Short-term test for the toxicogenomic assessment of ecotoxic modes of action in Myriophyllum spicatum

In environmental risk assessment of substances, the 14-day growth inhibition test following OECD test guideline 239 is employed to assess toxicity in the macrophyte Myriophyllum spicatum. Currently, this test evaluates physiological parameters and does not allow the identification of the mode of action (MoA) by which adverse effects are induced. However, for an improved ecotoxicity assessment of substances, knowledge about their ecotoxic MoA in non-target organisms is required. It has previously been suggested that the identification of gene expression changes can contribute to MoA identification. Therefore, we developed a shortened three-day assay for M. spicatum including the transcriptomic assessment of global gene expression changes and applied this assay to two model substances, the herbicide and photosynthesis inhibitor bentazone and the pharmaceutical and HMG-CoA reductase inhibitor atorvastatin. Due to the lack of a reference genome for M. spicatum we performed a de novo transcriptome assembly followed by a functional annotation to use the toxicogenomic results for MoA discrimination. The gene expression changes induced by low effect concentrations of these substances were used to identify differentially expressed genes (DEGs) and impaired biological functions for the respective MoA. We observed both concentration-dependent numbers and differentiated patterns of DEGs for both substances. While bentazone impaired genes involved in the response to reactive oxygen species as well as light response, and also genes involved in developmental processes, atorvastatin exposure led to a differential regulation of genes related to brassinosteroid response as well as potential metabolic shifts between the mevalonate and methyl erythritol 4-phosphate pathway. Based on these responses, we identified biomarker candidates for the assessment of MoA in M. spicatum. Utilizing the shortened assay developed in this study, the investigation of the identified biomarker candidates may contribute to the development of future MoA-specific screening approaches in the ecotoxicological hazard prediction using aquatic non-standard model organisms.

Toxicogenomics of Five Cytostatics in Fathead Minnow (Pimephales promelas) Larvae

In this study, the toxicogenomic effects of five cytostatics (tamoxifen, methotrexate, capecitabine, cyclophosphamide, and ifosfamide) on fathead minnow (Pimephales promelas) larvae were evaluated. Post-fertilization eggs were exposed to increasing concentrations of the drugs for six days. The expression levels of two genetic biomarkers for toxicity and four thyroid hormone-related gene pathways were measured. Interestingly, the results showed that all concentrations of the five cytostatics affect the transcription levels of both toxicity biomarker genes. Additionally, the thyroid hormone-related genes had different expression levels than the control, with the most significant changes observed in those larvae exposed to cyclophosphamide and ifosfamide. While a previous study found no effects on fish morphology, this study suggests that the five cytostatics modify subtle molecular responses of P. promelas, highlighting the importance of assessing multibiological level endpoints throughout the lifecycle of animals to understand the full portrait of potential effects of cytostatics and other contaminants.

Exploring the molecular mechanisms by which per- and polyfluoroalkyl substances induce polycystic ovary syndrome through in silico toxicogenomic data mining

The pathogeny of polycystic ovary syndrome (PCOS) is intricate, with endocrine disruptors (EDCs) being acknowledged as significant environmental factors. Research has shown a link between exposure to per- and polyfluoroalkyl substances (PFAS) and the development and progression of PCOS, although the precise mechanism is not fully understood. This study utilized toxicogenomics and comparative toxicogenomics databases to analyze data and investigate how PFAS mixtures may contribute to the development of PCOS. The results indicated that 74 genes are associated with both PFAS exposure and PCOS progression. Enrichment analysis suggested that cell cycle regulation and steroid hormone synthesis may be crucial pathways through which PFAS mixtures participate in the development of PCOS, involving important genes such as CCNB1 and SRD5A1. Furthermore, the study identified transcription factors (TFs) and miRNAs that may be involved in the onset and progression of PCOS, constructing regulatory networks encompassing TFs-mRNA interactions and miRNA-mRNA relationships to elucidate their regulatory roles in gene expression. By utilizing data mining techniques based on toxicogenomic databases, this study provides relatively comprehensive insights into the association between exposure factors and diseases compared to traditional toxicology studies. These findings offer new perspectives for further in vivo or in vitro investigations and contribute to understanding the pathogenesis of PCOS, thereby providing valuable references for identifying clinical treatment targets.

Screening the critical protein subnetwork to delineate potential mechanisms and protective agents associated with arsenic-induced cutaneous squamous cell carcinoma: A toxicogenomic study

Recent studies show that complex mechanisms are involved in arsenic-induced malignant transformation of cells. This study aimed to decipher molecular mechanisms associated with arsenic-induced cutaneous squamous cell carcinoma (cSCC) and suggest potential protective factors. RNA-seq-based differentially expressed genes between arsenic-exposed human keratinocytes (HaCaT) and controls were used to construct a protein-protein interaction (PPI) network and discover critical subnetwork-based mechanisms. Protective compounds against arsenic toxicity were determined and their target interactions in the core sub-network were identified by the comparative toxicogenomic database (CTD). The binding affinity between the effective factor and target was calculated by molecular docking. A total of 15 key proteins were screened out as critical arsenic-responsive subnetwork (FN1, IL-1A, CCN2, PECAM1, FGF5, EDN1, FGF1, PXDN, DNAJB9, XBP1, ERN1, PDIA4, DNAJB11, FOS, PDIA6) and 7 effective protective agents were identified (folic acid, quercetin, zinc, acetylcysteine, methionine, catechin, selenium). The GeneMANIA predicted detailed interactions of the subnetwork and revealed terms related to unfolded protein response as the main processes. FN1, IL1A and CCN2, as top significant genes, had good docking affinity with folic acid and quercetin, as selected key compounds. Integration of gene expression and protein-protein interaction related to arsenic exposure in cSCC explored the potential mechanisms and protective agents.

DTox: A deep neural network-based in visio lens for large scale toxicogenomics data

With the advancement of large-scale omics technologies, particularly transcriptomics data sets on drug and treatment response repositories available in public domain, toxicogenomics has emerged as a key field in safety pharmacology and chemical risk assessment. Traditional statistics-based bioinformatics analysis poses challenges in its application across multidimensional toxicogenomic data, including administration time, dosage, and gene expression levels. Motivated by the visual inspection workflow of field experts to augment their efficiency of screening significant genes to derive meaningful insights, together with the ability of deep neural architectures to learn the image signals, we developed DTox, a deep neural network-based in visio approach. Using the Percellome toxicogenomics database, instead of utilizing the numerical gene expression values of the transcripts (gene probes of the microarray) for dose-time combinations, DTox learned the image representation of 3D surface plots of distinct time and dosage data points to train the classifier on the experts' labels of gene probe significance. DTox outperformed statistical threshold-based bioinformatics and machine learning approaches based on numerical expression values. This result shows the ability of image-driven neural networks to overcome the limitations of classical numeric value-based approaches. Further, by augmenting the model with explainability modules, our study showed the potential to reveal the visual analysis process of human experts in toxicogenomics through the model weights. While the current work demonstrates the application of the DTox model in toxicogenomic studies, it can be further generalized as an in visio approach for multi-dimensional numeric data with applications in various fields in medical data sciences.

The alternation of halobenzoquinone disinfection byproduct on toxicogenomics of DNA damage and repair in uroepithelial cells

Halobenzoquinones (HBQs) were recently discovered as an emerging class of drinking water disinfection byproducts with carcinogenic concern. However, the molecular mechanism underlying HBQs-induced DNA damage is not clear. In this study, we integrated in vitro genotoxicity, computational toxicology, and the quantitative toxicogenomic analysis of HBQs on DNA damage/repair pathways in human bladder epithelial cells SV-HUC-1. The results showed that HBQs could induce cytotoxicity with the descending order as 2,6-DIBQ > 2,6-DCBQ ≈ 2,6-DBBQ. Also, HBQs can increase DNA damage in SV-HUC-1 cells and thus generate genotoxicity. However, there is no significant difference in genotoxicity among the three HBQs. The results of molecular docking and molecular dynamics simulation further confirmed that HBQs had high binding fractions and stability to DNA. Toxicogenomic analysis indicated that HBQs interfered with DNA repair pathways, mainly affecting base excision repair, nucleotide excision repair and homologous recombination repair. These results have provided new insights into the underlying molecular mechanisms of HBQs-induced DNA damage, and contributed to the understanding of the relationship between exposure to DBPs and risks of developing bladder cancer.

