Accurate mutation detection and quantification are crucial for understanding mutagenesis and its potential health implications. Traditional in vivo mutagenicity assays, such as the transgenic rodent gene mutation assay, are limited by their focus on single reporter genes and inability to efficiently generate mutation spectra. Error-corrected sequencing (ECS) technologies like Duplex Sequencing (DS) offer significant advantages, including extremely low error rates and ability to measure mutation frequencies (MFs) across various tissues and model organisms. Before DS can be adopted for regulatory purposes, its performance characteristics, particularly the type 1 error rate must be rigorously established. We evaluated the type 1 error rate of DS through empirical analysis of vehicle control data and complementary simulation studies. Using 138 control mouse liver samples from 28 studies analyzed with the TwinStrand Mouse Mutagenesis Panel, we performed variance component analysis and found that experiment-level variability exceeds within-experiment sample variability. To evaluate the impact of between-study heterogeneity, we simulated overdispersed binomial data informed by the observed variance components. Removing the most variable studies reduced overdispersion and improved control of the type 1 error rate. Our findings demonstrate that DS maintains appropriate type 1 error rates (~0.05) when study heterogeneity is limited and at least four samples per group are used. Under greater overdispersion, sample sizes of five or six per group may be needed to achieve comparable control of the type 1 error rate. These results underscore the importance of combining empirical and simulation-based approaches to evaluate and optimize the statistical performance of emerging genomic technologies.

Summary of major conclusions from the 8th International Workshop on Genotoxicity Testing (IWGT), Ottawa, Canada

Gene mutations can be detected in mammalian cells in vitro using indicator genes like the hypoxanthine-guanine-phosphoribosyltransferase (HPRT) gene. These assays have been adopted as OECD test guidelines (TG, e.g. OECD TG no. 476) and are used for regulatory purposes. The in vitro transgenic rodent assay (TGRA), typically performed in primary MutaMouse hepatocytes, is a novel approach for the detection and quantification of gene mutations. Its performance resembles the in vivo TGRA, an in vivo gene mutation assay that has been adopted as OECD TG (no. 488). Although the potential of the in vitro TGRA to identify mutagens has been reported, the performance of this assay as compared to an established in vitro gene mutation assay has not been reported. This study compared the in vitro TGRA with the HPRT assay using ten known in vivo mutagens. The in vitro TGRA correctly identified all ten mutagens, whereas the HPRT assay identified only nine. Benchmark concentration (BMC) modelling for the nine substances detected by both assays revealed overlapping confidence intervals for six compounds, indicating comparable sensitivity. For three mutagens, the HPRT assay yielded lower BMC intervals. Additionally, eight substances known to be non-mutagenic in vivo were tested in the in vitro TGRA, where applicable up to cytotoxic concentrations. While cytotoxicity did not induce increased mutant frequencies, it reduced DNA yield, impairing mutagenicity assessment. The results of this study add to the information on the sensitivity and robustness of the in vitro TGRA and provide essential information for the validation of the assay.

A document by Rushikesh M. Shukla. Click on the document to view its contents.

This laboratory has reported that the combined use of MicroFlow and MultiFlow assays provides information regarding chemicals’ genotoxic mode of action (MoA). In an effort to go beyond MoA assessments, we incorporated a panel of biological response modifiers that elicit specific effects on the assays’ biomarker response profiles. This was done to pursue our hypothesis that such perturbation signatures would reveal information on clastogenic mechanisms and molecular targets. For this proof-of-concept study, we exposed TK6 cells to 20 previously identified clastogens. TK6 cells in 96-well plates in the presence and absence of each of four modifying agents at one optimized concentration: talazoparib (PARP inhibitor), MK-8776 (CHK1 inhibitor), AZD-7648 (DNA-PK inhibitor), or a cocktail of reactive oxygen species scavengers. In parallel, cells were also exposed to each of the test chemicals for 4 hr, at which time cells were washed and allowed to recover for an additional 20 hours. For each of these treatment conditions, sample processing and flow cytometric analyses were performed using standard MicroFlow and MultiFlow procedures to measure micronuclei, γH2AX, phosphohistone-H3 (p-H3), p53 activation, and relative nuclei counts. The resulting biomarker response data were processed with PROAST benchmark dose (BMD) software, with modifying agent as a covariate. Unsupervised hierarchical clustering of the collective potency metrics for various combinations of biomarkers showed that clastogens with similar genotoxic mechanisms grouped together. Overall, this study shows that in combination with biological response modifiers, MultiFlow and MicroFlow biomarkers can provide mechanistic insights into chemical-induced genotoxicity.

