Genetic toxicology in the 21st century: reflections and future directions

Revisiting the approaches to DNA damage detection in genetic toxicology: insights and regulatory implications

Genetic toxicology is crucial for evaluating the potential risks of chemicals and drugs to human health and the environment. The emergence of high-throughput technologies has transformed this field, providing more efficient, cost-effective, and ethically sound methods for genotoxicity testing. It utilizes advanced screening techniques, including automated in vitro assays and computational models to rapidly assess the genotoxic potential of thousands of compounds simultaneously. This review explores the transformation of traditional in vitro and in vivo methods into computational models for genotoxicity assessment. By leveraging advances in machine learning, artificial intelligence, and high-throughput screening, computational approaches are increasingly replacing conventional methods. Coupling conventional screening with artificial intelligence (AI) and machine learning (ML) models has significantly enhanced their predictive capabilities, enabling the identification of genotoxicity signatures tied to molecular structures and biological pathways. Regulatory agencies increasingly support such methodologies as humane alternatives to traditional animal models, provided they are validated and exhibit strong predictive power. Standardization efforts, including the establishment of common endpoints across testing approaches, are pivotal for enhancing comparability and fostering consensus in toxicological assessments. Initiatives like ToxCast exemplify the successful incorporation of HTS data into regulatory decision-making, demonstrating that well-interpreted in vitro results can align with in vivo outcomes. Innovations in testing methodologies, global data sharing, and real-time monitoring continue to refine the precision and personalization of risk assessments, promising a transformative impact on safety evaluations and regulatory frameworks.

Evaluating the Genotoxicity and Mutagenicity of Food Contaminants: Acrylamide, Penitrem A, and 3-Acetyldeoxynivalenol in Individual and Combined Exposure In Vitro

This study aimed to evaluate the genotoxic effects of food contaminants exposure in human neuroblastoma SH-SY5Y cells using the micronucleus (MN) assay and Ames test. Acrylamide (AA), penitrem A (PEN A), and 3-acetyldeoxynivalenol (3-ADON) were tested both individually and in combination. Since humans are likely to be exposed to these substances simultaneously through diet, it is crucial to investigate their combined effects of the compounds rather than just their individual toxicities. The results demonstrated significant increases in MN frequency for all individual treatments and in a dose-dependent manner for AA and 3-ADON. Combined treatments also resulted in higher MN frequencies, particularly for AA + 3-ADON and PEN A + 3-ADON respect to the control. However, the Ames test revealed no mutagenic potential for any of the individual or combined treatments, consistent with previous studies. These findings suggest that while food contaminants induce chromosomal damage (MN induction), they do not cause gene mutations. Nonetheless, the lack of single mutations activity does not exclude the potential health risks of combined mycotoxin exposure, especially given the observed genotoxicity due to the DNA damage through chromosomal aberrations. Future studies focused on the mechanism of action should investigate the combined effects of food contaminants in more detail to better assess their potential health risks.

Genotoxicity in Unconventional Mammalian Models of Wild, Urban, and Agricultural Ecosystems: A Systematic Review Under the One Health Approach

Background/Objectives: This systematic review evaluates unconventional mammalian models from wild, agricultural, and urban/domestic ecosystems for genotoxicity assessment under the One Health framework. Non-human primates (NHPs), cattle, and domestic dogs are analyzed as sentinel species due to their distinct environmental niches, unique human interactions, and species-specific traits. In conjunction with this, evidence is presented about the in vitro use of cells of these mammals for the genotoxicological evaluation of different chemical substances, such as veterinary drugs, environmental pollutants, and pesticides. The synthesis focuses on standardized genetic toxicology assays (e.g., chromosomal aberrations, micronucleus, comet assay) aligned with Organization for Economic Cooperation and Development (OECD) guidelines. Methods: A structured search of international literature identified studies employing OECD-compliant genotoxicity assays in NHPs, cattle, dogs, and others not listed in OECD. Data was categorized by species, assay type, chemical class evaluated, environmental context (wild, agricultural, urban), and merits of the papers. Results: NHPs, despite their phylogenetic proximity to humans, show limited genotoxicity data in contrast to biomedical research, which has been constrained by ethical concerns and fieldwork logistics. Cattle emerge as robust models in agricultural settings due to the abundance of studies on the genotoxic capacity of pesticides, veterinary drug, and environmental biomonitoring, with direct implications for food safety. Domestic dogs are recognized as powerful sentinels for human health due to shared exposomes, physiological similarities (e.g., shorter cancer latency), and reduced lifestyle confounders; however, genotoxicity studies in dogs remain sparse compared to chemical exposure monitoring or cancer research. Conclusions: This review advocates for expanded, integrated use of these models to address genotoxic threats across ecosystems, which would benefit both animal and human health. In the application of biomonitoring studies with sentinel animals, a critical gap persists: the frequent lack of integration between xenobiotic quantification in environmental and biological samples, along with genotoxicity biomarkers evaluation in sentinel populations, which hinders comprehensive environmental risk assessment.

Use of peptide nucleic acid probe to determine telomere dynamics in improving chromosome analysis in genetic toxicology studies

Genetic toxicology, strategically located at the intersection of genetics and toxicology, aims to demystify the complex interplay between exogenous agents and our genetic blueprint. Telomeres, the protective termini of chromosomes, play instrumental roles in cellular longevity and genetic stability. Traditionally karyotyping and fluorescence in situ hybridisation (FISH), have been indispensable tools for chromosomal analysis following exposure to genotoxic agents. However, their scope in discerning nuanced molecular dynamics is limited. Peptide Nucleic Acids (PNAs) are synthetic entities that embody characteristics of both proteins and nucleic acids and have emerged as potential game-changers. This perspective report comprehensively examines the vast potential of PNAs in genetic toxicology, with a specific emphasis on telomere research. PNAs' superior resolution and precision make them a favourable choice for genetic toxicological assessments. The integration of PNAs in contemporary analytical workflows heralds a promising evolution in genetic toxicology, potentially revolutionizing diagnostics, prognostics, and therapeutic avenues. In this timely review, we attempted to assess the limitations of current PNA-FISH methodology and recommend refinements.