Toxicity of Metal Oxide Nanoparticles: Looking through the Lens of Toxicogenomics

The impact of solubility on the toxicity of metal oxide nanoparticles (MONPs) requires further exploration to ascertain the impact of the dissolved and particulate species on response. In this study, FE1 mouse lung epithelial cells were exposed for 2-48 h to 4 MONPs of varying solubility: zinc oxide, nickel oxide, aluminum oxide, and titanium dioxide, in addition to microparticle analogues and metal chloride equivalents. Previously published data from FE1 cells exposed for 2-48 h to copper oxide and copper chloride were examined in the context of exposures in the present study. Viability was assessed using Trypan Blue staining and transcriptomic responses via microarray analysis. Results indicate material solubility is not the sole property governing MONP toxicity. Transcriptional signaling through the 'HIF-1α Signaling' pathway describes the response to hypoxia, which also includes genes associated with processes such as oxidative stress and unfolded protein responses and represents a conserved response across all MONPs tested. The number of differentially expressed genes (DEGs) in this pathway correlated with apical toxicity, and a panel of the top ten ranked DEGs was constructed (Hmox1, Hspa1a, Hspa1b, Mmp10, Adm, Serpine1, Slc2a1, Egln1, Rasd1, Hk2), highlighting mechanistic differences among tested MONPs. The HIF-1α pathway is proposed as a biomarker of MONP exposure and toxicity that can help prioritize MONPs for further evaluation and guide specific testing strategies.

Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research

Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.

Involvement of toxic metals and PCBs mixture in the thyroid and male reproductive toxicity: In silico toxicogenomic data mining

Toxicological research is mostly limited to considering the effects of a single substance, even though the real exposure of people is reflected in their daily exposure to many different chemical substances in low-doses. This in silico toxicogenomic study aims to provide evidence for the selected environmental (organo)metals (lead, cadmium, methyl mercury) + polychlorinated biphenyls mixture involvement in the possible alteration of thyroid, and male reproductive system function, and furthermore to predict the possible toxic mechanisms of the environmental cocktail. The Comparative Toxicogenomic Database, GeneMANIA online software, and ToppGene Suite portal were used as the main tools for toxicogenomic data mining and gene ontology analysis. The results show that 35 annotated common genes between selected chemicals and endocrine system diseases can interact on the co-expression level. Our study highlighted the disruption of the cytokines, the cell's response to oxidative stress, and the influence of the transcription factors as the potential core of toxicological mechanisms of the discussed mixture's effects. The connected toxicological effects of the tested mixture were abnormal sperm cells, a disrupted level of testosterone, and thyroid hormones. The core mechanisms of these effects were inflammation, oxidative stress, disruption of androgen receptor signaling, and the alteration of the FOXO3-Keap-1/NRF2-HMOX1-NQO1 pathway signaling most likely controlled by the co-expression of overlapped genes among used chemicals. This in silico research can be used as a potential core for the determination of biomarkers that can be monitored in future further in vitro and in vivo experiments.

Toxicogenetic, biochemical, and anatomical effects of the herbicide Clethodim on Allium cepa L

Pesticides are compounds with several chemical or biological agents developed to potentiate the biocide action. Their use is associated with increased economic and agricultural productivity worldwide but can harm health and the environment, damaging existing biota. Clethodim is a systemic post-emergent herbicide for grasses, highly selective for cotton, coffee, onions, carrots, soybeans, etc. Therefore, this work aimed to evaluate the harmful effect of the herbicide Clethodim with the model plant Allium cepa. A series of tests were conducted to evaluate the effects of the herbicide under study. Germination tests, root growth, cell, and nucleolar cycle analysis, as well as oxidative stress assessment and histological analysis of the roots, were performed. The results indicated that the herbicide demonstrated phytotoxicity, inhibiting germination at C1 (1.92 g/L) and C3 (0.84 g/L), and root growth at all concentrations, presenting mutagenicity at C1 (1.92 g/L) and C4 (0.24 g/L), evidenced by the increased frequency of micronuclei. In addition, changes were observed in the enzymatic activity of the enzymes catalase at concentrations C1 (1.92 g/L) and C2 (0.96 g/L) and ascorbate peroxidase at concentrations C1 (1.92 g/L), C2 (0. 96 g/L), and C3 (0.48 g/L) and in cell elongation at concentrations C1 (1.92 g/L) and C3 (0.48 g/L), demonstrated in histological analyses of the root apex.

Transgenerational effects of BDE-47 to zebrafish based on histomorphometry and toxicogenomic analyses

Exposure to 2, 2', 4, 4'-tetrabromodiphenyl ether (BDE-47) has been found to have an impact on reproductive output and endocrine function in female zebrafish (Danio rerio). However, the transgenerational effects of BDE-47 have not been fully explored in previous reports. In this study, female zebrafish were exposed to BDE-47 for three consecutive weeks. The oogenesis, sex hormones, reproductive histology, and transcriptional profiles of genes along the hypothalamus-pituitary-gonad (HPG) axis were assessed in the exposed-F0 generation. After mating with unexposed males, the transgenerational effects of BDE-47 were evaluated on the basis of histopathology, morphometry and toxicogenome of the unexposed F1 generations at the larval stage. Results indicated that exposure to BDE-47 impaired reproductive capacity, disrupted endocrine system in F0 zebrafish, and compromised craniofacial skeletons and vertebrae development in F1 generations. In addition, through the use of toxicogenomics approach, immune-responsive pathways were found to be significantly enriched, and the transcript expression profiling of immune-related DEGs (IRDs) were dramatically inhibited in F1 generations following maternal BDE-47 exposure, indicating its immunotoxicity to offspring larvae. These findings advance our understanding of the transgenerational toxicity of BDE-47 and advocate for a more comprehensive assessment of other PBDE congeners through histomorphometry and toxicogenomic approaches.

Toxicogenomic Effects of Dissolved Saxitoxin on the Early Life Stages of the Longfin Yellowtail (Seriola rivoliana)

Harmful algal blooms (HABs) can produce a variety of noxious effects and, in some cases, the massive mortality of wild and farmed marine organisms. Some HAB species produce toxins that are released into seawater or transferred via food webs (particulate toxin fraction). The objective of the present study was to identify the toxicological effects of subacute exposure to saxitoxin (STX) during embryonic and early larval stages in Seriola rivoliana. Eggs were exposed to dissolved 19 STX (100 μg L-1). The toxic effects of STX were evaluated via the hatching percentage, the activity of three enzymes (protein and alkaline phosphatases and peroxidase), and the expression of four genes (HSF2, Nav1.4b, PPRC1, and DUSP8). A low hatching percentage (less than 5%) was observed in 44 hpf (hours post fertilization) embryos exposed to STX compared to 71% in the unexposed control. At this STX concentration, no oxidative stress in the embryos was evident. However, STX induced the expression of the NaV1.4 channel α-subunit (NaV1.4b), which is the primary target of this toxin. Our results revealed the overexpression of all four candidate genes in STX-intoxicated lecithotrophic larvae, reflecting the activation of diverse cellular processes involved in stress responses (HSF2), lipid metabolism (PPRC1), and MAP kinase signaling pathways associated with cell proliferation and differentiation (DUSP8). The effects of STX were more pronounced in young larvae than in embryos, indicating a stage-specific sensitivity to the toxin.

Effects of mixed heavy metals on obstructive lung function: findings from epidemiological and toxicogenomic data

The molecular mechanisms and associations of mixed heavy metals (lead, mercury, and cadmium) on obstructive lung function (OLF) in males and females remain unknown. Here, we evaluated the interaction between the forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) ratio and three common heavy metals in males and females (n = 6221). Molecular processes involved in OLF development caused by mixed heavy metals were also identified to corroborate the earlier findings. In both males and females, as well as across the entire population, we found that serum cadmium levels were inversely related to the FEV1/FVC ratio. Interactions between serum cadmium and lead, as well as cadmium and mercury, were observed in relation to the FEV1/FVC ratio. Additionally, we observed negative correlations between the FEV1/FVC ratio and mixed serum cadmium, lead, and mercury in both men and women as well as in the overall population. Seven genes were identified as contributing to the etiology of OLF and targeted by combined heavy metals in silico analysis (CYP1A1, CRP, CXCL8, HMOX1, IL6, NOS2, and TNF). The primary relationships between these genes were co-expression interactions. The significant transcription factors and miRNAs associated with OLF and a combination of the examined heavy metals were identified as NFKB2, hsa-miR-155-5p, and hsa-miR-203a-3p. The main biological processes involved in the emergence of OLF induced by mixed heavy metals were listed as inflammatory and oxidative stress pathways, lung fibrosis, chronic obstructive pulmonary disease, as well as cytokine activity, monooxygenase activity, oxidoreductase activity, and interleukin-8 production. Threshold estimations and miRNA sponge patterns for heavy metal exposure levels associated with OLF were evaluated for both males and females. This study found that cadmium plays the most important role in the mixture of cadmium, lead, and mercury in the pathogenesis of OLF. Future studies are required to verify our findings and uncover the molecular mechanisms of long-term exposure to a variety of heavy metals, especially cadmium, in other populations, including children, adolescents, and the elderly.

