The impact of contaminants on Copepod sp. and its molecular response is least explored, despite their abundance and dominance among invertebrates in aquatic environments. In the present investigation, Dioithona rigida, a cyclopoid zooplankton, was treated with selenium nanoparticles (SeNPs) to determine the associated biochemical changes, and the chronic exposure effects were recorded using transcriptomic analysis. It was found that, SeNPs were acutely toxic with a lethal dose 50% of 140.9 mg/L. The de novo assembled transcriptome of the copepod comprised 81,814 transcripts, which underwent subsequent annotations to biological processes (23,378), cellular components (21,414), and molecular functions (31,015). Comparison of the expressed transcripts against the treated sample showed that a total of 186 transcript genes were differentially expressed among the D. rigida treatments (control and SeNPs). The significant downregulated genes are coding for DNA repair, DNA-templated DNA replication, DNA integration, oxidoreductase activity and transmembrane transport. Similarly, significant upregulations were observed in protein phosphatase binding and regulation of membrane repolarization. Understanding the impact of SeNPs on copepods is crucial not only for aquatic ecosystem health but also for human health, as these organisms play a key role in marine food webs, ultimately affecting the fish consumed by humans. By elucidating the molecular responses and potential toxicological effects of SeNPs, this study provides key insights for risk assessments and regulatory policies, ensuring the safety of seafood and protecting human health from the unintended consequences of nanoparticle pollution.
The toxicity analysis in Dioithona rigida is the first of its kind as a copepod model for analysis on dietary fixation of metal toxicity at the trophic level. Since this copepod is a major zooplankton fed by fish and crustacean larvae in marine ecosystems, the toxicity analysis on this copepod will give us more insights of the trophic-level food transfer. As far as our knowledge, this is the first study that opted to construct the de novo transcriptomic pipeline for this copepod, treated with selenium nanoparticles. The effectiveness of this work may be further extrapolated to assess the effect of other metal nanoparticles in this model organism. Although the selenium toxicity in marine ecosystem is an established sector, through our combined approach of biochemical analysis and omics approach, the solid framework and comprehensive insight of the selenium toxicity in reproductive fitness and molecular changes has been studied. This study chose to seek a reliable alternative in the sense of new copepod model and omics approach to analyse the relevant metal nanoparticle toxicity in the marine ecosystem.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental contaminant that disrupts hepatic function leading to steatotic liver disease (SLD)-like pathologies, such as steatosis, steatohepatitis, and fibrosis. These effects are mediated by the aryl hydrocarbon receptor following changes in gene expression. Although diverse cell types are involved, initial cell-specific changes in gene expression have not been reported. In this study, differential gene expression in hepatic cell types was examined in male C57BL/6 mice gavaged with 30 µg/kg of TCDD using single-nuclei RNA-sequencing. Ten liver cell types were identified with the proportions of most cell types remaining unchanged, except for neutrophils which increased at 72 h. Gene expression suggests TCDD induced genes related to oxidative stress in hepatocytes as early as 2 h. Lipid homeostasis was disrupted in hepatocytes, macrophages, B cells, and T cells, characterized by the induction of genes associated with lipid transport, steroid hormone biosynthesis, and the suppression of β-oxidation, while linoleic acid metabolism was altered in hepatic stellate cells (HSCs), B cells, portal fibroblasts, and plasmacytoid dendritic cells. Pro-fibrogenic processes were also enriched, including the induction retinol metabolism genes in HSCs and the early induction of anti-fibrolysis genes in hepatocytes, endothelial cells, HSCs, and macrophages. Hepatocytes also had gene expression changes consistent with hepatocellular carcinoma. Collectively, these findings underscore the effects of TCDD in initiating SLD-like phenotypes and identified cell-specific gene expression changes related to oxidative stress, steatosis, fibrosis, cell proliferation and the development of HCC.

Bisphenol A (BPA), a widely used chemical in the production of plastics and epoxy resins, has garnered significant attention due to its association with adverse health effects, particularly its endocrine-disrupting properties. Regulatory measures aimed at reducing human exposure to BPA have led to a proliferation of alternative chemicals used in various consumer and industrial products. While these alternatives serve to reduce BPA exposure, concerns have arisen regarding their safety and potential toxicity as regrettable substitutes. Previous efforts have demonstrated that in vitro high-throughput transcriptomics (HTTr) studies can be used to assess the endocrine-disrupting potential of BPA alternatives, and this strategy produces transcriptomic points-of-departure (tPODs) that are protective of human health when compared to the PODs from traditional rodent studies. In this study, we used in vitro HTTr to assess the potential for toxicity of eleven data-poor legacy chemicals sharing structural similarities to BPA. Human breast cancer MCF-7 cells were exposed to BPA and 11 alternatives at concentrations ranging from 0.1 to 25 μM to assess toxicity. Analysis of global transcriptomic changes and a previously characterized estrogen receptor alpha (ERα) transcriptomic biomarker signature revealed that 9 of 11 chemicals altered gene expression relative to controls. One of the chemicals (2,4\'-Bisphenol A) activated the ERα biomarker at the same concentration as BPA (i.e., 4,4\'-BPA) but was deemed to be more potent as it induced global transcriptomic changes at lower concentrations. These results address data gaps in support of ongoing screening assessments to identify BPA alternatives with hazard potential and help to identify potential candidates that may serve as safer alternatives.

