Toxicity testing in the 21st century: a vision and a strategy

Identifying the link between chemical exposures and breast cancer in African American women via integrated in vitro and exposure biomarker data

Among women, breast cancer is the most prevalent form of cancer worldwide and has the second highest mortality rate of any cancer in the United States. The breast cancer related death rate is 40 % higher in non-Hispanic Black women compared to non-Hispanic White women. The incidence of triple negative breast cancer (TNBC), an aggressive subtype of breast cancer for which there is no targeted therapy, is also approximately three times higher for Black, relative to, White women. The drivers of these differences are poorly understood. Here, we aimed to identify chemical exposures which play a role in breast cancer disparities. Using chemical biomonitoring data from the National Health and Nutrition Examination Survey (NHANES) and biological activity data from the EPA's ToxCast program, we assessed the toxicological profiles of chemicals to which US Black women are disproportionately exposed. We conducted a literature search to identify breast cancer targets in ToxCast to analyze the response of chemicals with exposure disparities in these assays. Forty-three chemical biomarkers are significantly higher in Black women. Investigation of these chemicals in ToxCast resulted in 32,683 assays for analysis, 5172 of which contained nonzero values for the concentration at which the dose-response fitted model reaches the cutoff considered "active". Of these chemicals BPA, PFOS, and thiram are most comprehensively assayed. 2,5-dichlorophenol, 1,4-dichlorobenzene, and methyl and propyl parabens had higher biomarker concentrations in Black women and moderate testing and activity in ToxCast. The distribution of active concentrations for these chemicals in ToxCast assays are comparable to biomarker concentrations in Black women NHANES participants. Through this integrated analysis, we identify that multiple chemicals, including thiram, propylparaben, and p,p' DDE, have disproportionate exposures in Black women and have breast cancer associated biological activity at human exposure relevant doses.

Systematic analysis of chemical-protein interactions from zebrafish embryo by proteome-wide thermal shift assay, bridging the gap between molecular interactions and toxicity pathways

The molecular interaction between chemicals and proteins often promotes alteration of cellular function. One of the challenges of the toxicology is to predict the impact of exposure to chemicals. Assessing the impact of exposure implies to understand their mechanism of actions starting from identification of specific protein targets of the interaction. Current methods can mainly predict effects of characterized chemicals with knowledge of its targets, and mechanism of actions. Here, we show that proteome-wide thermal shift methods can identify chemical-protein interactions and the protein targets from bioactive chemicals. We analyzed the identified targets from a soluble proteome extracted from zebrafish embryo, that is a model system for toxicology. To evaluate the utility to predict mechanism of actions, we discussed the applicability in four cases: single chemicals, chemical mixtures, novel chemicals, and novel drugs. Our results showed that this methodology could identify the protein targets, discriminate between protein increasing and decreasing in solubility, and offering additional data to complement the map of intertwined mechanism of actions. We anticipate that the proteome integral solubility alteration (PISA) assay, as it is defined here for the unbiased identification of protein targets of chemicals could bridge the gap between molecular interactions and toxicity pathways. SIGNIFICANCE: One of the challenges of the environmental toxicology is to predict the impact of exposure to chemicals on environment and human health. Our phenotype should be explained by our genotype and the environmental exposure. Genomic methodologies can offer a deep analysis of human genome that alone cannot explain our risks of disease. We are starting to understand the key role of exposure to chemicals on our health and risks of disease. Here, we present a proteomic-based method for the identification of soluble proteins interacting with chemicals in zebrafish embryo and discuss the opportunities to complement the map of toxicity pathway perturbations. We anticipate that this PISA assay could bridge the gap between molecular interactions and toxicity pathways.

Phytochemical Profile, Free Radical Scavenging and Anti-Inflammatory Properties of Acalypha Indica Root Extract: Evidence from In Vitro and In Vivo Studies

In our in vitro and in vivo studies, we used Acalypha indica root methanolic extract (AIRME), and investigated their free radical scavenging/antioxidant and anti-inflammatory properties. Primarily, phytochemical analysis showed rich content of phenols (70.92 mg of gallic acid/g) and flavonoids (16.01 mg of rutin/g) in AIRME. We then performed HR-LC-MS and GC-MS analyses, and identified 101 and 14 phytochemical compounds, respectively. Among them, ramipril glucuronide (1.563%), antimycin A (1.324%), swietenine (1.134%), quinone (1.152%), oxprenolol (1.118%), choline (0.847%), bumetanide (0.847%) and fenofibrate (0.711%) are the predominant phytomolecules. Evidence from in vitro studies revealed that AIRME scavenges DPPH and hydroxyl radicals in a concentration dependent manner (10–50 μg/mL). Similarly, hydrogen peroxide and lipid peroxidation were also remarkably inhibited by AIRME as concentration increases (20–100 μg/mL). In vitro antioxidant activity of AIRME was comparable to ascorbic acid treatment. For in vivo studies, carrageenan (1%, sub-plantar) was injected to rats to induce localized inflammation. Acute inflammation was represented by paw-edema, and significantly elevated (p < 0.05) WBC, platelets and C-reactive protein (CRP). However, AIRME pretreatment (150/300 mg/kg bodyweight) significantly (p < 0.05) decreased edema volume. This was accompanied by a significant (p < 0.05) reduction of WBC, platelets and CRP with both doses of AIRME. The decreased activities of superoxide dismutase, catalase, glutathione reductase and glutathione peroxidase in paw tissue were restored (p < 0.05 / p < 0.01) with AIRME in a dose-dependent manner. Furthermore, AIRME attenuated carrageenan-induced neutrophil infiltrations and vascular dilation in paw tissue. For the first time, our findings demonstrated the potent antioxidant and anti-inflammatory properties of AIRME, which could be considered to develop novel anti-inflammatory drugs.

Ketamine induction of physiological functions alterations in Caenorhabditis elegans by chronic and multigenerational exposure and corresponding aquatic environmental risk assessment

Although ketamine (KET) has been widely detected in aquatic environments, the ecotoxicity data in aquatic invertebrates and associated risk remained unclear. This study aimed to investigate the adverse effects on benthos (Caenorhabditis elegans (C.elegans)) posed by KET from chronic (10 days) and multigenerational (four generations) exposure. Such exposure induced dose-dependent alterations on apoptosis, reactive oxygen species (ROS) induction, locomotion activity, feeding rate, chemotaxis, and brood size of nematodes, showing a cumulative damage through generations. KET posed vulva deformations and worm bags of C. elegans with a dosed-dependent increase. As a consequence, the fecundity and viability of worms would be impaired, which could eventually impact aquatic ecosystem equilibrium. Meanwhile, the bioactivation/detoxification process of xenobiotics and longevity regulating pathway induced by KET might be responsible for the physiological function disorders. Accordingly, the risk quotients (RQ) of KET in surface water in China were calculated using the 90% indicator protection concentration (C_0.1) derived from multiple toxicity indicators cumulative analyses. The results would be more objective considering numerous biomarkers changes of one species in comparison with traditional method using no observed effect concentrations (NOEC) of teratogenesis. The risk in surface water in southern China was up to high level (RQ > 1), suggesting long-term monitoring was imperative.

Alterations in small RNA profiles in liver following a subchronic exposure to a low-dose pesticide mixture in Sprague-Dawley rats

Small RNAs have emerged as a promising new type of biomarker to monitor health status and track the development of diseases. Here we report changes in the levels of small RNAs in the liver of rats exposed to a mixture of six pesticides frequently detected in foodstuffs (azoxystrobin, boscalid, chlorpyrifos, glyphosate, imidacloprid and thiabendazole). Multivariate analysis with OPLS-DA methods showed that small RNA profiles can discriminate samples from pesticide treated rats from their concurrent controls. A total of 9 miRNAs were found to have their levels altered in the liver of the pesticide-treated rats in comparison to the controls, which included 7 that were downregulated (miR-22-5p, miR-193a-3p, miR-32-5p, miR-33-5p, miR-122-5p, miR-22-3p, miR-130a-3p) and 2 that were upregulated (miR-486-5p, miR-146a-5p). These miRNAs were predicted to regulate genes, which were found to have their expression altered by the pesticide mixture and have known health implications in the regulation of hepatic metabolism. This supports and extends our recent conclusions that high- throughput 'omics' analyses can reveal molecular perturbations, which can potentially act as sensitive and accurate markers of health risks arising from exposure to environmental pollutants such as pesticides.

