The challenge of the application of 'omics technologies in chemicals risk assessment: Background and outlook

Using transcriptomics data and Adverse Outcome Pathway networks to explore endocrine disrupting properties of Cadmium and PCB-126

Omics-technologies such as transcriptomics offer valuable insights into toxicity mechanisms. However, integrating this type of data into regulatory frameworks remains challenging due to uncertainties regarding toxicological relevance and links to adverse outcomes. Furthermore, current assessments of endocrine disruptors (EDs) relevant to human health require substantial amounts of data, and primarily rely on standardized animal studies. Identifying EDs is a high priority in the EU, but so are efforts to replace and reduce animal testing. Alternative methods to investigate EDs are needed, and so are health risk assessment methods that support uptake of novel mechanistic information. This study aims to utilize Adverse Outcome Pathways (AOPs) to integrate transcriptomics data for identifying EDs, by establishing a link between molecular data and adverse outcomes. Cadmium (Cd) and 3,3',4,4',5-pentachlorobiphenyl (PCB126) were used as model compounds due to their observed effects on the endocrine system. An AOP network for the estrogen, androgen, thyroid, and steroidogenesis (EATS)-modalities was constructed. RNA sequencing (RNA-Seq) was conducted on zebrafish (Danio rerio) embryos exposed to Cd or PCB126 for 4 days. RNA-Seq data were then linked to the AOP network via Gene Ontology (GO) terms. Enrichment Maps in Cytoscape and the QIAGEN Ingenuity Pathway Analysis (IPA) software were also used to identify potential ED properties and to support the assessment. Potentially EATS-related GO Biological Process (BP) terms were identified for both compounds. A lack of accurate standardized terms in KEs of the AOP network hindered a data-driven mapping approach. Instead, manual mapping of GO BP terms onto the AOP network revealed more connections, underscoring the need for harmonizing AOP development for regulatory use. Both the Enrichment Maps and the IPA results further supported potentially EATS-related effects of both compounds. While AOP networks show promise in integrating RNA-Seq data, several challenges remain.

Experimental reporting of fish transcriptomic responses in environmental toxicology and ecotoxicology

Due to its increasing affordability and efforts to understand transcriptional responses of organisms to biotic and abiotic stimuli, transcriptomics has become an important tool with significant impact on toxicological investigations and hazard and risk assessments, especially during development and application of new approach methodologies (NAMs). Data generated using transcriptomic methodologies have directly informed adverse outcome pathway frameworks, chemical and biological read across, and aided in the identification of points of departure. Using data reporting frameworks for transcriptomics data offers improved transparency and reproducibility of research and an opportunity to identify barriers to adoption of these NAMs, especially in environmental toxicology and ecotoxicology with aquatic models. Improved reporting also allows for reexamination of existing data, limiting needs for experiment replication and further reducing animal experimentation. Here, we use a standardized form of data reporting for omics-based studies, the Organisation for Economic Co-operation and Development omics reporting framework, which specifically reports on a list of parameters that should be included in transcriptomics studies used in a regulatory context. We focused specifically on fish studies using RNA- Sequencing (Seq)/microarray technologies within a toxicology context. Inconsistencies in reporting and methodologies among the experimental designs (toxicology vs. molecular characterization) were observed in addition to foundational differences in reporting of sample concentration or preparation or quality assessments, which can affect reproducibility and read across, confidence in results, and contribute substantially to understanding molecular mechanisms of toxicants and toxins. Our findings present an opportunity for improved research reporting. We also provide several recommendations as logical steps to reduce barriers to adoption of transcriptomics within environmental toxicology and ecotoxicology.

Cohort Studies and Multi-omics Approaches to Low-Dose Ionizing Radiation-Induced Cardiovascular Disease: A Comprehensive Review

The effect of low-dose ionizing radiation exposure on the risk of cardiovascular disease (CVD) represents a significant concern in the field of radiation protection. The prevailing approach to mitigating the adverse effects of low-dose or low-dose-rate radiation does not currently incorporate the potential risk of CVD, despite the possibility that such risk may be a substantial contributor to overall health hazards. Current evidence suggests a potential association between radiation exposure and CVD; however, the overall findings remain inconclusive. This is particularly due to the uncertainty surrounding the influence of significant non-radiation risk factors on the associations reported in epidemiological studies. It is difficult to discern the underlying connection in observational epidemiology when there is substantial variation in baseline risk factors. The paucity of epidemiological research in this domain is being partially offset by the advancement of multi-omics approaches. These methods assist in identifying radiosensitive targets, comprehending underlying biological processes, and pinpointing biomarkers. This, in turn, fortifies the evidence gleaned from epidemiological studies. In this review, we delve into the body of epidemiological research pertaining to CVD induced by low-dose ionizing radiation and the application of multi-omics techniques. The integration of these two methodologies holds the promise of identifying specific molecules or biological pathways that can be employed to validate endpoints related to radiation risk assessment.

Proteomic analysis of human iPSC-derived sympathetic neurons identifies proteostasis collapse as a molecular signature following subtoxic rotenone exposure

Rotenone is a toxic isoflavone and an inhibitor of the mitochondrial respiratory chain. Rotenone is commonly used due to its piscicidal and pesticidal properties. The peripheral nervous system (PNS) lacks protective barriers and is exposed to many environmental substances due to its long-reaching structure. A causal association between rotenone and human PNS dysfunction is currently a subject of investigation. Here, we treated human induced pluripotent stem cell (iPSC)-derived peripheral sympathetic neurons with a subtoxic dose of rotenone (10 µg/L) that is considered safe for human health and is permitted for environmental use. Indeed, no overt toxicity was observed in the human peripheral neurons and neurite morphology was intact in the treated neurons. Surprisingly, we detected significant changes in the proteome of rotenone-exposed sympathetic neurons with a signature of protein homeostasis (proteostasis) collapse. Screening the proteostasis modules of protein translation, proteolysis, and chaperones, revealed severe perturbations in clusters of autophagy regulators. Our proteomic profiling reveals compromised proteostasis as a consequence of low-dose non-toxic exposure to rotenone, which can disrupt the ability of the PNS to cope with proteotoxic stress. Exposed individuals may have varying degrees of tolerance to such vulnerabilities but they may eventually progress into peripheral neuropathies.

Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics

Proteomic investigations yield high-dimensional datasets, yet their application to large-scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label-free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost-effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.

Feature-agnostic metabolomics for determining effective subcytotoxic doses of common pesticides in human cells

Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. The data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.

Assessing lethal and sublethal effects of pesticides on honey bees in a multifactorial context

The registration of novel pesticides that are subsequently banned because of their unexpected negative effects on non-target species can have a huge environmental impact. Therefore, the pre-emptive evaluation of the potential effects of new compounds is essential. To this aim both lethal and sublethal effects should be assessed in a realistic scenario including the other stressors that can interact with pesticides. However, laboratory studies addressing such interactive effects are rare, while standardized laboratory-based protocols focus on lethal effects and not on sub-lethal effects. We propose to assess both lethal and sublethal effects in a multifactorial context including the other stressors affecting the non-target species. We tested this approach by studying the impact on honey bees of the insecticide sulfoxaflor in combination with a common parasite, a sub-optimal temperature and food deprivation. We studied the survival and the transcriptome of honey bees, to assess both the lethal and the potential sublethal effects of the insecticide, respectively. With this method we show that a field realistic concentration of sulfoxaflor in food does not affect the survival of honey bees; however, the significant impact on some key genes indicates that sublethal effects are possible in a realistically complex scenario. Moreover, our results demonstrate the feasibility and reliability of a novel approach to hazard assessment considering the interactive effects of pesticides. We anticipate our approach to be a starting point for a paradigm shift in toxicology: from an unifactorial, mortality-centered assessment to a multifactorial, comprehensive approach. This is something of the utmost importance to preserve pollination, thus contributing to the sustainability of our food production system.

404-error "Disease not found": Unleashing the translational potential of -omics approaches beyond traditional disease classification in heart failure research

The emergence of personalized medicine, facilitated by the progress in -omics technologies, has initiated a new era in medical diagnostics and treatment. This review examines the potential of -omics approaches in heart failure, a condition that has not yet fully capitalized on personalized strategies compared to other medical fields like cancer therapy. Here, we argue that integrating multi-omics technology with systems medicine approaches could fundamentally transform heart failure management, moving away from the traditional paradigm of 'one size fits all'. Our review examines how omics can enhance understanding of heart failure's molecular foundations and contribute to a more comprehensive disease classification. We draw attention to the current state of medical practice that only relies on clinical evidence and a number of standard laboratory tests. At the same time, we propose a shift towards a universal approach that uses quantitative data from multi-omics to unravel complex molecular interactions. The discussion centres around the potential of the transition as a means to enhance individual risk assessment and emphasizes management within clinical settings. While the use of omics in cardiovascular research is not recent, many past studies have focused only on a single omics approach. In order to achieve a better understanding of disease mechanisms, we explore more holistic approaches using genomics, transcriptomics, epigenomics, and proteomics. This review concludes with a call to action to adopt multi-omics in clinical trials and practice to pave the way for more personalized disease management and more effective heart failure interventions.

20 years of polybrominated diphenyl ethers on toxicity assessments

Polybrominated diphenyl ethers (PBDEs) serve as brominated flame retardants which continue to receive considerable attention because of their persistence, bioaccumulation, and potential toxicity. Although PBDEs have been restricted and phased out, large amounts of commercial products containing PBDEs are still in use and discarded annually. Consequently, PBDEs added to products can be released into our surrounding environments, particularly in aquatic systems, thus posing great risks to human health. Many studies and reviews have described the possible toxic effects of PBDEs, while few studies have comprehensively summarized and analyzed the global trends of their toxicity assessment. Therefore, this study utilizes bibliometrics to evaluate the worldwide scientific output of PBDE toxicity and analyze the hotspots and future trends of this field. Firstly, the basic information including the most contributing countries/institutions, journals, co-citations, influential authors, and keywords involved in PBDE toxicity assessment will be visualized. Subsequently, the potential toxicity of PBDE exposure to diverse systems, such as endocrine, reproductive, neural, and gastrointestinal tract systems, and related toxic mechanisms will be discussed. Finally, we conclude this review by outlining the current challenges and future perspectives in environmentally relevant PBDE exposure, potential carriers for PBDE transport, the fate of PBDEs in the environment and human bodies, advanced stem cell-derived organoid models for toxicity assessment, and promising omics technologies for obtaining toxic mechanisms. This review is expected to offer systematical insights into PBDE toxicity assessments and facilitate the development of PBDE-based research.

Ecotoxicity of commonly used oilfield-based emulsifiers on Guinean Tilapia (Tilapia guineensis) using histopathology and behavioral alterations as protocol

This study examined the histological aberrations in the gill and liver tissues and behavioural changes of Tilapia guineensis fingerlings exposed to lethal concentrations of used Oilfield-based emulsifiers for 96 h. Various concentrations of the surfactants were tested, ranging from 0.0 to 15.0 ml/L. The behaviour of the fish was observed throughout the experiment, and the results showed that increasing concentrations of the surfactants led to progressively abnormal behaviour, including hyperventilation and altered opercular beat frequency. These behavioural changes indicated respiratory distress and neurotoxic effects. Histological analysis revealed structural aberrations in the gill and liver tissues, with higher concentrations causing more severe damage, such as lesions, necrosis, inflammation, and cellular degeneration. This implies that surfactants released even at low concentrations are capable of inducing changes in the tissues of aquatic organisms. These findings highlight the toxic effects of the surfactants on fish health and provide biomarkers of toxicity. Future research should focus on understanding the specific mechanisms and long-term consequences of surfactant toxicity on fish genetic composition, populations, and ecosystems to implement effective conservation measures.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction

Assessing chemical safety is essential to evaluate the potential risks of chemical exposure to human health and the environment. Traditional methods relying on animal testing are being replaced by 3R (reduction, refinement, and replacement) principle-based alternatives, mainly depending on in vitro test methods and the Adverse Outcome Pathway framework. However, these approaches often focus on the properties of the compound, missing the broader chemical-biological interaction perspective. Currently, the lack of comprehensive molecular characterization of the in vitro test system results in limited real-world representation and contextualization of the toxicological effect under study. Leveraging omics data strengthens the understanding of the responses of different biological systems, emphasizing holistic chemical-biological interactions when developing in vitro methods. Here, we discuss the relevance of meticulous test system characterization on two safety assessment relevant scenarios and how omics-based, data-driven approaches can improve the future generation of alternative methods.

Deeper insights into the effects of low dietary levels of polychlorinated biphenyls on pig metabolism using gas chromatography-high resolution mass spectrometry metabolomics

Polychlorinated biphenyls (PCBs) are a class of contaminants of great concern, linked to the development of many chronic diseases. Adverse effects of PCBs have been documented in humans after accidental and massive exposure. However, little is known about the effect of chronic exposure to low-dose PCB mixtures, and studies regarding scattered lifetime exposures to non-dioxin-like (NDL)-PCBs are especially missing. In this work, serum samples from pigs chronically exposed through their diet during 22 days to Aroclor 1260 (i.e. a commercially available mixture of NDL-PCBs) underwent a metabolomics analysis using gas chromatography-high resolution mass spectrometry (GC-HRMS), with the objective to investigate the effect of exposure to low doses of NDL-PCBs (few ng/kg body weight (b.w.) per day). The study showed that the serum profiles of 84 metabolites are significantly altered by the administration of Aroclor 1260, of which 40 could be identified at level 1. The aggregate interpretation of the results of this study, together with the outcome of a previous one involving LC-HRMS profiling, provided a substantial and concise overview of the effect of low dose exposure to NDL-PCBs, reflecting the hepatotoxic and neurotoxic effects already reported in literature at higher and longer exposures. These results are intended to contribute to the debate on the current toxicological reference values for these substances.

Influence of chemical dose and exposure duration on protein synthesis in green sea turtle primary cells

Understanding the impacts of chemical exposure in marine wildlife is challenging, due to practical and ethical constraints that preclude traditional toxicology research on these animals. This study addressed some of these limitations by presenting an ethical and high throughput cell-based approach to elucidate molecular-level effects of contaminants on sea turtles. The experimental design addressed basic questions of cell-based toxicology, including chemical dose and exposure time. Primary green turtle skin cells were exposed to polychlorinated biphenyl (PCB) 153 and perfluorononanoic acid (PFNA) for 24 and 48 h, at three sub-lethal, environmentally relevant concentrations (1, 10 and 100 μg/L). Sequential window acquisition of all theoretical mass spectra (SWATH-MS) identified over 1000 differentially abundant proteins within the 1% false discovery rate (FDR) threshold. The 24 h exposure resulted in a greater number of differentially abundant proteins, compared to 48 h exposure, for both contaminants. However, there were no statistically significant dose-response relationships for the number of differentially synthesised proteins, nor differences in the proportion of increased vs decreased proteins between or within exposure times. Known in vivo markers of contaminant exposure, superoxide dismutase and glutathione S-transferase, were differentially abundant following exposure to PCB153 and PFNA. SIGNIFICANCE: Cell-based (in vitro) proteomics provides an ethical and high throughput approach to understanding the impacts of chemical contamination on sea turtles. Through investigating effects of chemical dose and exposure duration on unique protein abundance in vitro, this study provides an optimised framework for conducting cell-based studies in wildlife proteomics, and highlights that proteins detected in vitro could act as biomarkers of chemical exposure and effect in vivo.

Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity

In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.

An innovative index to incorporate transcriptomic data into weight of evidence approaches for environmental risk assessment

The sharp decrease in the cost of RNA-sequencing and the rapid improvement in computational analysis of eco-toxicogenomic data have brought new insights into the adverse effects of chemicals on aquatic organisms. Yet, transcriptomics is generally applied qualitatively in environmental risk assessments, hampering more effective exploitation of this evidence through multidisciplinary studies. In view of this limitation, a methodology is here presented to quantitatively elaborate transcriptional data in support to environmental risk assessment. The proposed methodology makes use of results from the application of Gene Set Enrichment Analysis to recent studies investigating the response of Mytilus galloprovincialis and Ruditapes philippinarum exposed to contaminants of emerging concern. The degree of changes in gene sets and the relevance of physiological reactions are integrated in the calculation of a hazard index. The outcome is then classified according to five hazard classes (from absent to severe), providing an evaluation of whole-transcriptome effects of chemical exposure. The application to experimental and simulated datasets proved that the method can effectively discriminate different levels of altered transcriptomic responses when compared to expert judgement (Spearman correlation coefficient of 0.96). A further application to data collected in two independent studies of Salmo trutta and Xenopus tropicalis exposed to contaminants confirmed the potential extension of the methodology to other aquatic species. This methodology can serve as a proof of concept for the integration of "genomic tools" in environmental risk assessment based on multidisciplinary investigations. To this end, the proposed transcriptomic hazard index can now be incorporated into quantitative Weight of Evidence approaches and weighed, with results from other types of analysis, to elucidate the role of chemicals in adverse ecological effects.

PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping

Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances' mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols.

