Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays

Gene-environment interactions within a precision environmental health framework

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

High-Throughput Screening to Advance In Vitro Toxicology: Accomplishments, Challenges, and Future Directions

Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.

Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting

Quantitative risk assessments of chemicals are routinely performed using in vivo data from rodents; however, there is growing recognition that non-animal approaches can be human-relevant alternatives. There is an urgent need to build confidence in non-animal alternatives given the international support to reduce the use of animals in toxicity testing where possible. In order for scientists and risk assessors to prepare for this paradigm shift in toxicity assessment, standardization and consensus on in vitro testing strategies and data interpretation will need to be established. To address this issue, an Expert Working Group (EWG) of the 8th International Workshop on Genotoxicity Testing (IWGT) evaluated the utility of quantitative in vitro genotoxicity concentration-response data for risk assessment. The EWG first evaluated available in vitro methodologies and then examined the variability and maximal response of in vitro tests to estimate biologically relevant values for the critical effect sizes considered adverse or unacceptable. Next, the EWG reviewed the approaches and computational models employed to provide human-relevant dose context to in vitro data. Lastly, the EWG evaluated risk assessment applications for which in vitro data are ready for use and applications where further work is required. The EWG concluded that in vitro genotoxicity concentration-response data can be interpreted in a risk assessment context. However, prior to routine use in regulatory settings, further research will be required to address the remaining uncertainties and limitations.

Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes

In silico (quantitative) structure-activity relationship modeling is an approach that provides a fast and cost-effective alternative to assess the genotoxic potential of chemicals. However, one of the limiting factors for model development is the availability of consolidated experimental datasets. In the present study, we collected experimental data on micronuclei in vitro and in vivo, utilizing databases and conducting a PubMed search, aided by text mining using the BioBERT large language model. Chemotype enrichment analysis on the updated datasets was performed to identify enriched substructures. Additionally, chemotypes common for both endpoints were found. Five machine learning models in combination with molecular descriptors, twelve fingerprints and two data balancing techniques were applied to construct individual models. The best-performing individual models were selected for the ensemble construction. The curated final dataset consists of 981 chemicals for micronuclei in vitro and 1309 for mouse micronuclei in vivo, respectively. Out of 18 chemotypes enriched in micronuclei in vitro, only 7 were found to be relevant for in vivo prediction. The ensemble model exhibited high accuracy and sensitivity when applied to an external test set of in vitro data. A good balanced predictive performance was also achieved for the micronucleus in vivo endpoint.

A pesticide and iPSC dopaminergic neuron screen identifies and classifies Parkinson-relevant pesticides

Parkinson's disease (PD) is a complex neurodegenerative disease with etiology rooted in genetic vulnerability and environmental factors. Here we combine quantitative epidemiologic study of pesticide exposures and PD with toxicity screening in dopaminergic neurons derived from PD patient induced pluripotent stem cells (iPSCs) to identify Parkinson's-relevant pesticides. Agricultural records enable investigation of 288 specific pesticides and PD risk in a comprehensive, pesticide-wide association study. We associate long-term exposure to 53 pesticides with PD and identify co-exposure profiles. We then employ a live-cell imaging screening paradigm exposing dopaminergic neurons to 39 PD-associated pesticides. We find that 10 pesticides are directly toxic to these neurons. Further, we analyze pesticides typically used in combinations in cotton farming, demonstrating that co-exposures result in greater toxicity than any single pesticide. We find trifluralin is a driver of toxicity to dopaminergic neurons and leads to mitochondrial dysfunction. Our paradigm may prove useful to mechanistically dissect pesticide exposures implicated in PD risk and guide agricultural policy.

Non-sugar sweeteners and cancer: Toxicological and epidemiological evidence

Several toxicological and epidemiological studies were published during the last five decades on non-sugar sweeteners (NSS) and cancer. Despite the large amount of research, the issue still continues to be of interest. In this review, we provided a comprehensive quantitative review of the toxicological and epidemiological evidence on the possible relation between NSS and cancer. The toxicological section includes the evaluation of genotoxicity and carcinogenicity data for acesulfame K, advantame, aspartame, cyclamates, saccharin, steviol glycosides and sucralose. The epidemiological section includes the results of a systematic search of cohort and case-control studies. The majority of the 22 cohort studies and 46 case-control studies showed no associations. Some risks for bladder, pancreas and hematopoietic cancers found in a few studies were not confirmed in other studies. Based on the review of both the experimental data on genotoxicity or carcinogenicity of the specific NSS evaluated, and the epidemiological studies it can be concluded that there is no evidence of cancer risk associated to NSS consumption.

Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application

Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA’s ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280–286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration–response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.

Repurposing drugs as COVID-19 therapies: a toxicity evaluation

Drug repurposing is an appealing method to address the Coronavirus 2019 (COVID-19) pandemic because of the low cost and efficiency. We analyzed our in-house database of approved drug screens and compared their activity profiles with results from a severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) cytopathic effect (CPE) assay. The activity profiles of the human ether-à-go-go-related gene (hERG), phospholipidosis (PLD), and many cytotoxicity screens were found significantly correlated with anti-SARS-CoV-2 activity. hERG inhibition is a nonspecific off-target effect that has contributed to promiscuous drug interactions, whereas drug-induced PLD is an undesirable effect linked to hERG blockers. Thus, this study identifies preferred drug candidates as well as chemical structures that should be avoided because of their potential to induce toxicity. Lastly, we highlight the hERG liability of anti-SARS-CoV-2 drugs currently enrolled in clinical trials.

The expression of Phase II drug-metabolizing enzymes in human B-lymphoblastoid TK6 cells

In vitro genotoxicity testing plays an important role in chemical risk assessment. The human B-lymphoblastoid cell line TK6 is widely used as a standard cell line for regulatory safety evaluations. Like many other mammalian cell lines, TK6 cells have limited metabolic capacity; therefore, usually require a source of exogenous metabolic activation for use in genotoxicity testing. Previously, we developed a set of TK6-derived cell lines that individually express one of fourteen cytochrome P450s (CYPs). In the present study, we surveyed a panel of major Phase II drug-metabolizing enzymes to characterize their baseline expression in TK6 cells. These results may serve as a reference enzymatic profile of this commonly used cell line.

Implementing in vitro bioactivity data to modernize priority setting of chemical inventories

Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioac­tivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioac­tivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.

Overall lack of genotoxic activity among five common low- and no-calorie sweeteners: A contemporary review of the collective evidence

Low- and no-calorie sweeteners (LNCS) are food additives that have been widely consumed for many decades. Their safety has been well established by authoritative bodies globally and is re-evaluated periodically. The objective herein was to survey and summarize the genotoxicity potential of five commonly utilized LNCS: acesulfame potassium (Ace-K), aspartame, saccharin, steviol glycosides and sucralose. Data from peer-reviewed literature and the ToxCast/Tox21 database were evaluated and integrated with the most recent weight-of-evidence evaluations from authoritative sources. Emphasis was placed on assays most frequently considered for hazard identification and risk assessment: mutation, clastogenicity and/or aneugenicity, and indirect DNA damage, such as changes in DNA repair mechanisms or gene expression data. These five sweeteners have been collectively evaluated in hundreds of in vivo or in vitro studies that employ numerous testing models, many of which have been conducted according to specific testing guidelines. The weight-of-evidence demonstrates overall negative findings across assay types for each sweetener when considering the totality of study design, reliability and reporting quality, as well as the lack of carcinogenic responses (or lack of responses relevant to humans) in animal cancer bioassays as well as observational studies in humans. This conclusion is consistent with the opinions of authoritative sources that have consistently determined that these sweeteners lack mutagenic and genotoxic potential.

Evidence-based meta-analysis of the genotoxicity induced by microplastics in aquatic organisms at environmentally relevant concentrations

Microplastics (MPs) attract global concern due to their ubiquitous existence in aquatic environments. However, the genotoxic effect of MPs on aquatic organisms in the natural environment remains controversial. Therefore, this meta-analysis was conducted by recompiling 44 individual studies from 12 publications to determine whether MPs could induce genotoxicity in aquatic organisms at environmentally relevant concentrations (≤1 mg/L, median = 0.5 mg/L). Multiple genotoxic endpoints were involved, including the percentage of DNA in tail (TDNA%), tail length (TL), olive tail moment (OTM), and the number of micronuclei (NM), and their increases represented the biologically adverse effects (i.e. genotoxicity). The results showed that all included endpoints tended to increase after exposure to MPs, among which TDNA%, TL and NM were significantly increased by 20%, 32% and 81% compared with the control group, respectively. The overall estimate of all endpoints in the MPs-treated groups was remarkably increased by 24%, with high statistical power and no obvious publication bias, suggesting the evident genotoxicity caused by MPs. In addition, the magnitudes of MPs-induced genotoxicity were independent of selected endpoint, MP composition, morphology, exposure concentration and duration, but closely correlated with particle size, living habitat and tested species. Overall, this work provided a reference for the health risk assessment of MPs in the natural environment, contributing to our understanding the action mode of MPs at environmentally relevant concentrations.