Dynamic microfluidic bioreactor-Hip simulator (DMBH) system for implant toxicity monitoring

The generation of degradation products (DPs) like ions and organo-metallic particles from corroding metallic implants is an important healthcare concern. These DPs generate local and systemic toxicity. The impact on local toxicity is well documented, however, little is known about systemic toxicity. This is mainly due to the limited scope of the current microtiter plate-based (static) toxicity assay techniques. These methods do not mimic the systemic (dynamic) conditions. In this study, it is hypothesized that DPs incubated with cells in static conditions might provide improper systemic toxicity results, as there is no movement mimicking the blood circulation around cells. This study reports the development of a three-chambered prototype microfluidic system connected to the operational hip implant simulator to test the cellular response induced by the DPs. This setup is called a dynamic microfluidic bioreactor-hip simulator system. We hypothesize that a dynamic microfluidic system will provide a realistic toxicology response induced by DPs than a static cell culture plate. To prove the hypothesis, Neuro2a (N2a) cells were used as representative cells to study systemic neurotoxicity by the implant DPs. The microfluidic bioreactor system was validated by comparing the cell toxicity against the traditional static system and using COMSOL modeling for media flow with DPs. The hip implant simulator used in this study was a state-of-the-art sliding hip simulator developed in our lab. The results suggested that static toxicity was significantly more compared to dynamic microfluidic-based toxicity. The newly developed DMBH system tested for in situ systemic toxicity on N2a cells and demonstrated very minimum toxicity level (5.23%) compared to static systems (31.16%). Thus, the new DMBH system is an efficient tool for in situ implant metal systemic toxicity testing.

New insights into the conversion of electropherograms to the effective electrophoretic mobility scale

CE-MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE-MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self-contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV-Vis absorption-like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data.

Characterising the relationships between physiological indicators and all-cause mortality (NHANES): a population-based cohort study

BACKGROUND

Mortality risk stratification based on dichotomising a physiological indicator with a cutoff point might not adequately capture increased mortality risk and might not account for non-linear associations. We aimed to characterise the linear and non-linear relationships of 27 physiological indicators with all-cause mortality to evaluate whether the current clinical thresholds are suitable in distinguishing patients at high risk for mortality from those at low risk.

METHODS

For this observational cohort study of the US non-institutionalised population, we used data from adults (≥18 years) included in the 1999-2014 National Health and Nutrition Examination Survey (NHANES) linked with National Death Index mortality data collected from Jan 1, 1999, up until Dec 31, 2015. We used Cox proportional hazards regression models adjusted for age, sex, and race or ethnicity to assess associations of physiological indicators with all-cause mortality. We assessed non-linear associations by discretising the physiological indicator into nine quantiles (termed novemtiles) and by using a weighted sum of cubic polynomials (spline). We used ten-fold cross validation to select the most appropriate model using the concordance index, Nagelkerke R2, and Akaike Information Criterion. We identified the level of each physiological indicator that led to a 10% increase in mortality risk to define our cutoffs used to compare with the current clinical thresholds.

FINDINGS

We included 47 266 adults of 82 091 assessed for eligibility. 25 (93%) of 27 indicators showed non-linear associations with substantial increases compared with linear models in mortality risk (1·5-2·5-times increase). Height and 60 s pulse were the only physiological indicators to show linear associations. For example, participants with an estimated glomerular filtration rate (GFR) of less than 65 mL/min per 1·73 m2 or between 90-116 mL/min per 1·73 m2 are at moderate (hazard ratio 1-2) mortality risk. Those with a GFR greater than 117 mL/min per 1·73 m2 show substantial (hazard ratio ≥2) mortality risk. Both lower and higher values of cholesterol are associated with increased mortality risk. The current clinical thresholds do not align with our mortality-based cutoffs for fat deposition indices, 60 s pulse, triglycerides, cholesterol-related indicators, alkaline phosphatase, glycohaemoglobin, homoeostatic model assessment of insulin resistance, and GFR. For these indicators, the misalignment suggests the need to consider an additional bound when only one is provided.

INTERPRETATION

Most clinical indicators were shown to have non-linear associations with all-cause mortality. Furthermore, considering these non-linear associations can help derive reliable cutoffs to complement risk stratification and help inform clinical care delivery. Given the poor alignment with our proposed cutoffs, the current clinical thresholds might not adequately capture mortality risk.

NMR spectroscopy of wastewater: A review, case study, and future potential

NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (¹³C, ¹⁵N, ¹⁹F, ³¹P, ²⁹Si) as well as other environmentally relevant nuclei and metals such as ²⁷Al, ⁵¹V, ²⁰⁷Pb and ¹¹³Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.

Dependence of Graphene Oxide (GO) Toxicity on Oxidation Level, Elemental Composition, and Size

The mass production of graphene oxide (GO) unavoidably elevates the chance of human exposure, as well as the possibility of release into the environment with high stability, raising public concern as to its potential toxicological risks and the implications for humans and ecosystems. Therefore, a thorough assessment of GO toxicity, including its potential reliance on key physicochemical factors, which is lacking in the literature, is of high significance and importance. In this study, GO toxicity, and its dependence on oxidation level, elemental composition, and size, were comprehensively assessed. A newly established quantitative toxicogenomic-based toxicity testing approach, combined with conventional phenotypic bioassays, were employed. The toxicogenomic assay utilized a GFP-fused yeast reporter library covering key cellular toxicity pathways. The results reveal that, indeed, the elemental composition and size do exert impacts on GO toxicity, while the oxidation level exhibits no significant effects. The UV-treated GO, with significantly higher carbon-carbon groups and carboxyl groups, showed a higher toxicity level, especially in the protein and chemical stress categories. With the decrease in size, the toxicity level of the sonicated GOs tended to increase. It is proposed that the covering and subsequent internalization of GO sheets might be the main mode of action in yeast cells.

In vivo and in vitro transcriptomics meta-analyses reveal that BPA may affect TGF-beta signaling regardless of the toxicology system employed

Bisphenol A (BPA) is a high-production-volume monomer for the manufacture of a wide variety of polycarbonate plastics and resins. Evidence suggests BPA can induce carcinogenesis, reproductive toxicity, abnormal inflammatory or immune response, and developmental disorders of the brain or nervous system. However, whether BPA affects the very same basic molecular processes in all the in vivo and in vitro systems employed to exert its molecular mechanisms of toxicity remains to be clarified. In this study, we collected multi-source global transcriptomics datasets for BPA-exposed organisms and cells, and evaluated the adverse effects of BPA by using data integration and gene functional enrichment analyses. We found that BPA may affect basic cellular processes, such as cell growth, survival, proliferation, differentiation, and apoptosis, independent of species and specific in vivo or in vitro systems. Mechanistically, BPA could regulate cell-extra cellular matrix interactions via challenging TGF-beta signaling pathways. Furthermore, we compared our in vitro BPA-dependent mouse embryoid body (EB) global differentiation transcriptomics with all the other datasets. We verified the EB-based toxicological system could recapitulate several in vivo and other in vitro findings very efficiently, and in a less time- and resource-consuming fashion. Taken together, this study emphasizes the utility of meta-analyses to understand common molecular mechanisms of toxicity of synthetic chemicals.