Identifying multiscale translational safety biomarkers using a network-based systems approach

Animal testing is the current standard for drug and chemicals safety assessment, but hazards translation to human is uncertain. Human in vitro models can address the species translation but might not replicate in vivo complexity. Herein, we propose a network-based method addressing these translational multiscale problems that derives in vivo liver injury biomarkers applicable to in vitro human early safety screening. We applied weighted correlation network analysis (WGCNA) to a large rat liver transcriptomic dataset to obtain co-regulated gene clusters (modules). We identified modules statistically associated with liver pathologies, including a module enriched for ATF4-regulated genes as associated with the occurrence of hepatocellular single-cell necrosis, and as preserved in human liver in vitro models. Within the module, we identified TRIB3 and MTHFD2 as a novel candidate stress biomarkers, and developed and used BAC-eGFPHepG2 reporters in a compound screening, identifying compounds showing ATF4-dependent stress response and potential early safety signals.

Multiomics Point of Departure (moPOD) Modeling Supports an Adverse Outcome Pathway Network for Ionizing Radiation

While adverse biological effects of acute high-dose ionizing radiation have been extensively investigated, knowledge on chronic low-dose effects is scarce. The aims of the present study were to identify hazards of low-dose ionizing radiation to Daphnia magna using multiomics dose-response modeling and to demonstrate the use of omics data to support an adverse outcome pathway (AOP) network development for ionizing radiation. Neonatal D. magna were exposed to γ radiation for 8 days. Transcriptomic analysis was performed after 4 and 8 days of exposure, whereas metabolomics and confirmative bioassays to support the omics analyses were conducted after 8 days of exposure. Benchmark doses (BMDs, 10% benchmark response) as points of departure (PODs) were estimated for both dose-responsive genes/metabolites and the enriched KEGG pathways. Relevant pathways derived using the BMD modeling and additional functional end points measured by the bioassays were overlaid with a previously published AOP network. The results showed that several molecular pathways were highly relevant to the known modes of action of γ radiation, including oxidative stress, DNA damage, mitochondrial dysfunction, protein degradation, and apoptosis. The functional assays showed increased oxidative stress and decreased mitochondrial membrane potential and ATP pool. Ranking of PODs at the pathway and functional levels showed that oxidative damage related functions had relatively low PODs, followed by DNA damage, energy metabolism, and apoptosis. These were supportive of causal events in the proposed AOP network. This approach yielded promising results and can potentially provide additional empirical evidence to support further AOP development for ionizing radiation.

New approach methodologies: A quantitative in vitro to in vivo extrapolation case study with PFASs

PER: and polyfluoroalkyl substances (PFASs) have been associated with increased blood lipids in humans. Perfluorooctanoic acid (PFOA) has been also linked with elevated alanine transferase (ALT) serum levels in humans, and in rodents the liver is a main target organ for many PFASs. With the focus on New Approach Methodologies, the chronic oral equivalent effect doses were calculated for PFOA, PFNA (perfluorononanoic acid), PFHxS (perfluorohexanesulfonic acid) and PFOS (perfluorooctane sulfonic acid) based on in vitro effects measured in the HepaRG cell line. Selected in vitro readouts were considered biomarkers for lipid disturbances and hepatotoxicity. Concentration-response data obtained from HepaRG cells on triglyceride (TG) accumulation and expression changes of 12 selected genes (some involved in cholesterol homeostasis) were converted into corresponding human dose-response data, using physiologically based kinetic (PBK) model-facilitated reverse dosimetry. Next to this, the biokinetics of the chemicals were studied in the cell system. The current European dietary PFASs exposure overlaps with the calculated oral equivalent effect doses, indicating that the latter may lead to interference with hepatic gene expression and lipid metabolism. These findings illustrate an in vitro-in silico methodology, which can be applied for more PFASs, to select those that should be prioritized for further hazard characterization.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B₁, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B₁, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less is known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD.

RESULTS

The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

The Evolution of Regulatory Toxicology: Where is the Gardener?

There is a need for paradigm change in the methodology employed for toxicological testing and assessment. It could be said that this change is well on its way, through an evolutionary progress analogous to that of natural selection. Darwin's Theory of Evolution has defined the idea of evolution and descendancy since the last third of the 19th century. Increasingly, this concept of 'evolution' is being applied beyond the field of biology. This Comment article discusses the progress of toxicological testing in the context of 'evolutionary pressure' and deliberates how this process can help foster the development, implementation and acceptance of mechanistic and human-relevant methods in this field. By comparing the current regulatory landscape in toxicity testing and assessment to specific elements in Charles Darwin's evolutionary theory, we aim to better understand the needs and requirements for the future.

A bioinformatics framework for targeted gene expression assay design: Application to in vitro developmental neurotoxicity screening in a rat model

Brain development involves a series of intricately choreographed neuronal differentiation and maturation steps that are acutely vulnerable to interferences from chemical exposures. Many genes involved in neurodevelopmental processes show evolutionarily conserved expression patterns in mammals and may constitute useful indicators/biomarkers for the evaluation of potential developmental neurotoxicity. Based on these premises, this study developed a bioinformatics framework to guide the design of a gene expression-based in vitro developmental neurotoxicity assay targeting evolutionary conserved genes associated with neuronal differentiation and maturation in rat cerebellar granule cells (CGCs). Rat, mouse and human genes involved in neurodevelopment and presenting one-to-one orthology were selected and orthologous exons within these genes were identified. PCR primer sets were designed within these orthologous exons and their specificity was evaluated in silico. The performance and specificity of rat, mouse and human PCR primer sets were then confirmed experimentally. Finally, RT-qPCR analyses in CGCs exposed in vitro to well-known neurotoxicants (Chlorpyrifos and Chlorpyrifos oxon) uncovered perturbations of expression levels for most of the selected genes. This bioinformatics framework for gene and target sequence selection may facilitate the identification of transcriptional biomarkers for developmental neurotoxicity assays and the comparison of gene expression data across experimental models from different mammalian species.

