Environmental Chemicals Research Articles

Low doses of acetyl trihexyl citrate plasticizer promote adipogenesis in hepatocytes and mice.

Accumulating epidemiological evidence underscores the association between pervasive environmental factors and an increased risk of metabolic diseases. Environmental chemicals, recognized disruptors of endocrine and metabolic processes, may contribute to the global prevalence of metabolic disorders, including obesity. Acetyl tributyl citrate (ATHC), categorized as a citric acid ester plasticizer, serves as a substitute for di-(2-ethylhexyl) phthalate (DEHP) in various everyday products. Despite its widespread use and the increasing risk of exposure in humans and animals due to its high leakage rates, information regarding the safety of exposure to environmentally relevant doses of ATHC remains limited. This study aimed to investigate the potential impact of ATHC exposure on metabolic homeostasis. Both in vivo and in vitro exposure models were used to characterize the effects induced by ATHC exposure. C57BL/6J male mice were subjected to a diet containing ATHC for 12weeks, and metabolism-related parameters were monitored and analyzed throughout and after the exposure period. Results indicated that sub-chronic dietary exposure to ATHC induced an increase in body fat percentage, elevated serum lipid levels, and increased lipid content in the liver tissue of mice. Furthermore, the effect of ATHC exposure on murine hepatocytes were examined and results indicated that ATHC significantly augmented lipid levels in AML12 hepatocytes, disrupting energy homeostasis and altering the expression of genes associated with fatty acid synthesis, uptake, oxidation, and secretion pathways. Conclusively, both in vivo and in vitro results suggest that exposure to low levels of ATHC may be linked to an elevated risk of obesity and fatty liver in mice. The potential implications of ATHC on human health warrant comprehensive evaluation in future studies.

Network analysis to reveal the most commonly detected compounds in predator-prey pairs in freshwater and marine mammals and fish in Europe

Marine and freshwater mammalian predators and fish samples, retrieved from environmental specimen banks (ESBs), natural history museum (NHMs) and other scientific collections, were analysed by LIFE APEX partners for a wide range of legacy and emerging contaminants (2545 in total). Network analysis was used to visualize the chemical occurrence data and reveal the predominant chemical mixtures for the freshwater and marine environments. For this purpose, a web tool was created to explore these chemical mixtures in predator-prey pairs. Predominant chemicals, defined as the most prevalent substances detected in prey-predator pairs were identified through this innovative approach. The analysis established the most frequently co-occurring substances in chemical mixtures from AP&P in the marine and freshwater environments. Freshwater and marine environments shared 23 chemicals among their top 25 predominant chemicals. Legacy chemical, including perfluorooctanesulfonic acid (PFOS), brominated diphenyl ethers (BDEs), polychlorinated biphenyls (PCBs), hexachlorobenzene and mercury were dominant chemicals in both environments. Furthermore, N-acetylaminoantipyrine was a predominant pharmaceutical in both environments. The LIFE APEX chemical mixture application (https://norman-data.eu/LIFE_APEX_Mixtures) was proven to be useful to establish most prevalent compounds in terms of number of detected counts in prey-predator pairs. Nonetheless, further research is needed to establish food chain associations of the predominant chemicals.

Quantum Chemistry-Based Prediction of Electron Ionization Mass Spectra for Environmental Chemicals.

There is a lack of experimental electron ionization high-resolution mass spectra available to assist compound identification. The in silico generation of mass spectra by quantum chemistry can aid annotation workflows, in particular to support the identification of compounds that lack experimental reference spectra, such as environmental chemicals. We present an open-source, semiautomated workflow for the in silico prediction of electron ionization high-resolution mass spectra at 70 eV based on the QCxMS software. The workflow was applied to predict the spectra of 367 environmental chemicals, and the accuracy was evaluated by comparison to experimental reference spectra acquired. The molecular flexibility, number of rotatable bonds, and number of electronegative atoms of a compound were negatively correlated with prediction accuracy. Few analytes are predicted to sufficient accuracy for the direct application of predicted spectra in spectral matching workflows (overall average score 428). The m/z values of the top 5 most abundant ions of predicted spectra rarely match ions in experimental spectra, evidencing the disconnect between simulated fragmentation pathways and empirical reaction mechanisms.

Microbial Immobilized Enzyme Biocatalysts for Multipollutant Mitigation: Harnessing Nature's Toolkit for Environmental Sustainability.