Multiplexed quantitative evaluation on mitochondrial toxicity of tris (2,3-dibromopropyl) phosphate in hepatocyte

The frequent detection of (2,3-dibromopropyl) phosphate (TDBPP) in environment has led to a consistent risk to organisms. However, little is known about the toxicity of TDBPP exclusive for its carcinogen. Mitochondrion that tightly relates to adverse outcomes once deteriorated is referred as a target of environmental pollutants. Here, we investigated the role of mitochondrial abnormality in development of cellular pathobiology especially lipid deposition when response to TDBPP in mitochondria-rich hepatocyte (AML12) at the same order of magnitude as the environmental concentrations (10^-6 mol/L or below) via multiplexed quantitative high content analytic system. The present study claimed TDBPP shifted mitochondria from fusion morphology to fission phenotype charactering by less mitochondrial networks, larger mitochondrial areas and shorter branch length at 10^-7 mol/L or above. This dynamic imbalance was triggered by high levels of fis and drp1 genes when treated with TDBPP. The deformation caused by TDBPP reciprocally influenced biogenesis through PGC1α and electron transport chains via ectopic expression of genes encoding for mitochondria complex I and III subunits. Accordingly, we observed high mitoROS level and low mitochondria membrane potential. Consequently, cells contained those abnormal mitochondria were predisposed to accumulating lipids after exposure to TDBPP. Here we showed that TDBPP deteriorated mitochondrial morphology and function, which may induce lipid generation. As for a banned while still emerged contaminant, our study also claimed further exploration on the non-carcinogenic toxicity of TDBPP.

Comparative and mechanistic toxicity assessment of structure-dependent toxicity of carbon-based nanomaterials

The wide application of carbon-based nanomaterials (CNMs) has resulted in the ubiquity of CNMs in the natural environment and they potentially impose adverse consequences on ecosystems and human health. In this study, we comprehensively evaluated and compared potential toxicological effects and mechanisms of seven CNMs in three representative types (carbon blacks, graphene nanoplatelets, and fullerenes), to elucidate the correlation between their physicochemical/structural properties and toxicity. We employed a recently-developed quantitative toxicogenomics-based toxicity testing system with GFP-fused yeast reporter library targeting main cellular stress response pathways, as well as conventional phenotype-based bioassays. The results revealed that DNA damage, oxidative stress, and protein stress were the major mechanisms of action for all the CNMs at sub-cytotoxic concentration levels. The molecular toxicity nature were concentration-dependent, and they exhibited both similarity within the same structural group and distinctiveness among different CNMs, evidencing the structure-driven toxicity of CNMs. The toxic potential based on toxicogenomics molecular endpoints revealed the remarkable impact of size and structure on the toxicity. Furthermore, the phenotypic endpoints derived from conventional phenotype-based bioassays correlated with quantitative molecular endpoints derived from the toxicogenomics assay, suggesting that the selected protein biomarkers captured the main cellular effects that are associated with phenotypic adverse outcomes.

Assessing how in vitro assay types predict in vivo toxicology data

In vivo animal bioassays are increasingly being supplemented with in vitro assays to serve as the new standard for chemical toxicity tests. Despite this shift, investigators face challenges related to increased reliance on in vitro data. The aim of this study was to deploy a streamlined method to assess the ability of in vitro data to predict similar results as in vivo data by correlating chemical toxicity rankings obtained using Benchmark Doses and Benchmark Dose Lower Limits (BMD(L)s) derived from in vivo and in vitro assays. In vitro and in vivo assay characteristics were assessed for their impact on the predictive ability of in vitro data. Minimum best-fit BMD(L)s were calculated for chemicals using Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). Forty-one chemicals met the inclusion criteria of this study. Relative chemical toxicity rankings were assessed through Kappa statistics, Pearson correlations, and/or Ordinary Least Squares (OLS) regressions. Results illustrated likely ability of in vitro data to predict similar results as short-term in vivo data. Further, rankings derived from in vitro cytotoxicity assays, unlike stress response assays, significantly correlated with rankings derived from short-term in vivo assays. These results support the use of in vitro data as a prioritization tool within toxicity testing.

Reproducibility and robustness of high-throughput S1500+ transcriptomics on primary rat hepatocytes for chemical-induced hepatotoxicity assessment

•

TempO-Seq assays of rat hepatocytes in collagen sandwich are highly reproducible.

•

Gene expression analysis shows S1500+ is representative of the whole transcriptome.

•

Connectivity mapping shows consistency between TempO-Seq and Affymetrix data.

•

Gene set enrichment shows consistency between S1500+ and the whole transcriptome.

•

Gene set enrichment using hallmark gene sets informs hepatotoxicity.

Cell-based in vitro models coupled with high-throughput transcriptomics (HTTr) are increasingly utilized as alternative methods to animal-based toxicity testing. Here, using a panel of 14 chemicals with different risks of human drug-induced liver injury (DILI) and two dosing concentrations, we evaluated an HTTr platform comprised of collagen sandwich primary rat hepatocyte culture and the TempO-Seq surrogate S1500+ (ST) assay. First, the HTTr platform was found to exhibit high reproducibility between technical and biological replicates (r greater than 0.85). Connectivity mapping analysis further demonstrated a high level of inter-platform reproducibility between TempO-Seq data and Affymetrix GeneChip data from the Open TG-GATES project. Second, the TempO-Seq ST assay was shown to be a robust surrogate to the whole transcriptome (WT) assay in capturing chemical-induced changes in gene expression, as evident from correlation analysis, PCA and unsupervised hierarchical clustering. Gene set enrichment analysis (GSEA) using the Hallmark gene set collection also demonstrated consistency in enrichment scores between ST and WT assays. Lastly, unsupervised hierarchical clustering of hallmark enrichment scores broadly divided the samples into hepatotoxic, intermediate, and non-hepatotoxic groups. Xenobiotic metabolism, bile acid metabolism, apoptosis, p53 pathway, and coagulation were found to be the key hallmarks driving the clustering. Taken together, our results established the reproducibility and performance of collagen sandwich culture in combination with TempO-Seq S1500+ assay, and demonstrated the utility of GSEA using the hallmark gene set collection to identify potential hepatotoxicants for further validation.

Review of Typha spp. (cattails) as toxicity test species for the risk assessment of environmental contaminants on emergent macrophytes

Macrophytes play an important role in aquatic ecosystems, and thus are often used in ecological risk assessments of potentially deleterious anthropogenic substances. Risk assessments for macrophyte populations or communities are commonly based on inferences drawn from standardized toxicity tests conducted on floating non-rooted Lemna species, or submerged-rooted Myriophyllum species. These tests follow strict guidelines to produce reliable and robust results with legal credibility for environmental regulations. However, results and inferences from these tests may not be transferrable to emergent macrophytes due to their different morphology and physiology. Emergent macrophytes of the genus Typha L. are increasingly used for assessing phytotoxic effects of environmental stressors, although standardized testing protocols have not yet been developed for this genus. In this review we present a synthesis of previous toxicity studies with Typha, based on which we evaluate the potential to develop standard toxicity tests for Typha spp. with seven selection criteria: ecological relevance to the ecosystem; suitability for different exposure pathways; availability of plant material; ease of cultivation; uniform growth; appropriate and easily measurable toxicity endpoints; and sensitivity toward contaminants. Typha meets criteria 1-3 fully, criteria 4 and 5 partly based on current limited data, and we identify knowledge gaps that limit evaluation of the remaining two criteria. We provide suggestions for addressing these gaps, and we summarize the experimental design of ecotoxicology studies that have used Typha. We conclude that Typha spp. can serve as future standard test species for ecological risk assessments of contaminants to emergent macrophytes.

Signaling pathway perturbation analysis for assessment of biological impact of cigarette smoke on lung cells

Exposure to cigarette smoke (CS) results in injury to the epithelial cells of the human respiratory tract and has been implicated as a causative factor in the development of chronic obstructive pulmonary disease and lung cancers. The application of omics-scale methodologies has improved the capacity to understand cellular signaling processes underlying response to CS exposure. We report here the development of an algorithm based on quantitative assessment of transcriptomic profiles and signaling pathway perturbation analysis (SPPA) of human bronchial epithelial cells (HBEC) exposed to the toxic components present in CS. HBEC were exposed to CS of different compositions and for different durations using an ISO3308 smoking regime and the impact of exposure was monitored in 2263 signaling pathways in the cell to generate a total effect score that reflects the quantitative degree of impact of external stimuli on the cells. These findings support the conclusion that the SPPA algorithm provides an objective, systematic, sensitive means to evaluate the biological impact of exposures to CS of different compositions making a powerful comparative tool for commercial product evaluation and potentially for other known or potentially toxic environmental smoke substances.