Genotoxicity assessment: opportunities, challenges and perspectives for quantitative evaluations of dose-response data

Genotoxicity data are mainly interpreted in a qualitative way, which typically results in a binary classification of chemical entities. For more than a decade, there has been a discussion about the need for a paradigm shift in this regard. Here, we review current opportunities, challenges and perspectives for a more quantitative approach to genotoxicity assessment. Currently discussed opportunities mainly include the determination of a reference point (e.g., a benchmark dose) from genetic toxicity dose-response data, followed by calculation of a margin of exposure (MOE) or derivation of a health-based guidance value (HBGV). In addition to new opportunities, major challenges emerge with the quantitative interpretation of genotoxicity data. These are mainly rooted in the limited capability of standard in vivo genotoxicity testing methods to detect different types of genetic damage in multiple target tissues and the unknown quantitative relationships between measurable genotoxic effects and the probability of experiencing an adverse health outcome. In addition, with respect to DNA-reactive mutagens, the question arises whether the widely accepted assumption of a non-threshold dose-response relationship is at all compatible with the derivation of a HBGV. Therefore, at present, any quantitative genotoxicity assessment approach remains to be evaluated case-by-case. The quantitative interpretation of in vivo genotoxicity data for prioritization purposes, e.g., in connection with the MOE approach, could be seen as a promising opportunity for routine application. However, additional research is needed to assess whether it is possible to define a genotoxicity-derived MOE that can be considered indicative of a low level of concern. To further advance quantitative genotoxicity assessment, priority should be given to the development of new experimental methods to provide a deeper mechanistic understanding and a more comprehensive basis for the analysis of dose-response relationships.

In vitro toxicity assessment of haloacetamides via a toxicogenomics assay

It is important to study the stress effects and mechanisms of haloacetamide (HAcAm) disinfection byproducts to reveal their health hazards. In this context, toxicological g was applied to evaluate the effects of four HAcAms, revealing the status of gene expression on Escherichia coli in different stress response types (oxidative, protein, membrane, general, DNA). This study revealed that the main toxic action modes of these HAcAms were general and membrane stresses by high-resolution, real-time gene expression profiling combined with clustering analysis. The results of time-gene evaluation showed that the presence of chloroacetamide (CAcAm) and bromoacetamide (BAcAm) generated more reactive oxygen species, thus activating oxidative stress. Trichloroacetamide (tCAcAm) induced altered expression of glutathione marker genes and membrane stress-related genes, and iodoacetamide (IAcAm) caused severe DNA damage by damaging DNA strands and individual nucleotides mainly through damage to nucleic acids and bases. Furthermore, quantitative structure-activity relationship (QSAR) modelling results indicated that the biological activities of HAcAms were related to their quantum chemical and topological properties.

In Vitro Transcriptome Analysis of Cobalt Boride Nanoparticles on Human Pulmonary Alveolar Cells

Nanobiotechnology influences many different areas, including the medical, food, energy, clothing, and cosmetics industries. Considering the wide usage of nanomaterials, it is necessary to investigate the toxicity potentials of specific nanosized molecules. Boron-containing nanoparticles (NPs) are attracting much interest from scientists due to their unique physicochemical properties. However, there is limited information concerning the toxicity of boron-containing NPs, including cobalt boride (Co₂B) NPs. Therefore, in this study, Co₂B NPs were characterized using X-ray crystallography (XRD), transmission electron microscope (TEM), scanning electron microscope (SEM), and energy-dispersive X-ray spectroscopy (EDX) techniques. Then, we performed 3-(4,5-dimethyl-thiazol-2-yl) 2,5-diphenyltetrazolium bromide (MTT), lactate dehydrogenase (LDH) release, and neutral red (NR) assays for assessing cell viability against Co₂B NP exposure on cultured human pulmonary alveolar epithelial cells (HPAEpiC). In addition, whole-genome microarray analysis was carried out to reveal the global gene expression differentiation of HPAEpiC cells after Co₂B NP application. The cell viability tests unveiled an IC50 value for Co₂B NPs of 310.353 mg/L. The results of our microarray analysis displayed 719 gene expression differentiations (FC ≥ 2) among the analyzed 40,000 genes. The performed visualization and integrated discovery (DAVID) analysis revealed that there were interactions between various gene pathways and administration of the NPs. Based on gene ontology biological processes analysis, we found that the P53 signaling pathway, cell cycle, and cancer-affecting genes were mostly affected by the Co₂B NPs. In conclusion, we suggested that Co₂B NPs would be a safe and effective nanomolecule for industrial applications, particularly for medical purposes.

Early Drug-Induced Liver Injury (DILI) Risk Screening: "Free", as good as it gets

For all the promise of and need for clinical drug-induced liver injury (DILI) risk screening systems, demonstrating the predictive value of these systems versus readily available physicochemical properties and inherent dosing information has not been thoroughly evaluated. Therefore, we utilized a systematic approach to evaluate the predictive value of in vitro safety assays including Bile Salt Export Pump (BSEP) transporter inhibition and cytotoxicity in HepG2 and transformed human liver epithelial (THLE) along with physicochemical properties. We also evaluated the predictive value of in vitro ADME assays including hepatic partition coefficient (Kp) and its unbound counterpart since they provide insight on hepatic accumulation potential. The datasets comprised of 569 marketed drugs with FDA DILIrank annotation (Most vs Less/None), dose and physicochemical information, 384 drugs with Kp and plasma protein binding data, and 279 drugs with safety assay data. For each dataset and combination of input parameters, we developed random forest machine learning models and measured model performance using the receiver operator characteristic area-under-the-curve (ROC AUC). The median ROC AUC across the various data and parameters sets ranged from 0.67 to 0.77 with little evidence of additive predictivity when including safety or ADME assay data. Subsequent machine learning models consistently demonstrated daily dose, fraction sp3 or ionization, and cLogP/D inputs produced the best, simplest model for predicting clinical DILI risk with an ROC AUC of 0.75. This systematic framework should be used for future assay predictive value assessments and highlights the need for continued improvements to clinical DILI risk annotation.