Abnormality of mussel in the early developmental stages induced by graphene and triphenyl phosphate: In silico toxicogenomic data-mining, in vivo, and toxicity pathway-oriented approach

Increasing number of complex mixtures of organic pollutants in coastal area (especially for nanomaterials and micro/nanoplastics associated chemicals) threaten aquatic ecosystems and their joint hazards are complex and demanding tasks. Mussels are the most sensitive marine faunal groups in the world, and their early developmental stages (embryo and larvae) are particularly susceptible to environmental contaminants, which can distinguish the probable mechanisms of mixture-induced growth toxicity. In this study, the potential critical target and biological processes affected by graphene and triphenyl phosphate (TPP) were developed by mining public toxicogenomic data. And their combined toxic effects were verified by toxicological assay at early developmental stages in filter-feeding mussels (embryo and larvae). It showed that interactions among graphene/TPP with 111 genes (ABCB1, TP53, SOD, CAT, HSP, etc.) affected phenotypes along conceptual framework linking these chemicals to developmental abnormality endpoints. The PPAR signaling pathway, monocarboxylic acid metabolic process, regulation of lipid metabolic process, response to oxidative stress, and gonad development were noted as the key molecular pathways that contributed to the developmental abnormality. Enriched phenotype analysis revealed biological processes (cell proliferation, cell apoptosis, inflammatory response, response to oxidative stress, and lipid metabolism) affected by the investigated mixture. Combined, our results supported that adverse effects induced by contaminants/ mixture could not only be mediated by single receptor signaling or be predicted by the simple additive effect of contaminants. The results offer a framework for better comprehending the developmental toxicity of environmental contaminants in mussels and other invertebrate species, which have considerable potential for hazard assessment of coastal mixture.

Toxicogenomics Approaches to Address Toxicity and Carcinogenicity in the Liver

Toxicogenomic technologies query the genome, transcriptome, proteome, and the epigenome in a variety of toxicological conditions. Due to practical considerations related to the dynamic range of the assays, sensitivity, cost, and technological limitations, transcriptomic approaches are predominantly used in toxicogenomics. Toxicogenomics is being used to understand the mechanisms of toxicity and carcinogenicity, evaluate the translational relevance of toxicological responses from in vivo and in vitro models, and identify predictive biomarkers of disease and exposure. In this session, a brief overview of various transcriptomic technologies and practical considerations related to experimental design was provided. The advantages of gene network analyses to define mechanisms were also discussed. An assessment of the utility of toxicogenomic technologies in the environmental and pharmaceutical space showed that these technologies are being increasingly used to gain mechanistic insights and determining the translational relevance of adverse findings. Within the environmental toxicology area, there is a broader regulatory consideration of benchmark doses derived from toxicogenomics data. In contrast, these approaches are mainly used for internal decision-making in pharmaceutical development. Finally, the development and application of toxicogenomic signatures for prediction of apical endpoints of regulatory concern continues to be area of intense research.

CTD tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health

The molecular mechanisms connecting environmental exposures to adverse endpoints are often unknown, reflecting knowledge gaps. At the Comparative Toxicogenomics Database (CTD), we developed a bioinformatics approach that integrates manually curated, literature-based interactions from CTD to generate a "CGPD-tetramer": a 4-unit block of information organized as a step-wise molecular mechanism linking an initiating Chemical, an interacting Gene, a Phenotype, and a Disease outcome. Here, we describe a novel, user-friendly tool called CTD Tetramers that generates these evidence-based CGPD-tetramers for any curated chemical, gene, phenotype, or disease of interest. Tetramers offer potential solutions for the unknown underlying mechanisms and intermediary phenotypes connecting a chemical exposure to a disease. Additionally, multiple tetramers can be assembled to construct detailed modes-of-action for chemical-induced disease pathways. As well, tetramers can help inform environmental influences on adverse outcome pathways (AOPs). We demonstrate the tool's utility with relevant use cases for a variety of environmental chemicals (eg, perfluoroalkyl substances, bisphenol A), phenotypes (eg, apoptosis, spermatogenesis, inflammatory response), and diseases (eg, asthma, obesity, male infertility). Finally, we map AOP adverse outcome terms to corresponding CTD terms, allowing users to query for tetramers that can help augment AOP pathways with additional stressors, genes, and phenotypes, as well as formulate potential AOP disease networks (eg, liver cirrhosis and prostate cancer). This novel tool, as part of the complete suite of tools offered at CTD, provides users with computational datasets and their supporting evidence to potentially fill exposure knowledge gaps and develop testable hypotheses about environmental health.

An in silico toxicogenomic approach in constructing the aflatoxin B1-mediated regulatory network of hub genes in hepatocellular carcinoma

Aflatoxin B1 (AFB1) can cause hepatocellular carcinoma (HCC) through a mutagenic mode of action but can also lead to global changes in gene expression; however, the AFB1 network of molecular pathways involved in HCC is not known. Here, we used toxicogenomic data from human liver cells exposed to AFB1 to infer the network of AFB1-responsive molecular pathways involved in HCC. The following computational tools: STRING, MCODE, cytoHubba, iRegulon, kinase enrichment tool KEA3, and DAVID were used to identify protein-protein interaction network, hub genes, transcription factors (TFs), upstream kinases, and biological processes (BPs). Predicted molecular events were validated with an external dataset, whereas the hub genes in HCC were validated using the UALCAN database. The results revealed an association between AFB1 and the hub genes involved in the cell cycle. We identified TFs that regulate the hub genes and linked them with upstream kinases including cyclin-dependent kinases, mitogen-activated protein kinase 1, and AKT. This approach enabled the construction of the AFB1-mediated regulatory network consisting of upstream kinases, TFs, hub genes, and BPs, thus revealing the signaling hierarchy and information flow that may contribute to AFB1-induced HCC. This could be a useful tool in predicting the molecular mechanisms involved in chemical-induced diseases when available toxicogenomic data exist.

The Effect of Historical Data-Based Informative Prior on Benchmark Dose Estimation of Toxicogenomics

High-throughput toxicogenomics as an advanced toolbox of Tox21 plays an increasingly important role in facilitating the toxicity assessment of environmental chemicals. However, toxicogenomic dose-response analyses are typically challenged by limited data, which may result in significant uncertainties in parameter and benchmark dose (BMD) estimation. Integrating historical data via prior distribution using a Bayesian method is a useful but not-well-studied strategy. The objective of this study is to evaluate the effectiveness of informative priors in genomic dose-response modeling and BMD estimation. Specifically, we aim to identify plausible informative priors and evaluate their effects on BMD estimates at both gene and pathway levels. A general informative prior and eight time-specific (from 3 h to 29 d) informative priors for seven commonly used continuous dose-response models were derived. Results suggest that the derived informative priors are sensitive to the specific data sets used for elicitation. Real data-based simulations indicate that BMD estimation with the time-specific informative priors can achieve increased or equivalent accuracy, significantly decreased uncertainty, and a slightly enhanced correlation with the points of departure estimated from apical end points than the counterparts with noninformative priors. Overall, our study systematically examined the effects of historical data-based informative priors on BMD estimates, highlighting the benefits of plausible information priors in advancing the practice of toxicogenomics.