Use of a rapid human primary cell-based disease screening model, to compare next generation products to combustible cigarettes

A growing number of public health bodies, regulators and governments around the world consider electronic vapor products a lower risk alternative to conventional cigarettes. Of critical importance are rapid new approach methodologies to enable the screening of next generation products (NGPs) also known as next generation tobacco and nicotine products. In this study, the activity of conventional cigarette (3R4F) smoke and a range of NGP aerosols (heated tobacco product, hybrid product and electronic vapor product) captured in phosphate buffered saline, were screened by exposing a panel of human cell-based model systems using Biologically Multiplexed Activity Profiling (BioMAP® Diversity PLUS® Panel, Eurofins Discovery). Following exposure, the biological activity for a wide range of biomarkers in the BioMAP panel were compared to determine the presence of toxicity signatures that are associated with specific clinical findings. NGP aerosols were found to be weakly active in the BioMAP Diversity PLUS Panel (≤3/148 biomarkers) whereas significant activity was observed for 3R4F (22/148 biomarkers). Toxicity associated biomarker signatures for 3R4F included immunosuppression, skin irritation and thrombosis, with no toxicity signatures seen for the NGPs. BioMAP profiling could effectively be used to differentiate between complex mixtures of cigarette smoke or NGP aerosol extracts in a panel of human primary cell-based assays. Clinical validation of these results will be critical for confirming the utility of BioMAP for screening NGPs for potential adverse human effects.

Novel test strategies for in vitro seizure liability assessment

INTRODUCTION

The increasing incidence of mental illnesses and neurodegenerative diseases results in a high demand for drugs targeting the central nervous system (CNS). These drugs easily reach the CNS, have a high affinity for CNS targets, and are prone to cause seizures as an adverse drug reaction. Current seizure liability assessment heavily depends on in vivo or ex vivo animal models and is therefore ethically debated, labor intensive, expensive, and not always predictive for human risk.

AREAS COVERED

The demand for CNS drugs urges the development of alternative safety assessment strategies. Yet, the complexity of the CNS hampers reliable detection of compound-induced seizures. This review provides an overview of the requirements of in vitro seizure liability assays and highlights recent advances, including micro-electrode array (MEA) recordings using rodent and human cell models.

EXPERT OPINION

Successful and cost-effective replacement of in vivo and ex vivo models for seizure liability screening can reduce animal use for drug development, while increasing the predictive value of the assays, particularly if human cell models are used. However, these novel test strategies require further validation and standardization as well as additional refinements to better mimic the human in vivo situation and increase their predictive value.

Alternaria toxins-Still emerging?

Alternaria molds are known to cause the contamination of food with their secondary metabolites, a chemically very heterogeneous group of compounds. Yet, after decades of research on the occurrence and the toxicity of Alternaria toxins in academia, no regulation has been implemented yet, thus leaving these potential food contaminants in the status of so-called "emerging mycotoxins". However, research on this topic has been far from static, leading to the European Food Safety Authority repeatedly calling for more data on the occurrence and toxicity of genotoxic metabolites such as alternariol (AOH) and its monomethyl ether (AME). To give an overview on recent developments in the field, this comprehensive review summarizes published data and addresses current challenges arising from the chemical complexity of Alternaria's metabolome, mixture effects and the emergence of novel biological targets like cell membranes or the interaction with different receptors. Besides toxicodynamics, we review recent research on toxicokinetics, including the first in vivo studies which incorporated the rarely investigated-but highly genotoxic-perylene quinones. Furthermore, a particular focus lies on the advances of liquid chromatography/tandem mass spectrometry (LC-MS/MS)-based analytical tools for determining a broader spectrum of Alternaria toxins including modified/masked forms and assessing exposure via human biomonitoring (HBM).

Pre-validation of choriogenin H transgenic medaka eleutheroembryos as a quantitative estrogenic activity test method

The choriogenin H - EGFP transgenic medaka (Oryzias melastigma) has been used to test estrogenic substances and quantify estrogenic activity into 17β-estradiol (E2) equivalency (EEQ). The method uses 8 eleutheroembryos in 2 ml solution per well and 3 wells per treatment in 24-well plates at 26 ± 1 °C for 24 ± 2 h, with subsequent measurements of induced GFP signal intensity. EEQ measurements are calculated using a E2 probit regression model with a coefficient of determination (R²) > 0.90. The selectivity was confirmed evaluating 27 known estrogenic and 5 known non-estrogenic compounds. Limit of quantitation (LOQ), recovery rate and bias were calculated to be 1 ng/ml EEQ, 104% and 4% respectively. Robustness analysis revealed exposure temperature is a sensitive parameter that should be kept at 26 ± 1 °C. The repeatability of intra- and inter-laboratories achieved CV < 30% for most tested food and cosmetics samples. The lot-lot stability was confirmed by the stable EEQ qualitative control (QC, 1 ng/mL E2) and calibration curve results. The stability of standard reagents, samples and sample extracts was also investigated. These data demonstrated this method to be an accurate indicator of estrogenic activity for both chemicals and extracts.

Toxicity of Carbon Nanomaterials-Towards Reliable Viability Assessment via New Approach in Flow Cytometry

The scope of application of carbon nanomaterials in biomedical, environmental and industrial fields is recently substantially increasing. Since in vitro toxicity testing is the first essential step for any commercial usage, it is crucial to have a reliable method to analyze the potentially harmful effects of carbon nanomaterials. Even though researchers already reported the interference of carbon nanomaterials with common toxicity assays, there is still, unfortunately, a large number of studies that neglect this fact. In this study, we investigated interference of four bio-promising carbon nanomaterials (graphene acid (GA), cyanographene (GCN), graphitic carbon nitride (g-C₃N₄) and carbon dots (QCDs)) in commonly used LIVE/DEAD assay. When a standard procedure was applied, materials caused various types of interference. While positively charged g-C₃N₄ and QCDs induced false results through the creation of free agglomerates and intrinsic fluorescence properties, negatively charged GA and GCN led to false signals due to the complex quenching effect of the fluorescent dye of a LIVE/DEAD kit. Thus, we developed a new approach using a specific gating strategy based on additional controls that successfully overcame all types of interference and lead to reliable results in LIVE/DEAD assay. We suggest that the newly developed procedure should be a mandatory tool for all in vitro flow cytometry assays of any class of carbon nanomaterials.

A Tiered Female Ovarian Toxicity Screening Identifies Toxic Effects of Checkpoint Kinase 1 Inhibitors on Murine Growing Follicles

Ovarian toxicity (ovotoxicity) is one of the major side effects of pharmaceutical compounds for women at or before reproductive age. The current gold standard for screening of compounds' ovotoxicity largely relies on preclinical investigations using whole animals. However, in vivo models are time-consuming, costly, and harmful to animals. Here, we developed a 3-tiered ovotoxicity screening approach starting from encapsulated in vitro follicle growth (eIVFG) and screened for the potential ovotoxicity of 8 preclinical compounds from AstraZeneca (AZ). Results from Tiers 1 to 2 screenings using eIVFG showed that the first 7 tested AZ compounds, AZ-A, -B, -C, -D, -E, -F, and -G, had no effect on examined mouse follicle and oocyte reproductive outcomes, including follicle survival and development, 17β-estradiol secretion, ovulation, and oocyte meiotic maturation. However, AZ-H, a preclinical compound targeting the checkpoint kinase 1 inhibitor to potentiate the anticancer effects of DNA-damaging agents, significantly promoted granulosa cell apoptosis and the entire growing follicle atresia at clinically relevant concentrations of 1 and 10 μM. The more targeted explorations in Tier 2 revealed that the ovotoxic effect of AZ-H primarily resulted from checkpoint kinase 1 inhibition in granulosa cells. Using in vivo mouse model, the Tier 3 screening confirmed the in vitro ovotoxicities of AZ-H discovered in Tiers 1 and 2. Also, although AZ-H at 0.1 μM alone was not ovotoxic, it significantly exacerbated gemcitabine-induced ovotoxicities on growing follicles. Taken together, our study demonstrates that the tiered ovotoxicity screening approach starting from eIVFG identifies and prioritizes pharmaceutical compounds of high ovotoxicity concern.