HepG2 spheroids as a biosensor-like cell-based system for (geno)toxicity assessment

3D spheroids developed from HepG2 cells were used as a biosensor-like system for the detection of (geno)toxic effects induced by chemicals. Benzo(a)pyrene (B(a)P) and amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) with well-known mechanisms of action were used for system validation. HepG2 spheroids grown for 3 days were exposed to BaP and PhIP for 24 and 72 h. The growth and viability of spheroids were monitored by planimetry and Live/Dead staining of cells. Multi-parametric flow cytometric analysis was applied for simultaneous detection of specific end-effects including cell cycle analysis (Hoechst staining), cell proliferation (KI67 marker), and DNA double-strand breaks (ℽH2AX) induced by genotoxic compounds. Depending on the exposure concentration/time, BaP reduced spheroid growth, affected cell proliferation by arresting cells in S and G2 phase and induced DNA double-strand breaks (DSB). Simultaneous staining of ℽH2AX formation and cell cycle analysis revealed that after BaP (10 μM; 24 h) exposure 60% of cells in G0/G1 phase had DNA DSB, while after 72 h only 20% of cells contained DSB indicating efficient repair of DNA lesions. PhIP did not influence the spheroid size whereas accumulation of cells in the G2 phase occurred after both treatment times. The evaluation of DNA damage revealed that at 200 μM PhIP 50% of cells in G0/G1 phase had DNA DSB, which after 72-h exposure dropped to 40%, showing lower repair capacity of PhIP-induced DSB compared to BaP-induced. The developed approach using simultaneous detection of several parameters provides mechanistic data and thus contributes to more reliable genotoxicity assessment of chemicals as a high-content screening tool.

Machine Learning for In Silico ADMET Prediction

ADMET (absorption, distribution, metabolism, excretion, and toxicity) describes a drug molecule's pharmacokinetics and pharmacodynamics properties. ADMET profile of a bioactive compound can impact its efficacy and safety. Moreover, efficacy and safety are considered some of the major causes of clinical attrition in the development of new chemical entities. In past decades, various machine learning or quantitative structure-activity relationship (QSAR) methods have been successfully integrated in the modeling of ADMET. Recent advances have been made in the collection of data and the development of various in silico methods to assess and predict ADMET of bioactive compounds in the early stages of drug discovery and development process.

GFP-fused yeast cells as whole-cell biosensors for genotoxicity evaluation of nitrosamines

Nitrosamine compounds, represented by N-nitrosodimethylamine, are regarded as potentially genotoxic impurities (PGIs) due to their hazard warning structure, which has attracted great attention of pharmaceutical companies and regulatory authorities. At present, great research gaps exist in genotoxicity assessment and carcinogenicity comparison of nitrosamine compounds. In this work, a collection of GFP-fused yeast cells representing DNA damage repair pathways were used to evaluate the genotoxicity of eight nitrosamine compounds (10^-6-10⁵ μg/mL). The high-resolution expression profiles of GFP-fused protein revealed the details of the DNA damage repair of nitrosamines. Studies have shown that nitrosamine compounds can cause extensive DNA damage and activate multiple repair pathways. The evaluation criteria based on the total expression level of protein show a good correlation with the mammalian carcinogenicity data TD₅₀, and the yeast cell collection can be used as a potential reliable criterion for evaluating the carcinogenicity of compounds. The assay based on DNA damage pathway integration has high sensitivity and can be used as a supplementary method for the evaluation of trace PGIs in actual production. KEY POINTS: • The genotoxicity mechanism of nitrosamines was systematically studied. • The influence of compound structure on the efficacy of genotoxicity was explored. • GFP-fused yeast cells have the potential to evaluate impurities in production.

The Challenges of 21st Century Neurotoxicology: The Case of Neurotoxicology Applied to Nanomaterials

After a short background discussing engineered nanomaterials (ENMs) and their physicochemical properties and applications, the present perspective paper highlights the main specific points that need to be considered when examining the question of neurotoxicity of nanomaterials. It underlines the necessity to integrate parameters, specific tools, and tests from multiple sources that make neurotoxicology when applied to nanomaterials particularly complex. Bringing together the knowledge of multiple disciplines e.g., nanotoxicology to neurotoxicology, is necessary to build integrated neurotoxicology for the third decade of the 21st Century. This article focuses on the greatest challenges and opportunities offered by this specific field. It highlights the scientific, methodological, political, regulatory, and educational issues. Scientific and methodological challenges include the determination of ENMs physicochemical parameters, the lack of information about protein corona modes of action, target organs, and cells and dose– response functions of ENMs. The need of standardization of data collection and harmonization of dedicated neurotoxicological protocols are also addressed. This article highlights how to address those challenges through innovative methods and tools, and our work also ventures to sketch the first list of substances that should be urgently prioritized for human modern neurotoxicology. Finally, political support with dedicated funding at the national and international levels must also be used to engage the communities concerned to set up dedicated educational program on this novel field.