The Chicken Egg Genotoxicity Assay (CEGA) is an avian egg-based model that utilizes the livers of developing chicken embryo-fetuses to assess the ability of chemicals to produce direct DNA damage. The main goal of the study was to evaluate target tissue exposure and metabolism in the CEGA to assess its suitability as a biologically relevant new approach methodology (NAM) for detecting genotoxic potential of chemicals. An imaging study using two-photon excitation microscopy following administration of a fluorescent dye (acridine orange) verified that chemicals following administration into the air sac of the fertilized chicken egg reach the target organ, liver. Additionally, a metabolism study using liquid chromatography with high resolution mass spectrometry (LC/MS), conducted after administration of benzo[a]pyrene (B(a)P) according to the CEGA protocol, confirmed the formation of sufficient amounts of reactive metabolite(s) responsible for genotoxic effects of a parent compound upon reaching the target tissue. Moreover, RNA sequencing study revealed that B(a)P in embryo-fetal chicken livers significantly upregulated several genes responsible for the activity of CYP1A1 enzyme which is critical for bioactivation of B(a)P. These findings support previous reports in CEGA, where B(a)P produced DNA damage in the liver tissues in the form of strand breaks and adducts. Overall, the findings in the study support the conclusion that the CEGA can be considered a robust potential alternative to animal testing strategy for assessing the genotoxic potential of chemicals

New approach methodologies (NAMs) used to assess chemicals for biological effects are typically designed to limit the amount of test article required, and to promote efficiencies such as compatibility with liquid handlers, etc. This is certainly true in the case of genetic toxicology, where many methods have been and continue to be developed with 96- or 384-well plate processing in mind. However, one recognized concern with microwell plates is that the volatility of test substances and/or their metabolites and/or their degradation products may affect adjacent wells. Here, we describe an approach that combines breathable membranes as well as activated carbon filters to mitigate volatility issues in 96 well plates. These experiments were performed with cyclophosphamide-exposed TK6 cells, and utilized the biomarkers micronuclei, p53, gammaH2AX, phospho-histone H3, and nuclei to counting bead ratios to both demonstrate volatility impact, and to assess the effectiveness of the solution described herein.

Current genotoxicity testing strategies face several challenges, including a high incidence of misleading positive results that lead to unnecessary animal testing, limited mechanistic insights, insufficient integration of innovative methodologies, and a lack of quantitative assessment. Despite rapid advancements in technology and scientific understanding, genotoxicity testing batteries have remained largely unchanged for years. To modernize genotoxicity assessment and incorporate innovative approaches, the development of Integrated Approaches for Testing and Assessment (IATAs) is essential. These frameworks combine existing knowledge with data from New Approach Methodologies (NAMs) aiming to reduce or eliminate reliance on in vivo testing. Genotoxicity is particularly well-suited for IATA development as numerous cutting-edge, non-animal methods have emerged in recent years, including 3D test systems, Prediscreen®, MultiFlow®, ToxTracker®, and transcriptomic-based biomarkers such as GENOMARK and TGx-DDI. However, the integration of NAMs into IATAs must be systematic and scientifically robust. In this process, the Adverse Outcome Pathway (AOP) framework plays a crucial role by linking molecular-level events to adverse health effects, thereby supporting the structured selection of NAMs. This article explores the key challenges and gaps within the current European regulatory frameworks for chemical compound genotoxicity assessment and discuss how an AOP-based IATA can address these issues. Additionally, we present a global AOP network for permanent DNA damage, designed to guide IATA development and improve regulatory decision-making. This integrated approach has the potential to enhance the accuracy, efficiency, and ethical standards of genotoxicity assessment while reducing reliance on animal testing.