Differences in P-glycoprotein activity in human and rodent blood-brain barrier assessed by mechanistic modelling

Variation in the efficacy and safety of central nervous system drugs between humans and rodents can be explained by physiological differences between species. An important factor could be P-glycoprotein (Pgp) activity in the blood–brain barrier (BBB), as BBB expression of this drug efflux transporter is reportedly lower in humans compared to mouse and rat and subject to an age-dependent increase. This might complicate animal to human extrapolation of brain drug disposition and toxicity, especially in children. In this study, the potential species-specific effect of BBB Pgp activity on brain drug exposure was investigated. An age-dependent brain PBPK model was used to predict cerebrospinal fluid and brain mass concentrations of Pgp substrate drugs. For digoxin, verapamil and quinidine, in vitro kinetic data on their transport by Pgp were derived from literature and used to scale to in vivo parameters. In addition, age-specific digoxin transport was simulated for children with a postnatal age between 25 and 81 days. BBB Pgp activity in the model was optimized using measured CSF data for the Pgp substrates ivermectin, indinavir, vincristine, docetaxel, paclitaxel, olanzapine and citalopram, as no useful in vitro data were available. Inclusion of Pgp activity in the model resulted in optimized predictions of their brain concentration. Total brain-to-plasma AUC values (Kp,brain) in the simulations without Pgp were divided by the Kp,brain values with Pgp. Kp ratios ranged from 1 to 45 for the substrates investigated. Comparison of human with rodent Kp,brain ratios indicated ≥ twofold lower values in human for digoxin, verapamil, indinavir, paclitaxel and citalopram and ≥ twofold higher values for vincristine. In conclusion, BBB Pgp activity appears species-specific. An age-dependent PBPK model-based approach could be useful to extrapolate animal data to human adult and paediatric predictions by taking into account species-specific and developmental BBB Pgp expression.

Cell-Type-Specific High Throughput Toxicity Testing in Human Midbrain Organoids

Toxicity testing is a crucial step in the development and approval of chemical compounds for human contact and consumption. However, existing model systems often fall short in their prediction of human toxicity in vivo because they may not sufficiently recapitulate human physiology. The complexity of three-dimensional (3D) human organ-like cell culture systems ("organoids") can generate potentially more relevant models of human physiology and disease, including toxicity predictions. However, so far, the inherent biological heterogeneity and cumbersome generation and analysis of organoids has rendered efficient, unbiased, high throughput evaluation of toxic effects in these systems challenging. Recent advances in both standardization and quantitative fluorescent imaging enabled us to dissect the toxicities of compound exposure to separate cellular subpopulations within human organoids at the single-cell level in a framework that is compatible with high throughput approaches. Screening a library of 84 compounds in standardized human automated midbrain organoids (AMOs) generated from two independent cell lines correctly recognized known nigrostriatal toxicants. This approach further identified the flame retardant 3,3',5,5'-tetrabromobisphenol A (TBBPA) as a selective toxicant for dopaminergic neurons in the context of human midbrain-like tissues for the first time. Results were verified with high reproducibility in more detailed dose-response experiments. Further, we demonstrate higher sensitivity in 3D AMOs than in 2D cultures to the known neurotoxic effects of the pesticide lindane. Overall, the automated nature of our workflow is freely scalable and demonstrates the feasibility of quantitatively assessing cell-type-specific toxicity in human organoids in vitro.

A prospective whole-mixture approach to assess risk of the food and chemical exposome

Many widely used chemicals result in ubiquitous human exposure from multiple sources, including diet. Legislation mainly deals with the toxicological evaluation of single substances owing to a methodological and conceptual lack of alternatives, and does so within defined silos subject to over 40 distinct regulations in the EU alone. Furthermore, much of the research and many of the initiatives concerned with the assessment and evaluation of chemical mixtures and their potential effects on human health rely on retrospective analysis. Here we propose an approach for the prospective identification, assessment and regulation of mixtures relevant to human health. We address two distinct aspects of toxicology-which chemicals actually do occur together, and how potential mixture-related health hazards can be predicted-with an adapted concept of the exposome and large-scale hazard screens. The proactive use of the likelihood of co-exposure, together with the new approach of methods-based testing, may be a timely and feasible way of identifying those substances and mixtures where hazards may have been overlooked and regulatory action is needed. Ideally, we would generate co-exposure patterns for specific consumer groups, depending on lifestyle and dietary habits, to assess the specific risk of identified mixtures.

Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional generative adversarial network (cGAN) or deep neural networks (DNN), and leveraging this large set of toxicity data we could efficiently predict toxic outcomes of untested chemicals. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure. In vivo toxicity and chemical data were used to train two neural network generators. The first was a DNN (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train generators to produce toxicity data. Our results showed that Go-ZT significantly outperformed the cGAN, support vector machine, random forest and multilayer perceptron models in cross-validation, and when tested against an external test dataset. By combining both Go-ZT and GAN-ZT, our consensus model improved the SE, SP, PPV, and Kappa, to 71.4%, 95.9%, 71.4% and 0.673, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.837. Considering their potential use as prescreening tools, these models could provide in vivo toxicity predictions and insight into the hundreds of thousands of untested chemicals to prioritize compounds for HT testing.

Development of a method for assessing the accumulation and metabolization of antidepressant drugs in zebrafish (Danio rerio) eleutheroembryos

Antidepressant drugs are widely used for the treatment of common mental or other psychiatric disorders such as depression, which affect about 121 million people worldwide. This widespread use has contributed to the input of these pharmaceuticals and their metabolites into the environment. The aim of this work was to develop an analytical method to quantify the most widely used antidepressant drugs, selective serotonin reuptake inhibitors (SSRI), and their main metabolites in the environment. For this, a new and reliable miniaturized extraction method based on dispersive SPE cleanup procedure for extraction of SSRI followed by derivatization with n-heptafluorobutyrylimidazole, and detection by GC-MS was developed. The methodology, including a first-order one-compartment model, was then applied to a bioconcentration study in zebrafish (Danio rerio) eleutheroembryos. The results showed low bioaccumulation of these compounds; however, a biotransformation evidence of the parent compounds into their metabolites was observed after 6 h of exposure. These results indicate the need to integrate metabolic transformation rates to fully model and understand the bioaccumulation patterns of SSRI and their metabolites.

Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

Linking Coregulated Gene Modules with Polycyclic Aromatic Hydrocarbon-Related Cancer Risk in the 3D Human Bronchial Epithelium

Exposure to polycyclic aromatic hydrocarbons (PAHs) often occurs as complex chemical mixtures, which are linked to numerous adverse health outcomes in humans, with cancer as the greatest concern. The cancer risk associated with PAH exposures is commonly evaluated using the relative potency factor (RPF) approach, which estimates PAH mixture carcinogenic potential based on the sum of relative potency estimates of individual PAHs, compared to benzo[a]pyrene (BAP), a reference carcinogen. The present study evaluates molecular mechanisms related to PAH cancer risk through integration of transcriptomic and bioinformatic approaches in a 3D human bronchial epithelial cell model. Genes with significant differential expression from human bronchial epithelium exposed to PAHs were analyzed using a weighted gene coexpression network analysis (WGCNA) two-tiered approach: first to identify gene sets comodulated to RPF and second to link genes to a more comprehensive list of regulatory values, including inhalation-specific risk values. Over 3000 genes associated with processes of cell cycle regulation, inflammation, DNA damage, and cell adhesion processes were found to be comodulated with increasing RPF with pathways for cell cycle S phase and cytoskeleton actin identified as the most significantly enriched biological networks correlated to RPF. In addition, comodulated genes were linked to additional cancer-relevant risk values, including inhalation unit risks, oral cancer slope factors, and cancer hazard classifications from the World Health Organization's International Agency for Research on Cancer (IARC). These gene sets represent potential biomarkers that could be used to evaluate cancer risk associated with PAH mixtures. Among the values tested, RPF values and IARC categorizations shared the most similar responses in positively and negatively correlated gene modules. Together, we demonstrated a novel manner of integrating gene sets with chemical toxicity equivalence estimates through WGCNA to understand potential mechanisms.