Transcriptomic analyses of livers from mice exposed to 1,4-dioxane for up to 90 days to assess potential mode(s) of action underlying liver tumor development

1,4-Dioxane is a volatile organic compound with industrial and commercial applications as a solvent and in the manufacture of other chemicals. 1,4-Dioxane has been demonstrated to induce liver tumors in chronic rodent bioassays conducted at very high doses. The available evidence for 1,4-dioxane-induced liver tumors in rodents aligns with a threshold-dependent mode of action (MOA), with the underlying mechanism being less clear in the mouse than in rats. To gain a better understanding of the underlying molecular mechanisms related to liver tumor development in mice orally exposed to 1,4-dioxane, transcriptomics analysis was conducted on liver tissue collected from a 90-day drinking water study in female B6D2F₁/Crl mice (Lafranconi et al., 2020). Using tissue samples from female mice exposed to 1,4-dioxane in the drinking water at concentrations of 0, 40, 200, 600, 2,000 or 6,000 ppm for 7, 28, and 90 days, transcriptomic analyses demonstrate minimal treatment effects on global gene expression at concentrations below 600 ppm. At higher concentrations, genes involved in phase II metabolism and mitotic cell cycle checkpoints were significantly upregulated. There was an overall lack of enrichment of genes related to DNA damage response. The increase in mitotic signaling is most prevalent in the livers of mice exposed to 1,4-dioxane at the highest concentrations for 90 days. This finding aligns with phenotypic changes reported by Lafranconi et al. (2020) after 90-days of exposure to 6,000 ppm 1,4-dioxane in the same tissues. The transcriptomics analysis further supports overarching study findings demonstrating a non-mutagenic, threshold-based, mitogenic MOA for 1,4-dioxane-induced liver tumors.

A history of the roles of cytochrome P450 enzymes in the toxicity of drugs

The history of drug metabolism began in the 19th Century and developed slowly. In the mid-20th Century the relationship between drug metabolism and toxicity became appreciated, and the roles of cytochrome P450 (P450) enzymes began to be defined in the 1960s. Today we understand much about the metabolism of drugs and many aspects of safety assessment in the context of a relatively small number of human P450s. P450s affect drug toxicity mainly by either reducing exposure to the parent molecule or, in some cases, by converting the drug into a toxic entity. Some of the factors involved are enzyme induction, enzyme inhibition (both reversible and irreversible), and pharmacogenetics. Issues related to drug toxicity include drug-drug interactions, drug-food interactions, and the roles of chemical moieties of drug candidates in drug discovery and development. The maturation of the field of P450 and drug toxicity has been facilitated by advances in analytical chemistry, computational capability, biochemistry and enzymology, and molecular and cell biology. Problems still arise with P450s and drug toxicity in drug discovery and development, and in the pharmaceutical industry the interaction of scientists in medicinal chemistry, drug metabolism, and safety assessment is critical for success.

Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models

In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro methods together with other computational methods such as quantitative structure-activity relationship modeling and absorption, distribution, metabolism, and excretion calculations are being used. An overview of machine learning and its applications in predictive toxicology is presented here, including support vector machines (SVMs), random forest (RF) and decision trees (DTs), neural networks, regression models, naïve Bayes, k-nearest neighbors, and ensemble learning. The recent successes of these machine learning methods in predictive toxicology are summarized, and a comparison of some models used in predictive toxicology is presented. In predictive toxicology, SVMs, RF, and DTs are the dominant machine learning methods due to the characteristics of the data available. Lastly, this review describes the current challenges facing the use of machine learning in predictive toxicology and offers insights into the possible areas of improvement in the field.

Evaluation of pyrrolizidine alkaloid-induced genotoxicity using metabolically competent TK6 cell lines