The ever-increasing presence of micropollutants necessitates the development of environmentally friendly bioremediation strategies. Inspired by the remarkable versatility and potent catalytic activities of microbial enzymes, researchers are exploring their application as biocatalysts for innovative environmental cleanup solutions. Microbial enzymes offer remarkable substrate specificity, biodegradability, and the capacity to degrade a wide array of pollutants, positioning them as powerful tools for bioremediation. However, practical applications are often hindered by limitations in enzyme stability and reusability. Enzyme immobilization techniques have emerged as transformative strategies, enhancing enzyme stability and reusability by anchoring them onto inert or activated supports. These improvements lead to more efficient pollutant degradation and cost-effective bioremediation processes. This review delves into the diverse immobilization methods, showcasing their success in degrading various environmental pollutants, including pharmaceuticals, dyes, pesticides, microplastics, and industrial chemicals. By highlighting the transformative potential of microbial immobilized enzyme biocatalysts, this review underscores their significance in achieving a cleaner and more sustainable future through the mitigation of micropollutant contamination. Additionally, future research directions in areas such as enzyme engineering and machine learning hold immense promise for further broadening the capabilities and optimizing the applications of immobilized enzymes in environmental cleanup.

Performance of the Social Responsiveness Scale-2 for the Assessment of Autistic Behaviors in a Sample of Canadian Preschool-Aged Children.

Behavioral traits of autism spectrum disorder (ASD) typically present in early childhood, underscoring the importance of screening tools for the early identification of ASD. The current study compared scores on the Social Responsiveness Scale-Second Edition (SRS-2) Preschool Form between the US standardization sample (n = 247) and a Canadian cohort of preschool-aged children (n = 595) recruited from the Maternal-Infant Research on Environmental Chemicals (MIREC) study. In the MIREC sample, we examined whether ASD-like traits are correlated with sociodemographic characteristics and child intellectual abilities, and how maternal ratings of social skills assessed by the SRS-2 are associated with maternal ratings of general problem behaviors. Mean total SRS-2 raw score was significantly lower in the MIREC sample (mean = 29.7, SD = 15.8) compared to the US standardization sample (mean = 41.9, SD = 26.0). Total raw score in the US standardization sample did not significantly differ between males (mean = 40.6, SD = 23.1) and females (mean = 42.8, SD = 28.7), whereas in the MIREC sample the total raw score was significantly higher among males (mean = 33.0, SD = 17.1) than females (mean = 26.6, SD = 13.9). A significantly larger proportion of the MIREC sample was White, younger in age, and had more educated parents compared to the US standardization sample. ASD-like traits were correlated with lower intellectual abilities, a less enriched home environment, more behavioral problems, and poorer adaptive skills. SRS-2 Preschool Form scores were significantly lower in the Canadian sample compared to the US standardization sample, which may reflect demographic differences between the two groups. Girls may be under-identified when SRS-2 Preschool Form norms are used for screening ASD.

Abstract Tu149: FDA-Approved Antidepressant Trazodone Potentially Increases the Risk of Dyslipidemia

Cardiovascular disease is the leading cause of death. Many cardiovascular health problems, such as atherosclerosis, are caused by dyslipidemia. One xenobiotic nuclear receptor, Pregnane X Receptor (PXR), plays a significant role in atherosclerosis and dyslipidemia, and is activated by various environmental chemicals, including endocrine-disrupting chemicals (EDCs). EDCs are found in common household items such as plastics, medications, and food. Trazodone is a clinically used medication to treat depression by aiding in restoring the balance of serotonin in the brain. But it is unclear if Trazodone has possible impacts on cardiovascular risk factors such as dyslipidemia. Our preliminary data suggested that Trazodone activated human PXR in both intestinal (LS180) and hepatic (HepG2) cells. We hypothesize that Trazodone could regulate the cholesterol uptake mediated by PXR signaling. In this study we use cell-based transfection assay to evaluate the underlying mechanisms by which Trazodone activates PXR. We found that Trazodone was a more potent agonist of human PXR than mouse PXR. Trazodone could activate PXR more intensely in human liver cells compared with human intestinal cells. Our data suggested that Trazodone was a selective PXR agonist and promoted the dissociation between PXR and its nuclear corepressors. Next, we are to identify the key amino acid residues within PXR ligand binding pocket that interact with Trazodone by using computational docking study along with site-mutagenesis assay. Furthermore, we plan to estimate if Trazodone altered cholesterol uptake by human intestinal cells using fluorescence-labeled cholesterol. In conclusion, we explore the potential molecular mechanisms of how FDA-approved antidepressant Trazodone activates human PXR and increases the possible risk of dyslipidemia, which provides potential evidence on future cardiovascular disease risk assessment for Trazodone as well as other antidepressant drugs.