Applications of advanced neuro-behavioral analysis strategies in aquatic ecotoxicology

Despite mounting evidence of pleiotropic ecological risks, the understanding of the eco-neurotoxic impact of most industrially relevant chemicals is still very limited. In particularly the acute and chronic exposures to industrial pollutants on nervous systems and thus potential alterations in ecological fitness remain profoundly understudied. Since the behavioral phenotype is the highest-level and functional manifestation of integrated neurological functions, the alterations in neuro-behavioral traits have been postulated as very sensitive and physiologically integrative endpoints to assess eco-neurotoxicological risks associated with industrial pollutants. Due to a considerable backlog of risk assessments of existing and new production chemicals there is a need for a paradigm shift from high cost, low throughput ecotoxicity test models to next generation systems amenable to higher throughput. In this review we concentrate on emerging aspects of laboratory-based neuro-behavioral phenotyping approaches that can be amenable for rapid prioritizing pipelines. We outline the importance of development and applications of innovative neuro-behavioral assays utilizing small aquatic biological indicators and demonstrate emerging concepts of high-throughput chemo-behavioral phenotyping. We also discuss new analytical approaches to effectively and rapidly evaluate the impact of pollutants on higher behavioral functions such as sensory-motor assays, decision-making and cognitive behaviors using innovative model organisms. Finally, we provide a snapshot of most recent analytical approaches that can be applied to elucidate mechanistic rationale that underlie the observed neuro-behavioral alterations upon exposure to pollutants. This review is intended to outline the emerging opportunities for innovative multidisciplinary research and highlight the existing challenges as well barriers to future development.

In vitro prediction of clinical signs of respiratory toxicity in rats following inhalation exposure

To date there are no OECD validated alternative approaches to study toxicity following inhalation exposure to airborne chemicals. The available OECD test guidelines for acute inhalation toxicity aim to estimate a value of the lethal air concentration of the test chemical leading to the death of 50% of the exposed animals (LC50), to satisfy hazard classification and labelling requirements. This paper explores the view that alternative approaches must compare to outcomes of existing guideline methods to become accepted and implemented in a regulatory context. This case study describes the initiatives taken to validate the lung surfactant bioassay, an in vitro cell-free method, and discusses the challenges faced. While the lung surfactant bioassay could not predict the GHS classification for acute inhalation toxicity of 26 chemicals, the assay successfully predicted the clinical signs of respiratory toxicity observed during or shortly after exposure in vivo as reported in registration dossiers. The lung surfactant bioassay is a promising alternative approach to assess the potential of chemicals to cause changes to respiration remaining after exposure (indicating decreased lung function), and can be combined with other test methods in an integrated approach to testing and assessment of inhaled substances.

Current opinion on risk assessment of cosmetics

Risk assessment of cosmetic ingredients is a useful scientific method to characterize potential adverse effects resulting from using cosmetics. The process of risk assessment consists of four steps: hazard identification, dose-response assessment, exposure assessment, and risk characterization. Hazard identification of chemicals refers to the initial stage of risk assessment and generally utilizes animal studies to evaluate toxicity. Since 2013, however, toxicity studies of cosmetic ingredients using animals have not been permitted in the EU and alternative toxicity test methods for animal studies have momentum to be developed for cosmetic ingredients. In this paper, we briefly review the alternative test methods that are available for cosmetic ingredients including read-across, in silico, in chemico, and invitro methods. In addition, new technologies such as omics and artificial intelligence (AI) have been discussed to expand or improve the knowledge and hazard identification of cosmetic ingredients. Aggregate exposure of cosmetic ingredients is another safety issue and methods for its improvement were reviewed. There have been concerns over the safety of nano-cosmetics for a long time, but the risk of nano-cosmetics remains unclear. Therefore, current issues of cosmetic risk assessment are discussed and expert opinion will be provided for the safety of cosmetics.

Ensemble machine learning to evaluate the in vivo acute oral toxicity and in vitro human acetylcholinesterase inhibitory activity of organophosphates

Organophosphates (OPs) are hazardous chemicals widely used in industry and agriculture. Distribution of their residues in nature causes serious risks to humans, animals, and plants. To reduce hazards from OPs, quantitative structure-activity relationship (QSAR) models for predicting their acute oral toxicity in rats and mice and inhibition constants concerning human acetylcholinesterase were developed according to the bioactivity data of 456 unique OPs. Based on robust, two-dimensional molecular descriptors and quantum chemical descriptors, which accurately reflect OP electronic structures and reactivities, the influences of eight machine-learning algorithms on the prediction performance of the QSAR models were explored, and consensus QSAR models were constructed. Several strict model validation indices and the results of applicability domain evaluations show that the established consensus QSAR models exhibit good robustness, practical prediction abilities, and wide application scopes. Poor correlation was observed between acute oral toxicity at the mammalian level and the inhibition constants at the molecular level, indicating that the acute toxicity of OPs cannot be evaluated only by the experimental data of enzyme inhibitory activity, their toxicokinetic characteristics must also be considered. The constructed QSAR models described herein provide rapid, theoretical assessment of the bioactivity of unstudied or unknown OPs, as well as guidance for making decisions regarding their regulation.

GGL-Tox: Geometric Graph Learning for Toxicity Prediction

Toxicity analysis is a major challenge in drug design and discovery. Recently significant progress has been made through machine learning due to its accuracy, efficiency, and lower cost. US Toxicology in the 21st Century (Tox21) screened a large library of compounds, including approximately 12 000 environmental chemicals and drugs, for different mechanisms responsible for eliciting toxic effects. The Tox21 Data Challenge offered a platform to evaluate different computational methods for toxicity predictions. Inspired by the success of multiscale weighted colored graph (MWCG) theory in protein-ligand binding affinity predictions, we consider MWCG theory for toxicity analysis. In the present work, we develop a geometric graph learning toxicity (GGL-Tox) model by integrating MWCG features and the gradient boosting decision tree (GBDT) algorithm. The benchmark tests of the Tox21 Data Challenge are employed to demonstrate the utility and usefulness of the proposed GGL-Tox model. An extensive comparison with other state-of-the-art models indicates that GGL-Tox is an accurate and efficient model for toxicity analysis and prediction.

Testing the efficacy of broad-acting sorbents for environmental mixtures using isothermal analysis, mammalian cells, and H. vulgaris

The hazards associated with frequent exposure to polycyclic aromatic hydrocarbons (PAHs), pesticides, Aroclors, plasticizers, and mycotoxins are well established. Adsorption strategies have been proposed for the remediation of soil and water, although few have focused on the mitigation of mixtures. This study tested a hypothesis that broad-acting sorbents can be developed for diverse chemical mixtures. Adsorption of common and hazardous chemicals was characterized using isothermal analysis from Langmuir and Freundlich equations. The most effective sorbents included medical-grade activated carbon (AC), parent montmorillonite clay, acid-processed montmorillonite (APM), and nutrient-amended montmorillonite clays. Next, we tested the ability of broad-acting sorbents to prevent cytotoxicity of class-specific mixtures using 3 mammalian in vitro models (HLF, ESD3, and 3T3 cell lines) and the hydra assay. AC showed the highest efficacy for mitigating pesticides, plasticizers, PAHs, and mycotoxins. Clays, such as APM, were effective against pesticides, Aroclors, and mycotoxins, while amended clays were most effective against plasticizers. Finally, a sorbent mixture was shown to be broadly active. These results are supported by the high correlation coefficients for the Langmuir model with high capacity, affinity, and free energy, as well as the significant protection of cells and hydra (p < 0.05). The protection percentages in 3T3 cells and hydra showed the highest correlation as suggested by both Pearson and Spearman with r = 0.84 and rho = 0.73, respectively (p < 0.0001). Collectively, these studies showed that broad-acting sorbents may be effective in preventing toxic effects of chemical mixtures and provided information on the most effective sorbents based on adsorption isotherms, and in vitro and aquatic organism test methods.

