In Vitro and in Silico Derived Relative Effect Potencies of Ah-Receptor-Mediated Effects by PCDD/Fs and PCBs in Rat, Mouse, and Guinea Pig CALUX Cell Lines

Quantitative Structure Retention-Relationship Modeling: Towards an Innovative General-Purpose Strategy

Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal chromatographic conditions that enable this separation is time consuming and requires a lot of lab work. Quantitative Structure Retention Relationship models (QSRR) are helpful for doing this job with minimal time and cost expenditures by predicting retention times of known compounds without performing experiments. In the current work, several QSRR models were built and compared for their adequacy in predicting the retention times. The regression models were based on a combination of linear and non-linear algorithms such as Multiple Linear Regression, Support Vector Regression, Least Absolute Shrinkage and Selection Operator, Random Forest, and Gradient Boosted Regression. Models were built for five pH conditions, i.e., at pH 2.7, 3.5, 6.5, and 8.0. In the end, the model predictions were combined using stacking and the performances of all models were compared. The k-nearest neighbor-based application domain filter was established to assess the reliability of the prediction for further compound prioritization. Altogether, this study can be insightful for analytical chemists working with RPLC to begin with the computational prediction modeling such as QSRR to predict the separation of small molecules.

Systematic review of associations of polychlorinated biphenyl (PCB) exposure with declining semen quality in support of the derivation of reference doses for mixture risk assessments

BACKGROUND

Mixture risk assessments require reference doses for common health endpoints of all the chemicals to be considered together. In support of a mixture risk assessment for male reproductive health, we conducted a systematic review of the literature on associations between exposures to Polychlorinated Biphenyls (PCBs) and declines in semen quality. PCBs can act as Aryl-hydrocarbon Receptor (AhR)-agonists and Androgen Receptor (AR)-antagonists, both mechanisms which can affect sperm parameters. PCBs and other AR-antagonists can produce additive combination effects. Based on these observations our objective was to systematically gather data from animal and human studies to derive a reference dose for declines in semen quality for individual PCB.

METHODS

We systematically reviewed and evaluated the evidence in human epidemiological and experimental animal studies on associations between PCBs and deteriorations in semen quality. Human data and findings from animal studies with PCB mixtures were considered as supporting evidence. Information for individual congeners from animal studies was required for inclusion in mixture risk assessment. Using a robust confidence rating approach, we identified suitable studies to derive reference doses for individual PCB congeners.

RESULTS

Evaluation of human epidemiological studies revealed several reports of adverse effects on sperm parameters linked to PCB exposures, although some studies reported improved semen quality. Our review of experimental animal studies found that treatments with PCBs affected semen quality, in most cases adversely. We found robust evidence that PCB-118 and -169 were linked to declines in semen quality. Evidence for adverse effects of PCB-126, -132, -149, and -153 was moderate, whereas for PCB-77 it was slight and for PCB-180 indeterminate. Using widely accepted risk assessment procedures, we estimated reference dose values of 0.0029 µg/kg/day for PCB-118 and 0.00533 µg/kg/day for PCB-169. In addition, we derived values for PCB-126: 0.000073 µg/kg/day, PCB-132: 0.0228 µg/kg/day, PCB-149: 0.656 µg/kg/day, and PCB-153: 0.0058 µg/kg/day.

CONCLUSIONS

We found robust evidence for links between PCB exposure and deteriorations in semen quality, and derived reference doses for a set of congeners. We intend to use these values in combination with congener-specific exposure data in a mixture risk assessment for declines in semen quality, involving several other antiandrogenic chemicals.