High-dose exposure to synthetic chemicals, hormones, or homeostatic substances in experimental animals or humans can induce artefactual pathology

The maximum tolerated dose (MTD) provides the highest probability of a positive result in a toxicology bioassay. The assumption underlying the MTD in animal bioassays is that adverse effects at very high doses are qualitatively the same as those occurring at low doses. In contrast with the MTD, the optimal top dose in a toxicology animal study is the highest dose that does not produce a pathological end point that presents no risk at lower doses, for example, the dose below which cytotoxicity induces tumors in the absence of genotoxicity or other carcinogenic mechanisms. Normal concentrations or biological activity levels of many substances necessary for normal physiological function induce pathology when found at high levels. For example, the demonstration that ingestion of abnormally high levels of certain dietary fats can cause or exacerbate atherosclerosis in relevant animal models like rhesus macaques does not demonstrate that normal levels of these fats should be considered as toxic. Excessive estrogenic stimulation is associated with breast, ovarian, and endometrial cancers. This does not imply that normal age-appropriate levels of estrogen are toxic. Normal wound healing is associated with transforming growth factors beta 1 and 2. Excessive stimulation of fibroblasts by these growth factors results in hypertrophic scarring and keloid formation. An understanding of the mode of action of a test substance can facilitate the selection of dose levels much higher than those expected to be experienced by humans, but not beyond a dose level at which pathology is an experimental artefact of the high-dose level.

Genetic toxicology in silico protocol

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library

The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizing enzymes and transporters. Thus, identifying regulatory factors for CAR activation is important for understanding its mechanisms. Numerous studies conducted previously on CAR activation and its toxicity focused on in vivo or in vitro analyses, which are expensive, time consuming, and require many animals. We developed a computational model that predicts agonists for the CAR using the Toxicology in the 21st Century 10k library. Additionally, we evaluate the prediction performance of novel deep learning (DL)-based quantitative structure-activity relationship analysis called the DeepSnap-DL approach, which is a procedure of generating an omnidirectional snapshot portraying three-dimensional (3D) structures of chemical compounds. The CAR prediction model, which applies a 3D structure generator tool, called CORINA-generated and -optimized chemical structures, in the DeepSnap-DL demonstrated better performance than the existing methods using molecular descriptors. These results indicate that high performance in the prediction model using the DeepSnap-DL approach may be important to prepare suitable 3D chemical structures as input data and to enable the identification of modulators of the CAR.

In Silico Approaches in Predictive Genetic Toxicology

Genetic toxicology testing is a weight-of-evidence approach to identify and characterize chemical substances that can cause genetic modifications in somatic and/or germ cells. Prediction of genetic toxicology using computational tools is gaining more attention and preferred by regulatory authorities as an alternate safety assessment for in vivo or in vitro approaches. Due to the cost and time associated with experimental genetic toxicity tests, it is essential to develop more robust in silico methods to predict chemical genetic toxicity. A number of in silico genotoxicity predictive tools/models are developed based on the experimental data gathered over the years. These in silico tools are divided into statistical quantitative structure-activity relationships (QSAR)-based approaches and expert-based systems. This chapter covers the state of the art in silico toxicology approaches and standardized protocols, essential for conducting genetic toxicity predictions of chemicals. This chapter also highlights various parameters for the validation of the prediction results obtained from QSAR models.

The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives

The field of experimental toxicology is rapidly advancing by incorporating novel techniques and methods that provide a much more granular view into the mechanisms of potential adverse effects of chemical exposures on human health. The data from various in vitro assays and computational models are useful not only for increasing confidence in hazard and risk decisions, but also are enabling better, faster and cheaper assessment of a greater number of compounds, mixtures, and complex products. This is of special value to the field of green chemistry where design of new materials or alternative uses of existing ones is driven, at least in part, by considerations of safety. This article reviews the state of the science and decision-making in scenarios when little to no data may be available to draw conclusions about which choice in green chemistry is "safer." It is clear that there is no "one size fits all" solution and multiple data streams need to be weighed in making a decision. Moreover, the overall level of familiarity of the decision-makers and scientists alike with new assessment methodologies, their validity, value and limitations is evolving. Thus, while the "impact" of the new developments in toxicology on the field of green chemistry is great already, it is premature to conclude that the data from new assessment methodologies have been widely accepted yet.

The transformics assay: first steps for the development of an integrated approach to investigate the malignant cell transformation in vitro

The development of alternative methods to animal testing is a priority in the context of regulatory toxicology. Carcinogenesis is a field where the demand for alternative methods is particularly high. The standard rodent carcinogenicity bioassay requires a large use of animals, high costs, prolonged duration and shows several limitations, which can affect the comprehension of the human relevance of animal carcinogenesis. The cell transformation assay (CTA) has long been debated as a possible in vitro test to study carcinogenesis. This assay provides an easily detectable endpoint of oncotransformation, which can be used to anchor the exposure to the acquisition of the malignant phenotype. However, the current protocols do not provide information on either molecular key events supporting the carcinogenesis process, nor the mechanism of action of the test chemicals. In order to improve the use of this assay in the integrated testing strategy for carcinogenesis, we developed the transformics method, which combines the CTA and transcriptomics, to highlight the molecular steps leading to in vitro malignant transformation. We studied 3-methylcholanthrene (3-MCA), a genotoxic chemical able to induce in vitro cell transformation, at both transforming and subtransforming concentrations in BALB/c 3T3 cells and evaluated the gene modulation at critical steps of the experimental protocol. The results gave evidence for the potential key role of the immune system and the possible involvement of the aryl hydrocarbon receptor (AhR) pathway as the initial steps of the in vitro transformation process induced by 3-MCA, suggesting that the initiating events are related to non-genotoxic mechanisms.