Multi-omics phenotyping of the gut-liver axis reveals metabolic perturbations from a low-dose pesticide mixture in rats

Health effects of pesticides are not always accurately detected using the current battery of regulatory toxicity tests. We compared standard histopathology and serum biochemistry measures and multi-omics analyses in a subchronic toxicity test of a mixture of six pesticides frequently detected in foodstuffs (azoxystrobin, boscalid, chlorpyrifos, glyphosate, imidacloprid and thiabendazole) in Sprague-Dawley rats. Analysis of water and feed consumption, body weight, histopathology and serum biochemistry showed little effect. Contrastingly, serum and caecum metabolomics revealed that nicotinamide and tryptophan metabolism were affected, which suggested activation of an oxidative stress response. This was not reflected by gut microbial community composition changes evaluated by shotgun metagenomics. Transcriptomics of the liver showed that 257 genes had their expression changed. Gene functions affected included the regulation of response to steroid hormones and the activation of stress response pathways. Genome-wide DNA methylation analysis of the same liver samples showed that 4,255 CpG sites were differentially methylated. Overall, we demonstrated that in-depth molecular profiling in laboratory animals exposed to low concentrations of pesticides allows the detection of metabolic perturbations that would remain undetected by standard regulatory biochemical measures and which could thus improve the predictability of health risks from exposure to chemical pollutants.

Evaluation of the effects of low nanomolar bisphenol A-like compounds' levels on early human embryonic development and lipid metabolism with human embryonic stem cell in vitro differentiation models

The widely used chemical bisphenol A (BPA) has been associated with several health effects. In recent years, many derivatives were developed to replace BPA although without thorough toxicological evaluation. Here, we employed a human embryoid body (EB)-based in vitro global differentiation and hepatic specification models, followed by RNA-seq analyses, to comprehensively study the potential developmental toxicity of six BPA replacements (BPS, BPF, BPZ, BPB, BPE, and BPAF), as compared to BPA. We found that those bisphenols may disrupt lineage commitment and lipid metabolism during early embryonic development. These effects mostly manifested via the dysregulation of HOX and APO family genes. Moreover, among the seven bisphenols analyzed, BPE seemed to have the mildest effects.

Comprehensive analysis of organophosphorus flame retardant-induced mitochondrial abnormalities: Potential role in lipid accumulation

Organophosphorus flame retardants (OPFRs), a group of new emerging endocrine disruption chemicals, have been reported to cause metabolic disturbance. Currently, mitochondrial abnormality is a new paradigm for evaluating chemical-mediated metabolic disruption. However, a comprehensive correlation between these two aspects of OPFR remains elusive. In the work reported here, 3 markers for morphological abnormality, and 7 markers of mitochondrial dysfunction were detected after treatment with two aryl-OPFRs (TCP and TPhP) and three chlorinated-OPFRs (TDCPP, TCPP, and TCEP) on hepatocyte. The two aryl-OPFRs and TDCPP can cause intracellular lipid accumulation at non-cytotoxic concentrations (<10 μM), while the other two chlorinated-OPFRs only caused lipid deposition at 10 μM. Furthermore, at the tested concentrations, all of them reduced mitochondrial (mito)-network numbers, enlarged mito-area/cells, and skewed mitoATP/glycoATP. Excluding TCEP, the other four chemicals induced mito-ROS and depleted mitochondrial membrane potential (MMP). Notably, only TCP, TPhP and TDCPP impeded mitoATP generation rate and mito-respiratory rate. Based on potency estimates, the capacity for lipid accumulation was significantly correlated with mito-network numbers (R² = 0.6481, p < 0.01), mitoATP/glycoATP (R² = 0.5197, p < 0.01), mitoROS (R² = 0.7197, p < 0.01), and MMP (R² = 0.7715, p < 0.01). Remarkably, the mito-respiratory rate (R² = 0.8753, p < 0.01) exhibited the highest correlation. Thus, the more potent lipid inducers TPhP, TCP and TDCPP could be identified. The results of this study demonstrate that aryl-OPFRs are more potent in metabolic disruption than other esters examined. Metabolic disruption should be examined further for chemicals that have the capacity to counteract the aforementioned functions of mitochondrial.

Case Study in 21st Century Ecotoxicology: Using In Vitro Aromatase Inhibition Data to Predict Short-Term In Vivo Responses in Adult Female Fish

The present study evaluated whether in vitro measures of aromatase inhibition as inputs into a quantitative adverse outcome pathway (qAOP) construct could effectively predict in vivo effects on 17β-estradiol (E2) and vitellogenin (VTG) concentrations in female fathead minnows. Five chemicals identified as aromatase inhibitors in mammalian-based ToxCast assays were screened for their ability to inhibit fathead minnow aromatase in vitro. Female fathead minnows were then exposed to 3 of those chemicals: letrozole, epoxiconazole, and imazalil in concentration-response (5 concentrations plus control) for 24 h. Consistent with AOP-based expectations, all 3 chemicals caused significant reductions in plasma E2 and hepatic VTG transcription. Characteristic compensatory upregulation of aromatase and follicle-stimulating hormone receptor (fshr) transcripts in the ovary were observed for letrozole but not for the other 2 compounds. Considering the overall patterns of concentration-response and temporal concordance among endpoints, data from the in vivo experiments strengthen confidence in the qualitative relationships outlined by the AOP. Quantitatively, the qAOP model provided predictions that fell within the standard error of measured data for letrozole but not for imazalil and epoxiconazole. However, the inclusion of measured plasma concentrations of the test chemicals as inputs improved model predictions, with all predictions falling within the range of measured values. Results highlight both the utility and limitations of the qAOP and its potential use in 21st century ecotoxicology. Environ Toxicol Chem 2021;40:1155-1170. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Characterizing the effects of titanium dioxide and silver nanoparticles released from painted surfaces due to weathering on zebrafish (Danio rerio)

Silver (nAg) and titanium dioxide nanoparticles (nTiO₂) are common engineered nanoparticles (ENPs) added into paint for their antimicrobial and whitening properties, respectively. Weathering of outdoor painted surfaces can release such ENPs, though little is known about the potential effects of released ENPs on aquatic species. The objective of this study was to characterize the toxicity of nAg and nTiO₂ released from painted panels using fish liver cells (CRL2643) and zebrafish embryos (OECD 236 embryotoxicity test). Cells and embryos were exposed to suspensions of pristine nAg or nTiO₂, panels (unpainted or painted with nAg or nTiO₂) or base paint, after sonication. Cell viability and gene expression were assessed using resazurin assay and qPCR, respectively, while embryo mortality and deformities were scored visually via microscopic examination. In the cell studies, both paint-released nanoparticles did not affect viability, but paint-released nAg resulted in differential expression of a few genes including gclc and ncf1. In embryos, paint-released nAg increased mortality and incidence of deformities, whereas paint-released nTiO₂ resulted in differential expression of several genes including gclc, ncf1, txnrd1, gpx1b, and cyp1c1 but without major phenotypic abnormalities. Comparing the two types of exposures, paint-released exposures affected both molecular (gene expression) and apical (embryotoxicity) endpoints, while pristine exposures affected the expression of some genes but had no apical effects. The differing effects of paint-released and pristine nanoparticle exposures suggest that further research is needed to further understand how paint coatings (and the products of their weathering and aging) may influence nanoparticle toxicity to aquatic organisms.

Approaches in metabolomics for regulatory toxicology applications

Innovative methodological approaches are needed to conduct human health and environmental risk assessments on a growing number of marketed chemicals. Metabolomics is progressively proving its value as an efficient strategy to perform toxicological evaluations of new and existing substances, and it will likely become a key tool to accelerate chemical risk assessments. However, additional guidance with widely accepted and harmonized procedures is needed before metabolomics can be routinely incorporated in decision-making for regulatory purposes. The aim of this review is to provide an overview of metabolomic strategies that have been successfully employed in toxicity assessment as well as the most promising workflows in a regulatory context. First, we provide a general view of the different steps of regulatory toxicology-oriented metabolomics. Emphasis is put on three key elements: robustness of experimental design, choice of analytical platform, and use of adapted data treatment tools. Then, examples in which metabolomics supported regulatory toxicology outputs in different scenarios are reviewed, including chemical grouping, elucidation of mechanisms of toxicity, and determination of points of departure. The overall intention is to provide insights into why and how to plan and conduct metabolomic studies for regulatory toxicology purposes.