Face mask derived micro(nano)plastics and organic compounds potentially induce threat to aquatic ecosystem security revealed by toxicogenomics-based assay

Micro(nano)plastics widely detected in aquatic environments have caused serious threat to water quality security. However, as a potential important source of micro(nano)plastics in surface water during the COVID-19 pandemic, the ecological risks of face mask waste to aquatic environments remain poorly understood. Herein, we comprehensively characterized the micro(nano)plastics and organic compounds released from four daily used face masks in aqueous environments and further evaluated their potential impacts on aquatic ecosystem safety by quantitative genotoxicity assay. Results from spectroscopy and high-resolution mass spectrum showed that plastic microfibers/particles (∼11%-83%) and leachable organic compounds (∼15%-87%) were dominantly emitted pollutants, which were significantly higher than nanoplastics (< ∼5%) based on mass of carbon. Additionally, a toxicogenomics approach using green fluorescence protein-fused whole-cell array revealed that membrane stress was the primary response upon the exposure to micro(nano)plastics, whereas the emitted organic chemicals were mainly responsible for DNA damage involving most of the DNA repair pathways (e.g., base/nucleotide excision repair, mismatch repair, double-strand break repair), implying their severe threat to membrane structure and DNA replication of microorganisms. Therefore, the persistent release of discarded face masks derived pollutants might exacerbate water quality and even adversely affect aquatic microbial functions. These findings would contribute to unraveling the potential effects of face mask waste on aquatic ecosystem security and highlight the necessity for more developed management regulations in face mask disposal.

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.

Exposure to mixed chemicals elevated triiodothyronine (T3) and follicle-stimulating hormone (FSH) levels: epidemiology and in silico toxicogenomic involvement

There is a dearth of evidence on the effects of a mixture of numerous different types of chemicals on hormone functions. We hypothesized that exposure to mixed chemicals may alter hormone levels. Thus, this study was to identify an association between the mixed chemicals (25 chemicals) and hormone levels (thyroxine (T4) and triiodothyronine (T3), thyroid-stimulating hormone (TSH), and follicle-stimulating hormone (FSH)) among 5687 Korean adults using four different statistical approaches. Furthermore, we elucidate the effects of the key chemicals on thyroid disease and infertility based on the findings from epidemiology data. The positive associations between mixed chemicals and T3 and between mixed chemicals and FSH were observed across different methods after adjusting for all possible confounders. In the weighted quantile sum regression models, there were positive associations between mixed chemicals and T3 (β = 4.43, 95%CI: 2.81-5.88) and ln-transformed FSH (lnFSH) (β = 0.15, 95%CI: 0.10-0.20). In the quantile g-computation models, positive associations were found between mixed chemicals and T3 (β=2.15, 95%CI: 0.17-4.14) and lnFSH (β=0.15, 95%CI: 0.07-0.22). In the Bayesian kernel machine regression models, culminative effects of mixed chemicals showed positive associations with T3 and lnFSH; mercury (group posterior inclusion probabilities (PIPs) = 0.557 and conditional PPI = 0.556) and lead (group PIP group = 0.815 and conditional PPI = 0.951) were the most important chemicals for T3 and FSH, respectively. The results obtained were partially robust when subjected to in silico toxicogenomic data. We identified several molecular mechanisms that were implicated in Hg-induced thyroid disease, including the selenium micronutrient network, oxidative stress response, IL-17 signaling pathway, poorly differentiated thyroid carcinoma, and primary hyperthyroidism. The molecular processes implicated in Pb-induced infertility were "response to nutrient levels," "gonad development," "male infertility," "female infertility," and "intrinsic pathway for apoptosis," with a particular focus on FSH. The present study investigated the threshold levels of the studied chemicals and their potential impact on the disruption of T3 and FSH hormones. Future research is warranted to determine the effects of mixed chemicals on various hormones because there have been few studies on the disruption of hormones caused by such mixed chemicals.

A curated gene and biological system annotation of adverse outcome pathways related to human health

Adverse outcome pathways (AOPs) are emerging as a central framework in modern toxicology and other fields in biomedicine. They serve as an extension of pathway-based concepts by depicting biological mechanisms as causally linked sequences of key events (KEs) from a molecular initiating event (MIE) to an adverse outcome. AOPs guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation. While AOPs model the systemic mechanisms at various levels of biological organisation, toxicogenomics provides the means to study the molecular mechanisms of chemical exposures. Systematic integration of these two concepts would improve the application of AOP-based knowledge while also supporting the interpretation of complex omics data. Hence, we established this link through rigorous curation of molecular annotations for the KEs of human relevant AOPs. We further expanded and consolidated the annotations of the biological context of KEs. These curated annotations pave the way to embed AOPs in molecular data interpretation, facilitating the emergence of new knowledge in biomedicine.

Predicting thrombotic cardiovascular outcomes induced by waterpipe-associated chemicals using comparative toxicogenomic database: Genes, phenotypes, and pathways

Hookah, or waterpipe, is a tobacco smoking device that has gained popularity in the United States. A growing body of evidence demonstrates that waterpipe smoke (WPS) is associated with various adverse effects on human health, including infectious diseases, cancer, and cardiovascular diseases (CVDs), particularly thrombotic events. However, the molecular mechanisms through which WPS contributes to disease development remain unclear. In this study, we utilized an analytical approach based on the Comparative Toxicogenomics Database (CTD) to integrate chemical, gene, phenotype, and disease data to predict potential molecular mechanisms underlying the effects of WPS, based on its chemical and toxicant profile. Our analysis revealed that CVDs were among the top disease categories with regard to the number of curated interactions with WPS chemicals. We identified 5674 genes common between those modulated by WPS chemicals and traditional tobacco smoking. The CVDs with the most curated interactions with WPS chemicals were hypertension, atherosclerosis, and myocardial infarction, whereas "particulate matter", "heavy metals", and "nicotine" showed the highest number of curated interactions with CVDs. Our analysis predicted that the potential mechanisms underlying WPS-induced thrombotic diseases involve common phenotypes, such as inflammation, apoptosis, and cell proliferation, which are shared across all thrombotic diseases and the three aforementioned chemicals. In terms of enriched signaling pathways, we identified several, including chemokine and MAPK signaling, with particulate matter exhibiting the most statistically significant association with all 12 significant signaling pathways related to WPS chemicals. Collectively, our predictive comprehensive analysis provides evidence that WPS negatively impacts health and offers insights into the potential mechanisms through which it exerts these effects. This information should guide further research to explore and better understand the WPS and other tobacco product-related health consequences.

ESPERANTO: a GLP-field sEmi-SuPERvised toxicogenomics metadAta curatioN TOol

SUMMARY

Biological data repositories are an invaluable source of publicly available research evidence. Unfortunately, the lack of convergence of the scientific community on a common metadata annotation strategy has resulted in large amounts of data with low FAIRness (Findable, Accessible, Interoperable and Reusable). The possibility of generating high-quality insights from their integration relies on data curation, which is typically an error-prone process while also being expensive in terms of time and human labour. Here, we present ESPERANTO, an innovative framework that enables a standardized semi-supervised harmonization and integration of toxicogenomics metadata and increases their FAIRness in a Good Laboratory Practice-compliant fashion. The harmonization across metadata is guaranteed with the definition of an ad hoc vocabulary. The tool interface is designed to support the user in metadata harmonization in a user-friendly manner, regardless of the background and the type of expertise.

AVAILABILITY AND IMPLEMENTATION

ESPERANTO and its user manual are freely available for academic purposes at https://github.com/fhaive/esperanto. The input and the results showcased in Supplementary File S1 are available at the same link.

Comparative toxicogenomics of benzotriazole ultraviolet stabilizers at environmental concentrations in Asian clam (Corbicula fluminea): Insight into molecular networks and behavior

Benzotriazole ultraviolet stabilizers (BUVSs) are widespread emerging pollutants, which can pose exposure risks to benthic organisms. However, the toxicity and mechanisms of BUVSs congeners in benthic clams are far from elucidated. In this study, Asian clams (Corbicula fluminea) were exposed to one of UV-234, UV-326, UV-329, or UV-P at environmentally relevant levels (0.1, 1, and 10 μg/L) for 21 days. Filtration rate (FR) was increased in clams exposed to all BUVSs and there were notable histopathologic changes, including irregular digestive lumen, lipid droplet vacuolation, and degraded epithelial cells. To determine the molecular underpinnings following BUVSs exposure, the transcriptome responses in digestive glands were compared. Differentially expressed genes shared among BUVSs treatments were associated with focal adhesion, TNF-α/NF-κB proinflammatory pathways, and apoptosis. Following this, biochemical analysis of biomarkers related to apoptosis were conducted to further validate response. Exposure to BUVSs inhibited anti-oxidant enzyme activity and induced oxidative stress. Heat shock proteins were also triggered with exposure, and there was an induction of caspase-3 and caspase-9 activity. Molecular responses were not identical in the digestive gland of C. fluminea when comparing responses to BUVSs; nevertheless conserved mechanism (impairment of the oxidative defense system, immune system disruption, and induction of apoptosis) among BUVSs congeners was noted. This study provides novel insight into the toxicity and hazards of BUVSs in benthic organisms.