The ability to produce direct DNA damage (genotoxicity) underlies the carcinogenic mode of action of various chemicals. As such, genotoxicity endpoints are typically evaluated in a regulatory-approved battery of in vitro tests with potential in vivo follow-up. Growing concern for animal welfare and implementation of new regulations which restrict the use of laboratory animals necessitated the introduction of New Approach Methodologies (NAMs). The avian egg-based (in ovo) models, the Chicken and related Turkey Egg Fetal Liver DNA Damage Assays, were developed as metabolically competent NAMs to potentially replace short-term in vivo genotoxicity assays for chemicals that are genotoxic in vitro. Both models utilize avian fetal livers for the evaluation of endpoints indicative of DNA damage produced by either direct or indirect mechanisms, specifically, the formation of nuclear DNA adducts and strand breaks. Moreover, avian embryos carry genetic and morphologic resemblance to mammals and can be used for an extensive evaluation of other endpoints including histopathology and tissue-specific genomic profiling. Avian fetal livers contain a full complement of metabolizing enzymes and are capable of bioactivation, detoxication, and elimination of xenobiotics. The comprehensive analysis of 87 and 59 chemicals assessed in the chicken and turkey models, respectively, revealed a stronger correlation with the results from in vivo assays demonstrating that in ovo models can detect the genotoxic potential of a broader range of compounds compared to in vitro assays with S9 supplementation. In conclusion, fertilized avian egg fetal liver assays offer a promising alternative to traditional in vivo genotoxicity assays.

Adverse outcome pathways (AOPs) provide a framework to organize and weigh evidence linking molecular interactions of toxicants in cells to outcomes of regulatory concern. Applying this framework facilitates the interpretation of data produced using new test methods. We used AOP #296 which describes how oxidative DNA damage leads to mutations and chromosomal aberrations to develop an integrated testing strategy to evaluate whether a chemical operates through this pathway. We exposed human TK6 cells to increasing concentrations of 4-nitroquinoline 1-oxide (4NQO), a tobacco mimetic that causes oxidative DNA damage, in a time-series design. We measured oxidative DNA damage and strand breaks using the high-throughput CometChip assay with and without formamidopyrimidine DNA glycosylase (Fpg), alongside analyses of micronucleus (MN) frequency by flow cytometry, and mutations by error-corrected next-generation sequencing (Duplex Sequencing). Our analysis shows how these methods can be combined to quantify 4NQO-induced, concentration- and time-dependent increases in: (a) oxidative DNA damage (occurred early and at lower concentrations than single strand breaks); (b) strand breaks (remained elevated to 6 hours post-exposures); (c) MN frequency (at 24 hours); (d) mutation frequency (at 48 hours); and, (e) C>A transversions consistent with expected substitutions induced by oxidative DNA lesions. The time-series shows the repair of oxidative DNA damage with persistent strand breaks remaining at 6 hours. Overall, we provide an example of an AOP-informed testing strategy and contribute to quantitative understanding of AOP #296. We also demonstrate the high value of Duplex Sequencing for elucidating the mechanisms associated with exposure to oxidative stress inducers.

In vitro genotoxicity has historically served a hazard identification role, with simple binary outcomes provided for each of several single endpoint assays. This will need to change, given: i) efforts to curtail animal testing, ii) the increased use of multiplexed in vitro assays and the ongoing development of NAMS, and iii) the desire to holistically consider quantitative results from multiple biomarkers/endpoints that take potency into consideration. To help facilitate more quantitative analyses of multiple biomarkers and/or assay streams, we explored the combined use of PROAST and Toxicological Prioritization Index (ToxPi) software. As a proof-of-concept, this investigation employed the MultiFlow® DNA damage assay, focusing on γH2AX and p53 biomarkers at two time points, whereby 10 genotoxicants were evaluated in the presence and absence of rat liver S9 metabolic activation. Whereas PROAST was used to calculate BMD point estimates and confidence intervals (CI), ToxPi synthesized the BMD results into visual, quantitative summaries conveying genotoxic potency and metabolic properties. Our analyses suggest that ToxPi’s data synthesis and visualization modules provide useful insights into compound potency, chemical grouping, and genotoxic mechanisms. By integrating multiple data sources, we find that ToxPi offers a powerful complementary approach to traditional BMD CI potency graphs, particularly for the simultaneous analysis of multiple biomarkers enhancing chemical potency analysis of complex datasets.