Toward High-Throughput Fish Embryo Toxicity Tests in Aquatic Toxicology

Addressing the shift from classical animal testing to high-throughput in vitro and/or simplified in vivo proxy models has been defined as one of the upcoming challenges in aquatic toxicology. In this regard, the fish embryo toxicity test (FET) has gained significant popularity and wide standardization as one of the sensitive alternative approaches to acute fish toxicity tests in chemical risk assessment and water quality evaluation. Nevertheless, despite the growing regulatory acceptance, the actual manipulation, dispensing, and analysis of living fish embryos remains very labor intensive. Moreover, the FET is commonly performed in plastic multiwell plates under static or semistatic conditions, potentially inadequate for toxicity assessment of some organic, easily degradable or highly adsorptive toxicants. Recent technological advances in the field of mechatronics, fluidics and digital vision systems demonstrate promising future opportunities for automation of many analytical stages in embryo toxicity testing. In this review, we highlight emerging advances in fluidic and laboratory automation systems that can prospectively enable high-throughput FET testing (HT-FET) akin to pipelines commonly found in in vitro drug discovery pipelines. We also outline the existing challenges, barriers to future development and provide an outlook of ground-breaking fluidic technologies in embryo toxicity testing.

Pre-validation of a Calu-3 epithelium cytotoxicity assay for predicting acute inhalation toxicity of chemicals

Although in vivo inhalation toxicity tests have been widely conducted, the testing of many chemicals is limited for economic and ethical reasons. Therefore, we previously developed an in vitro acute inhalation toxicity test method. The goal of the present pre-validation study was to evaluate the transferability, reproducibility, and predictive capacity of this method. After confirming the transferability of the Calu-3 epithelium cytotoxicity assay, reproducibility was evaluated using 20 test substances at three independent institutions. Cytotoxicity data were analyzed using statistical methods, including the intra-class correlation coefficient and Bland-Altman plots for within- and between-laboratory reproducibility. The assay for the 20 test substances showed excellent agreement within and between laboratories. To evaluate the predictive capacity, 77 test substances were analyzed for acute inhalation toxicity. Accuracy was measured using a cutoff of 40%, and the relevance was analyzed as a receiver-operating characteristic (ROC) curve. An accuracy of 72.73% was obtained, and the area under the ROC curve was 0.77, indicating moderate performance. In this study, we found that the in vitro acute inhalation toxicity test method demonstrated good reliability and relevance for predicting the acute toxicity of inhalable chemicals. Hence, this assay has potential as an alternative test for screening acutely toxic inhalants.

Does the food processing contaminant acrylamide cause developmental neurotoxicity? A review and identification of knowledge gaps

There is a worldwide concern on adverse health effects of dietary exposure to acrylamide (AA) due to its presence in commonly consumed foods. AA is formed when carbohydrate rich foods containing asparagine and reducing sugars are prepared at high temperatures and low moisture conditions. Upon oral intake, AA is rapidly absorbed and distributed to all organs. AA is a known human neurotoxicant that can reach the developing foetus via placental transfer and breast milk. Although adverse neurodevelopmental effects have been observed after prenatal AA exposure in rodents, adverse effects of AA on the developing brain has so far not been studied in humans. However, epidemiological studies indicate that gestational exposure to AA impair foetal growth and AA exposure has been associated with reduced head circumference of the neonate. Thus, there is an urgent need for further research to elucidate whether pre- and perinatal AA exposure in humans might impair neurodevelopment and adversely affect neuronal function postnatally. Here, we review the literature with emphasis on the identification of critical knowledge gaps in relation to neurodevelopmental toxicity of AA and its mode of action and we suggest research strategies to close these gaps to better protect the unborn child.

Nanoparticle-induced inflammation and fibrosis in ex vivo murine precision-cut liver slices and effects of nanoparticle exposure conditions

Chronic exposure and accumulation of persistent nanomaterials by cells have led to safety concerns on potential long-term effects induced by nanoparticles, including chronic inflammation and fibrosis. With this in mind, we used murine precision-cut liver tissue slices to test potential induction of inflammation and onset of fibrosis upon 72 h exposure to different nanomaterials (0–200 µg/ml). Tissue slices were chosen as an advanced ex vivo 3D model to better resemble the complexity of the in vivo tissue environment, with a focus on the liver where most nanomaterials accumulate. Effects on the onset of fibrosis and inflammation were investigated, with particular care in optimizing nanoparticle exposure conditions to tissue. Thus, we compared the effects induced on slices exposed to nanoparticles in the presence of excess free proteins (in situ), or after corona isolation. Slices exposed to daily-refreshed nanoparticle dispersions were used to test additional effects due to ageing of the dispersions. Exposure to amino-modified polystyrene nanoparticles in serum-free conditions led to strong inflammation, with stronger effects with daily-refreshed dispersions. Instead, no inflammation was observed when slices were exposed to the same nanoparticles in medium supplemented with serum to allow corona formation. Similarly, no clear signs of inflammation nor of onset of fibrosis were detected after exposure to silica, titania or carboxylated polystyrene in all conditions tested. Overall, these results show that liver slices can be used to test nanoparticle-induced inflammation in real tissue, and that the exposure conditions and ageing of the dispersions can strongly affect tissue responses to nanoparticles.

Evaluation of an in vitro assay to screen for the immunotoxic potential of chemicals to fish

A wide variety of environmental contaminants has been shown to disrupt immune functions of fish and may compromise their defense capability against pathogens. Immunotoxic effects, however, are rarely considered in ecotoxicological testing strategies. The aim of this study was to systematically evaluate the suitability of an in vitro immuno-assay using selected fish immune parameters to screen for chemicals with known immunotoxic potential and to differentiate them from non-immunotoxicants. Non-stimulated and lipopolysaccharide-stimulated head kidney leukocytes of rainbow trout (Oncorhynchus mykiss) were exposed for 3 h or 19 h to chemicals with different modes of action. As immune parameters, phagocytosis activity, oxidative burst activity and cytokine transcription (IL-1β, TNFα, IL-10) were examined, accompanied by in silico modelling. The immunotoxicants dexamethasone, benzo(a)pyrene, ethinylestradiol and bisphenol A significantly altered the immune parameters at non-cytotoxic concentrations whereas diclofenac had only weak effects. However, the two baseline chemicals with no known immunotoxic potential, butanol and ethylene glycol, caused significant effects, too. From our results it appears that the in vitro fish leukocyte assay as performed in the present study has only a limited capacity for discriminating between immunotoxicants and non-immunotoxicants.

Developmental biology meets toxicology: contributing reproductive mechanisms to build adverse outcome pathways

An adverse outcome pathway (AOP) is a simplified description of the sequence of mechanistic events that lead to a particular toxicological effect, from initial trigger to adverse outcome. Although designed to inform regulatory risk assessors, the AOP framework also provides a platform for innovative collaborations between experts from relevant research fields and the regulatory community. The underpinning for any AOP is basic knowledge about molecular and developmental processes; such knowledge can only be attained by solid bioscientific research. Starting with this fundamental knowledge, the objective is to devise novel testing strategies that focus on key events in a causative pathway. It is anticipated that such a knowledge-based approach will ultimately alleviate many of the burdens associated with classical chemical testing strategies that typically involve large-scale animal toxicity regimens. This hails from the notion that a solid understanding of the underlying mechanisms will allow the development and use of alternative test methods, including both in vitro and in silico approaches. This review is specifically targeted at professionals working in bioscientific fields, such as developmental and reproductive biology, and aims to (i) inform on the existence of the AOP framework and (ii) encourage new cross-disciplinary collaborations. It is hoped that fundamental biological knowledge can thus be better exploited for applied purposes: firstly, an improved understanding of how our perpetual exposure to environmental chemicals is causing human reproductive disease and, secondly, new approaches to screen for harmful chemicals more efficiently. This is not an instructional manual on how to create AOPs; rather, we discuss how to harness fundamental knowledge from the biosciences to assist regulatory toxicologists in their efforts to protect humans against chemicals that harm human reproductive development and function.