Pyrrolizidine alkaloid (PA)-containing plants are among the most common poisonous plants affecting humans, livestock, and wildlife worldwide. A large number of PAs are known to induce genetic damage after metabolic activation. In the present study, using a battery of fourteen newly developed TK6 cell lines, each expressing a single human cytochrome P450 (CYP1A1, 1A2, 1B1, 2A6, 2B6, 2C8, 2C18, 2C9, 2C19, 2D6, 2E1, 3A4, 3A5, and 3A7), we identified specific CYPs responsible for bioactivating three PAs - lasiocarpine, riddelliine, and senkirkine. Among the fourteen cell lines, cells expressing CYP3A4 showed significant increases in PA-induced cytotoxicity, evidenced by decreased ATP production and cell viability, and increased caspase 3/7 activities. LC-MS/MS analysis revealed the formation of 1-hydroxymethyl-7-hydroxy-6,7-dihydropyrrolizine (DHP), the main reactive metabolite of PAs, in CYP3A4-expressing TK6 cells. DHP was also detected in CYP3A5- and 3A7-expressing cells after PA exposure, but to a much lesser extent. Subsequently, using a high-throughput micronucleus assay, we demonstrated that PAs induced concentration-dependent increases in micronuclei and G2/M phase cell cycle arrest in three CYP3A variant-expressing TK6 cell lines. Using Western blotting, we observed that PA-induced apoptosis, cell cycle changes, and DNA damage were primarily mediated by CYP3A4. Benchmark dose (BMD) modeling demonstrated that lasiocarpine, of the three PAs, was the most potent inducer of micronuclei, with a BMD₁₀₀ of 0.036 μM. These results indicate that our TK6 cell system holds promise for genotoxicity screening of compounds requiring metabolic activation, identifying specific CYPs involved in bioactivation, and discriminating the genotoxic compounds that have different chemical structures.

In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS

Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is important for health hazard identification. In this study, alternative methods were used as prioritization tools to study the genotoxic mode of action (MoA) of 150 flavor compounds. In particular, clastogen-sensitive (γH2AX and p53) and aneugen-sensitive (p-H3 and polyploidy) biomarkers of DNA damage in human TK6 cells were aggregated through a supervised three-pronged ensemble machine learning prediction model to prioritize chemicals based on genotoxicity. In addition, in silico quantitative structure-activity relationship (QSAR) models were used to predict genotoxicity and carcinogenic potential. The in vitro assay identified 25 flavors as positive for genotoxicity: 15 clastogenic, eight aneugenic and two with a mixed MoA (clastogenic and aneugenic). Twenty-three of these 25 flavors predicted to induce DNA damage in vitro are documented in public literature to be in e-liquid or in the aerosols produced by ENDS products with youth-appealing flavors and names. QSAR models predicted 46 (31%) of 150 compounds having at least one positive call for mutagenicity, clastogenicity or rodent carcinogenicity, 49 (33%) compounds were predicted negative for all three endpoints, and remaining compounds had no prediction call. The parallel use of these predictive technologies to elucidate MoAs for potential genetic damage, hold utility as a screening strategy. This study is the first high-content and high-throughput genotoxicity screening study with an emphasis on flavors in ENDS products.

The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.

Enhancing the sensitivity of the thymidine kinase assay by using DNA repair-deficient human TK6 cells

The OECD guidelines define the bioassays of identifying mutagenic chemicals, including the thymidine kinase (TK) assay, which specifically detects the mutations that inactivate the TK gene in the human TK6 lymphoid line. However, the sensitivity of this assay is limited because it detects mutations occurring only in the TK gene but not any other genes. Moreover, the limited sensitivity of the conventional TK assay is caused by the usage of DNA repair-proficient wild-type cells, which are capable of accurately repairing DNA damage induced by chemicals. Mutagenic chemicals produce a variety of DNA lesions, including base lesions, sugar damage, crosslinks, and strand breaks. Base damage causes point mutations and is repaired by the base excision repair (BER) and nucleotide excision repair (NER) pathways. To increase the sensitivity of TK assay, we simultaneously disrupted two genes encoding XRCC1, an important BER factor, and XPA, which is essential for NER, generating XRCC1 ^-/- /XPA ^-/- cells from TK6 cells. We measured the mutation frequency induced by four typical mutagenic agents, methyl methane sulfonate (MMS), cis-diamminedichloro-platinum(II) (cisplatin, CDDP), mitomycin-C (MMC), and cyclophosphamide (CP) by the conventional TK assay using wild-type TK6 cells and also by the TK assay using XRCC1 ^-/- /XPA ^-/- cells. The usage of XRCC1 ^-/- /XPA ^-/- cells increased the sensitivity of detecting the mutagenicity by 8.6 times for MMC, 8.5 times for CDDP, and 2.6 times for MMS in comparison with the conventional TK assay. In conclusion, the usage of XRCC1 ^-/- /XPA ^-/- cells will significantly improve TK assay.