Genotoxicity Assessment of Drinking Water Disinfection Byproducts by DNA Damage and Repair Pathway Profiling Analysis

Genotoxicity is considered a major concern for drinking water disinfection byproducts (DBPs). Of over 700 DBPs identified to date, only a small number has been assessed with limited information for DBP genotoxicity mechanism(s). In this study, we evaluated genotoxicity of 20 regulated and unregulated DBPs applying a quantitative toxicogenomics approach. We used GFP-fused yeast strains that examine protein expression profiling of 38 proteins indicative of all known DNA damage and repair pathways. The toxicogenomics assay detected genotoxicity potential of these DBPs that is consistent with conventional genotoxicity assays end points. Furthermore, the high-resolution, real-time pathway activation and protein expression profiling, in combination with clustering analysis, revealed molecular level details in the genotoxicity mechanisms among different DBPs and enabled classification of DBPs based on their distinct DNA damage effects and repair mechanisms. Oxidative DNA damage and base alkylation were confirmed to be the main molecular mechanisms of DBP genotoxicity. Initial exploration of QSAR modeling using moleular genotoxicity end points (PELI) suggested that genotoxicity of DBPs in this study was correlated with topological and quantum chemical descriptors. This study presents a toxicogenomics-based assay for fast and efficient mechanistic genotoxicity screening and assessment of a large number of DBPs. The results help to fill in the knowledge gap in the understanding of the molecular mechanisms of DBP genotoxicity.

The “false-positive” conundrum in the NTP 2-year rodent cancer study database

In 1990, Ames and Gold described a conundrum of “too many carcinogens” among chemicals tested in rodent bioassays. Their proposed nongenotoxic carcinogenic mechanism was amplification of the background mutation rate via cytotoxicity induced by high doses of the test chemicals, thereby leading to increases in reparative cellular proliferation rates. Recently, we have statistically and mechanistically analyzed the entire 594-study (470 final reports) NTP 2-year rodent cancer database to better understand the conundrum posed by Ames and Gold. Our analysis provides several lines of evidence that support the contention of Ames and Gold. First, across different routes of administration, relatively phylogenetically similar rats and mice are nonetheless discordant for the development of tumors at similar organ sites. Tumor site concordance across sex within species is higher than tumor site concordance across species. Second, many chemicals negative in the Ames test nonetheless induce tumors in either rats or mice. Third, 11 out of 58 chemicals tested by the inhalation route induce lung tumors in mice and not rats, are negative in the Ames test, and exhibit hyperplasia. In 2017, Tomasetti et al. provided evidence for the clinical relevance in humans of the Ames and Gold mechanism regarding amplification of the background mutation rate by demonstrating that the majority of human tumors result from accumulated mutations due to DNA replication errors.

Developing a genetic signature to predict drug response in ovarian cancer

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

Genotoxicity testing: Comparison of the γH2AX focus assay with the alkaline and neutral comet assays

Genotoxicity testing relies on the quantitative measurement of adverse effects, such as chromosome aberrations, micronuclei, and mutations, resulting from primary DNA damage. Ideally, assays will detect DNA damage and cellular responses with high sensitivity, reliability, and throughput. Several novel genotoxicity assays may fulfill these requirements, including the comet assay and the more recently developed γH2AX assay. Although they are thought to be specific for genotoxicants, a systematic comparison of the assays has not yet been undertaken. In the present study, we compare the γH2AX focus assay with the alkaline and neutral versions of the comet assay, as to their sensitivities and limitations for detection of genetic damage. We investigated the dose-response relationships of γH2AX foci and comet tail intensities at various times following treatment with four prototypical genotoxicants, methyl methanesulfonate (MMS), N-methyl-N'-nitro-N-nitrosoguanidine (MNNG), mitomycin C, and hydrogen peroxide (H₂O₂) and we tested whether there is a correlation between the endpoints, i.e., alkali-labile sites and DNA strand breaks on the one hand and the cell's response to DNA double-strand breaks and blocked replication forks on the other. Induction of γH2AX foci gave a linear dose response and all agents tested were positive in the assay. The increase in comet tail intensity was also a function of dose; however, mitomycin C was almost completely ineffective in the comet assay, and the doses needed to achieve a significant effect were somewhat higher for some treatments in the comet assay than in the γH2AX foci assay, which was confirmed by threshold analysis. There was high correlation between tail intensity and γH2AX foci for MMS and H₂O₂, less for MNNG, and none for mitomycin C. From this we infer that the γH2AX foci assay is more reliable, sensitive, and robust than the comet assay for detecting genotoxicant-induced DNA damage.

A high-fidelity method for genomic sequencing of single somatic cells reveals a very high mutational burden

Postzygotic mutations in somatic cells lead to genome mosaicism and can be the cause of cancer, possibly other human diseases and aging. Somatic mutations are difficult to detect in bulk tissue samples. Here, we review the available assays for measuring somatic mutations, with a focus on recent single-cell, whole genome sequencing methods. Impact statement Somatic mutations cause cancer, possibly other diseases and aging. Yet, very little is known about the frequency of such mutations in vivo, their distribution across the genome, and their possible functional consequences other than cancer. Even in cancer, we do not know the heterogeneity of mutations within a tumor and if seemingly normal cells in its surroundings already have elevated mutation frequencies. Here, we review a new, whole genome amplification system that allows accurate quantification and characterization of single-cell mutational landscapes in human cells and tissues in relation to disease.