How safe are wild-caught salmons exposed to various industrial chemicals? First ever in silico models for salmon toxicity data gaps filling

Salmons are crucial to ecosystems and economic activities like commercial fishing and aquaculture, while also serving as an important source of nutrients, underscoring their ecological significance and the need for sustainable management. To better understand the toxicity and biological interactions between the salmon and industrial chemicals in the aquatic environment, we utilized the ToxValDB database to develop first ever computational toxicity models for six salmon subspecies (covering Atlantic and Pacific salmon) across two genera, employing Quantitative Structure-Activity Relationship (QSAR) and quantitative Read-Across Structure-Activity Relationship (q-RASAR) methods. For three smaller datasets (Oncorhynchus nerka, Oncorhynchus keta, and Oncorhynchus gorbuscha), we created mathematical models using the entire datasets where QSAR models demonstrated superior statistical quality compared to q-RASAR. Conversely, the three larger datasets (Oncorhynchus kisutch, Oncorhynchus tshawytscha, and Salmon salar) were divided into training and test sets, the q-RASAR models yielded better results compared to QSAR models. Mechanistic interpretations of these models revealed that descriptors such as Burden eigenvalues (BCUT), autocorrelation of topological structure (ATSC), and molecular polarizability were significant predictors of toxicity. For instance, higher polarizability and certain topological features were associated with increased toxicity as per the developed models. Statistically superior models for each subspecies were used to predict the aquatic toxicity of 1085 untested organic chemicals for toxicity data gap filling and risk assessment considering the applicability domain (AD). These insights are pivotal for designing safer chemicals and emphasize the need for sustainable management of salmon populations.

Evaluation of the Effects of Di-(2-ethylhexyl) phthalate (DEHP) on Caenorhabditis elegans Survival and Fertility.

Di-2-ethylhexyl (DEHP), which is widely used in industrial products, is produced annually in excess of 2 million tons worldwide. DEHP is an endocrine disruptor and one of the major environmental pollutant chemicals (EDCs) in nature. There is some information about the effects of these products, which provide great advantages in every respect, on human health and the environment. In this study, C. elegans organism was used to evaluate the health and environmental risks of DEHP. The survival and fertility effects of DEHP on the C. elegans organism were examined and the results were evaluated. In the study, it was determined that DEHP not only shortened the survival time of C. elegans but also caused a decrease in fertility. DEHP (0.625mM and 10mM) caused a 23.2-30.6% decrease in fertility. Additionally, the LC50 (50% lethal concentration) value of DEHP was found to be 321µg/mL.

Micro/Nanoplastic Exposure on Placental Health and Adverse Pregnancy Risks: Novel Assessment System Based upon Targeted Risk Assessment Environmental Chemicals Strategy.

Micro/nanoplastics (MNPs), as emerging pollutants, have been detected in both the maternal and fetal sides of the placenta in pregnant women, and their reproductive toxicity has been demonstrated in in vivo and in vitro experimental models. The Targeted Risk Assessment of Environmental Chemicals (TRAEC) strategy has been innovatively devised to facilitate valid risk assessment, encompassing a comprehensive evaluation of reliability, correlation, outcome fitness, and integrity across four dimensions based on the included published evidence and our own findings. This study serves as an application case of TRAEC, with 40 items of research evidence on the toxicity of MNPs to the placenta, which were rigorously screened and incorporated into the final scoring system. The final score for this TRAEC case study is 5.63, suggesting a moderate-to-low risk of reproductive toxicity associated with MNPs in the placenta, which may potentially increase with decreasing particle size. It is essential to emphasize that the findings also report original data from assays indicating that exposure to high-dose groups (100 μg/mL, 200 μg/mL) of 50 nm and 200 nm polystyrene nanoplastics (PS-NPs) induces HTR8/SVneo cell cycle arrest and cell apoptosis, which lead to reproductive toxicity in the placenta by disrupting mitochondrial function. Overall, this study employed the TRAEC strategy to provide comprehensive insight into the potential reproductive health effects of ubiquitous MNPs.

