The promise of toxicogenomics for genetic toxicology: past, present and future

Perfluorohexanesulfonic Acid (PFHxS) Induces Hepatotoxicity through the PPAR Signaling Pathway in Larval Zebrafish (Danio rerio)

In recent years, the industrial substitution of long-chain per- and polyfluoroalkyl substances (PFAS) with short-chain alternatives has become increasingly prevalent, resulting in the widespread environmental detection of perfluorohexanesulfonic acid (PFHxS), a short-chain PFAS. However, there remains limited information about the potential adverse effects of PFHxS at environmental concentrations to wildlife. Here, early life stage zebrafish (Danio rerio) were exposed to environmentally relevant concentrations of PFHxS to better characterize the adverse effects of PFHxS on aquatic organisms. Nontargeted, transcriptomic analysis revealed potential hepatotoxic effects in exposed larvae, including macrovesicular and microvesicular hepatic steatosis, as well as focal liver necrosis. Morphological, histological, biochemical, and targeted transcript expression profiles further confirmed significant alterations in hepatocellular lesion numbers, liver pathological structures, relative liver size, liver biochemical parameters, and liver function genes. To validate the PPAR-mediated toxicological mechanism identified as an enriched pathway through in silico bioinformatics analysis, we tested the coexposure to an antagonist and PPAR morpholino knockdown. This intervention alleviated PFHxS-induced hepatic effects, including reductions in the levels of aspartate aminotransferase, alanine aminotransferase, total cholesterol, and total triglycerides. Our results demonstrate that environmentally relevant concentrations of PFHxS can impair liver development and function in fish, which could have potential risks to aquatic organisms.

Improving ADMET Prediction Accuracy for Candidate Drugs: Factors to Consider in QSPR Modeling Approaches

Quantitative Structure-Property Relationship (QSPR) employs mathematical and statistical methods to reveal quantitative correlations between the pharmacokinetics of compounds and their molecular structures, as well as their physical and chemical properties. QSPR models have been widely applied in the prediction of drug absorption, distribution, metabolism, excretion, and toxicity (ADMET). However, the accuracy of QSPR models for predicting drug ADMET properties still needs improvement. Therefore, this paper comprehensively reviews the tools employed in various stages of QSPR predictions for drug ADMET. It summarizes commonly used approaches to building QSPR models, systematically analyzing the advantages and limitations of each modeling method to ensure their judicious application. We provide an overview of recent advancements in the application of QSPR models for predicting drug ADMET properties. Furthermore, this review explores the inherent challenges in QSPR modeling while also proposing a range of considerations aimed at enhancing model prediction accuracy. The objective is to enhance the predictive capabilities of QSPR models in the field of drug development and provide valuable reference and guidance for researchers in this domain.

Titanium dioxide nanoparticles: revealing the mechanisms underlying hepatotoxicity and effects in the gut microbiota

Numerous studies in recent years have questioned the safety of oral exposure to titanium dioxide nanoparticles (TiO2 NPs). TiO2 NPs are not only likely to accumulate in the gastrointestinal tract, but they are also found to penetrate the body circulation and reach distant organs. The liver, which is considered to be a target organ for nanoparticles, is of particular concern. TiO2 NPs accumulate in the liver and cause oxidative stress and inflammatory reactions, resulting in pathological damage. The impact of TiO2 NPs on liver aspartate aminotransferase (AST) and alanine aminotransferase (ALT) was studied using a meta-analysis. According to the findings, TiO2 NPs exposure can cause an elevation in AST and ALT levels in the blood. Furthermore, TiO2 NPs are eliminated mostly through feces, and their lengthy residence in the gut exposes them to microbiota. The gut microbiota is also dysbiotic due to titanium dioxide's antibacterial capabilities. This further leads to changes in the amount of microbiota metabolites, which can reach the liver with blood circulation and trigger hepatotoxicity through the gut-liver axis. This review examines the gut-liver axis to assess the effects of gut microbiota dysbiosis on the liver to provide suggestions for assessing the gut-hepatotoxicity of TiO2 NPs.

Using Machine Learning to make nanomaterials sustainable

Sustainable development is a key challenge for contemporary human societies; failure to achieve sustainability could threaten human survival. In this review article, we illustrate how Machine Learning (ML) could support more sustainable development, covering the basics of data gathering through each step of the Environmental Risk Assessment (ERA). The literature provides several examples showing how ML can be employed in most steps of a typical ERA.A key observation is that there are currently no clear guidance for using such autonomous technologies in ERAs or which standards/checks are required. Steering thus seems to be the most important task for supporting the use of ML in the ERA of nano- and smart-materials. Resources should be devoted to developing a strategy for implementing ML in ERA with a strong emphasis on data foundations, methodologies, and the related sensitivities/uncertainties. We should recognise historical errors and biases (e.g., in data) to avoid embedding them during ML programming.

Analyses of Transcriptomics Cell Signalling for Pre-Screening Applications in the Integrated Approach for Testing and Assessment of Non-Genotoxic Carcinogens

With recent rapid advancement of methodological tools, mechanistic understanding of biological processes leading to carcinogenesis is expanding. New approach methodologies such as transcriptomics can inform on non-genotoxic mechanisms of chemical carcinogens and can be developed for regulatory applications. The Organisation for the Economic Cooperation and Development (OECD) expert group developing an Integrated Approach to the Testing and Assessment (IATA) of Non-Genotoxic Carcinogens (NGTxC) is reviewing the possible assays to be integrated therein. In this context, we review the application of transcriptomics approaches suitable for pre-screening gene expression changes associated with phenotypic alterations that underlie the carcinogenic processes for subsequent prioritisation of downstream test methods appropriate to specific key events of non-genotoxic carcinogenesis. Using case studies, we evaluate the potential of gene expression analyses especially in relation to breast cancer, to identify the most relevant approaches that could be utilised as (pre-) screening tools, for example Gene Set Enrichment Analysis (GSEA). We also consider how to address the challenges to integrate gene panels and transcriptomic assays into the IATA, highlighting the pivotal omics markers identified for assay measurement in the IATA key events of inflammation, immune response, mitogenic signalling and cell injury.

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.

•

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

•

Application of a toxicogenomics approach to analyze genotoxicity.

•

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

Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG

Transcript signatures are a promising approach to identify and classify genotoxic and non-genotoxic compounds and are of interest as biomarkers or for future regulatory application. Not much data, however, is yet available about the concordance of transcriptional responses in different cell types or tissues. Here, we analyzed transcriptomic responses to selected genotoxic food contaminants in the human p53-competent lymphoblastoid cell line TK6 using RNA sequencing. Responses to treatment with five genotoxins, as well as with four non-genotoxic liver toxicants, were compared with previously published gene expression data from the human liver cell model HepaRG. A significant overlap of the transcriptomic changes upon genotoxic stress was detectable in TK6 cells, whereas the comparison with the HepaRG model revealed considerable differences, which was confirmed by bioinformatic data mining for cellular upstream regulators or pathways. Taken together, the study presents a transcriptomic signature for genotoxin exposure in the human TK6 blood cell model. The data demonstrate that responses in different cell models have considerable variations. Detection of a transcriptomic genotoxin signature in blood cells indicates that gene expression analyses of blood samples might be a valuable approach to also estimate responses to toxic exposure in target organs such as the liver.