Toxicogenomic signatures associated with methylmercury induced developmental toxicity in the zebrafish embryos

Methylmercury (MeHg) is a toxicant with adverse effects on embryogenesis from fish to man. The developmental outcomes of MeHg are well understood, but molecular understanding of toxicity is rather limited. We performed here a genome-wide transcriptional analyses of 6, 30, and 50 μg/L MeHg exposed zebrafish embryos from 4 to 72 h post-fertilization (hpf) using RNA-sequencing and microarray, and conducted a systematical comparison of MeHg-induced transcriptomic responses reported in this and our previous studies. We observed MeHg significantly to disrupt expression of 1050, 1931, and 2996 genes, respectively including gene ontologies in terms of visual and sensory perception, phototransduction, ferroptosis, and GABAergic synapse. Significantly altered genes were associated with ontology categorized into metabolism, such as fatty acid, amino acid, and glutathione metabolism across all experiments. Expression of genes involved in Wnt, Shh, and Notch signaling pathways previously demonstrated to be crucial for development was changed at varying levels dependent on exposure concentrations and durations. Our findings show MeHg significantly to affect expression of genes associated with tissue and/or organs developmental processing including eye, lateral line, fins, and brain, especially in embryos exposed to 6 μg/L, which did not cause obviously toxic effects on zebrafish embryos. We obtain 21 genes being significantly altered by MeHg in a concentration and stage independent manner, and might be served as signatures for developmental toxicity and/or teratogenic effects.

In vitro toxicity assessment of haloacetamides via a toxicogenomics assay

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

Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that can reduce animal experimentation. However, to unleash the full potential of AOPs and build confidence into toxicogenomics, robust associations between AOPs and patterns of molecular alteration need to be established. Systematic curation of molecular events to AOPs will create the much-needed link between toxicogenomics and systemic mechanisms depicted by the AOPs. This, in turn, will introduce novel ways of benefitting from the AOPs, including predictive models and targeted assays, while also reducing the need for multiple testing strategies. Hence, a multi-step strategy to annotate AOPs is developed, and the resulting associations are applied to successfully highlight relevant adverse outcomes for chemical exposures with strong in vitro and in vivo convergence, supporting chemical grouping and other data-driven approaches. Finally, a panel of AOP-derived in vitro biomarkers for pulmonary fibrosis (PF) is identified and experimentally validated.

A transcriptome-wide association study of uterine fibroids to identify potential genetic markers and toxic chemicals

Uterine fibroid is one of the most prevalent benign tumors in women, with high socioeconomic costs. Although genome-wide association studies (GWAS) have identified several loci associated with uterine fibroid risks, they could not successfully interpret the biological effects of genomic variants at the gene expression levels. To prioritize uterine fibroid susceptibility genes that are biologically interpretable, we conducted a transcriptome-wide association study (TWAS) by integrating GWAS data of uterine fibroid and expression quantitative loci data. We identified nine significant TWAS genes including two novel genes, RP11-282O18.3 and KBTBD7, which may be causal genes for uterine fibroid. We conducted functional enrichment network analyses using the TWAS results to investigate the biological pathways in which the overall TWAS genes were involved. The results demonstrated the immune system process to be a key pathway in uterine fibroid pathogenesis. Finally, we carried out chemical–gene interaction analyses using the TWAS results and the comparative toxicogenomics database to determine the potential risk chemicals for uterine fibroid. We identified five toxic chemicals that were significantly associated with uterine fibroid TWAS genes, suggesting that they may be implicated in the pathogenesis of uterine fibroid. In this study, we performed an integrative analysis covering the broad application of bioinformatics approaches. Our study may provide a deeper understanding of uterine fibroid etiologies and informative notifications about potential risk chemicals for uterine fibroid.

Antimitotic and toxicogenetic action of Stevia urticifolia aerial parts on proliferating vegetal and mammalian cells: in vitro and in vivo traditional and replacement methods

Stevia urticifolia Thunb. is an underexploited herb possessing bioactive flavonoids, saponins, and terpenoids. The aim of this study was to examine the antiproliferative and toxicogenetic properties of the ethyl acetate extract from Stevia urticifolia aerial parts (EtAcSur) upon Artemia salina, erythrocytes, Allium cepa and sarcoma 180 cells and fibroblasts, as well as in vivo studies on mice to determine systemic, macroscopic, and behavioral alterations and bone marrow chromosomal damage. The assessment using A. salina larvae and mouse blood cells revealed LC₅₀ and EC₅₀ values of 68.9 and 113.6 µg/ml, respectively. Root growth and mitosis were inhibited by EtAcSur, and chromosomal aberrations were detected only at 100 μg/ml. EtAcSur exhibited potent concentration-dependent viability reduction of S180 and L-929 cells and antioxidant capacity employing ABTS^• and DPPH^•. No previous in vivo studies were performed before with the EtAcSur. Signals of acute toxicity were not observed at 300 mg/kg. Physiological and toxicological investigations at 25 and 50 mg/mg/day i.p. for 8 days did not markedly change body or organ relative weights, nor patterns of spontaneous locomotor and exploratory activities. In contrast, clastogenic effects on bone marrow were found at 50 mg/mg/day. EtAcSur was found to (1) produce toxicity in microcrustaceans, (2) capacity as free radical scavenger, (3) antimitotic, cytotoxic and clastogenic activties upon vegetal and mammalian cells, and (4) lethality on both tumor and normal murine cells indistinctly. In vivo damage systemic effects were not remarkable and clinical signals of toxicity were not observed, suggesting the significant pharmacological potential of S. urticifolia for the development of antineoplastic agents.Abbreviations: ABTS: 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid); DMSO: dimethylsulfoxide; DPPH: 1,1-diphenyl-2-picrylhydrazyl; EC₅₀: effective concentration 50%; EtAcSur: ethyl acetate extract from Stevia urticifolia aerial parts; Hb, hemoglobin; IC₅₀: inhibitory concentration 50%; LC₅₀,: lethal concentration 50%; MI: mitotic index; RBC, red blood cells; Trolox: 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid.

A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data

Drug-induced toxicity damages the health and is one of the key factors causing drug withdrawal from the market. It is of great significance to identify drug-induced target-organ toxicity, especially the detailed pathological findings, which are crucial for toxicity assessment, in the early stage of drug development process. A large variety of studies have devoted to identify drug toxicity. However, most of them are limited to single organ or only binary toxicity. Here we proposed a novel multi-label learning model named Att-RethinkNet, for predicting drug-induced pathological findings targeted on liver and kidney based on toxicogenomics data. The Att-RethinkNet is equipped with a memory structure and can effectively use the label association information. Besides, attention mechanism is embedded to focus on the important features and obtain better feature presentation. Our Att-RethinkNet is applicable in multiple organs and takes account the compound type, dose, and administration time, so it is more comprehensive and generalized. And more importantly, it predicts multiple pathological findings at the same time, instead of predicting each pathology separately as the previous model did. To demonstrate the effectiveness of the proposed model, we compared the proposed method with a series of state-of-the-arts methods. Our model shows competitive performance and can predict potential hepatotoxicity and nephrotoxicity in a more accurate and reliable way. The implementation of the proposed method is available at https://github.com/RanSuLab/Drug-Toxicity-Prediction-MultiLabel.