Urinary and Fecal Excretion of 121 Environmental Chemicals in Pet Dogs and Cats: Significance of Feces in Biomonitoring of Exposures.

Laboratory animal studies have reported the biliary excretion of chemicals following exposure. Nevertheless, feces are rarely used as a matrix in biomonitoring of chemical exposures. In this study, feces and urine from pet dogs and cats were analyzed for the presence of 45 plasticizers, 45 environmental phenols, and 31 pesticides. Thirty-two analytes were detected in ≥70% pet feces, while up to 29 analytes were frequently (≥70%) found in urine. The sum concentrations of all analytes (∑All) in pet feces were significantly higher than those measured in urine (median: 393-666 ng/g wet weight in feces vs 216-464 ng/mL in urine). Plasticizers were the dominant class of chemicals, accounting for 81-97% and 69-77% of ∑All in urine and feces, respectively. Analyte concentrations measured in paired urine and feces exhibited weak correlations. The excretion rates of the chemicals via urine and feces were calculated through a reverse dosimetry approach. Low-molecular-weight phthalates excreted predominantly in urine, whereas high-molecular-weight phthalates and several organophosphate triesters were excreted predominantly in feces. The fecal excretion rates of parabens, benzophenones, bisphenols, naphthalene, 2,4-dichloronicotinic acid, and 4-nitrophenol were similar to or higher than those of urinary excretion. Our results suggest that feces are an important matrix in biomonitoring of exposure to environmental chemicals.

Multiomics Screening Identified CpG Sites and Genes That Mediate the Impact of Exposure to Environmental Chemicals on Cardiometabolic Traits.

An understanding of the molecular mechanism whereby an environmental chemical causes a disease is important for the purposes of future applications. In this study, a multiomics workflow was designed to combine several publicly available datasets in order to identify CpG sites and genes that mediate the impact of exposure to environmental chemicals on cardiometabolic traits. Organophosphate and prenatal lead exposure were previously reported to change methylation level at the cg23627948 site. The outcome of the analyses conducted in this study revealed that, as the cg23627948 site becomes methylated, the expression of the GNA12 gene decreases, which leads to a higher body fat percentage. Prenatal perfluorooctane sulfonate exposure was reported to increase the methylation level at the cg21153102 site. Findings of this study revealed that higher methylation at this site contributes to higher diastolic blood pressure by changing the expression of CHP1 and GCHFR genes. Moreover, HKR1 mediates the impact of B12 supplementation → cg05280698 hypermethylation on higher kidney function, while CTDNEP1 mediates the impact of air pollution → cg03186999 hypomethylation on higher systolic blood pressure. This study investigates CpG sites and genes that mediate the impact of environmental chemicals on cardiometabolic traits. Furthermore, the multiomics approach described in this study provides a convenient workflow with which to investigate the impact of an environmental factor on the body's biomarkers, and, consequently, on health conditions, using publicly available data.

Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer.

Chemical exposures may impact human metabolism and contribute to the etiology of neurodegenerative disorders like Alzheimer's Disease (AD). Identifying these small metabolites involves matching experimental spectra to reference spectra in databases. However, environmental chemicals or physiologically active metabolites are usually present at low concentrations in human specimens. The presence of noise ions can significantly degrade spectral quality, leading to false negatives and reduced identification rates. In response to this challenge, the Spectral Denoising algorithm removes both chemical and electronic noise. Spectral Denoising outperformed alternative methods in benchmarking studies on 240 tested metabolites. It improved high confident compound identifications at an average 35-fold lower concentrations than previously achievable. Spectral Denoising proved highly robust against varying levels of both chemical and electronic noise even with >150-fold higher intensity of noise ions than true fragment ions. For human plasma samples of AD patients that were analyzed on the Orbitrap Astral mass spectrometer, Denoising Search detected 2.3-fold more annotated compounds compared to the Exploris 240 Orbitrap instrument, including drug metabolites, household and industrial chemicals, and pesticides. This combination of advanced instrumentation with a superior denoising algorithm opens the door for precision medicine in exposome research.