Polarizability and aromaticity index govern AhR-mediated potencies of PAHs: A QSAR with consideration of freely dissolved concentrations

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants associated with adverse human effects including cancer, and the aryl hydrocarbon receptor (AhR) is a key ligand-activated transcription factor mediating their toxicity. However, there is presently a lack of data on AhR potencies of PAHs. Simple, transparent, interpretable and predictive quantitative structure-activity relationship (QSAR) models are helpful, especially with the consideration of freely dissolved concentrations linked to bioavailability. Here, QSAR models on AhR-mediated luciferase activity of PAHs were developed with nominal median effect concentrations (EC₅₀, _nom) and freely dissolved concentration (EC_{50, free}) as endpoints, and quantum chemical and Dragon descriptors as predictor variables. Results indicated that only the EC_{50, free} model met the acceptable criteria of QSAR model (determination coefficient (R²) > 0.600, leave-one-out cross validation (Q_LOO²) > 0.500, and external validation coefficient (Q_EXT²) > 0.500), implying that it has good goodness-of-fit, robustness and external predictive power. Molecular polarizability and aromaticity index reflecting the partition behavior and intermolecular interactions can effectively predict AhR-mediated potencies of PAHs. The results highlight the necessity of adoption of the freely dissolved concentration in the QSAR modeling and more in silico models need to be further developed for different animal models (in vivo or in vitro).

Predictive modeling of aryl hydrocarbon receptor (AhR) agonism

The aryl hydrocarbon receptor (AhR) plays a key role in the regulation of gene expression in metabolic machinery and detoxification systems. In the recent years, this receptor has attracted interest as a therapeutic target for immunological, oncogenic and inflammatory conditions. In the present report, in silico and in vitro approaches were combined to study the activation of the AhR. To this end, a large database of chemical compounds with known AhR agonistic activity was employed to build 5 classifiers based on the Adaboost (AdB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP) and Support Vector Machine (SVM) algorithms, respectively. The built classifiers were examined, following a 10-fold external validation procedure, demonstrating adequate robustness and predictivity. These models were integrated into a majority vote based ensemble, subsequently used to screen an in-house library of compounds from which 40 compounds were selected for prospective in vitro experimental validation. The general correspondence between the ensemble predictions and the in vitro results suggests that the constructed ensemble may be useful in predicting the AhR agonistic activity, both in a toxicological and pharmacological context. A preliminary structure-activity analysis of the evaluated compounds revealed that all structures bearing a benzothiazole moiety induced AhR expression while diverse activity profiles were exhibited by phenolic derivatives.

Influence of Co-Dosed Lipids from Biota Extracts on the Availability of Chemicals in In Vitro Cell-Based Bioassays

Extraction of chemicals from biota leads to co-extraction of lipids. When dosing such extracts into in vitro bioassays, co-dosed lipids act as an additional phase that can reduce the bioavailability of the chemicals and the apparent sensitivity of the assay. Equilibrium partitioning between medium, cells, and co-dosed lipids was described with an existing equilibrium partitioning model for cell-based bioassays extended by an additional lipid phase. We experimentally investigated the influence of co-dosed lipids on the effects elicited by four test chemicals of different hydrophobicity in two bioassays, indicative of the aryl hydrocarbon receptor and oxidative stress response (AREc32). The partitioning model explained the effect of the test chemicals in the presence of spiked triolein within a factor of 0.33-5.83 between the measured and predicted effect concentration (EC). We applied the model to marine mammal blubber extracted with silicone. Extracts dosed in the AREc32 bioassay showed a linear increase of apparent EC with increasing lipid fraction. The partitioning model was used to interpret the role of the co-extracted lipid. A quantitative lipid correction of bioassay results in the presence of co-dosed lipids was possible for known compounds and defined mixtures, while we could only estimate a range for mixtures of unknown chemicals.