Use of transcriptomics in hazard identification and next generation risk assessment: A case study with clothianidin

Toxicological risk assessment is essential in the evaluation and authorization of different classes of chemical substances. Genotoxicity and mutagenicity testing are of highest priority and rely on established in vitro systems with bacterial and mammalian cells, sometimes followed by in vivo testing using rodent animal models. Transcriptomic approaches have recently also shown their value to determine transcript signatures specific for genotoxicity. Here, we studied how transcriptomic data, in combination with in vitro tests with human cells, can be used for the identification of genotoxic properties of test compounds. To this end, we used liver samples from a 28-day oral toxicity study in rats with the pesticidal active substances imazalil, thiacloprid, and clothianidin, a neonicotinoid-type insecticide with, amongst others, known hepatotoxic properties. Transcriptomic results were bioinformatically evaluated and pointed towards a genotoxic potential of clothianidin. In vitro Comet and γH2AX assays in human HepaRG hepatoma cells, complemented by in silico analyses of mutagenicity, were conducted as follow-up experiments to check if the genotoxicity alert from the transcriptomic study is in line with results from a battery of guideline genotoxicity studies. Our results illustrate the combined use of toxicogenomics, classic toxicological data and new approach methods in risk assessment. By means of a weight-of-evidence decision, we conclude that clothianidin does most likely not pose genotoxic risks to humans.

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Analysis of clothianidin genotoxicity in silico, in vitro and in vivo.

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Application of a toxicogenomics approach to analyze genotoxicity.

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Weight-of-evidence decision supports classification as “non-genotoxic”.

R-ODAF: Omics data analysis framework for regulatory application

Despite the widespread use of transcriptomics technologies in toxicology research, acceptance of the data by regulatory agencies to support the hazard assessment is still limited. Fundamental issues contributing to this are the lack of reproducibility in transcriptomics data analysis arising from variance in the methods used to generate data and differences in the data processing. While research applications are flexible in the way the data are generated and interpreted, this is not the case for regulatory applications where an unambiguous answer, possibly later subject to legal scrutiny, is required. A reference analysis framework would give greater credibility to the data and allow the practitioners to justify their use of an alternative bioinformatic process by referring to a standard. In this publication, we propose a method called omics data analysis framework for regulatory application (R-ODAF), which has been built as a user-friendly pipeline to analyze raw transcriptomics data from microarray and next-generation sequencing. In the R-ODAF, we also propose additional statistical steps to remove the number of false positives obtained from standard data analysis pipelines for RNA-sequencing. We illustrate the added value of R-ODAF, compared to a standard workflow, using a typical toxicogenomics dataset of hepatocytes exposed to paracetamol.

Innovation in regulatory approaches for endocrine disrupting chemicals: The journey to risk assessment modernization in Canada

Globally, regulatory authorities grapple with the challenge of assessing the hazards and risks to human and ecosystem health that may result from exposure to chemicals that disrupt the normal functioning of endocrine systems. Rapidly increasing number of chemicals in commerce, coupled with the reliance on traditional, costly animal experiments for hazard characterization - often with limited sensitivity to many important mechanisms of endocrine disruption -, presents ongoing challenges for chemical regulation. The consequence is a limited number of chemicals for which there is sufficient data to assess if there is endocrine toxicity and hence few chemicals with thorough hazard characterization. To address this challenge, regulatory assessment of endocrine disrupting chemicals (EDCs) is benefiting from a revolution in toxicology that focuses on New Approach Methodologies (NAMs) to more rapidly identify, prioritize, and assess the potential risks from exposure to chemicals using novel, more efficient, and more mechanistically driven methodologies and tools. Incorporated into Integrated Approaches to Testing and Assessment (IATA) and guided by conceptual frameworks such as Adverse Outcome Pathways (AOPs), emerging approaches focus initially on molecular interactions between the test chemical and potentially vulnerable biological systems instead of the need for animal toxicity data. These new toxicity testing methods can be complemented with in silico and computational toxicology approaches, including those that predict chemical kinetics. Coupled with exposure data, these will inform risk-based decision-making approaches. Canada is part of a global network collaborating on building confidence in the use of NAMs for regulatory assessment of EDCs. Herein, we review the current approaches to EDC regulation globally (mainly from the perspective of human health), and provide a perspective on how the advances for regulatory testing and assessment can be applied and discuss the promises and challenges faced in adopting these novel approaches to minimize risks due to EDC exposure in Canada, and our world.

First transcriptome of the copepod Gladioferens pectinatus subjected to chronic contaminant exposures

Contaminants are often at low concentrations in ecosystems and their effects on exposed organisms can occur over long periods of time and across multiple generations. Alterations to subcellular mechanistic pathways in response to exposure to contaminants can provide insights into mechanisms of toxicity that methods measuring higher levels of biological may miss. Analysis of the whole transcriptome can identify novel mechanisms of action leading to impacts in exposed biota. The aim of this study was to characterise how exposures to copper, benzophenone and diclofenac across multiple generations altered molecular expression pathways in the marine copepod Gladioferens pectinatus. Results of the study demonstrated differential gene expression was observed in cultures exposure to diclofenac (569), copper (449) and benzophenone (59). Pathways linked to stress, growth, cellular and metabolic processes were altered by exposure to all three contaminants with genes associated with oxidative stress and xenobiotic regulation also impacted. Protein kinase functioning, cytochrome P450, transcription, skeletal muscle contraction/relaxation, mitochondrial phosphate translocator, protein synthesis and mitochondrial methylation were all differentially expressed with all three chemicals. The results of the study also suggested that using dimethyl sulfoxide as a dispersant influenced the transcriptome and future research may want to investigate it's use in molecular studies. Data generated in this study provides a first look at transcriptomic response of G. pectinatus exposed to contaminants across multiple generations, future research is needed to validate the identified biomarkers and link these results to apical responses such as population growth to demonstrate the predictive capacity of molecular tools.