Advances in Single-Cell Toxicogenomics in Environmental Toxicology

The toxicity evaluation system of environmental pollutants has undergone numerous changes due to the application of new technologies. Single-cell toxicogenomics is rapidly changing our view on environmental toxicology by increasing the resolution of our analysis to the level of a single cell. Applications of this technology in environmental toxicology have begun to emerge and are rapidly expanding the portfolio of existing technologies and applications. Here, we first summarized different methods involved in single-cell isolation and amplification in single-cell sequencing process, compared the advantages and disadvantages of different methods, and analyzed their development trends. Then, we reviewed the main advances of single-cell toxicogenomics in environmental toxicology, emphatically analyzed the application prospects of this technology in identifying the target cells of pollutants in early embryos, clarifying the heterogeneous response of cell subtypes to pollutants, and finding pathogenic bacteria in unknown microbes, and highlighted the unique characteristics of this approach with high resolution, high throughput, and high specificity by examples. We also offered a prediction of the further application of this technology and the revolution it brings in environmental toxicology. Overall, these advances will provide practical solutions for controlling or mitigating exogenous toxicological effects that threaten human and ecosystem health, contribute to improving our understanding of the physiological processes affected by pollutants, and lead to the emergence of new methods of pollution control.

Short-Term Test for Toxicogenomic Analysis of Ecotoxic Modes of Action in Lemna minor

In the environmental risk assessment of substances, toxicity to aquatic plants is evaluated using, among other methods, the 7 dayLemna sp. growth inhibition test following the OECD TG 221. So far, the test is not applicable for short-term screening of toxicity, nor does it allow evaluation of toxic modes of action (MoA). The latter is also complicated by the lack of knowledge of gene functions in the test species. Using ecotoxicogenomics, we developed a time-shortened 3 day assay inLemna minor which allows discrimination of ecotoxic MoA. By examining the changes in gene expression induced by low effect concentrations of the pharmaceutical atorvastatin and the herbicide bentazon at the transcriptome and proteome levels, we were able to identify candidate biomarkers for the respective MoA. We developed a homology-based functional annotation pipeline for the reference genome ofL. minor, which allowed overrepresentation analysis of the gene ontologies affected by both test compounds. Genes affected by atorvastatin mainly influenced lipid synthesis and metabolism, whereas the bentazon-responsive genes were mainly involved in light response. Our approach is therefore less time-consuming but sensitive and allows assessment of MoA in L. minor. Using this shortened assay, investigation of expression changes of the identified candidate biomarkers may allow the development of MoA-specific screening approaches in the future.

Mapping DEHP to the adverse outcome pathway network for human female reproductive toxicity

Adverse outcome pathways (AOPs) and AOP networks are tools for mechanistic presentation of toxicological effects across different levels of biological organization. These tools are used to better understand how chemicals impact human health. In this study, a four-step workflow was used to derive the AOP network of human female reproductive toxicity (HFRT-AOP) from five AOPs available in the AOP-Wiki and ten AOPs obtained from the literature. Standard network analysis identified key events (KEs) that are point of convergence and divergence, upstream and downstream KEs, and bottlenecks across the network. To map di-(2-ethylhexyl) phthalate (DEHP) to the HFRT-AOP network, we extracted DEHP target genes and proteins from the Comparative Toxicogenomic and the CompTox Chemicals Dashboard databases. Enriched GO terms analysis was used to identify relevant biological processes in the ovary that are DEHP targets, whereas screening of scientific literature was performed manually and automatically using AOP-helpFinder. We combined this information to map DEHP to HFRT-AOP network to provide insight on the KEs and system-level perturbations caused by this endocrine disruptor and the emergent paths. This approach can enable better understanding of the toxic mechanism of DEHP-induced human female reproductive toxicity and reveal potential novel DEHP female reproductive targets for experimental studies.

Zinc pyrithione (ZPT) -induced embryonic toxicogenomic responses reveal involvement of oxidative damage, apoptosis, endoplasmic reticulum (ER) stress and autophagy

Zinc pyrithione (ZPT) is a frequently used organometallic biocide, carrying potentially adverse consequences to multiple species in the environment. Previously we have demonstrated its embryonic, organ developmental and liver metabolic toxicity of zebrafish. However, details of ZPT toxicity during embryogenesis are still limited. The present study was designed to evaluate the effects and possible mechanisms of ZPT-induced embryonic toxicogenomic responses by morphological investigations, transcriptome and gene quantitative analysis, as well as biochemical assays. The results revealed that treatment with ZPT caused embryogenesis toxicity, specifically in irregular cell division and rearrangement, delayed differentiations of eyes and notochords, the epiboly and germ ring formation and somite segmentation defects. In addition, ZPT exposure altered gene expression during early embryonic development, especially related with morphological abnormities and metabolic dysfunctions including reduction of oxidoreductase activity. Activities of antioxidants and caspases examinations showed inductions of oxidative stress and apoptosis by ZPT and quantitative analysis of marker genes further indicated that ZPT also triggered endoplasmic reticulum (ER) stress and autophagy. Thus, we deduce here that ZPT-induced embryonic toxicogenomic responses reveal involvement of oxidative damage, apoptosis, endoplasmic reticulum (ER) stress and autophagy.

Toxicogenetic assessment of a pre-workout supplement: In vitro mutagenicity, cytotoxicity, genotoxicity and glutathione determination in liver cell lines and in silico ADMET approaches

The benefits of practicing physical activity, such as weight loss and control, are commonly associated with caloric restriction diets and may be improved by the ingestion of thermogenic and ergogenic supplements. However, there is a lack of safety data on commonly marketed nutritional supplements. Therefore, this investigation aims to evaluate a pre-workout supplement for mutagenicity using the Ames test, hepatocytoxicity in HepG2 and F C3H cells after 24 h, 48 h and 72 h, genotoxicity using the CBMN assay, determination of gluthatione activity and computational prediction of the three major isolated compounds present in the supplement. The mutagenicity test showed a mutagenic response in TA98 His⁺ revertants of 5 mg/plate in the presence of metabolic activation, cytotoxicity in TA98 of 5 mg/plate in the absence of metabolic conditions, and in TA102 of 0.5 mg/plate both in the presence and absence of metabolic activation. In our in vitro eukaryotic cell viability, WST-1, LDH and alkaline phosphatase assays, the supplement showed hepatocytotoxicity both dose-dependently and time-dependently. In the cytokinesis blocking micronuclei assay, the supplement induced micronuclei, nuclear buds, nucleoplasmatic, bridge formation, and a decreased in nuclear division. In addition, the supplement decreased intra and extracellular GSH. Computational analysis showed that the three isolated compounds most present in the supplement have the potential to cause hepatotoxicity. In the present investigation, the pre-workout supplement induced mutagenic, genotoxic, and cytotoxic responses and GSH decrease. Thus, considering food safety and public health sanitary vigilance, the consumption of this pre-workout supplement may harm the health of its consumers.

Associating diethylhexyl phthalate to gestational diabetes mellitus via adverse outcome pathways using a network-based approach

Gestational diabetes mellitus (GDM) is a common pregnancy complication that is harmful to both the woman and fetus. Several epidemiological studies have found that exposure to diethylhexyl phthalate (DEHP), an endocrine disruptor ubiquitous in the environment, may be associated with GDM. This study aims to investigate the mechanism between DEHP and GDM using the adverse outcome pathway (AOP) framework, which can integrate information from different sources to elucidate the causal pathways between chemicals and adverse outcomes. We applied a network-based workflow to integrate diverse information to generate computational AOPs and accelerate the AOP development. The interactions among DEHP, genes, phenotypes, and GDM were retrieved from several publicly available databases, including the Comparative Toxicogenomics Database (CTD), Computational Toxicology (CompTox) Chemicals Dashboard, DisGeNET, MalaCards, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on the above interactions, a DEHP-Gene-Phenotype-GDM network consisting of 52 nodes and 227 edges was formed to support AOP construction. The filtered genes and phenotypes were assembled as molecular initiating events (MIEs) and key events (KEs) according to the upstream and downstream relationships, generating a computational AOP (cAOP) network. Based on the Organization for Economic Co-operation and Development handbook of AOPs, a cAOP was assessed and applied to determine the effects of DEHP on GDM. DEHP could increase TNF-α, downregulate the glucose uptake process, and lead to GDM. Overall, this study revealed the utility of computational methods in integrating a variety of datasets, supporting AOP development, and facilitating a better understanding of the underlying mechanism of exposure to chemicals on human health.