Development of an in vitro PIG-A gene mutation assay in human cells

Mutagens can be carcinogens, and traditionally, they have been identified in vitro using the Salmonella 'Ames' reverse mutation assay. However, prokaryotic DNA packaging, replication and repair systems are mechanistically very different to those in the humans we inevitably seek to protect. Therefore, for many years, mammalian cell line genotoxicity assays that can detect eukaryotic mutagens as well as clastogens and aneugens have been used. The apparent lack of specificity in these largely rodent systems, due partly to their mutant p53 status, has contributed to the use of animal studies to resolve data conflicts. Recently, silencing mutations at the PIG-A locus have been demonstrated to prevent glycophosphatidylinositol (GPI) anchor synthesis and consequentially result in loss of GPI-anchored proteins from the cell's extracellular surface. The successful exploitation of this mutant phenotype in animal studies has triggered interest in the development of an analogous in vitro PIG-A mutation screening assay. This article describes the development of a robust assay design using metabolically active human cells. The assay includes viability and cell membrane integrity assessment and conforms to the future ideas of the 21st-century toxicology testing.

Advancing toxicology research using in vivo high throughput toxicology with small fish models

Small freshwater fish models, especially zebrafish, offer advantages over traditional rodent models, including low maintenance and husbandry costs, high fecundity, genetic diversity, physiology similar to that of traditional biomedical models, and reduced animal welfare concerns. The Collaborative Workshop on Aquatic Models and 21st Century Toxicology was held at North Carolina State University on May 5-6, 2014, in Raleigh, North Carolina, USA. Participants discussed the ways in which small fish are being used as models to screen toxicants and understand mechanisms of toxicity. Workshop participants agreed that the lack of standardized protocols is an impediment to broader acceptance of these models, whereas development of standardized protocols, validation, and subsequent regulatory acceptance would facilitate greater usage. Given the advantages and increasing application of small fish models, there was widespread interest in follow-up workshops to review and discuss developments in their use. In this article, we summarize the recommendations formulated by workshop participants to enhance the utility of small fish species in toxicology studies, as well as many of the advances in the field of toxicology that resulted from using small fish species, including advances in developmental toxicology, cardiovascular toxicology, neurotoxicology, and immunotoxicology. We alsoreview many emerging issues that will benefit from using small fish species, especially zebrafish, and new technologies that will enable using these organisms to yield results unprecedented in their information content to better understand how toxicants affect development and health.

A Quantitative Toxicogenomics Assay for High-throughput and Mechanistic Genotoxicity Assessment and Screening of Environmental Pollutants

The ecological and health concern of mutagenicity and carcinogenicity potentially associated with an overwhelmingly large and ever-increasing number of chemicals demands for cost-effective and feasible method for genotoxicity screening and risk assessment. This study proposed a genotoxicity assay using GFP-tagged yeast reporter strains, covering 38 selected protein biomarkers indicative of all the seven known DNA damage repair pathways. The assay was applied to assess four model genotoxic chemicals, eight environmental pollutants and four negative controls across six concentrations. Quantitative molecular genotoxicity end points were derived based on dose response modeling of a newly developed integrated molecular effect quantifier, Protein Effect Level Index (PELI). The molecular genotoxicity end points were consistent with multiple conventional in vitro genotoxicity assays, as well as with in vivo carcinogenicity assay results. Further more, the proposed genotoxicity end point PELI values quantitatively correlated with both comet assay in human cell and carcinogenicity potency assay in mice, providing promising evidence for linking the molecular disturbance measurements to adverse outcomes at a biological relevant level. In addition, the high-resolution DNA damaging repair pathway alternated protein expression profiles allowed for chemical clustering and classification. This toxicogenomics-based assay presents a promising alternative for fast, efficient and mechanistic genotoxicity screening and assessment of drugs, foods, and environmental contaminants.

Incorporation of metabolic activation potentiates cyclophosphamide-induced DNA damage response in isogenic DT40 mutant cells

Elucidating the DNA repair pathways that are activated in the presence of genotoxic agents is critical to understand their modes of action. Although the DT40 cell-based DNA damage response (DDR) assay provides rapid and sensitive results, the assay cannot be used on genotoxic compounds that require metabolic activation to be reactive. Here, we applied the metabolic activation system to a DDR and micronucleus (MN) assays in DT40 cells. Cyclophosphamide (CP), a well-known cross-linking agent requiring metabolic activation, was preincubated with liver S9 fractions. When DT40 cells and mutant cells were exposed to the preactivated CP, CP caused increased cytotoxicity in FANC-, RAD9-, REV3- and RAD18-mutant cells compared to isogenic wild-type cells. We then performed a MN assay on DT40 cells treated with preactivated CP. An increase in the MN was observed in REV3- and FANC-mutant cells at lower concentrations of activated CP than in the parental DT40 cells. These results demonstrated that the incorporation of metabolic preactivation system using S9 fractions significantly potentiates DDR caused by CP in DT40 cells and their mutants. In addition, our data suggest that the metabolic preactivation system for DDR and MN assays has a potential to increase the relevance of this assay to screening various compounds for potential genotoxicity.

A systems biology approach reveals the dose- and time-dependent effect of primary human airway epithelium tissue culture after exposure to cigarette smoke in vitro

To establish a relevant in vitro model for systems toxicology-based mechanistic assessment of environmental stressors such as cigarette smoke (CS), we exposed human organotypic bronchial epithelial tissue cultures at the air liquid interface (ALI) to various CS doses. Previously, we compared in vitro gene expression changes with published human airway epithelia in vivo data to assess their similarities. Here, we present a follow-up evaluation of these in vitro transcriptomics data, using complementary computational approaches and an integrated mRNA-microRNA (miRNA) analysis. The main cellular pathways perturbed by CS exposure were related to stress responses (oxidative stress and xenobiotic metabolism), inflammation (inhibition of nuclear factor-κB and the interferon gamma-dependent pathway), and proliferation/differentiation. Within post-exposure periods up to 48 hours, a transient kinetic response was observed at lower CS doses, whereas higher doses resulted in more sustained responses. In conclusion, this systems toxicology approach has potential for product testing according to "21st Century Toxicology".