Di(ethylhexyl) phthalate (DEHP) is a ubiquitous environmental contaminant to which humans are exposed via multiple routes. Human health risk assessments for this substance have recently been updated, focusing on reproductive toxicity, including DEHP, in the list of chemicals classified as carcinogenic, mutagenic, or toxic to reproduction (CMR). Moreover, DEHP has also been defined as probably and possibly carcinogenic to humans based on its carcinogenicity in rodents. However, the mechanism of action of DEHP and its relevance in humans remain unclear. Rodent data suggests that DEHP induces cancer through non-genotoxic mechanisms related to multiple molecular signals, including PPARα activation, perturbation of fatty acid metabolism, induction of cell proliferation, decreased apoptosis, production of reactive oxygen species, and oxidative stress. According to the DEHP toxicological dataset, several in vitro cell transformation assays have been performed using different protocols and cellular models to produce different results. This study aimed to evaluate the carcinogenic potential of DEHP by using the A31-1-1 BALB/c-3T3 cell line in a standard cell transformation assay. Additionally, transcriptomic analysis was performed to explore the molecular responses and identify the affected toxicological pathways. Although DEHP treatment did not induce transformation in BALB/c-3T3 cells, the transcriptomic results revealed significant modulation of several pathways associated with DEHP metabolism, tissue-specific functions related to systemic metabolism, and basal cellular signaling with pleiotropic outcomes. Among these signaling pathways, modulation of cell-regulating signaling pathways, such as Notch, Wnt, and TGF-β, can be highlighted. More specific modulation of such genes and pathways with double functions in metabolism and neurophysiology underlies the well-known crosstalk that may be crucial for the mechanism of action of DEHP. Our findings offer evidence to support the notion that these models are effective in minimizing the use of animal testing for toxicity assessment.

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.

To identify pathway perturbations and examine biological modes of action (MOAs) for various perfluoroalkyl substances, we re-analyzed published in vitro gene expression studies from human primary liver spheroids. With treatment times ranging from 10 to 14 days, shorter-chain PFAS (those with 6 or fewer fluorinated carbon atoms in the alkyl chain) showed enrichment for pathways of fatty acid metabolism and fatty acid beta-oxidation with upregulated genes. Longer-chain PFAS compounds, specifically PFOS (perfluorooctane sulfonate), PFDS (perfluorodecane sulfonate), and higher doses of PFOA (perfluorooctanoic acid), had enrichment for pathways involved in steroid metabolism, fatty acid metabolism, and biological oxidation for downregulated genes. Although PFNA (perfluorononanoic acid), PFDA (perfluorodecanoic acid), and PFUnDA (perfluoroundecanoic acid) were more toxic and could only be examined after a 1-day treatment, all three had enrichment patterns similar to those observed with PFOS. With PFOA there were dose-dependent changes in pathway enrichment, shifting from upregulation of fatty acid metabolism and downregulation of steroid metabolism to downregulation of both at higher doses. The response to PFHpS (perfluoroheptanesulfonic acid) was similar to the PFOA pattern at the lower treatment dose. Based on results of transcription factor binding sites analyses, we propose that downregulation of pathways of lipid metabolism by longer chain PFAS may be due to inhibitory interactions of PPARD on genes controlled by PPARA and PPARG. In conclusion, our transcriptomic analysis indicates that the biological MOAs of PFAS compounds differ according to chain length and dose, and that risk assessments for PFAS should consider these differences in biological MOAs when evaluating mixtures of these compounds.

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

Drug-induced liver injury (DILI) is the most common trigger for acute liver failure and the leading cause of attrition in drug development. In this study, we developed an in silico framework to screen drug-induced hepatocellular toxicity (INSIGHT) by integrating the post-treatment transcriptomic data from both rodent models and primary human hepatocytes. We first built an early prediction model using logistic regression with elastic net regularization for 123 compounds and established the INSIGHT framework that can screen for drug-induced hepatotoxicity. The 235 signature genes identified by INSIGHT were involved in metabolism, bile acid synthesis, and stress response pathways. Applying the INSIGHT to an independent transcriptomic dataset treated by 185 compounds predicted that 27 compounds show a high DILI risk, including zoxazolamine and emetine. Further integration with cell image data revealed that predicted compounds with high DILI risk can induce abnormal morphological changes in the endoplasmic reticulum and mitochondrion. Clustering analysis of the treatment-induced transcriptomic changes delineated distinct DILI mechanisms induced by these compounds. Our study presents a computational framework for a mechanistic understanding of long-term liver injury and the prospective prediction of DILI risk.

The impact of emerging pollutants such as ibuprofen and dibutyl phthalate on aquatic species is a growing concern and the need for proper assessment and evaluation of these toxicants is imperative. The objective of this study was to examine the toxicogenomic impacts of ibuprofen and dibutyl phthalate on Clarias gariepinus, a widely distributed African catfish species. Results showed that exposure to the test compounds caused significant changes in gene expression, including upregulation of growth hormone, interleukin, melatonin receptors, 17β-Hydroxysteroid Dehydrogenase, heat shock protein, doublesex, and mab-3 related transcription factor. On the other hand, expression of forkhead Box Protein L2 and cytochrome P450 was downregulated, revealing a potential to induce female to male sex reversal. The binding affinities and hydrophobic interactions of the test compounds with the reference genes were also studied, showing that ibuprofen had the lowest binding energy and the highest affinity for the docked genes. Both compounds revealed a mutual molecular interaction with amino acids residues within the catalytic cavity of the docked genes. These results provide new insights into the toxic effects of ibuprofen and dibutyl phthalate on Clarias gariepinus, contributing to a better understanding of the environmental impact of these pollutants.