Integration of Toxicogenomics and Physiologically Based Pharmacokinetic Modeling in Human Health Risk Assessment of Perfluorooctane Sulfonate

Toxicogenomics and physiologically based pharmacokinetic (PBPK) models are useful approaches in chemical risk assessment, but the methodology to incorporate toxicogenomic data into a PBPK model to inform risk assessment remains to be developed. This study aimed to develop a probabilistic human health risk assessment approach by integrating toxicogenomic dose-response data and PBPK modeling using perfluorooctane sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic data, we identified the differentially expressed genes (DEGs) at each exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes and disease ontology enrichment analyses were conducted on the DEGs to identify significantly enriched pathways and diseases. The dose-response data of DEGs were analyzed using the Bayesian benchmark dose (BMD) method. Using a previously published PBPK model, the gene BMDs were converted to human equivalent doses (HEDs), which were summarized to pathway and disease HEDs and then extrapolated to reference doses (RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data. The results suggested that the median RfDs at different exposure paradigms were similar to the 2016 U.S. Environmental Protection Agency's recommended RfD, while the RfDs for the most sensitive pathways and diseases were closer to the recent European Food Safety Authority's guidance values. In conclusion, genomic dose-response data and PBPK modeling can be integrated to become a useful alternative approach in risk assessment of environmental chemicals. This approach considers multiple endpoints, provides toxicity mechanistic insights, and does not rely on apical toxicity endpoints.

Toxicogenomic profiling after sublethal exposure to nerve- and muscle-targeting insecticides reveals cardiac and neuronal developmental effects in zebrafish embryos

For specific primary modes of action (MoA) in environmental non-target organisms, EU legislation restricts the usage of active substances of pesticides or biocides. Corresponding regulatory hazard assessments are costly, time consuming and require large numbers of non-human animal studies. Currently, predictive toxicology of development compounds relies on their chemical structure and provides little insights into toxicity mechanisms that precede adverse effects. Using the zebrafish embryo model, we characterized transcriptomic responses to a range of sublethal concentrations of six nerve- and muscle-targeting insecticides with different MoA (abamectin, carbaryl, chlorpyrifos, fipronil, imidacloprid & methoxychlor). Our aim was to identify affected biological processes and suitable biomarker candidates for MoA-specific signatures. Abamectin showed the most divergent signature among the tested insecticides, linked to lipid metabolic processes. Differentially expressed genes (DEGs) after imidacloprid exposure were primarily associated with immune system and inflammation. In total, 222 early responsive genes to either MoA were identified, many related to three major processes: (1) cardiac muscle cell development and functioning (tcap, desma, bag3, hspb1, hspb8, flnca, myoz3a, mybpc2b, actc2, tnnt2c), (2) oxygen transport and hypoxic stress (alas2, hbbe1.1, hbbe1.3, hbbe2, hbae3, igfbp1a, hif1al) and (3) neuronal development and plasticity (npas4a, egr1, btg2, ier2a, vgf). The thyroidal function related gene dio3b was upregulated by chlorpyrifos and downregulated by higher abamectin concentrations. Important regulatory genes for cardiac muscle (tcap) and forebrain development (npas4a) were the most frequently ifferentially expressed across all insecticide treatments. We consider the identified gene sets as useful early warning biomarker candidates, i.e. for developmental toxicity targeting heart and brain in aquatic vertebrates. Our findings provide a better understanding about early molecular events in response to the analyzed MoA. Perceptively, this promotes the development for sensitive and informative biomarker-based in vitro assays for toxicological MoA prediction and AOP refinement, without the suffering of adult fish.

Comparative Toxicogenomics of Glyphosate and Roundup Herbicides by Mammalian Stem Cell-Based Genotoxicity Assays and Molecular Profiling in Sprague-Dawley Rats

Whether glyphosate-based herbicides (GBHs) are more potent than glyphosate alone at activating cellular mechanisms, which drive carcinogenesis remain controversial. As GBHs are more cytotoxic than glyphosate, we reasoned they may also be more capable of activating carcinogenic pathways. We tested this hypothesis by comparing the effects of glyphosate with Roundup GBHs both in vitro and in vivo. First, glyphosate was compared with representative GBHs, namely MON 52276 (European Union), MON 76473 (United Kingdom), and MON 76207 (United States) using the mammalian stem cell-based ToxTracker system. Here, MON 52276 and MON 76473, but not glyphosate and MON 76207, activated oxidative stress and unfolded protein responses. Second, molecular profiling of liver was performed in female Sprague-Dawley rats exposed to glyphosate or MON 52276 (at 0.5, 50, and 175 mg/kg bw/day glyphosate) for 90 days. MON 52276 but not glyphosate increased hepatic steatosis and necrosis. MON 52276 and glyphosate altered the expression of genes in liver reflecting TP53 activation by DNA damage and circadian rhythm regulation. Genes most affected in liver were similarly altered in kidneys. Small RNA profiling in liver showed decreased amounts of miR-22 and miR-17 from MON 52276 ingestion. Glyphosate decreased miR-30, whereas miR-10 levels were increased. DNA methylation profiling of liver revealed 5727 and 4496 differentially methylated CpG sites between the control and glyphosate and MON 52276 exposed animals, respectively. Apurinic/apyrimidinic DNA damage formation in liver was increased with glyphosate exposure. Altogether, our results show that Roundup formulations cause more biological changes linked with carcinogenesis than glyphosate.

Machine learning-based biomarkers identification from toxicogenomics - Bridging to regulatory relevant phenotypic endpoints

One of the major challenges in realization and implementations of the Tox21 vision is the urgent need to establish quantitative link between in-vitro assay molecular endpoint and in-vivo regulatory-relevant phenotypic toxicity endpoint. Current toxicomics approach still mostly rely on large number of redundant markers without pre-selection or ranking, therefore, selection of relevant biomarkers with minimal redundancy would reduce the number of markers to be monitored and reduce the cost, time, and complexity of the toxicity screening and risk monitoring. Here, we demonstrated that, using time series toxicomics in-vitro assay along with machine learning-based feature selection (maximum relevance and minimum redundancy (MRMR)) and classification method (support vector machine (SVM)), an "optimal" number of biomarkers with minimum redundancy can be identified for prediction of phenotypic toxicity endpoints with good accuracy. We included two case studies for in-vivo carcinogenicity and Ames genotoxicity prediction, using 20 selected chemicals including model genotoxic chemicals and negative controls, respectively. The results suggested that, employing the adverse outcome pathway (AOP) concept, molecular endpoints based on a relatively small number of properly selected biomarker-ensemble involved in the conserved DNA-damage and repair pathways among eukaryotes, were able to predict both Ames genotoxicity endpoints and in-vivo carcinogenicity in rats. A prediction accuracy of 76% with AUC = 0.81 was achieved while predicting in-vivo carcinogenicity with the top-ranked five biomarkers. For Ames genotoxicity prediction, the top-ranked five biomarkers were able to achieve prediction accuracy of 70% with AUC = 0.75. However, the specific biomarkers identified as the top-ranked five biomarkers are different for the two different phenotypic genotoxicity assays. The top-ranked biomarkers for the in-vivo carcinogenicity prediction mainly focused on double strand break repair and DNA recombination, whereas the selected top-ranked biomarkers for Ames genotoxicity prediction are associated with base- and nucleotide-excision repair The method developed in this study will help to fill in the knowledge gap in phenotypic anchoring and predictive toxicology, and contribute to the progress in the implementation of tox 21 vision for environmental and health applications.

OUP accepted manuscript

Purpose

Endocrine disruptors are a rising concern due to the wide array of health issues that it can cause. Although there are tools for mode of action (MoA)-based prediction of endocrine disruption (e.g. QSAR Toolbox and iSafeRat), none of them is based on toxicogenomics data. Here, we present EDTox, an R Shiny application enabling users to explore and use a computational method that we have recently published to identify and prioritize endocrine disrupting (ED) chemicals based on toxicogenomic data. The EDTox pipeline utilizes previously trained toxicogenomic-driven classifiers to make predictions on new untested compounds by using their molecular initiating events. Furthermore, the proposed R Shiny app allows users to extend the prediction systems by training and adding new classifiers based on new available toxicogenomic data. This functionality helps users to explore the ED potential of chemicals in new, untested exposure scenarios.

Availability and implementation

This tool is available as web application (www.edtox.fi) and stand-alone software on GitHub and Zenodo (https://doi.org/10.5281/zenodo.5817093).

Supplementary information

Supplementary data are available at Bioinformatics online.