Development and Application of TK6-derived Cells Expressing Human Cytochrome P450s for Genotoxicity Testing

Metabolism plays a key role in chemical genotoxicity; however, most mammalian cells used for in vitro genotoxicity testing lack effective metabolizing enzymes. We recently developed a battery of TK6-derived cell lines that individually overexpress 1 of 8 cytochrome P450s (CYP1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, and 3A4) using a lentiviral expression system. The increased expression and metabolic function of each individual CYP in each established cell line were confirmed using real-time PCR, Western blotting, and mass spectrometry analysis; the parental TK6 cells and empty vector (EV) transduced cells had negligible CYP levels. Subsequently, we evaluated these cell lines using 2 prototypical polyaromatic hydrocarbon mutagens, 7,12-dimethylbenz[a]anthracene (DMBA) and benzo[a]pyrene (B[a]P), that require metabolic activation to exert their genotoxicity. DMBA-induced cytotoxicity, phosphorylation of histone H2A.X, and micronucleus formation were significantly increased in TK6 cells with CYP1A1, 1B1, 2B6, and 2C19 expression as compared with EV controls. B[a]P significantly increased cytotoxicity, DNA damage, and chromosomal damage in TK6 cells overexpressing CYP1A1 and 1B1 when compared with EV controls. B[a]P also induced micronucleus formation in TK6 cells expressing CYP1A2. These results suggest that our CYP-expressing TK6 cell system can be used to detect the genotoxicity of compounds requiring metabolic transformation.

EURL ECVAM Genotoxicity and Carcinogenicity Database of Substances Eliciting Negative Results in the Ames Test: Construction of the Database

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EURL ECVAM Consolidated Genotoxicity and Carcinogenicity Database extended.

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Negative Ames test results were compiled and reviewed.

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A database of Ames negative results was constructed.

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Database chemical space characterization was conducted.

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OFG representation of carcinogens and non-carcinogens was characterised.

The bacterial reverse mutation test (Ames test) is the most commonly used genotoxicity test; it is a primary component of the chemical safety assessment data required by regulatory agencies worldwide. Within the current accepted in vitro genotoxicity test battery, it is considered capable of revealing DNA reactivity, and identifying substances that can produce gene mutations via different mechanisms. The previously published consolidated EURL ECVAM Genotoxicity and Carcinogenicity Database, which includes substances that elicited a positive response in the Ames test, constitutes a collection of data that serves as a reference for a number of regulatory activities in the area of genotoxicity testing. Consequently, we considered it important to expand the database to include substances that fail to elicit a positive response in the Ames test, i.e., Ames negative substances. Here, we describe a curated collection of 211 Ames negative substances, with a summary of complementary data available for other genotoxicity endpoints in vitro and in vivo, plus available carcinogenicity data. A descriptive analysis of the data is presented. This includes a representation of the chemical space formed by the Ames-negative database with respect to other substances (e.g. REACH registered substances, approved drugs, pesticides, etc.) and a description of the organic functional groups found in the database. We also provide some suggestions on further analyses that could be made.

3Rs-friendly approach to exogenous metabolic activation that supports high-throughput genetic toxicology testing

MultiFlow® DNA Damage-p53, γH2AX, Phospho-Histone H3 is a miniaturized, flow cytometry-based assay that provides genotoxic mode of action information by distinguishing clastogens, aneugens, and nongenotoxicants. Work to date has focused on the p53-competent human cell line TK6. While mammalian cell genotoxicity assays typically supply exogenous metabolic activation in the form of concentrated rat liver S9, this is a less-than-ideal approach for several reasons, including 3Rs considerations. Here, we describe our experiences with low concentration S9 and saturating co-factors which were allowed to remain in contact with cells and test chemicals for 24 continuous hours. We exposed TK6 cells in 96-well plates to each of 15 reference chemicals over a range of concentrations, both in the presence and absence of 0.25% v/v phenobarbital/β-naphthoflavone-induced rat liver S9. After 4 and 24 hr of treatment cell aliquots were added to wells of a microtiter plate containing the working detergent/stain/antibody cocktail. After a brief incubation robotic sampling was employed for walk-away flow cytometric data acquisition. PROAST benchmark dose (BMD) modeling was used to characterize the resulting dose-response curves. For each of the 8 reference pro-genotoxicants studied, relative nuclei count, γH2AX, and/or p53 biomarker BMD values were order(s) of magnitude lower for 0.25% S9 conditions compared to 0% S9. Conversely, several of the direct-acting reference chemicals exhibited appreciably lower cytotoxicity and/or genotoxicity BMD values in the presence of S9 (eg, resorcinol). These results prove the efficacy of the low concentration S9 system, and indicate that an efficient and highly scalable multiplexed assay can effectively identify chemicals that require bioactivation to exert their genotoxic effects.