) present and make available this RNA-sequencing database (i.e., 724 samples from 49 experiments) under the FAIR principles (FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability), while also summarizing key meta-data attributes and (2) use ExpressAnalyst (including the Seq2Fun algorithm and EcoOmicsDB) to perform a comparative transcriptomics analysis of this database focusing on baseline and differential transcriptomic changes across species-life stage-chemical combinations. The database is available in NCBI GEO under accession number GSE239776. Across all species, the number of raw reads per sample ranged between 13 and 58 million, with 30% to 79% of clean reads mapped to the "vertebrate" subgroup database in EcoOmicsDB. Principal component analyses of the reads illustrated separation across the three taxonomic groups as well as some between tissue types. The most common differentially expressed gene was CYP1A1 followed by CTSE, FAM20CL, MYC, ST1S3, RIPK4, VTG1, and VIT2. The most common enriched pathways were metabolic pathways, biosynthesis of cofactors and biosynthesis of secondary metabolites, and chemical carcinogenesis, drug metabolism, and metabolism of xenobiotics by cytochrome P450. The RNA-sequencing database in the present study may be used by the research community for multiple purposes, including, for example, cross-species investigations, in-depth analyses of a particular test compound, and transcriptomic meta-analyses. Environ Toxicol Chem 2024;00:1-6. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

From Protein Sequence to Structure: The Next Frontier in Cross-Species Extrapolation for Chemical Safety Evaluations.

Computational screening for potentially bioactive molecules using advanced molecular modeling approaches including molecular docking and molecular dynamic simulation is mainstream in certain fields like drug discovery. Significant advances in computationally predicting protein structures from sequence information have also expanded the availability of structures for nonmodel species. Therefore, the objective of the present study was to develop an analysis pipeline to harness the power of these bioinformatics approaches for cross-species extrapolation for evaluating chemical safety. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool compares protein-sequence similarity across species for conservation of known chemical targets, providing an initial line of evidence for extrapolation of toxicity knowledge. However, with the development of structural models from tools like the Iterative Threading ASSEmbly Refinement (ITASSER), analyses of protein structural conservation can be included to add further lines of evidence and generate protein models across species. Models generated through such a pipeline could then be used for advanced molecular modeling approaches in the context of species extrapolation. Two case examples illustrating this pipeline from SeqAPASS sequences to I-TASSER-generated protein structures were created for human liver fatty acid-binding protein (LFABP) and androgen receptor (AR). Ninety-nine LFABP and 268 AR protein models representing diverse species were generated and analyzed for conservation using template modeling (TM)-align. The results from the structural comparisons were in line with the sequence-based SeqAPASS workflow, adding further evidence of LFABL and AR conservation across vertebrate species. The present study lays the foundation for expanding the capabilities of the web-based SeqAPASS tool to include structural comparisons for species extrapolation, facilitating more rapid and efficient toxicological assessments among species with limited or no existing toxicity data. Environ Toxicol Chem 2023;42:463-474. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Defining the Biologically Plausible Taxonomic Domain of Applicability of an Adverse Outcome Pathway: A Case Study Linking Nicotinic Acetylcholine Receptor Activation to Colony Death.

For the majority of developed adverse outcome pathways (AOPs), the taxonomic domain of applicability (tDOA) is typically narrowly defined with a single or a handful of species. Defining the tDOA of an AOP is critical for use in regulatory decision-making, particularly when considering protection of untested species. Structural and functional conservation are two elements that can be considered when defining the tDOA. Publicly accessible bioinformatics approaches, such as the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool, take advantage of existing and growing databases of protein sequence and structural information to provide lines of evidence toward structural conservation of key events (KEs) and KE relationships (KERs) of an AOP. It is anticipated that SeqAPASS results could readily be combined with data derived from empirical toxicity studies to provide evidence of both structural and functional conservation, to define the tDOA for KEs, KERs, and AOPs. Such data could be incorporated in the AOP-Wiki as lines of evidence toward biological plausibility for the tDOA. We present a case study describing the process of using bioinformatics to define the tDOA of an AOP using an AOP linking the activation of the nicotinic acetylcholine receptor to colony death/failure in Apis mellifera. Although the AOP was developed to gain a particular biological understanding relative to A. mellifera health, applicability to other Apis bees, as well as non-Apis bees, has yet to be defined. The present study demonstrates how bioinformatics can be utilized to rapidly take advantage of existing protein sequence and structural knowledge to enhance and inform the tDOA of KEs, KERs, and AOPs, focusing on providing evidence of structural conservation across species. Environ Toxicol Chem 2023;42:71-87. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Combining In Vitro and In Silico New Approach Methods to Investigate Type 3 Iodothyronine Deiodinase Chemical Inhibition Across Species.

New approach methodologies (NAMs) are being developed to reduce and replace vertebrate animal testing in support of ecotoxicology and risk assessment. The US Environmental Protection Agency's Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) bioinformatic tool was used to evaluate amino acid sequence conservation of the type 3 iodothyronine deiodinase (DIO3) enzyme across species to demonstrate NAM applications for understanding effects of chemical interactions with a specific protein target. Existing literature was used to identify critical amino acids for thyroid hormone binding and interaction with a reducing cofactor. The SeqAPASS tool identifies whether known critical amino acids involved in ligand binding are exact, partial, or not matches across species compared with a template species based on molecular weight and side chain classification. This evaluation guided the design of variant proteins representing critical amino acid substitutions found in various species. Site-directed mutagenesis of the wild-type (WT) human DIO3 gene sequence was used to create six variant proteins expressed in cell culture, which were then tested in vitro for chemical inhibition. Significant differences in in vitro median inhibitory concentration results were observed among variants for potential competitive inhibitors. A molecular model representing the WT human DIO3 was constructed using Molecular Operating Environment (MOE) software and mutated in silico to create the six variants. The MOE Site Finder tool identified the proposed catalytic and cofactor sites and potential alternative binding sites. Virtual docking did not provide affinity scores with sufficient resolution to rank the potency of the chemical inhibitors. Chemical characteristics, function and location of substituted amino acids, and complexities of the protein target are important considerations in developing NAMs to evaluate chemical susceptibility across species. Environ Toxicol Chem 2023;42:1032-1048. © 2023 University of Wisconsin-Madison. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species.