Microarray-based analysis of gene expression in lycopersicon esculentum seedling roots in response to cadmium, chromium, mercury, and lead

The effects of heavy metals in agricultural soils have received special attention due to their potential for accumulation in crops, which can affect species at all trophic levels. Therefore, there is a critical need for reliable bioassays for assessing risk levels due to heavy metals in agricultural soil. In the present study, we used microarrays to investigate changes in gene expression of Lycopersicon esculentum in response to Cd-, Cr-, Hg-, or Pb-spiked soil. Exposure to (1)/10 median lethal concentrations (LC50) of Cd, Cr, Hg, or Pb for 7 days resulted in expression changes in 29 Cd-specific, 58 Cr-specific, 192 Hg-specific and 864 Pb-specific genes as determined by microarray analysis, whereas conventional morphological and physiological bioassays did not reveal any toxicant stresses. Hierarchical clustering analysis showed that the characteristic gene expression profiles induced by Cd, Cr, Hg, and Pb were distinct from not only the control but also one another. Furthermore, a total of three genes related to "ion transport" for Cd, 14 genes related to "external encapsulating structure organization", "reproductive developmental process", "lipid metabolic process" and "response to stimulus" for Cr, 11 genes related to "cellular metabolic process" and "cellular response to stimulus" for Hg, 78 genes related to 20 biological processes (e.g., DNA metabolic process, monosaccharide catabolic process, cell division) for Pb were identified and selected as their potential biomarkers. These findings demonstrated that microarray-based analysis of Lycopersicon esculentum was a sensitive tool for the early detection of potential toxicity of heavy metals in agricultural soil, as well as an effective tool for identifying the heavy metal-specific genes, which should be useful for assessing risk levels due to heavy metals in agricultural soil.

Functional genomic screening approaches in mechanistic toxicology and potential future applications of CRISPR-Cas9

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment. Chemical toxicants act by many different mechanisms, however, and the genes involved in adverse outcome pathways (AOPs) and AOP networks are not yet characterized. Functional genomic approaches can reveal both toxicity pathways and susceptibility genes, through knockdown or knockout of all non-essential genes in a cell of interest, and identification of genes associated with a toxicity phenotype following toxicant exposure. Screening approaches in yeast and human near-haploid leukemic KBM7 cells have identified roles for genes and pathways involved in response to many toxicants but are limited by partial homology among yeast and human genes and limited relevance to normal diploid cells. RNA interference (RNAi) suppresses mRNA expression level but is limited by off-target effects (OTEs) and incomplete knockdown. The recently developed gene editing approach called clustered regularly interspaced short palindrome repeats-associated nuclease (CRISPR)-Cas9, can precisely knock-out most regions of the genome at the DNA level with fewer OTEs than RNAi, in multiple human cell types, thus overcoming the limitations of the other approaches. It has been used to identify genes involved in the response to chemical and microbial toxicants in several human cell types and could readily be extended to the systematic screening of large numbers of environmental chemicals. CRISPR-Cas9 can also repress and activate gene expression, including that of non-coding RNA, with near-saturation, thus offering the potential to more fully characterize AOPs and AOP networks. Finally, CRISPR-Cas9 can generate complex animal models in which to conduct preclinical toxicity testing at the level of individual genotypes or haplotypes. Therefore, CRISPR-Cas9 is a powerful and flexible functional genomic screening approach that can be harnessed to provide unprecedented mechanistic insight in the field of modern toxicology.

Beyond a means of exposure: a new view of the mother in toxicology research

Toxicological studies generally view pregnant animals as a conduit through which gestational exposure of offspring to chemicals can be achieved, allowing for the study of developmental toxicity.

Comparative and mechanistic genotoxicity assessment of nanomaterials via a quantitative toxicogenomics approach across multiple species

This study reports a comparative and mechanistic genotoxicity assessment of four engineered nanomaterials (ENMs) across three species, including E. coli, yeast, and human cells, with the aim to reveal the distinct potential genotoxicity mechanisms among the different nanomaterials and their association with physiochemical features. Both the conventional phenotypic alkaline comet test and the newly developed quantitative toxicogenomics assay, that detects and quantifies molecular level changes in the regulation of six DNA damage repair pathways, were employed. The proposed molecular endpoints derived from the toxicogenomics assays, namely TELI (Transcriptional Effect Level Index) and PELI (Protein Effect Level Index), correlated well with the phenotypic DNA damage endpoints from comet tests, suggesting that the molecular genotoxicity assay is suitable for genotoxicity detection. Temporal altered gene or protein expression profiles revealed various potential DNA damage types and relevant genotoxic mechanisms induced by the tested ENMs. nTiO2_a induced a wide spectrum of DNA damage consistently across three species. Three carbon-based ENMs, namely carbon black, single wall carbon nanotube (SWCNT) and fullerene, exhibited distinct, species and ENM property-dependent DNA damage mechanisms. All carbon based ENMs induced relatively weak DNA damage repair response in E. coli, but more severe DNA double strand break in eukaryotes. The differences in cellular structure and defense systems among prokaryotic and eukaryotic species lead to distinct susceptibility and mechanisms for ENM uptake and, thus, varying DNA damages and repair responses. The observation suggested that eukaryotes, especially mammalian cells, are likely more susceptible to genotoxicity than prokaryotes in the ecosystem when exposed to these ENMs.