A Scoping Review of Technologies and Their Applicability for Exposome-Based Risk Assessment in the Oil and Gas Industry

INTRODUCTION

Oil and gas workers have been shown to be at increased risk of chronic diseases including cancer, asthma, chronic obstructive pulmonary disease, and hearing loss, among others. Technological advances may be used to assess the external (e.g. personal sensors, smartphone apps and online platforms, exposure models) and internal exposome (e.g. physiologically based kinetic modeling (PBK), biomonitoring, omics), offering numerous possibilities for chronic disease prevention strategies and risk management measures. The objective of this study was to review the literature on these technologies, by focusing on: (i) evaluating their applicability for exposome research in the oil and gas industry, and (ii) identifying key challenges that may hamper the successful application of such technologies in the oil and gas industry.

METHOD

A scoping review was conducted by identifying peer-reviewed literature with searches in MEDLINE/PubMed and SciVerse Scopus. Two assessors trained on the search strategy screened retrieved articles on title and abstract. The inclusion criteria used for this review were: application of the aforementioned technologies at a workplace in the oil and gas industry or, application of these technologies for an exposure relevant to the oil and gas industry but in another occupational sector, English language and publication period 2005-end of 2019.

RESULTS

In total, 72 articles were included in this scoping review with most articles focused on omics and bioinformatics (N = 22), followed by biomonitoring and biomarkers (N = 20), external exposure modeling (N = 11), PBK modeling (N = 10), and personal sensors (N = 9). Several studies were identified in the oil and gas industry on the application of PBK models and biomarkers, mainly focusing on workers exposed to benzene. The application of personal sensors, new types of exposure models, and omics technology are still in their infancy with respect to the oil and gas industry. Nevertheless, applications of these technologies in other occupational sectors showed the potential for application in this sector.

DISCUSSION AND CONCLUSION

New exposome technologies offer great promise for personal monitoring of workers in the oil and gas industry, but more applied research is needed in collaboration with the industry. Current challenges hindering a successful application of such technologies include (i) the technological readiness of sensors, (ii) the availability of data, (iii) the absence of standardized and validated methods, and (iv) the need for new study designs to study the development of disease during working life.

Trends in the Application of "Omics" to Ecotoxicology and Stress Ecology

Our ability to predict and assess how environmental changes such as pollution and climate change affect components of the Earth's biome is of paramount importance. This need positioned the fields of ecotoxicology and stress ecology at the center of environmental monitoring efforts. Advances in these interdisciplinary fields depend not only on conceptual leaps but also on technological advances and data integration. High-throughput "omics" technologies enabled the measurement of molecular changes at virtually all levels of an organism's biological organization and thus continue to influence how the impacts of stressors are understood. This bibliometric review describes literature trends (2000-2020) that indicate that more different stressors than species are studied each year but that only a few stressors have been studied in more than two phyla. At the same time, the molecular responses of a diverse set of non-model species have been investigated, but cross-species comparisons are still rare. While transcriptomics studies dominated until 2016, a shift towards proteomics and multiomics studies is apparent. There is now a wealth of data at functional omics levels from many phylogenetically diverse species. This review, therefore, addresses the question of how to integrate omics information across species.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Evaluation of the Effects of Solvents Used in the Fabrication of Microfluidic Devices on Cell Cultures

Microfluidic microphysiological systems (MPSs) or "organs-on-a-chip" are a promising alternative to animal models for drug screening and toxicology tests. However, most microfluidic devices employ polydimethylsiloxane (PDMS) as the structural material; and this has several drawbacks. Cyclo-olefin polymers (COPs) are more advantageous than PDMS and other thermoplastic materials because of their low drug absorption and autofluorescence. However, most COP-based microfluidic devices are fabricated by solvent bonding of the constituent parts. Notably, the remnant solvent can affect the cultured cells. This study employed a photobonding process with vacuum ultraviolet (VUV) light to fabricate microfluidic devices without using any solvent and compared their performance with that of solvent-bonded systems (using cyclohexane, dichloromethane, or toluene as the solvent) to investigate the effects of residual solvent on cell cultures. Quantitative immunofluorescence assays indicated that the coating efficiencies of extracellular matrix proteins (e.g., Matrigel and collagen I) were lower in solvent-bonded COP devices than those in VUV-bonded devices. Furthermore, the cytotoxicity of the systems was evaluated using SH-SY5Y neuroblastoma cells, and increased apoptosis was observed in the solvent-processed devices. These results provide insights into the effects of solvents used during the fabrication of microfluidic devices and can help prevent undesirable reactions and establish good manufacturing practices.

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

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

Approaches in metabolomics for regulatory toxicology applications

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

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

Are we forgetting the "proteomics" in multi-omics ecotoxicology?

Proteomics plays a significant role in discerning the effects of chemical exposures in animal taxa. Multi-omics applications have become more pervasive in toxicology, however questions remain about whether proteomics is being utilized by the community to its full potential - are we placing too much stock in transcriptomics and other omics approaches for developing adverse outcome pathways? Proteins are more relevant than transcripts because they are direct mediators of the resulting phenotype. There is also rarely perfect stoichiometry between transcript and protein abundance and transcript abundance may not accurately predict physiologic response. Proteins direct all levels of phenotype: structural proteins dictate physical form, enzymes catalyze biochemical reactions, and proteins act as signaling proteins, antibodies, transporters, ion pumps, and transcription factors to control gene expression. Molecular initiating events (MIEs) of AOPs predominantly occur at the level of the protein (e.g. ligand-receptor binding) and proteomics can elucidate novel MIEs and mapping KEs in AOPs. This critical review highlights the need for proteomics in multi-omics studies in environmental toxicology and outlines steps required for inclusion and wider acceptance in chemical risk assessment. We also present case studies of multi-omics approaches that utilize proteomics and discuss some of the challenges and opportunities for proteomics in comparative ecotoxicology. Our intention is not to minimize the importance of other omics technologies, as each has strengths and limitations, but rather to encourage researchers to consider proteomics-based methods in multi-omics studies and AOP development.