The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Quantitative Cross-Species Comparison of Serum Albumin Binding of Per- and Polyfluoroalkyl Substances from Five Structural Classes.

Per- and polyfluoroalkyl substances (PFAS) are a class of over 8,000 chemicals that are persistent, bioaccumulative, and toxic to humans, livestock, and wildlife. Serum protein binding affinity is instrumental in understanding PFAS toxicity, yet experimental binding data is limited to only a few PFAS congeners. Previously, we demonstrated the usefulness of a high-throughput, in vitro differential scanning fluorimetry assay for determination of relative binding affinities of human serum albumin for 24 PFAS congeners from 6 chemical classes. In the current study, we used this differential scanning fluorimetry assay to comparatively examine differences in human, bovine, porcine, and rat serum albumin binding of 8 structurally informative PFAS congeners from 5 chemical classes. With the exception of the fluorotelomer alcohol 1H,1H,2H,2H-perfluorooctanol (6:2 FTOH), each PFAS congener bound by human serum albumin was also bound by bovine, porcine, and rat serum albumin. The critical role of the charged functional headgroup in albumin binding was supported by the inability of serum albumin of each species tested to bind 6:2 FTOH. Significant interspecies differences in serum albumin binding affinities were identified for each of the bound PFAS congeners. Relative to human albumin, perfluoroalkyl carboxylic and sulfonic acids were bound with greater affinity by porcine and rat serum albumin, and perfluoroalkyl ether congeners bound with lower affinity to porcine and bovine serum albumin. These comparative affinity data for PFAS binding by serum albumin from human, experimental model and livestock species reduce critical interspecies uncertainty and improve accuracy of predictive toxicity assessments for PFAS.

Weight of evidence for cross-species conservation of androgen receptor-based biological activity.

The U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) is tasked with assessing chemicals for their potential to perturb endocrine pathways, including those controlled by androgen receptor (AR). To address challenges associated with traditional testing strategies, EDSP is considering in vitro high-throughput screening assays to screen and prioritize chemicals more efficiently. The ability of these assays to accurately reflect chemical interactions in nonmammalian species remains uncertain. Therefore, a goal of the EDSP is to evaluate how broadly results can be extrapolated across taxa. To assess the cross-species conservation of AR-modulated pathways, computational analyses and systematic literature review approaches were used to conduct a comprehensive analysis of existing in silico, in vitro, and in vivo data. First, molecular target conservation was assessed across 585 diverse species based on the structural similarity of ARs. These results indicate that ARs are conserved across vertebrates and are predicted to share similarly susceptibility to chemicals that interact with the human AR. Systematic analysis of over 5000 published manuscripts was used to compile in vitro and in vivo cross-species toxicity data. Assessment of in vitro data indicates conservation of responses occurs across vertebrate ARs, with potential differences in sensitivity. Similarly, in vivo data indicate strong conservation of the AR signaling pathways across vertebrate species, although sensitivity may vary. Overall, this study demonstrates a framework for utilizing bioinformatics and existing data to build weight of evidence for cross-species extrapolation and provides a technical basis for extrapolating hAR-based data to prioritize hazard in nonmammalian vertebrate species.

Detailed comparative analysis of environmental microparticle deposition characteristics between human and monkey nasal cavities using a surface mapping technique.

Inhaled particulate matter is associated with nasal diseases such as allergic rhinitis, rhinosinusitis and neural disorders. Its health risks on humans are usually evaluated by measurements on monkeys as they share close phylogenetic relationship. However, the reliability of cross-species toxicological extrapolation is in doubt due to physiological and anatomical variations, which greatly undermine the reliability of these expensive human surrogate models. This study numerically investigated in-depth microparticle transport and deposition characteristics on human and monkey (Macaca fuscata) nasal cavities that were reconstructed from CT-images. Deposition characteristics of 1-30µm particles were investigated under resting and active breathing conditions. Similar trends were observed for total deposition efficiencies and a single correlation using Stokes Number was fitted for both species and both breathing conditions, which is convenient for monkey-human extrapolation. Regional deposition patterns were carefully compared using the surface mapping technique. Deposition patterns of low, medium and high inertial particles, classified based on their total deposition efficiencies, were further analyzed in the 3D view and the mapped 2D view, which allows locating particle depositions on specific nasal regions. According to the particle intensity contours and regional deposition profiles, the major differences were observed at the vestibule and the floor of the nasal cavity, where higher deposition intensities of medium and high inertial particles were shown in the monkey case than the human case. Comparisons of airflow streamlines indicated that the cross-species variations of microparticle deposition patterns are mainly contributed by two factors. First, the more oblique directions of monkey nostrils result in a sharper airflow turn in the vestibule region. Second, the monkey's relatively narrower nasal valves lead to higher impaction of medium and high inertial particles on the nasal cavity floor. The methods and findings in this study would contribute to an improved cross-species toxicological extrapolation between human and monkey nasal cavities.