A 28-day rat inhalation study with an integrated molecular toxicology endpoint demonstrates reduced exposure effects for a prototypic modified risk tobacco product compared with conventional cigarettes

Towards a systems toxicology-based risk assessment, we investigated molecular perturbations accompanying histopathological changes in a 28-day rat inhalation study combining transcriptomics with classical histopathology. We demonstrated reduced biological activity of a prototypic modified risk tobacco product (pMRTP) compared with the reference research cigarette 3R4F. Rats were exposed to filtered air or to three concentrations of mainstream smoke (MS) from 3R4F, or to a high concentration of MS from a pMRTP. Histopathology revealed concentration-dependent changes in response to 3R4F that were irritative stress-related in nasal and bronchial epithelium, and inflammation-related in the lung parenchyma. For pMRTP, significant changes were seen in the nasal epithelium only. Transcriptomics data were obtained from nasal and bronchial epithelium and lung parenchyma. Concentration-dependent gene expression changes were observed following 3R4F exposure, with much smaller changes for pMRTP. A computational-modeling approach based on causal models of tissue-specific biological networks identified cell stress, inflammation, proliferation, and senescence as the most perturbed molecular mechanisms. These perturbations correlated with histopathological observations. Only weak perturbations were observed for pMRTP. In conclusion, a correlative evaluation of classical histopathology together with gene expression-based computational network models may facilitate a systems toxicology-based risk assessment, as shown for a pMRTP.

Non-monotonic dose responses in studies of endocrine disrupting chemicals: bisphenol a as a case study

Non-monotonic dose response curves (NMDRCs) have been demonstrated for natural hormones and endocrine disrupting chemicals (EDCs) in a variety of biological systems including cultured cells, whole organ cultures, laboratory animals and human populations. The mechanisms responsible for these NMDRCs are well known, typically related to the interactions between the ligand (hormone or EDC) and a hormone receptor. Although there are hundreds of examples of NMDRCs in the EDC literature, there are claims that they are not 'common enough' to influence the use of high-to-low dose extrapolations in risk assessments. Here, we chose bisphenol A (BPA), a well-studied EDC, to assess the frequency of non-monotonic responses. Our results indicate that NMDRCs are common in the BPA literature, occurring in greater than 20% of all experiments and in at least one endpoint in more than 30% of all studies we examined. We also analyzed the types of endpoints that produce NMDRCs in vitro and factors related to study design that influence the ability to detect these kinds of responses. Taken together, these results provide strong evidence for NMDRCs in the EDC literature, specifically for BPA, and question the current risk assessment practice where 'safe' low doses are predicted from high dose exposures.

Assessment of the in vitro γH2AX assay by High Content Screening as a novel genotoxicity test

The γH2AX assay is widely used as a marker of DNA damage in multiple scientific fields such as cancer biomarker, clinical studies and radiation biology. In particular, the in vitro γH2AX assay has been suggested as a novel in vitro genotoxicity test with potential as a pre-screening tool. However, to date, limited assessments have been carried out to evaluate the sensitivity, specificity and accuracy of the in vitro γH2AX assay. In this study, the microscopy-based system combining automated cellular image acquisition with software quantification for High Content Screening (HCS) has been used for the first time to evaluate the in vitro γH2AX assay. A panel of well-characterised genotoxic and non-genotoxic compounds was selected to assess the performance of the in vitro γH2AX assay in the human bronchial epithelial cell line BEAS-2B. The results obtained during this preliminary assessment indicate that the in vitro γH2AX assay has a high accuracy (86%) as a result of high sensitivity and specificity (86-92% and 80-88% respectively). Our data highlight the potential for γH2AX detection in HCS as a complement to the current regulatory genotoxicity battery of in vitro assays. We therefore recommend more comprehensive assessments to confirm the performance of the in vitro γH2AX assay by HCS with a more extensive set of compounds.

Systematic verification of upstream regulators of a computable cellular proliferation network model on non-diseased lung cells using a dedicated dataset

We recently constructed a computable cell proliferation network (CPN) model focused on lung tissue to unravel complex biological processes and their exposure-related perturbations from molecular profiling data. The CPN consists of edges and nodes representing upstream controllers of gene expression largely generated from transcriptomics datasets using Reverse Causal Reasoning (RCR). Here, we report an approach to biologically verify the correctness of upstream controller nodes using a specifically designed, independent lung cell proliferation dataset. Normal human bronchial epithelial cells were arrested at G1/S with a cell cycle inhibitor. Gene expression changes and cell proliferation were captured at different time points after release from inhibition. Gene set enrichment analysis demonstrated cell cycle response specificity via an overrepresentation of proliferation related gene sets. Coverage analysis of RCR-derived hypotheses returned statistical significance for cell cycle response specificity across the whole model as well as for the Growth Factor and Cell Cycle sub-network models.

Evaluation of whole wastewater effluent impacts on HepG2 using DNA microarray-based transcriptome analysis

DNA microarray-based transcriptome analysis with human hepatoma HepG2 cells was applied to evaluate the impacts of whole wastewater effluents from the membrane bioreactors (MBRs) and the activated sludge process (AS). In addition, the conventional bioassays (i.e., cytotoxicity tests and bioluminescence inhibition test), which were well-established for the evaluation of the overall effluent toxicity, were also performed for the same samples. Transcriptome analysis revealed that 2 to 926 genes, which were categorized to 0 to 225 biological processes, were differentially expressed after exposure to the effluents and the raw wastewater. Among the tested effluents, the effluent from a MBR operated at a relatively long solid retention time (i.e., 40 days) and small membrane pore size (i.e., 0.03 μm) showed the least impacts on the HepG2 even at the level comparable to tap water. The observed gene expression responses were in good agreement with the results of cytotoxicity tests, and provided additional molecular mechanistic information on adverse effects occurred in the sublethal region. Furthermore, the genes related to "lipid metabolism", "response to endogenous stimulus", and "response to inorganic substance" were selected as potential genetic markers, and their expression levels were quantified to evaluate the cellular impacts and treatability of wastewater effluents. Although the harmful impacts and innocuous impacts could not be distinguished at present, the results demonstrated that the DNA microarray-based transcriptome analysis with human HepG2 cells was a powerful tool to rapidly and comprehensively evaluate impacts of whole wastewater effluents.