Drivers of and Obstacles to the Adoption of Toxicogenomics for Chemical Risk Assessment: Insights from Social Science Perspectives

BACKGROUND

Some 20 y ago, scientific and regulatory communities identified the potential of omics sciences (genomics, transcriptomics, proteomics, metabolomics) to improve chemical risk assessment through development of toxicogenomics. Recognizing that regulators adopt new scientific methods cautiously given accountability to diverse stakeholders, the scope and pace of adoption of toxicogenomics tools and data have nonetheless not met the ambitious, early expectations of omics proponents.

OBJECTIVE

Our objective was, therefore, to inventory, investigate, and derive insights into drivers of and obstacles to adoption of toxicogenomics in chemical risk assessment. By invoking established social science frameworks conceptualizing innovation adoption, we also aimed to develop recommendations for proponents of toxicogenomics and other new approach methodologies (NAMs).

METHODS

We report findings from an analysis of 56 scientific and regulatory publications from 1998 through 2017 that address the adoption of toxicogenomics for chemical risk assessment. From this purposeful sample of toxicogenomics discourse, we identified major categories of drivers of and obstacles to adoption of toxicogenomics tools and data sets. We then mapped these categories onto social science frameworks for conceptualizing innovation adoption to generate actionable insights for proponents of toxicogenomics.

DISCUSSION

We identify the most salient drivers and obstacles. From 1998 through 2017, adoption of toxicogenomics was understood to be helped by drivers such as those we labeled Superior scientific understanding, New applications, and Reduced cost & increased efficiency but hindered by obstacles such as those we labeled Insufficient validation, Complexity of interpretation, and Lack of standardization. Leveraging social science frameworks, we find that arguments for adoption that draw on the most salient drivers, which emphasize superior and novel functionality of omics as rationales, overlook potential adopters' key concerns: simplicity of use and compatibility with existing practices. We also identify two perspectives-innovation-centric and adopter-centric-on omics adoption and explain how overreliance on the former may be undermining efforts to promote toxicogenomics. https://doi.org/10.1289/EHP6500.

Disentangling of the ecotoxicological signal using "omics" analyses, a lesson from the survey of the impact of cyanobacterial proliferations on fishes

Omics technologies offer unprecedented perspectives for the rational investigation of complex biological systems. Indeed, omics present the ability of offering an extensive perception of the biochemistry and physiology of the cell and of any perturbing consequences of contaminants through the joint investigation of thousands of molecular responses simultaneously; then it has recently conducted to a fervent attention by research ecotoxicologists. Beyond the presentation of latest advances, exemplified here by omics investigation of cyanobacterial deleterious effects on various fishes (at various experimental and biological scales and with various analytical tools and pipeline), the present review paper re-explores the promising perspectives and also the pitfalls of such holistic investigations of the ecotoxicological response of organisms for environmental assessment.

Gene Pyramiding for Sustainable Crop Improvement against Biotic and Abiotic Stresses

Sustainable agricultural production is endangered by several ecological factors, such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop-breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker-assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to biotic and abiotic stresses for sustainable crop improvement.

Mode of action-based risk assessment of genotoxic carcinogens

The risk assessment of chemical carcinogens is one major task in toxicology. Even though exposure has been mitigated effectively during the last decades, low levels of carcinogenic substances in food and at the workplace are still present and often not completely avoidable. The distinction between genotoxic and non-genotoxic carcinogens has traditionally been regarded as particularly relevant for risk assessment, with the assumption of the existence of no-effect concentrations (threshold levels) in case of the latter group. In contrast, genotoxic carcinogens, their metabolic precursors and DNA reactive metabolites are considered to represent risk factors at all concentrations since even one or a few DNA lesions may in principle result in mutations and, thus, increase tumour risk. Within the current document, an updated risk evaluation for genotoxic carcinogens is proposed, based on mechanistic knowledge regarding the substance (group) under investigation, and taking into account recent improvements in analytical techniques used to quantify DNA lesions and mutations as well as "omics" approaches. Furthermore, wherever possible and appropriate, special attention is given to the integration of background levels of the same or comparable DNA lesions. Within part A, fundamental considerations highlight the terms hazard and risk with respect to DNA reactivity of genotoxic agents, as compared to non-genotoxic agents. Also, current methodologies used in genetic toxicology as well as in dosimetry of exposure are described. Special focus is given on the elucidation of modes of action (MOA) and on the relation between DNA damage and cancer risk. Part B addresses specific examples of genotoxic carcinogens, including those humans are exposed to exogenously and endogenously, such as formaldehyde, acetaldehyde and the corresponding alcohols as well as some alkylating agents, ethylene oxide, and acrylamide, but also examples resulting from exogenous sources like aflatoxin B1, allylalkoxybenzenes, 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline (MeIQx), benzo[a]pyrene and pyrrolizidine alkaloids. Additionally, special attention is given to some carcinogenic metal compounds, which are considered indirect genotoxins, by accelerating mutagenicity via interactions with the cellular response to DNA damage even at low exposure conditions. Part C finally encompasses conclusions and perspectives, suggesting a refined strategy for the assessment of the carcinogenic risk associated with an exposure to genotoxic compounds and addressing research needs.