Emerging Bioinformatics Methods and Resources in Drug Toxicology

Assessing the drug safety at an early stage of a drug discovery program is a critical issue. With the recent advances in molecular biology and genomic, massive amounts of generated and accumulated data by advanced experimental technologies such as RNA sequencing or proteomics start to be at the disposal of the scientific community. Innovative and adequate bioinformatic methods, tools, and protocols are required to analyze properly these diverse and extensive data sources with the aim to identify key features that are related to toxicity observations. Furthermore, the assessment of drug safety can be performed across multiple scales of complexity from molecular, cellular to phenotypic levels; therefore, the application of network science contributes to a better interpretation of the drug's exposure effect on human health. Here, we review databases containing toxicogenomics and chemical-phenotype information, as well as appropriated bioinformatics approaches that are currently used to analyze such data. Extension to others methods such as dose-responses, time-dependent processes, and text mining is also presented giving an overview of suitable tools available for a best practice of drug safety analysis.

Temporal and spatial toxicogenetic damage in estuarine catfish Cathorops spixii from a marine protected area with evidence of anthropogenic influences

Taking action to contribute to the preservation of the natural coastal environment, which maintains a diversity of life, is important in today's world. In estuarine ecosystems that are included in marine protected areas (MPA), it is important to conduct biomonitoring over time to monitor the effects of xenobiotics on bioindicator species such as the catfish Cathorops spixii. This study aims to evaluate the toxicogenetic signals in C. spixii from a MPA (Cananéia-Iguape region, Brazilian coast). These genotoxic signals are demonstrated by the presence of micronuclei (MN) and abnormalities in erythrocytes (AE). This study also takes into account the environmental differences signaled by the water's properties (temperature, salinity, pH, DO, dissolved nutrients, and particulate material) over time (2009, 2014, 2017, and 2018). The results show that in the northern region of the estuary, and mainly in 2009, the water properties reveal the influence of the river in the form of the lowest levels of salinity and pH and the highest levels of nutrients. The most significant levels of suspended particulate material and chlorophyll-a are found in the southern region of the estuary, mainly in 2017 and 2018. In general, the C. spixii from the northern region had better well-being than catfish from the more preserved (southern) region. The data on MN and AE show evidence of toxicogenetic damage occurring over time and clastogenic/aneugenic effects mainly in fish sampled in 2018. The presence of a new AE, first recorded in C. spixii sampled in 2018, and named here as double bubbled, is another indicator of toxicogenetic effects. Finally, although the southern region of the estuary has better abiotic properties and conditions for primary production, the obtained toxicogenetic data for C. spixii reinforces the need for - and encourages the implementation of - monitoring actions in this marine protected area using bioindicator species of contamination.

Integration of data from the cell-based ERK1/2 ELISA and the Comparative Toxicogenomics Database deciphers the potential mode of action of bisphenol A and benzo[a]pyrene in lung neoplasm

Chemicals can activate a variety of signaling pathways, initiating changes in gene expression and cellular functions. Here, we combined experimental data on the chemical-induced extracellular signal-regulated kinase 1/2 (ERK1/2) activation with the Comparative Toxicogenomics Database (CTD) to connect signaling, genes, and phenotypes to reveal the potential chemical's mode of action (MOA) responsible for the disease state. Experimental data on ERK1/2 activation were derived from the cell-based phospho-ERK1/2 ELISA on human alveolar epithelial cells A549. A549 cells were exposed to bisphenol A (BPA), benzo[a]pyrene (BaP), tributyltin (TBT), and ibuprofen from 10^-12 M to 10^-5 M. Results show that BPA, BaP, and TBT can activate ERK1/2 in A549 cells. We selected BPA and BaP to elucidate the molecular events connecting chemical exposure, ERK1/2 signaling, phenotypes, and lung neoplasm (LN) using CTD. CTD analysis showed that BPA and BaP share 26 mitogen-activated protein kinase 1/3 (MAPK1/3) signaling genes associated with LN. Phenotype prioritization revealed 37 BPA, 10 BaP, and 11 shared key phenotypes associated with LN. Alignment of MAPK1/3 signaling genes and phenotypes showed that ERK1/2 and oxidative stress, EGFR gene, and positive regulation of cell proliferation and migration could be the shared key events (KE) for BPA and BaP. This analysis also identified protein kinase B and ERK1/2 signaling, FGF9, FGFR1 and FGFR2 genes, positive regulation of cell proliferation and angiogenesis as KE in MOA for BPA, whereas ERK1/2 signaling, IL6 and DAB2IP genes, negative regulation of cell proliferation and inflammatory response were identified as KE in MOA for BaP.

A toxicogenomic data space for system-level understanding and prediction of EDC-induced toxicity

Endocrine disrupting compounds (EDCs) are a persistent threat to humans and wildlife due to their ability to interfere with endocrine signaling pathways. Inspired by previous work to improve chemical hazard identification through the use of toxicogenomics data, we developed a genomic-oriented data space for profiling the molecular activity of EDCs in an in silico manner, and for creating predictive models that identify and prioritize EDCs. Predictive models of EDCs, derived from gene expression data from rats (in vivo and in vitro primary hepatocytes) and humans (in vitro primary hepatocytes and HepG2), achieve testing accuracy greater than 90%. Negative test sets indicate that known safer chemicals are not predicted as EDCs. The rat in vivo-based classifiers achieve accuracy greater than 75% when tested for invitro to in vivoextrapolation. This study reveals key metabolic pathways and genes affected by EDCs together with a set of predictive models that utilize these pathways to prioritize EDCs in dose/time dependent manner and to predict EDCevokedmetabolic diseases.

A toxicity pathway-based approach for modeling the mode of action framework of lead-induced neurotoxicity

BACKGROUND

The underlying mechanisms of lead (Pb) toxicity are not fully understood, which makes challenges to the traditional risk assessment. There is growing use of the mode of action (MOA) for risk assessment by integration of experimental data and system biology. The current study aims to develop a new pathway-based MOA for assessing Pb-induced neurotoxicity.

METHODS

The available Comparative Toxicogenomic Database (CTD) was used to search genes associated with Pb-induced neurotoxicity followed by developing toxicity pathways using Ingenuity Pathway Analysis (IPA). The spatiotemporal sequence of disturbing toxicity pathways and key events (KEs) were identified by upstream regulator analysis. The MOA framework was constructed by KEs in biological and chronological order.

RESULTS

There were a total of 71 references showing the relationship between lead exposure and neurotoxicity, which contained 2331 genes. IPA analysis showed that the neuroinflammation signaling pathway was the core toxicity pathway in the enriched pathways relevant to Pb-induced neurotoxicity. The upstream regulator analysis demonstrated that the aryl hydrocarbon receptor (AHR) signaling pathway was the upstream regulator of the neuroinflammation signaling pathway (11.76% overlap with upstream regulators, |Z-score|=1.451). Therefore, AHR activation was recognized as the first key event (KE1) in the MOA framework. The following downstream molecular and cellular key events were also identified. The pathway-based MOA framework of Pb-induced neurotoxicity was built starting with AHR activation, followed by an inflammatory response and neuron apoptosis.

CONCLUSION

Our toxicity pathway-based approach not only advances the development of risk assessment for Pb-induced neurotoxicity but also brings new insights into constructing MOA frameworks of risk assessment for new chemicals.

Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury

In recent years, network-based methods have become an attractive analytical approach for toxicogenomics studies. They can capture not only the global changes of regulatory gene networks but also the relationships between their components. Among them, a causal reasoning approach depicts the mechanisms of regulation that connect upstream regulators in signaling networks to their downstream gene targets. In this work, we applied CARNIVAL, a causal network contextualisation tool, to infer upstream signaling networks deregulated in drug-induced liver injury (DILI) from gene expression microarray data from the TG-GATEs database. We focussed on six compounds that induce observable histopathologies linked to DILI from repeated dosing experiments in rats. We compared responses in vitro and in vivo to identify potential cross-platform concordances in rats as well as network preservations between rat and human. Our results showed similarities of enriched pathways and network motifs between compounds. These pathways and motifs induced the same pathology in rats but not in humans. In particular, the causal interactions "LCK activates SOCS3, which in turn inhibits TFDP1" was commonly identified as a regulatory path among the fibrosis-inducing compounds. This potential pathology-inducing regulation illustrates the value of our approach to generate hypotheses that can be further validated experimentally.