Exposome Profiling of Environmental Pollutants in Seminal Plasma and Novel Associations with Semen Parameters.

Indicators of male fertility are in decline globally, but the underlying causes, including the role of environmental exposures, are unclear. This study aimed to examine organic chemical pollutants in seminal plasma, including both known priority environmental chemicals and less studied chemicals, to identify uncharacterized male reproductive environmental toxicants. Semen samples were collected from 100 individuals and assessed for sperm concentration, percent motility, and total motile sperm. Targeted and nontargeted organic pollutant exposures were measured from seminal plasma using gas chromatography, which showed widespread detection of organic pollutants in seminal plasma across all exposure classes. We used principal component pursuit (PCP) on our targeted panel and derived one component (driven by etriadizole) associated with total motile sperm (p < 0.001) and concentration (p = 0.03). This was confirmed by the exposome-wide association models using individual chemicals, where etriadizole was negatively associated with total motile sperm (FDR q = 0.01) and concentration (q = 0.07). Using PCP on 814 nontargeted spectral peaks identified a component that was associated with total motile sperm (p = 0.001). Bayesian kernel machine regression identified one principal driver of this association, which was analytically confirmed to be N-nitrosodiethylamine. These findings are promising and consistent with experimental evidence showing that etridiazole and N-nitrosodiethylamine may be reproductive toxicants.

Integrated Transfer Learning and Multitask Learning Strategies to Construct Graph Neural Network Models for Predicting Bioaccumulation Parameters of Chemicals.

Accurate prediction of parameters related to the environmental exposure of chemicals is crucial for the sound management of chemicals. However, the lack of large data sets for training models may result in poor prediction accuracy and robustness. Herein, integrated transfer learning (TL) and multitask learning (MTL) was proposed for constructing a graph neural network (GNN) model (abbreviated as TL-MTL-GNN model) using n-octanol/water partition coefficients as a source domain. The TL-MTL-GNN model was trained to predict three bioaccumulation parameters based on enlarged data sets that cover 2496 compounds with at least one bioaccumulation parameter. Results show that the TL-MTL-GNN model outperformed single-task GNN models with and without the TL, as well as conventional machine learning models trained with molecular descriptors or fingerprints. Applicability domains were characterized by a state-of-the-art structure-activity landscape-based (abbreviated as ADSAL) methodology. The TL-MTL-GNN model coupled with the optimal ADSAL was employed to predict bioaccumulation parameters for around 60,000 chemicals, with more than 13,000 compounds identified as bioaccumulative chemicals. The high predictive accuracy and robustness of the TL-MTL-GNN model demonstrate the feasibility of integrating the TL and MTL strategy in modeling small-sized data sets. The strategy holds significant potential for addressing small data challenges in modeling environmental chemicals.

Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes.

Environmental chemicals may contribute to the global burden of cardiovascular disease, but experimental data are lacking to determine which substances pose the greatest risk. Human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes are a high-throughput cardiotoxicity model that is widely used to test drugs and chemicals; however, most studies focus on exploring electro-physiological readouts. Gene expression data may provide additional molecular insights to be used for both mechanistic interpretation and dose-response analyses. Therefore, we hypothesized that both transcriptomic and functional data in human iPSC-derived cardiomyocytes may be used as a comprehensive screening tool to identify potential cardiotoxicity hazards and risks of the chemicals. To test this hypothesis, we performed concentration-response analysis of 464 chemicals from 12 classes, including both pharmaceuticals and nonpharmaceutical substances. Functional effects (beat frequency, QT prolongation, and asystole), cytotoxicity, and whole transcriptome response were evaluated. Points of departure were derived from phenotypic and transcriptomic data, and risk characterization was performed. Overall, 244 (53%) substances were active in at least one phenotype; as expected, pharmaceuticals with known cardiac liabilities were the most active. Positive chronotropy was the functional phenotype activated by the largest number of tested chemicals. No chemical class was particularly prone to pose a potential hazard to cardiomyocytes; a varying proportion (10-44%) of substances in each class had effects on cardiomyocytes. Transcriptomic data showed that 69 (15%) substances elicited significant gene expression changes; most perturbed pathways were highly relevant to known key characteristics of human cardiotoxicants. The bioactivity-to-exposure ratios showed that phenotypic- and transcriptomic-based POD led to similar results for risk characterization. Overall, our findings demonstrate how the integrative use of in vitro transcriptomic and phenotypic data from iPSC-derived cardiomyocytes not only offers a complementary approach for hazard and risk prioritization, but also enables mechanistic interpretation of the in vitro test results to increase confidence in decision-making.