IntroductionThe Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) framework is used to organize scientific knowledge in toxicology into linear sequences of causally related events that lead to adverse toxicological endpoints (Ankley et al., 2010; OECD, 2018). AOPs describe the critical interactions of a chemical or non-chemical stressor within a biological system. AOPs begins with a molecular initiating event (MIE) that leads to intermediate key events (KEs) and culminate in an adverse outcome (AO). KEs are connected by key event relationships (KERs) for which causality is evaluated using the modified Bradford-Hill criteria (Becker et al., 2015). These criteria include biological plausibility, evidence for the essentiality of KEs, and empirical evidence in the form of dose-, temporal- and incidence-concordance. The strength of these directional and causal relationships is evaluated through a weight of evidence analysis for each KER (Villeneuve et al., 2014). AOPs are purposefully simplified, describing KEs that can be routinely measured and are essential to pathway progression, to facilitate regulatory utility and test strategy development (Ankley et al., 2010). AOPs are developed in a linear manner; however, shared KEs lead to networks of AOPs. Through these networks, multiple MIEs can converge to lead to the same AOs. In addition, multiple different types of stressors may interact with the same MIE to progress AOPs. Thus, although simple in concept, the AOP network is the fundamental unit of application for risk assessment and can broadly reflect complex, multi-stressor interactions and outcomes. AOPs have primarily been used to describe the impacts of chemicals on human and ecological outcomes. However, there is growing interest in applying AOPs in the radiation field (NCRP 2020, Chauhan et al., 2019; Chauhan et al., 2024). A case example AOP to lung cancer that is relevant to stressors such as radon inhalation has been endorsed by the Nuclear Energy Agency (NEA) and the Working Group of the National Coordinators of the Test Guidelines Programme (WNT) and Working Party on Hazard Assessment (WPHA) of the OECD (https://aopwiki.org/aops/272). Furthermore, since June 2021, a Radiation/Chemical AOP Joint Topical Group under the auspices of the NEA High Level Group on Low Dose Research has been working to promote and integrate AOPs into radiation research and risk assessments (Chauhan, Beaton et al., 2022a; Chauhan, Hamada et al., 2022b; Chauhan, Beaton et al., 2024). As part of these efforts, AOPs are being developed to multiple AOs including those relevant to space exploration (Kozbenko et al., 2024; Carrothers et al., 2024; Sleiman et al., 2024; Sandhu et al., 2024). Herein we describe four AOPs (AOP#478; AOP#483; AOP#470; AOP#482) that form a network leading to non-cancer AOs of relevance to space travel.

The Bacterial reverse mutation (AMES) assay is crucial for detecting the mutagenic potential of chemicals using bacterial strains. The solubility of the test substance is key to achieving the recommended concentration for the assay. DMSO and water are typically preferred solvents due to their compatibility and historical data. The chosen solvent must not react with the test substance and must support bacterial survival and S9 activity. Selecting a solvent compatible with Salmonella typhimurium and Escherichia coli WP2 uvrA strains, considering a maximum cytotoxic concentration of 5 mg/plate, is challenging for genetic toxicologists. This study evaluated various solvents, including N,N-Dimethyl formamide, Acetone, Acetonitrile, Ethyl acetate, 95% Ethanol, Dimethylene Glycol Monomethyl ether, Methanol, P-Dioxane, Tetrahydrofuran, and Dimethyl acetamide. Results showed that all solvents, except Tetrahydrofuran, were compatible up to 100 µL/plate or more, as they did not inhibit bacterial growth or alter bacterial revertant colony counts, making them suitable for use in the Ames assay.

Tattoo inks contain several substances, including organic and inorganic pigments, additives, and solvents, which may pose a health risk to not only the tattooed skin but also to other parts of the human body due to intradermal exposure. Substances in tattoo inks are regulated by entry 75 in Annex XVII of REACH Regulation (EC) No. 1907/2006. However, despite these legal requirements, a well-defined criterion for the safety assessment of tattoo inks remains lacking. In this context, 2021 BfR opinion titled “Tattoo inks: minimum requirements and test methods” proposed a comprehensive risk assessment of pigments using in-vitro/in-chemico data in accordance with the OECD Guidelines and CLP Regulation. However, in the absence of experimental data, new approach methodologies (NAMs) can be used for data-gap filling. This work evaluates the applicability of in silico NAMs for data-gap filling to a list of tattoo ink ingredients identified by the JRC and BfR for genotoxicity assessment. The experimental in vitro genotoxicity data was acquired from the International Uniform ChemicaL Information Database (IUCLID) which makes the non-confidential REACH Study Results publicly accessible. The specific aims of this analysis were evaluation of in silico genotoxicity predictions from publicly available QSAR tools and structural alerts, development and validation of new QSAR models specific to tattoo ink ingredients, and application of in silico models for categorization and prioritization of data-poor ingredients for further screening. Based on the workflow developed in this study, 4 high priority, 11 medium priority and 2 low priority substances were identified for further assessment.

Gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens, providing opportunities for integrated testing and reducing animal use. In August 2022, an International Workshops on Genotoxicity Testing (IWGT) workshop was held to critically review current methods to identify genotoxicants using transcriptomic profiling. Here, we summarize the workgroup’s findings on the state of the science regarding the use of transcriptomic biomarkers to identify genotoxic chemicals in vitro and in vivo. A total of 1341 papers were examined to identify the biomarkers that show the most promise for identifying genotoxicants. This revealed two independently derived in vivo biomarkers and three in vitro biomarkers that, when used in conjunction with standard computational techniques, can identify genotoxic chemicals in vivo (rat or mouse liver) or in human cells in culture using different gene expression profiling platforms, with predictive accuracies of ≥ 92%. These biomarkers have been validated to differing degrees, but typically show high reproducibility across transcriptomic platforms and model systems. They offer several advantages for applications in different contexts of use in genotoxicity testing including: early signal detection, moderate to high-throughput screening capacity, adaptability to different cell types and tissues, and insights on mechanistic information on DNA-damage response. Workshop participants agreed on consensus statements to advance the regulatory adoption of transcriptomic biomarkers for genotoxicity. The participants agreed that transcriptomic biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies in vitro and using short-term rodent exposures to identify genotoxic and nongenotoxic chemicals that may……………….

Bone loss, commonly seen in osteoporosis, is a condition that entails a progressive decline of bone mineral density and microarchitecture, often seen in post-menopausal women. Bone loss has been widely reported in astronauts exposed to a plethora of stressors and in patients with osteoporosis following radiotherapy for cancer. Studies on mechanisms are well documented but the causal connectivity of events to bone loss development remains incompletely understood. Herein, the adverse outcome pathway (AOP) framework was used to organize data and develop a qualitative AOP beginning from deposition of energy (the molecular initiating event) to bone loss (the adverse outcome). A literature review was conducted to compile and evaluate the state of knowledge based on the modified Bradford Hill criteria. Following review of 1865 studies, an empirically supported AOP was developed, showing the progression to bone loss through many factors affecting the activities of bone-forming osteoblasts and bone-resorbing osteoclasts. The structural, functional, and quantitative basis of each proposed relationship was defined, for inference of causal changes between key events. Current knowledge and its gaps relating to dose-, time- and incidence-concordance across the key events were identified, as well as modulating factors that influence linkages. The new priorities for research informed by the AOP highlight areas for improvement to enable development of a quantitative AOP used to support risk assessment strategies for space travel or cancer radiotherapy.

I am honored to receive the 2023 Hollaender Award, for achievements in “application of the principles and techniques of environmental mutagenesis to the protection of human health”. People may assume that a career in applied science might not be as exciting or impactful as basic research. I hope my career “adventures” into environmental science, carcinogen investigations and photobiology, as well as publications in Nature and Science, will counter this assumption. The narrative is described in terms of “mentors” whose advice had a lasting impact: “come early and work hard” (meanwhile, have fun); “ think instead of/while screening” (i.e. performing mundane tasks); “avoid the big boo-boo”; “just go in the lab and do experiments”; “become an expert”. Many of the most critical events in science and in life are “random”, as demonstrated by accidental adventures that led to scientific as well as life-altering personal realizations. Adventures included forays into nitrosamine mutagenicity, nanomaterial assessment, germ cell mutagenic risk, bacterial mutagenicity assays, genotoxicity of cell phone radiation, personalized cancer prevention, and >25 years in regulatory safety assessment at FDA: review of genotoxicity data, experiments in the lab, and collaboration with others to foster better analyses of DNA damaging agents, generally in relation to cancer risk. Finally, with my work and that of my lifelong tripmate William Lijinsky as models, I suggest that a “non-hypothesis driven”, open-ended approach to research can be path-breaking and forefront.

At the 8th International Workshop on Genotoxicity Testing (IWGT) meeting in Ottawa, August 2022, a plenary session was dedicated to the genotoxicity risk evaluation of gene therapies, including insertional oncogenesis and off-target genome editing. This brief communication summarizes the topics of discussion and the main insights from the speakers. Common themes included recommendations to conduct tailored risk assessments based on a weight of evidence approach, to promote data sharing, transparency, and cooperation between stakeholders, and to develop state-of-the-art validated tests relevant to clinical scenarios.