Polychlorinated dibenzo-dioxins and polychlorinated dibenzo-furans exposure and altered lung function: The mediating role of oxidative stress

The lung has been reported to be one of the target organs of polychlorinated dibenzo-dioxins and polychlorinated dibenzo-furans (PCDD/Fs) in many toxicological studies. While the associations between PCDD/Fs exposure and lung function levels have not been investigated thoroughly. This study aimed to explore these associations and the potential mediating role of oxidative stress. In this study, 201 foundry workers and 222 non-exposed general residents were recruited from central China, and their lung function parameters were measured. Air and food samples were collected to determine the PCDD/Fs levels for individual PCDD/Fs exposure estimation. Serum PCDD/Fs levels were determined in a subgroup of individuals randomly selected from the study population to reflect the body burden. It was found that each 1-unit increase in ln-transformed concentration of PCDD/Fs exposure (fg TEQ/bw/day) was associated with a 0.47 L decrease in FVC and a 0.25 L decrease in FEV₁. Each 1-unit increase in ln-transformed concentration of serum PCDD/Fs (fg TEQ/g lipid) was associated with a 0.36 L decrease in FVC and a 0.24 L decrease in FEV₁. Urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) was not only positively related to PCDD/Fs exposure, but also inversely associated with FVC and FEV₁ are FVC (β = -0.15, 95% CI: -0.22 to -0.08) and FEV₁ (β = -0.07, 95% CI: -0.13 to -0.02). Mediation analysis revealed that urinary 8-OHdG mediated 12.22% of the associations of external PCDD/Fs exposure with FVC levels, 28.61% and 27.87% of the associations of serum PCDD/Fs with FVC and FEV₁ levels respectively. Our findings suggested that PCDD/Fs exposure was associated with decreased lung function levels by a mechanism partly involving oxidatively generated damage to DNA.

Elucidating the aryl hydrocarbon receptor antagonism from a chemical-structural perspective

The aryl hydrocarbon receptor (AhR) plays an important role in several biological processes such as reproduction, immunity and homoeostasis. However, little is known on the chemical-structural and physicochemical features that influence the activity of AhR antagonistic modulators. In the present report, in vitro AhR antagonistic activity evaluations, based on a chemical-activated luciferase gene expression (AhR-CALUX) bioassay, and an extensive literature review were performed with the aim of constructing a structurally diverse database of contaminants and potentially toxic chemicals. Subsequently, QSAR models based on Linear Discriminant Analysis and Logistic Regression, as well as two toxicophoric hypotheses were proposed to model the AhR antagonistic activity of the built dataset. The QSAR models were rigorously validated yielding satisfactory performance for all classification parameters. Likewise, the toxicophoric hypotheses were validated using a diverse set of 350 decoys, demonstrating adequate robustness and predictive power. Chemical interpretations of both the QSAR and toxicophoric models suggested that hydrophobic constraints, the presence of aromatic rings and electron-acceptor moieties are critical for the AhR antagonism. Therefore, it is hoped that the deductions obtained in the present study will contribute to elucidate further on the structural and physicochemical factors influencing the AhR antagonistic activity of chemical compounds.

Aryl hydrocarbon receptor signaling, toxicity, and gene expression responses to mono-methylchrysenes

Polycyclic aromatic hydrocarbons (PAHs) comprise a large family of toxic compounds that come from natural and anthropogenic sources. Chrysene is a PAH with multiple effects, but the toxic potentials of mono-methylchrysenes are less characterized. A comparison of chrysene and six mono-methylchrysenes was performed using assays for cytotoxicity, human aryl hydrocarbon receptor (AhR) reporter gene signaling, and AhR-regulated target gene and protein expression. Sulforhodamine B and trypan blue dye binding assays revealed these chrysenes to be similar in their cytotoxic effects on HepG2 cells. A yeast-based reporter assay detecting human AhR-mediated gene expression identified 4-methylchrysene as being six times more potent and 5-methylchrysene about one-third as potent as chrysene. Other methylchrysenes were more similar to chrysene in the ability to act as AhR ligands. The mono-methylchrysenes all strongly induced CYP1A1 mRNA and protein and moderately induced CYP1B1 expression in HepG2 cells. Levels of CYP1A2 mRNA were induced at higher concentrations of the chrysenes, but protein expression was not significantly altered. The PCR-based gene expression and immunoblotting analyses indicated induced expression differences across the chrysene members were similar to each other. Overall, the effects of methylated chrysenes were comparable to unsubstituted chrysene, suggesting members of this group may be considered approximately equivalent in their effects. © 2019 Wiley Periodicals, Inc.