Exposome-wide association study of cognition among older adults in the National Health and Nutrition Examination Survey.

Cognitive impairment among older adults is a growing public health challenge and environmental chemicals may be modifiable risk factors. A wide array of chemicals has not yet been tested for association with cognition in an environment-wide association framework. In the US National Health and Nutrition Examination Survey (NHANES) 1999-2000 and 2011-2014 cross-sectional cycles, cognition was assessed using the Digit Symbol Substitution Test (DSST, scores 0-117) among participants aged 60 years and older. Concentrations of environmental chemicals measured in blood or urine were log2 transformed and standardized. Chemicals with at least 50% of measures above the lower limit of detection were included (nchemicals=147, nclasses=14). We tested for associations between chemical concentrations and cognition using parallel survey-weighted multivariable linear regression models adjusted for age, sex, race/ethnicity, education, smoking status, fish consumption, cycle year, urinary creatinine, and cotinine. Participants with at least one chemical measurement (n=4,982) were mean age 69.8 years, 55.0% female, 78.2% non-Hispanic White, and 77.0% at least high school educated. The mean DSST score was 50.4 (standard deviation (SD)=17.4). In adjusted analyses, 5 of 147 exposures were associated with DSST at p-value<0.01. Notably, a SD increase in log2-scaled cotinine concentration was associated with 2.71 points lower DSST score (95% CI -3.69, -1.73). A SD increase in log2-scaled urinary tungsten concentration was associated with 1.34 points lower DSST score (95% CI -2.11, -0.56). Exposure to environmental chemicals, particularly heavy metals and tobacco smoke, may be modifiable factors for cognition among older adults.

Highly sensitive response to the toxicity of environmental chemicals in transparent casper zebrafish

The response sensitivity to toxic substances is the most concerned performance of animal model in chemical risk assessment. Casper (mitfaw2/w2;mpv17a9/a9), a transparent zebrafish mutant, is a useful in vivo model for toxicological assessment. However, the ability of casper to respond to the toxicity of exogenous chemicals is unknown. In this study, zebrafish embryos were exposed to five environmental chemicals, chlorpyrifos, lindane, α-endosulfan, bisphenol A, tetrabromobisphenol A (TBBPA), and an antiepileptic drug valproic acid. The half-lethal concentration (LC50) values of these chemicals in casper embryos were 62–87 % of that in the wild-type. After TBBPA exposure, the occurrence of developmental defects in the posterior blood island of casper embryos was increased by 67–77 % in relative to the wild-type, and the half-maximal effective concentration (EC50) in casper was 73 % of that in the wild-type. Moreover, the casper genetic background significantly increased the hyperlocomotion caused by chlorpyrifos and lindane exposure compared with the wild-type. These results demonstrated that casper had greater susceptibility to toxicity than wild-type zebrafish in acute toxicity, developmental toxicity and neurobehavioral toxicity assessments. Our data will inform future toxicological studies in casper and accelerate the development of efficient approaches and strategies for toxicity assessment via the use of casper.

AOP-Anchored Transcriptome Analysis Catalogue Accelerates the Discovery of Environmental Toxicants in Zebrafish.

Current toxicity screening approaches to evaluate the vast number of environmental chemicals that require assessment are hampered due to their significant costs, time requirements, and reliance on live animal testing. The aim of the present study was to develop an adverse outcome pathway (AOP)-anchored transcriptome analysis (AATA) catalogue to expedite the discovery of environmental toxicants. 437 AOPs from the AOPwiki (https://aopwiki.org/) and 2280 transcriptomics data sets from NCBI Gene Expression Omnibus (GEO) and EMBL-EBI ArrayExpress (AE) repositories were comprehensively reviewed and analyzed. By using the differentially expressed molecular key event (mKE) genes as connection nodes, we created a large-scale environmental substance─target gene (mKE)─predicted adverse outcomes (SGAs) network that included 78 substances, 1099 genes, and 354 adverse outcomes (AOs). To validate the reliability of the network, comprehensive literature verification was conducted. We demonstrated that 164 of the 354 AOs identified have been previously characterized in the literature. The results for 136 of these AOs were consistent with the predictions of the AATA catalogue, representing an accuracy rate of 82.9%. Besides, distinct patterns in molecular KEs and AOs among categories of substances, such as biocides and metals, were demonstrated. Some representative substances, including atrazine and copper, pose significant risks to fish at various levels of biological organization. Moreover, experimental verification of the AATA predictions was conducted, including exposures of zebrafish to perfluorooctanesulfonate, cresyl diphenyl phosphate, and lanthanum. Results demonstrated consistency with predictions of the AATA catalogue, with an accuracy rate of 92.3%. Collectively, the present findings support the AATA catalogue as an efficient and promising platform for identifying environmental toxicants to fish and thereby provide novel insights into the understanding of potential risks of environmental contaminants.