Assessing Toxicity with Human Cell-Based In Vitro Methods

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

In vitro toxicological characterisation of the antifungal compound soybean toxin (SBTX)

Soybean toxin (SBTX) is a protein isolated from soybean seeds and composed of two polypeptide subunits (17 and 27 kDa). SBTX has in vitro activity against phytopathogenic fungi such as Cercospora sojina, Aspergillus niger, and Penicillium herguei, and yeasts like Candida albicans, C. parapsilosis, Kluyveromyces marxiannus, and Pichia membranifaciens. The present study aimed to analyze in vitro whether SBTX causes any side effects on non-target bacterial and mammalian cells that could impede its potential use as a novel antifungal agent. SBTX at 100 μg/mL and 200 μg/mL did not hinder the growth of the bacteria Salmonella enterica (subspecies enterica serovar choleraesuis), Bacillus subtilis (subspecies spizizenii) and Staphylococcus aureus. Moreover, SBTX at concentrations up to 500 μg/mL did not significantly affect the viability of erythrocytes, neutrophils, and human intestinal Caco-2 cells. To study whether SBTX could induce relevant alterations in gene expression, in vitro DNA microarray experiments were conducted in which differentiated Caco-2 cells were exposed for 24 h to 100 μg/mL or 200 μg/mL SBTX. SBTX up-regulated genes involved in cell cycle and immune response pathways, but down-regulated genes that play a role in cholesterol biosynthesis and platelet degranulation pathways. Thus, although SBTX did not affect bacteria, nor induced cytotoxity in mammalian cells, it affected some biological pathways in the human Caco-2 cell line that warrants further investigation.

Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach

The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.

Factors Affecting the Perception of New Approach Methodologies (NAMs) in the Ecotoxicology Community

Given current legislative mandates to assess the safety of thousands of chemicals and the slow pace at which conventional testing proceeds, there is a need to accelerate chemical risk assessment. Governments and businesses are increasingly interested in new approach methodologies (NAMs) that promise to reduce costs and delays. We explore 5 sociological factors within the ecotoxicology community that can influence the perception of NAMs: 1) professional profile (educational cohort, employer), 2) internal science communication within professional forums, 3) concern for "error cost," 4) collaboration across stakeholders, and 5) fundamental beliefs regarding toxicology. We conducted an online survey (n = 171; 2018) asking participants about their experiences and perspectives at events of the Society of Environmental Toxicology and Chemistry (SETAC) to assess 1) how NAMs are discussed compared to conventional testing and 2) how respondents perceive their viability. We developed ordered logistic regression (OLR) models to understand the influence of exploratory variables (cohort, core views on toxicology, frequency of collaboration) on respondents' evaluation of the viability of different NAMs. Our results showed that 1) NAMs were more likely than conventional methods to be challenged in forum discussions, which may be fueled by concerns for error costs in regulatory decision making; 2) perceptions of the viability of NAMs tended to follow a "pattern of familiarity," whereby respondents that were more knowledgeable about a test method tended to find it more viable; 3) respondents who agreed with the Paracelsus maxim had a greater likelihood of finding conventional testing viable; and 4) the more a respondent reported collaborating with industry on alternative testing strategies, the more likely she or he was to report that NAMs were less viable. These results suggest that there are professional and organizational barriers to greater acceptance of NAMs that can be addressed through a social learning process within the professional community. Integr Environ Assess Manag 2020;16:269-281. © 2020 SETAC.

Prospects and challenges of multi-omics data integration in toxicology

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

A bioinformatics workflow for the evaluation of RT-qPCR primer specificity: Application for the assessment of gene expression data reliability in toxicological studies

The reliability of Reverse Transcription quantitative real-time PCR (RT-qPCR) gene expression data depends on proper primer design and RNA quality controls. Despite freely available genomic databases and bioinformatics tools, primer design deficiencies can be found across life science publications. In order to assess the prevalence of such deficiencies in the toxicological literature, 504 primer sets extracted from a random selection of 70 recent rat toxicological studies were evaluated. The specificity of each primer set was systematically analysed using a bioinformatics workflow developed from publicly available resources (NCBI Primer BLAST, in silico PCR in UCSC genome browser, Ensembl DNA database). Potential mismatches (9%), cross-matches (13.5%), co-amplification of multiple gene splice variants (9%) and sub-optimal amplicon sizes (25%) were identified for a significant proportion of the primer sets assessed in silico. Quality controls for gDNA contamination of RNA samples were infrequently reported in the surveyed manuscripts. Hence, the impacts of gDNA contamination on RT-qPCR data were further investigated, revealing that lowly expressed genes presented higher susceptibility to contaminating gDNA. In addition to the retrospective identification of potential primer design issues presented in this study, the described bioinformatics workflow can also be used prospectively to select candidate primer sets for experimental validation.

Monitoring from Battlefield to Bedside: Serum Repositories Help Identify Biomarkers, Perspectives on Mild Traumatic Brain Injury

OBJECTIVES

Serum repositories are foundations for seroepidemiological data, revealing targeted information about morbidities and existing heterogeneity in human populations. With the recent technological advances, we can perform high-throughput screening at an affordable cost using minimal plasma. Monitoring brain health after an injury is critical since mild Traumatic Brain Injury (mTBI) and other neurological symptoms are under-diagnosed. Our objective in this study is to present our preliminary serological data from one of our ongoing studies on mTBI.

METHODS

In this retrospective study, we used stored plasma samples to understand biomarkers of mTBI. We compared plasma samples from five patients with mTBI following their first concussive episode to five gender and age-matched healthy controls. We assessed multiple biomarkers to show the importance of biorepositories.

RESULTS

Most of the estimated plasma factors in mTBI subjects at baseline were comparable to normal healthy individuals except for the astroglial markers S100B and glial fibrillary acidic protein. Fluctuations of these biomarkers can affect the homeostasis of brain parenchyma by altering the neural network signaling, which in turn may result in intermittent behavioral symptoms.

CONCLUSION

Biorepositories are powerful resources for understanding the spectrum of morbidity. Biomarkers serve as a valuable diagnostic and therapeutic tool.