Effect-based trigger values for in vitro and in vivo bioassays performed on surface water extracts supporting the environmental quality standards (EQS) of the European Water Framework Directive

Effect-based methods including cell-based bioassays, reporter gene assays and whole-organism assays have been applied for decades in water quality monitoring and testing of enriched solid-phase extracts. There is no common EU-wide agreement on what level of bioassay response in water extracts is acceptable. At present, bioassay results are only benchmarked against each other but not against a consented measure of chemical water quality. The EU environmental quality standards (EQS) differentiate between acceptable and unacceptable surface water concentrations for individual chemicals but cannot capture the thousands of chemicals in water and their biological action as mixtures. We developed a method that reads across from existing EQS and includes additional mixture considerations with the goal that the derived effect-based trigger values (EBT) indicate acceptable risk for complex mixtures as they occur in surface water. Advantages and limitations of various approaches to read across from EQS are discussed and distilled to an algorithm that translates EQS into their corresponding bioanalytical equivalent concentrations (BEQ). The proposed EBT derivation method was applied to 48 in vitro bioassays with 32 of them having sufficient information to yield preliminary EBTs. To assess the practicability and robustness of the proposed approach, we compared the tentative EBTs with observed environmental effects. The proposed method only gives guidance on how to derive EBTs but does not propose final EBTs for implementation. The EBTs for some bioassays such as those for estrogenicity are already mature and could be implemented into regulation in the near future, while for others it will still take a few iterations until we can be confident of the power of the proposed EBTs to differentiate good from poor water quality with respect to chemical contamination.

Consensus toxicity factors for polychlorinated dibenzo-p-dioxins, dibenzofurans, and biphenyls combining in silico models and extensive in vitro screening of AhR-mediated effects in human and rodent cells

Consensus toxicity factors (CTFs) were developed as a novel approach to establish toxicity factors for risk assessment of dioxin-like compounds (DLCs). Eighteen polychlorinated dibenzo-p-dioxins, dibenzofurans (PCDD/Fs), and biphenyls (PCBs) with assigned World Health Organization toxic equivalency factors (WHO-TEFs) and two additional PCBs were screened in 17 human and rodent bioassays to assess their induction of aryl hydrocarbon receptor-related responses. For each bioassay and compound, relative effect potency values (REPs) compared to 2,3,7,8-tetrachlorodibenzo-p-dioxin were calculated and analyzed. The responses in the human and rodent cell bioassays generally differed. Most notably, the human cell models responded only weakly to PCBs, with 3,3',4,4',5-pentachlorobiphenyl (PCB126) being the only PCB that frequently evoked sufficiently strong responses in human cells to permit us to calculate REP values. Calculated REPs for PCB126 were more than 30 times lower than the WHO-TEF value for PCB126. CTFs were calculated using score and loading vectors from a principal component analysis to establish the ranking of the compounds and, by rescaling, also to provide numerical differences between the different congeners corresponding to the TEF scheme. The CTFs were based on rat and human bioassay data and indicated a significant deviation for PCBs but also for certain PCDD/Fs from the WHO-TEF values. The human CTFs for 2,3,4,7,8-pentachlorodibenzofuran, 1,2,3,4,7,8-hexachlorodibenzofuran, 1,2,3,4,6,7,8-heptachlorodibenzo-p-dioxin, and 1,2,3,4,7,8,9-heptachlorodibenzofuran were up to 10 times greater than their WHO-TEF values. Quantitative structure-activity relationship models were used to predict CTFs for untested WHO-TEF compounds, suggesting that the WHO-TEF value for 1,2,3,7,8-pentachlorodibenzofuran could be underestimated by an order of magnitude for both human and rodent models. Our results indicate that the CTF approach provides a powerful tool for condensing data from batteries of screening tests using compounds with similar mechanisms of action, which can be used to improve risk assessment of DLCs.