Insight into the Binding Interaction between PEDCs and hERRγ Utilizing Molecular Docking and Molecular Dynamics Simulations.

Phenolic environmental endocrine-disrupting chemicals (PEDCs) are persistent EDCs that are widely found in food packaging materials and environmental media and seriously threaten human health and ecological security. Human estrogen-related receptor γ (hERRγ) has been proposed as a mediator for the low-dose effects of many environmental PEDCs; however, the atomic-level descriptions of dynamical structural features and interactions of hERRγ and PEDCs are still unclarified. Herein, how three PEDCs, 4-(1-methylpropyl)phenol (4-sec-butylphenol), 5,6,7,8-tetrahydro-2-naphthol (tetrahydro-2-napthol), and 2,2-bis(4-hydroxy-3,5-dimethoxyphenyl)propane (BP(2,2)(Me)), interact with hERRγ to produce its estrogenic disruption effects was studied. Molecular docking and multiple molecular dynamics (MD) simulations were first conducted to distinguish the detailed interaction pattern of hERRγ with PEDCs. These binding structures revealed that residues around Leu271, Leu309, Leu345, and Phe435 are important when binding with PEDCs. Furthermore, the binding energies of PEDCs with hERRγ were also characterized using the molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methods, and the results showed that the interactions of CH-π, π-π, and hydrogen bonds are the major contributors for hERRγ binding to these three PEDCs. What is striking is that the methoxide groups of BP(2,2)(Me), as hydrophobic groups, can help to reduce the binding energy of PEDCs binding with hERRγ. These results provide important guidance for further understanding the influence of PEDCs on human health problems.

Addressing chemically-induced obesogenic metabolic disruption: selection of chemicals for in vitro human PPARα, PPARγ transactivation, and adipogenesis test methods.

Whilst western diet and sedentary lifestyles heavily contribute to the global obesity epidemic, it is likely that chemical exposure may also contribute. A substantial body of literature implicates a variety of suspected environmental chemicals in metabolic disruption and obesogenic mechanisms. Chemically induced obesogenic metabolic disruption is not yet considered in regulatory testing paradigms or regulations, but this is an internationally recognised human health regulatory development need. An early step in the development of relevant regulatory test methods is to derive appropriate minimum chemical selection lists for the target endpoint and its key mechanisms, such that the test method can be suitably optimised and validated. Independently collated and reviewed reference and proficiency chemicals relevant for the regulatory chemical universe that they are intended to serve, assist regulatory test method development and validation, particularly in relation to the OECD Test Guidelines Programme. To address obesogenic mechanisms and modes of action for chemical hazard assessment, key initiating mechanisms include molecular-level Peroxisome Proliferator-Activated Receptor (PPAR) α and γ agonism and the tissue/organ-level key event of perturbation of the adipogenesis process that may lead to excess white adipose tissue. Here we present a critical literature review, analysis and evaluation of chemicals suitable for the development, optimisation and validation of human PPARα and PPARγ agonism and human white adipose tissue adipogenesis test methods. The chemical lists have been derived with consideration of essential criteria needed for understanding the strengths and limitations of the test methods. With a weight of evidence approach, this has been combined with practical and applied aspects required for the integration and combination of relevant candidate test methods into test batteries, as part of an Integrated Approach to Testing and Assessment for metabolic disruption. The proposed proficiency and reference chemical list includes a long list of negatives and positives (20 chemicals for PPARα, 21 for PPARγ, and 11 for adipogenesis) from which a (pre-)validation proficiency chemicals list has been derived.